Tips and Tricks to Help Quit Smoking
The health benefits of quitting are pretty obvious but the addictive nature of nicotine makes it difficult. Do you gradually cut down the number of cigarettes you smoke in a day? That’s a little like dieting. It relies on willpower and it’s easily interrupted by a bad day at work or something equally stressful. You’re better off quitting, but how is that done? There are lots of products out there and loads of good advice too so stopping isn’t as hard as you’d imagine.
Make a plan. That’s the first thing you need to do. Make a promise to yourself that you will stop smoking, plan out how to do it and then prepare everything you need. A good time to quit can be a time when you won’t be able to smoke. If you’re going to take a 12-hour flight, you won’t be able to smoke for half a day. That could be a really good opportunity to cut cigarettes out of your life.
As part of your preparations work out when you tend to develop the cravings? Do they come after a meal or first thing in the morning, both of which are common for smokers? The good thing is that they only ever last five minutes. To stop the craving getting the better of you consider some strategies to combat them. Some people reach for a candy bar when they get the itch to smoke. That’s okay in the short term but you might create another problem for your body ? obesity. You need to think about what distracts you and decide to do when cravings strike.
Friends and Family
Stopping can be stressful so don’t do it alone. Tell your friends and family that you’ve decided to quit. They will be very supportive. If you need some outside help, look up a tobacco helpline on the web and then call them whenever you need help and support. Don’t forget that nicotine remains in the bloodstream for three days at most so you will only need to get through half a week in order to live a smoke-free life.
Getting yourself off the couch and into some sneakers can make a real difference to your chances of quitting for good. Even a five-minute walk at a normal pace can help you stop smoking by cutting cravings down. The exercise helps your body to produce anti-craving chemicals that course through your brain and make you feel good. There are lots of other health benefits to an active life including a weight loss, increased muscle strength and better overall fitness.
Food and Drink
Studies carried out in 2007 and 2013 by Nicotine and Tobacco Research concluded that some food and drink can help curb your cravings. Milk and other dairy products are the best foods to take when quitting. Smoking is less palatable when you drink milk. Coffee is considered the worst drink to have when you’re quitting so stay away from that. Fruits and vegetables also help you stop. You might be happier to read that popcorn is also great when you’re quitting.
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How to Quit Smoking
Smoking is an addictive habit that can lead to a number of health problems, ranging from various types of cancer to high blood pressure and heart disease. It’s also difficult to quit. Luckily, there are several options to try if you’re looking to stop smoking as soon as possible.
One method many people find to be helpful when they quit smoking is counseling or therapy. According to the American Cancer Society, it’s one of the more successful methods, especially when combined with one of the others. Fortunately, there are many options when it comes to counseling. Doctors and other medical professionals can meet with you to discuss your options and help keep you on track. Therapists can also help you come up with a plan, recognize your triggers and come up with ways to stop yourself from picking up a cigarette. You can receive counseling via phone through organizations like the American Cancer Society or the American Lung Association. You may even find support groups for smokers in your area where you can attend meetings once a week or several times a month.
Another option is to talk to your doctor about medications you can take to help you stop smoking. According to WebMD, products like bupropion and varenicline can help prevent cravings and even help curtail withdrawal symptoms. According to the American Cancer Society, medications may also help block the impact of nicotine on the brain. These are prescription medications, however, so you’ll need to talk to your doctor first.
Speaking of nicotine, some people quit by using nicotine replacement products, like gums and patches. Many of them are available over the counter at your local pharmacy. You can talk to your doctor or pharmacist about how to use them if you have questions, and when used properly, they may help you fight nicotine withdrawal symptoms, according to the American Cancer Society. There are also inhalers and nasal sprays made with nicotine that are available via prescription.
Because smoking is highly addictive, you may find that just one way of quitting doesn’t help. In this case, talk to your doctor or counselor about trying multiple options at once. You might choose to chew nicotine gum, attend counseling and take medication. Just make sure your combination methods won’t interfere with each other; that’s why talking with your doctor is important.
According to WebMD, 90 percent of people who try to quit smoking do so without using any kind of additional help. This cold turkey method only works permanently about five to seven percent of the time, but it is possible, notes WebMD. The U.S. government recommends making a plan when you quit, especially if you do it cold turkey. Find ways to stay busy, like exercising, watching movies and spending time with friends who don’t smoke. Identify your smoking triggers and stay away from them. That may mean spending more time with non-smokers, throwing out any smoking-related materials you own, switching up your routine and spending time in places where smoking isn’t allowed. Figure out another way to spend time on breaks at work. Also, remind yourself why you’re quitting. Maybe you want to get healthy or you want to live longer for your kids’ sake. Most importantly, stay positive, even on the bad days.
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Effectiveness of stop smoking interventions among adults: protocol for an overview of systematic reviews and an updated systematic review
1 Knowledge Synthesis Group, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Centre for Practice-Changing Research, 501 Smyth Road, Box 201, Ottawa, Ontario K1H 8L6 Canada
2 Public Health Agency of Canada, Ottawa, Ontario Canada
Brett D. Thombs
3 Lady Davis Institute of the Jewish General Hospital, Montreal, Quebec Canada
4 Department of Psychiatry, McGill University, Montreal, Quebec Canada
Becky skidmore, stéphane groulx.
5 Department of Community Health Sciences, University of Sherbrooke, Sherbrooke, Quebec Canada
6 Centre de recherche Charles-Le Moyne – Saguenay–Lac-Saint-Jean sur les innovations en santé (CR-CSIS), Université de Sherbrooke, Quebec, Quebec Canada
7 University of Calgary Cumming School of Medicine, Calgary, Alberta Canada
8 Alberta Health Services, Calgary, Alberta Canada
Donna L. Reynolds
9 Department of Family and Community Medicine, University of Toronto, Toronto, Ontario Canada
10 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario Canada
11 Division of Community Health and Humanities, Memorial University of Newfoundland, St. John’s, Newfoundland Canada
Steven L. Bernstein
12 Department of Emergency Medicine, Yale School of Medicine, New Haven, CT USA
13 Addictions Division, Centre for Addiction and Mental Health, Toronto, Ontario Canada
14 Department of Otolaryngology, University of Ottawa, Ottawa, Ontario Canada
15 The Ottawa Hospital, Ottawa, Ontario Canada
16 Department of Family Medicine, University of Ottawa, Ottawa, Ontario Canada
17 Ottawa Hospital Research Institute, Ottawa, Ontario Canada
18 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario Canada
19 Bruyere Research Institute, Ottawa, Ontario Canada
20 School of Psychology, University of Ottawa, Ottawa, Ontario Canada
Brian hutton, beverley j. shea, vivian welch, matt morrow.
21 Patient representative, Vancouver, British Columbia Canada
Adrienne stevens, associated data.
Tobacco smoking is the leading cause of cancer, preventable death, and disability. Smoking cessation can increase life expectancy by nearly a decade if achieved in the third or fourth decades of life. Various stop smoking interventions are available including pharmacotherapies, electronic cigarettes, behavioural support, and alternative therapies. This protocol outlines an evidence review which will evaluate the benefits and harms of stop smoking interventions in adults.
The evidence review will consist of two stages. First, an overview of systematic reviews evaluating the benefits and harms of various stop smoking interventions delivered in or referred from the primary care setting will be conducted. The second stage will involve updating a systematic review on electronic cigarettes identified in the overview; randomized controlled trials will be considered for outcomes relating to benefits while randomized controlled trials, non-randomized controlled trials, and comparative observational studies will be considered for evaluating harms. Search strategies will be developed and peer-reviewed by medical information specialists. The search strategy for the updated review on e-cigarettes will be developed using that of the candidate systematic review. The MEDLINE®, PsycINFO, Embase, and the Cochrane Library electronic databases will be searched as of 2008 for the overview of reviews and from the last search date of the selected review for the updated review. Organizational websites and trial registries will be searched for unpublished or ongoing reviews/studies. Two reviewers will independently screen the title and abstracts of citations using the liberal accelerated method. Full-text screening will be performed independently by two reviewers. Extracted data will be verified by a second reviewer. Disagreements regarding full-text screening and data extraction will be resolved by consensus or third-party adjudication. The methodological quality of systematic reviews, risk of bias of randomized and non-randomized trials, and methodological quality of cohort studies will be evaluated using AMSTAR 2, the Cochrane risk of bias tool, and a modified version of the Scottish Intercollegiate Guidelines Network critical appraisal tool, respectively. The GRADE framework will be used to assess the quality of the evidence for outcomes.
The evidence review will evaluate the benefits and harms of various stop smoking interventions for adults. Findings will be used to inform a national tobacco cessation guideline by the Canadian Task Force on Preventive Health Care.
Systematic review registration
PROSPERO (CRD42018099691, CRD42018099692)
Electronic supplementary material
The online version of this article (10.1186/s13643-018-0928-x) contains supplementary material, which is available to authorized users.
Prevalence and burden of tobacco smoking
In 2012, approximately 45,500 deaths (18% of all deaths in Canada) were attributed to tobacco smoking [ 1 ]. Smoking continues to be a leading cause of preventable death and disability [ 2 , 3 ]. Among smoking-related deaths, most were attributable to cancers, cardiovascular disease, and respiratory diseases [ 1 , 4 ].
Worldwide, it is estimated that nearly one in seven adults smoke tobacco daily [ 5 ]. According to the Canadian Community Health Survey (CCHS), five million (16%) Canadians over the age of 12 years in 2017 smoked tobacco [ 6 ]. In Canada, daily or occasional smoking is higher in males (19% versus 13%), particularly among those 20 to 34 years of age (24%) [ 6 ]. Among females, smoking is most prevalent in those 50 to 64 years of age (17%) [ 6 ]. Higher rates of smoking have been shown in people with lower education (<secondary education: 20%; completion of university: 10%) and lower income (lowest household income: 23%; highest household income: 12%) [ 7 , 8 ]. The rate of smoking in Indigenous populations is two to three times the national average, ranging from 34 to 53% across First Nations, Métis, and Inuit populations [ 9 ]. Studies suggest that smoking rates are also higher in people with substance use disorders and mental health issues [ 10 – 12 ]. Although smoking prevalence has declined overall across Canada, smoking rates vary across the country, with Prince Edward Island reporting the lowest (12%) and Newfoundland and Labrador reporting the highest (20%) rates [ 13 ].
Smoking is the leading cause of cancer with evidence linking it to increased risk of several types of cancers including lung, mouth, upper aerodigestive tract, bladder, cervix, colon, and rectum [ 14 ]. Smoking also increases the risk of non-malignant respiratory diseases (e.g. chronic obstructive pulmonary disease, tuberculosis), cardiovascular disease (e.g. coronary heart disease, stroke, artherosclerosis, aortic aneurysm, peripheral vascular disease), reproductive issues (e.g. infertility, spontaneous abortion, premature birth, low birth weight), neonatal death, sudden infant death syndrome, early menopause, osteoporosis, and many other chronic health conditions [ 15 – 19 ]. Tobacco smoking using a water pipe or hookah is associated with lung and esophageal cancer as well as infectious diseases due to sharing of the pipe [ 20 – 22 ]. Exposure to second- and third-hand smoke also increases the risk of many diseases including stroke, lung cancer, cervical cancer, respiratory diseases, infections, perinatal and neonatal death, and sudden infant death syndrome [ 16 , 23 – 26 ].
Smoking is associated with lower health-related quality of life. Longitudinal data from the Canadian National Population Health Survey found that individuals who smoke tobacco had a lower health-related quality of life compared to those who had never smoked. Smoking cessation was associated with improvement in health-related quality of life. In women, health-related quality of life was similar to those who had never smoked tobacco after 10 years of cessation. In men, it took 20 years of cessation to achieve a health-related quality of life equivalent to those who had never smoked tobacco [ 27 ].
In 2012, the total cost of tobacco use in Canada was estimated at $16 billion CDN [ 1 ]. This estimate includes both direct (i.e. hospital expenditure, physician care, medications) and indirect (i.e. economic loss associated with premature death and disability) costs which were approximately $6.5 billion and $9.5 billion, respectively [ 1 ].
Smoking cessation, defined as quitting or the discontinuation of tobacco smoking, reduces the risk of smoking-related diseases and premature death [ 3 , 28 , 29 ]. Quitting at 30 years of age increases life expectancy by a decade while quitting at 40 and 50 years of age increases expectancy by 9 and 6 years, respectively [ 30 ]. For every two individuals who quit smoking tobacco, one will avoid a tobacco-related death [ 31 ]. According to the 2017 Canadian Tobacco, Alcohol and Drugs Survey, about 63% of Canadians who reported smoking at some point in their life have successfully quit smoking [ 13 ]. Among the 44% of respondents who made an attempt to quit in the past year, 16% made a single attempt while 12% attempted four or more times [ 13 ]. In 2017, reducing smoking consumption was the most common cessation method (approximately 63%) among survey respondents, followed by the use of pharmacotherapies (approximately 55%) [ 13 ]. Approximately 32% of those who attempted to quit tobacco smoking in 2017 used electronic cigarettes (e-cigarette) as a cessation method [ 13 ].
Stop smoking interventions
Nicotine replacement therapy (NRT) and cytisine are available over-the-counter while varenicline and bupropion are available by prescription [ 32 ]. NRT is the most widely used pharmacotherapy for smoking cessation available over the counter. NRT products administer nicotine thereby reducing withdrawal symptoms and cigarette cravings [ 33 ]. It is available in various forms (e.g. patches, chewing gum, lozenges, tablets, buccal spray, and inhalers) and nicotine dosages [ 34 ]. Cytisine is a naturally occurring nicotine partial agonist found in the laburnum plant and is pharmacologically similar to varenicline [ 35 ]. It is approved as a natural remedy for smoking cessation in Canada [ 36 ].
Varenicline and bupropion do not contain nicotine. Varenicline is a nicotine receptor partial agonist that triggers the release of dopamine thereby reducing nicotine withdrawal symptoms and relieving cravings [ 37 ]. Varenicline also prevents the stimulating effects of nicotine [ 38 ]. Bupropion, the only antidepressant medication approved for smoking cessation [ 39 ], is a non-competitive antagonist of nicotinic acetylcholine receptors [ 40 ] and also inhibits uptake of dopamine, serotonin, and noradrenaline [ 41 ]. Although the mechanism of action is unclear, bupropion may promote cessation by reducing nicotine withdrawal symptoms via inhibition of dopamine and noradrenaline reuptake [ 42 ].
Electronic cigarettes, also known as e-cigarettes, electronic nicotine (or non-nicotine) delivery systems, or vaporizers, represent another potential intervention strategy by which individuals employ behaviour substitution in their efforts to quit smoking. Most e-cigarettes are battery-operated and are used to inhale a vapour that can contain nicotine and other chemicals such as flavourings, propylene glycol, and/or vegetable glycerin [ 43 , 44 ]. A heating element within the device releases liquid that is vaporized into a fog or smoke-like cloud [ 43 ]. These devices can provide similar behavioural and sensory cues of smoking with no or lower levels of nicotine [ 44 ]. There is some evidence to suggest that e-cigarettes significantly reduce exposure to other toxic compounds found in combusted cigarette smoke such as carbon monoxide, acrolein, acetaldehyde, and formaldehyde [ 45 , 46 ]. However, other studies have found that some e-cigarette brands contain high levels of toxic metals including nickel, cadmium, chromium, lead, and manganese [ 47 ]. The recently passed Canadian Tobacco and Vaping Products Act (Bill S-5) now allows adults to legally purchase e-cigarettes containing nicotine in Canada. However, it bans the sale of e-cigarettes to individuals under 18 years of age, specific flavours that are appealing to youth (e.g. confectionary, soft drink), ingredients that suggest health benefits (e.g. vitamin, caffeine), and certain types of advertising and promotion (e.g. health benefits, products using tobacco brands) [ 48 ].
There are various behavioural interventions used for tobacco cessation. Broadly, behavioural interventions may promote smoking cessation directly, be directed to improve adherence to smoking cessation pharmacotherapies, or promote other health behaviour change along with the stopping smoking behaviour (e.g. healthy eating, alcohol reduction).
Behavioural interventions can be classified by intensity (very brief, brief, intensive), frequency of contact, modality of contact, type of provider, and content. These factors can influence the effectiveness of the intervention. Details on the specific behavioural change technique(s) (i.e. the content or “the smallest active ingredients of interventions capable of inducing change in behaviour” [ 49 ]) that are being targeted are essential in determining not only what components of behaviour support systems are effective, but how they can be replicated in practice [ 49 ]. A taxonomy of behavioural change techniques used in individual behavioural support for smoking cessation has been developed to support such evaluations [ 50 ]. Examples of behavioural change techniques include goal setting (e.g. setting a quit date), advice on altering routines to avoid exposure to smoking cues, and providing information regarding withdrawal symptoms [ 50 ].
Another aspect of behavioural change interventions is understanding the psychological theory underpinning the design of the intervention. For example, the Transtheoretical Model of Change, also known as the ‘Stages of Change’ model, is highly used in the smoking cessation literature, but not supported empirically in systematic review evaluations [ 51 , 52 ]. Although these theories may have face validity, evaluating them is important not only to understand effectiveness but also to avoid harms. Evidence suggests that stage-based approaches for smoking cessation are not more effective than non-stage interventions indicating that readiness or motivation to stop smoking may not be integral for quitting [ 51 , 52 ]. Further, stage-based interventions might prevent providers from offering effective treatment to those deemed unmotivated to stop smoking thereby prolonging their exposure to the toxic constituents of smoke.
Brief advice interventions consist of healthcare professionals providing verbal instructions with a “stop smoking message” [ 53 ]. These interventions may vary in intensity, frequency, and duration but generally only last a few minutes. Individual or group therapies are led by counsellors such as physicians, nurses, clinical psychologists, and counsellors. The objective of such interventions is to provide an opportunity for people who smoke to share cessation experiences; derive support; learn coping skills to manage cravings, lapses, and relapses; and promote self-control [ 54 ]. More intensive face-to-face interventions require greater effort and resources and may only reach a small segment of the smoking population [ 55 ]. Telephone counselling can supplement or replace these therapies as a way of providing services to a larger number of people [ 56 ]. These can take the form of proactive (i.e. counsellor-initiated) or reactive counselling (i.e. tobacco smoker-initiated) [ 57 ].
Self-help interventions are information aids, such as manuals or programmes, used by individuals without the direct support of healthcare professionals [ 55 ]. The goal is to provide some of the benefits of brief advice and counselling but without the necessary attendance. Traditional self-help materials, such as print, audio, and video recordings, can be more widely accessible and are increasing their reach via newer technology (e.g. web-based, mobile applications and games, streaming content) [ 58 ]. However, increased reach may not necessarily be more effective if the content of the instruction is not effective.
Some therapies, such as exercise-based interventions, have been used alone or as adjuncts to other interventions. Exercise alleviates withdrawal symptoms and relieves cravings [ 59 ]. Although the mechanism of action is unclear, several hypotheses have been proposed [ 59 , 60 ]. The biological hypothesis suggests that exercise and nicotine have similar impacts on beta-endorphins, cortisol, noradrenaline, and adrenaline [ 59 , 60 ]. For example, like nicotine, exercise stimulates the release of adrenaline and noradrenaline thereby relieving cravings [ 59 ]. Although the evidence is inconsistent, the beneficial effect of exercise on cessation may also be attributed to increases in positive affect or distraction from withdrawal symptoms and cravings [ 59 , 60 ].
Alternative therapies for smoking cessation include hypnosis, acupuncture (including acupressure and electrostimulation), and laser therapy [ 59 , 61 ]. It is hypothesized that acupuncture, acupressure, and laser therapy alleviate withdrawal symptoms by stimulating peripheral nerves which triggers release of opioid peptides, dopamine, enkephalin, and serotonin [ 62 ]. The mechanism of action underpinning the effect of hypnotherapy on smoking cessation is related to strengthening impulse control [ 63 ]. St. John’s Wort is a herbal product commonly used by patients as an alternative to standard antidepressant medications [ 64 ]. St. John’s Wort may promote smoking cessation by alleviating tobacco withdrawal symptoms and decreasing negative affect through various mechanisms including inhibition of monoamine oxidase A and B and dopamine and noradrenaline reuptake [ 39 , 65 ]. S-Adenosylmethionine (SAMe), a natural health product, promotes the production of dopamine and norepinephrine and may therefore alleviate tobacco withdrawal symptoms [ 66 ].
Current clinical practice and recommendations
In 2011, the Canadian Action Network for the Advancement, Dissemination and Adoption of Practice-informed Tobacco Treatment (CAN-ADAPTT) published recommendations for adults and specific populations (e.g. Indigenous, hospital-based, mental health, substance use disorders, pregnant and breastfeeding women, and youth) that were informed by six guidelines [ 67 ]. CAN-ADAPTT recommends that healthcare providers routinely ask patients about their tobacco use and advise those who smoke tobacco to quit. Those willing to begin treatment should be offered assistance such as brief advice, individual and group counselling (focused on problem-solving skills or skills training and providing support), self-help materials, motivational interviewing, or pharmacotherapies. Where possible, CAN-ADAPTT recommends combining counselling and pharmacotherapies as the preferred approach. Providers are encouraged to follow-up regularly and modify treatment as needed.
The Registered Nurses’ Association of Ontario (2017) released recommendations based on previous guidelines and a systematic review [ 68 ]. They recommend using brief interventions to screen individuals for tobacco use, developing person-centered tobacco intervention plans, referring tobacco users to intensive interventions and counselling on the use of pharmacotherapies (i.e. NRT, varenicline, bupropion), and evaluating the effectiveness of these interventions and adjusting as needed. They conclude that there is insufficient evidence regarding e-cigarettes, hypnotherapy, laser therapy, electrostimulation, acupressure, and acupuncture as cessation tools. For pregnant or postpartum women, they recommended intensive behavioural counselling, in conjunction with NRT.
Guidelines from international organizations
Guidelines from international organizations are consistent in recommending behavioural interventions and/or pharmacotherapies (i.e. NRT, bupropion, and varenicline) for smoking cessation. The UK National Institute for Health and Care Excellence (NICE, 2018) recommends individual or group behavioural support, very brief advice, bupropion, combination of short- and long-acting NRT, or varenicline in conjunction with behavioural support [ 69 ]. New Zealand’s Ministry of Health (2014) recommends brief advice (approximately 30 s), behavioural support, NRT, buproprion, varenicline, and nortriptyline. They consider a combination of behavioural and pharmacotherapy to be the most effective [ 70 ]. As part of their “Risk estimation and the prevention of cardiovascular disease” guideline, the Scottish Intercollegiate Guidelines Network (2017) recommends (1) varenicline or combination NRT (i.e. “interventions involving more than one type of nicotine replacement delivery”) alone or as part of a smoking cessation programme, and (2) bupropion and single NRT [ 71 ]. The US Preventive Services Task Force is currently updating their 2015 guideline [ 17 ]. The 2015 guideline, based on an overview of reviews [ 72 ], recommends behavioural interventions and approved pharmacotherapies (i.e. bupropion, varenicline, NRT). Only behavioural interventions are recommended for pregnant women as the evidence regarding pharmacotherapies was insufficient for this subgroup.
We did not identify any guideline that recommends the use of e-cigarettes for smoking cessation. However, NICE recommends that, when advising those interested in using e-cigarettes containing nicotine, primary health care providers should communicate that “many people have found them helpful to quit smoking cigarettes” and that e-cigarettes, while not without risk, are less harmful than tobacco smoking [ 69 ]. Similarly, Public Health England’s recently developed guidance for clinicians includes e-cigarettes as a smoking cessation option to discuss with patients. The guidance indicates that e-cigarettes present less risk than smoking and that they may be as or more effective than nicotine replacement therapy [ 73 ]. Other organizations state that there is currently insufficient evidence regarding the beneficial effects of e-cigarettes to make recommendations [ 17 , 71 ].
A majority of the available guidelines are out of date (i.e. last database search range: 2008 to 2015). Although recent, the NICE guideline excludes several smoking cessation interventions including varenicline, exercise, and alternative therapies (e.g. acupuncture, hypnotherapy) [ 69 ]. Limitations in existing clinical practice guidelines necessitate the development of a Canadian guideline on tobacco cessation strategies for adults.
Objective and key questions
The goal of this evidence review is to determine the effectiveness of stop smoking strategies for adults. Pharmacotherapy, behaviour change interventions, electronic cigarettes, exercise interventions, and complementary and alternative medicine interventions will be considered. Adult populations will include subgroups of interest such as those with co-morbid conditions, pregnant women, various demographic factors, and the distinction of opportunistic and treatment-seeking individuals. This synthesis will be used by the Canadian Task Force on Preventive Health Care (Task Force) to inform their development of a clinical practice guideline on stop smoking interventions.
The evidence review will consist of two stages. First, the overview of stop smoking interventions will be conducted. An overview of systematic reviews approach was selected to compile the evidence base in light of the large volume of primary and synthesized evidence that exists. The second stage will involve updating the most recent, comprehensive, and high-quality systematic review on e-cigarettes identified in the overview of reviews. Only the e-cigarettes strategy will be updated because of the increasing use of this strategy and its quickly evolving evidence base. This protocol document serves to outline the methodology for both review types.
For the purpose of the evidence review, tobacco smoking will refer to any form of smoked tobacco (e.g. cigarettes, pipes, cigars, cigarillos, via water pipe or hookah). This will not include tobacco use for traditional or ceremonial purposes such as that used by Indigenous people in sacred rituals and prayers for healing and purification [ 74 , 75 ].
Stage 1: Overview of systematic reviews of stop smoking interventions
The overview will evaluate the benefits and harms of stop smoking interventions among adults. If feasible, the overview will also evaluate the benefits and harms of behavioural change techniques (i.e. “the smallest active ingredients of interventions capable of inducing change in behaviour” [ 49 ]). Figure 1 illustrates the framework of the overview of systematic reviews. The overview will address the following key questions:
Analytic framework for the overview of reviews. *Practitioner advice (of varying length/intensity, and by various provider types); Intensive individual counselling (of varying length, of varying number of sessions, and by various provider types); Intensive group counselling (of varying length, of varying number of sessions, and by various provider types); Self-help interventions (print-based or web-/computer-based); Internet or computer-based interventions with counselling/support; Telephone-based interventions (e.g., mobile phone-based, quit lines/help lines) with counselling/support; Nicotine receptor partial agonists (varenicline and cytisine); Bupropion; Nicotine replacement therapy (e.g., patch, gum, lozenge, mist, inhaler); Ecigarettes; Exercise interventions; ‘Alternative’ therapies (e.g., acupuncture, acupressure, electrostimulation, hypnosis, St. John’s Wort, S-adenosylmethionine); Combinations of interventions. **Practitioner advice (of varying length/intensity, and by various provider types); Intensive individual counselling (of varying length, of varying number of sessions, and by various provider types); Intensive group counselling (of varying length, of varying number of sessions, and by various provider types); Self-help interventions (print-based or web-/computer-based); Internet or computer-based interventions with counselling/support; Telephone-based interventions (e.g., mobile phone-based, quit lines/help lines) with counselling/support; Other behaviour change interventions evaluated on a case-by-case basis with the Working Group
Key question 1a ( KQ1a ). What are the benefits and harms of interventions to promote cessation of tobacco smoking among adults?
Key question 1b ( KQ1b ). What is the comparative effectiveness (benefits and harms) of interventions to promote cessation of tobacco smoking among adults?
Key question 1c ( KQ1c ). What are the benefits and harms of behavioural change techniques or clusters of techniques to promote cessation of tobacco smoking among adults?
Stage 2: Updated systematic review on e-cigarette use for smoking cessation
This update will evaluate the benefit and harms of e-cigarettes to promote cessation of tobacco smoking among adults. This protocol outlines key questions and eligibility criteria for the updated review. However, should the candidate review from which to update have slightly different parameters, we will transparently declare any necessary changes from the protocol in the final report.
Key question 2a ( KQ2a ). What are the benefits and harms of electronic cigarettes for tobacco smoking cessation in adults?
Key question 2b ( KQ2b ). What is the comparative effectiveness (benefits and harms) of electronic cigarettes for tobacco smoking cessation in adults?
The evidence review will be completed by the Evidence Review and Synthesis Centre (ERSC) at the Ottawa Hospital Research Institute. A working group (WG) of Task Force members and external content experts was formed for development of the topic, refinement of the key questions and scope, and rating of outcomes. Outcomes were rated on a scale of 1 to 9 according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology; those rated as critical (mean score 7 to 9) and important (mean score 4 to 6) for decision-making were selected. Patients identified through patient engagement activities conducted by the St. Michael’s Hospital Knowledge Translation Program have also rated the outcomes. The process of incorporating patient priorities is described in the CTFPHC’s Patient Engagement Protocol ( https://canadiantaskforce.ca/methods/patient-preferences-protocol/ ).
Reporting of this protocol was guided by the PRISMA Statement for Protocols (PRISMA-P) to the extent possible and where appropriate [ 76 ] (Additional file 1 ). The protocol is registered in PROSPERO ( https://www.crd.york.ac.uk/PROSPERO/ ) (CRD42018099691, CRD42018099692). The final overview will be reported using the Preferred Reporting Items for Overviews of systematic reviews including harms pilot checklist (PRIO-harms) [ 77 ], and the updated systematic review will be reported using PRISMA [ 78 ].
A team of clinical and content experts will be consulted at key points during the conduct of the evidence review. Amendments to this protocol will be noted in the final report.
Guidelines for the conduct of overviews of reviews are currently lacking [ 79 ]. Given this current gap, the methodology for this overview will be guided by the Cochrane Handbook of Systematic Reviews of Interventions ( Chapter 22 ) [ 80 ] as well as other available reports on overview methodology [ 79 , 81 – 85 ].
The search strategy will be developed and tested through an iterative process by an experienced medical information specialist in consultation with the review team. We will search Ovid MEDLINE®, Ovid MEDLINE® Epub Ahead of Print, In-Process & Other Non-Indexed Citations, PsycINFO, Embase Classic + Embase, and the Cochrane Library on Wiley. Databases will be searched from 2008 to the current date. The draft search strategy can be found in Additional file 2 . The search strategy will be peer-reviewed using the PRESS 2015 guideline [ 86 ]. Results of the PRESS reviews will be provided in an appendix in the final report.
We will search for unpublished literature and reports of ongoing and completed reports using the Canadian Agency for Drugs and Technologies in Health (CADTH) Grey Matters checklist [ 87 ] and through searches of the following websites: CADTH, Ontario Tobacco Research Unit, The Canadian Partnership Against Cancer (cancerview.ca), SurgeonGeneral.gov , Philip Morris, Foundation for a Smoke-free World, Public Health England, Tobacco.org , Truth Initiative, Physicians for a Smoke-Free Canada, Centers for Disease Control and Prevention Smoking and Health Resource Library, Canadian Cancer Society, American Cancer Society, American Thoracic Society, US National Cancer Institute, US National Comprehensive Cancer Network, National Institute for Health and Care Excellence, World Health Organization Framework Convention on Tobacco Control, World Health Organization’s International Clinical Trials Registry Platform, OpenTrials.net , International Prevention Research Institute, North American Quitline Consortium website, and the Ottawa Heart Institute’s Ottawa Model for Smoking Cessation. We will also scan the bibliographies of relevant reviews and other identified overviews for grey literature and references not identified in our database search. Grey literature searching will be restricted to English and French language documents and will be limited to what can be completed within 1 week by one reviewer.
KQ1a and KQ1b will examine interventions that can be delivered or referred to in the primary care setting. This includes certain behavioural change interventions, pharmacotherapies, e-cigarettes, exercise interventions, and alternative therapies (Table 1 ). Interventions that cannot be delivered or referred to by a wide variety of primary care practitioners (e.g. quit-to-win contests, biomedical risk assessment, aversive smoking, incentivized cessation) as well as specific behavioural counselling techniques (e.g. motivational interviewing, stage of change-based counselling) which require specialized training that has been shown to vary [ 88 ] and may not be readily available to all primary care practitioners will be excluded. We will also exclude reviews on broader public health interventions (e.g. mass media, taxation, packaging restrictions) as well as those on broad lifestyle interventions not specific to tobacco smoking behaviour and that do not attempt to isolate for the effect of our included interventions (i.e. when delivered as part of a multifaceted lifestyle intervention). Generally, pharmacotherapies that are not approved by Health Canada as smoking cessation aids (e.g. clonidine, lobeline, anxiolytics, nortriptyline, opioid antagonists, silver acetate, rimonabant) or not available in Canada (e.g. Nicobrevin, Nicobloc, nicotine vaccines, mecamylamine) will be excluded. However, due to their ease of access, an exception will be made for St. John’s Wort (sold in various forms in pharmacies and health stores across Canada), cytisine, and S-adenosylmethionine (SAMe) (licensed natural health products).
Inclusion and exclusion criteria for key question 1a and 1b
a In this context, primary care practitioners refer to the provider of first contact for the delivery or referral to stop smoking interventions. This could include physicians, nurses, pharmacists, oral health professionals, counsellors, etc.
b Reviews examining specialized behavioural counselling interventions will be excluded, as the target audience for this guideline is primary care. These interventions require specialized training, the amount of which has been shown to vary but can be substantial [ 88 ] and may not be readily available for many primary care practitioners
c We define “self-help interventions” to include “any manual or programme to be used by individuals to assist a quit attempt not aided by health professionals, counsellors or group support” as per the definition in Hartmann-Boyce et al. [ 55 ]. This differs from interventions that utilize computers, the web, or mobile phones to deliver interventions that involve counselling/support, although the platform of delivery may be the same
d Certain products are relevant for inclusion despite not being approved for use as smoking cessation aids by Health Canada, due to their ease of access. These include St. John’s wort (sold in various forms in pharmacies and health stores across Canada), cytisine, and S-adenosylmethionine (licensed natural health products)
e Patches, gums, mists/sprays, and inhalers are the available forms of NRT in Canada
f The practice of using e-cigarettes (“vaping”; including e-cigarettes with nicotine) is increasingly popular, with use being higher among tobacco smokers [ 89 ]. Data from the CDC suggest that it was the most commonly used method to quit smoking in 2014–2016 after simply giving up cigarettes all at once or gradually cutting back [ 90 ]. The massive interest in these products from the public and tobacco smokers, as well as the evolving evidence base surrounding them, makes them essential to include
g The outcome “relapse” was initially considered critical based on WG rating. However, based on discussion with WG members it was decided that this outcome should be considered important. It was also decided that this outcome is most important for KQ1b
h Although initially rated as being of limited importance by the WG, based on discussions with WG members, it was decided that this outcome should be considered as important. Clinical experts and patients rated this outcome as important
i Reviews will be considered systematic if they meet the four following criteria: (1) searches at least one database, (2) reports their selection criteria, (3) conducts quality or risk of bias assessment on included studies, and (4) provides a list and synthesis of included studies
j Overviews will included if they meet the following criteria: (1) search at least one database, (2) report their selection criteria and how they will handle the inclusion of overlapping reviews, (3) provide information on the quality or risk of bias assessment of studies included in reviews, (4) provide a list of relevant reviews, (5) report the synthesized evidence from the included reviews, and (6) explicit declaration that the decision to undertake the network meta-analysis was made with firsthand knowledge of the primary studies, to ensure appropriateness of the analysis
Systematic reviews for KQ1a and KQ1b will be selected for inclusion according to the eligibility criteria outlined in Table 1 [ 89 , 90 ].
In addition to the other interventions listed in Table 1 , the intent of KQ1a/b is to capture reviews which examine behavioural change interventions (e.g. practitioner advice, counselling, self-help interventions). These reviews may provide information on the active components of these interventions, referred to as behavioural change techniques . Examples of such techniques include providing information on consequences of smoking, explaining the importance of abrupt cessation, strengthening ex-smoker identity, and receiving prompt commitment from the patient [ 50 ]. If there is sufficient data, subgroup analysis by behavioural change technique or clusters of techniques will be performed for KQ1a/b (see the “ Subgroup analysis ” section).
While the intent of KQ1a/b is to synthesize reviews of behavioural change intervention s (these reviews may or may not report the behavioural change techniques used as part of these interventions), the intent of KQ1c is to capture reviews which specifically examine the effectiveness of behavioural change techniques or cluster of techniques. A taxonomy of behavioural change techniques used in smoking cessation interventions will guide the coding of techniques encountered in the literature [ 50 ].
Eligibility of reviews for KQ1c will be evaluated in consultation with the WG on a case-by-case basis with selection for inclusion dependent on applicability to the primary care setting. For example, the WG may decide to include behavioural change interventions outside of those listed in Table 2 or may decide to include reviews in specialty settings if the review examines behavioural change techniques that can reasonably be applied in primary care. Selection of reviews for KQ1c will be guided by the eligibility criteria outlined in Table 2 . All decisions regarding the selection of reviews will be reported in the completed review.
Inclusion and exclusion criteria for Key Question 1c
b We define “self-help interventions” to include “any manual or programme to be used by individuals to assist a quit attempt not aided by health professionals, counsellors or group support” as per the definition in Hartmann-Boyce et al. [ 55 ]. This differs from interventions that utilize computers, the web, or mobile phones to deliver interventions that involve counselling/support, although the platform of delivery may be the same
c The outcome “relapse” was initially considered critical based on WG rating. However, based on discussion with WG members, it was decided that this outcome should be considered important. It was also decided that this outcome is most important for head-to-head comparisons. We will only collect data for this outcome when the comparator is an active intervention such as behavioural change techniques or cluster of techniques delivered as part of a behavioural change intervention different from that offered to the intervention group (e.g. behavioural change technique or cluster of techniques delivered as part of practitioner advice versus intensive individual counselling)
d Although initially rated as being of limited importance by the WG, based on discussions with WG members, it was decided that this outcome should be considered as important. Clinical experts and patients rated this outcome as important
e Reviews will be considered systematic if they meet the four following criteria: (1) searches at least one database, (2) reports their selection criteria, (3) conducts quality or risk of bias assessment on included studies, and (4) provides a list and synthesis of included studies
6 Overviews will included if they meet the following criteria: (1) search at least one database, (2) report their selection criteria and how they will handle the inclusion of overlapping reviews, (3) provide information on the quality or risk of bias assessment of studies included in reviews, (4) provide a list of relevant reviews, (5) report the synthesized evidence from the included reviews, and (6) explicit declaration that the decision to undertake the network meta-analysis was made with firsthand knowledge of the primary studies, to ensure appropriateness of the analysis
Duplicates will be identified and removed using Reference Manager [ 91 ]. Title and abstract and full-text screening will be conducted using an online systematic review managing software, Distiller Systematic Review (DistillerSR) Software© [ 92 ]. Two reviewers will independently screen the title and abstracts of citations using the liberal accelerated method (i.e. a second reviewer verifies records excluded by a first reviewer). References will be randomized, and screening will be done concurrently to ensure that each reviewer cannot determine whether a given reference was excluded by another reviewer. The full text of potentially relevant citations will be retrieved, and two reviewers will independently assess the article for relevancy. If unclear whether a review is eligible after duplicate review, a third person will be consulted before excluding the review. Conflicts will be resolved by consensus or by consulting with a third team member. The reasons for exclusion at full-text screening will be documented.
Both screening forms will be piloted by reviewers prior to commencement of screening, with adjustments made, as needed, to maximize efficiency. If necessary, articles will be ordered via interlibrary loan. Only those received within 30 days will be included. Exclusions due to unavailability of articles will be noted.
A list of potentially relevant reviews available only in abstract form will be made available, but these studies will not be included in the overview.
Data mapping and overlap detection
Given the proliferation of systematic reviews [ 81 ], we anticipate that we will encounter multiple systematic reviews covering the same research question (i.e. population, intervention, comparison, outcomes, time points, and settings). Such reviews are expected to rely on the same evidence base (i.e. same studies and data); therefore, inclusion of these overlapping systematic reviews may potentially bias the overview findings as the same primary studies are counted more than once [ 93 ].
While there is currently no optimal approach for addressing the issue of overlapping reviews [ 79 ], existing options include the following: (1) limiting inclusion to a single systematic review using a priori established criteria or (2) including all available reviews and computing the degree of overlap [ 79 , 81 , 93 ]. Limiting inclusion to a single systematic review for a given research question may result in missing data, and while inclusion of all available reviews may improve comprehensiveness, it also increases workload and complexity [ 81 ].
To detect and address overlapping systematic reviews, we will first map the research questions (i.e. population, intervention, comparator, outcomes, time points, setting) and characteristics (i.e. date of last search, comprehensiveness, and quality) of all eligible systematic reviews. Where there are multiple reviews addressing the same research question, we will compare the review characteristics and exclude those which are “superseded by a later review, or (contain) no additional (studies) compared with a review of similar, or higher, methodological quality” [ 79 , 94 ]. For example, an up-to-date, high-quality systematic review may report on a single intervention (e.g. acupuncture) while another review, of lower methodological quality and with an older search date, may report on a number of alternative therapies including acupuncture. Although superseded by the former in terms of quality and recency, the latter review captures evidence on additional interventions. Inclusion of both reviews would be necessary to capture all available information on alternative therapies for smoking cessation. In this particular example, we would rely on the former review for data on acupuncture and on the latter for all other interventions (i.e. excluding acupuncture). As described by Pollock et al., the decision to exclude reviews based on these criteria can be a complex process often due to slight differences in research questions [ 94 ]. The criteria above will be used as a guide; with the pool of candidate reviews in hand, information will be mapped to facilitate decisions about potential exclusion. Decisions to exclude reviews due to redundancy will be tracked and documented in a table of characteristics of excluded reviews.
In cases where overlapping data cannot be avoided (i.e. overlapping reviews with similar search dates, quality, and comprehensiveness), we will include overlapping reviews and calculate the degree of overlap using the corrected covered area (CCA) [ 83 , 93 ]. Although reporting the degree of overlap is recommended, it does not minimize or omit potential bias caused by inclusion of overlapping reviews [ 83 , 93 ]. The CCA is calculated using the formula below, where N is the total number of studies across reviews (including multiple occurrences of the same study), r is the number of unique (first occurrence) studies, and c is the number of reviews.
The benefit of the correction for primary studies is that it diminishes the impact of large reviews that may add area but not necessarily overlap. Hence, the CCA corrects for the first time that studies are counted. The higher the CCA value, the greater the overlap among reviews: CCA value 0–5 would represent slight overlap, 6–10 of moderate overlap, 11–15 of high overlap, and > 15 of very high overlap.
Mapping of review characteristics will be conducted by a single reviewer. The decision to exclude a review, using the criteria described above, will be made by two reviewers via discussion, with review by the guideline WG. Where overlapping reviews are included, concordance of results/conclusions will be explored (see the “ Discordance ” section of the manuscript).
Quality assessment of systematic reviews
The methodological quality of reviews will be evaluated according to the AMSTAR 2 instrument (Additional file 3 ). This updated version of the original AMSTAR tool allows for the appraisal of systematic reviews of randomized and non-randomized studies of interventions [ 95 ]. We will evaluate each review against the 16-item instrument. An overall rating of quality will be assigned according to the algorithm suggested by Shea et al. [ 95 ]. Reviews failing to meet any of the seven critical AMSTAR 2 items will be deemed to have a “critical flaw” while non-fulfillment of the remaining items will be deemed a “non-critical weakness” of the review (Additional file 4 ). Reviews with one or more critical flaws will receive a low or critically low rating, respectively. Reviews with no critical flaws will be considered either high or moderate quality depending on the number of non-critical weaknesses (i.e. high-quality reviews have a maximum of one non-critical weaknesses and moderate-quality reviews have more than one weakness). Aside from decisions on inclusion related to assessing duplicate or overlapping reviews, reviews will not need to meet a particular threshold for methodological quality to be included.
The quality of systematic reviews will be evaluated by one reviewer and verified by another. Disagreements regarding by-item and overall rating of quality will be resolved by consensus or third-party adjudication if consensus cannot be reached.
Data extraction and management
Data extraction forms will be developed a priori in DistillerSR and pilot tested on a sample of studies to adjust forms, where needed, to maximize efficiency. Full data abstraction will be completed by one reviewer and verified by a second reviewer. Disagreements will be resolved by consensus or third party adjudication if consensus cannot be reached.
Additional file 5 lists draft items to be collected from reviews during data extraction. We will extract data as synthesized and/or reported in the reviews. We will not consult primary studies for the purpose of data extraction, risk of bias assessment, or for verifying the accuracy of the data reported in the systematic reviews.
We will collect data regarding outcomes of interest as reported by review authors. For reviews reporting a meta-analysis, we will collect the pooled effect estimates, corresponding confidence intervals, and results of statistical tests for heterogeneity (e.g. number of studies, number of participants, chi-square, Cochrane Q, corresponding p values, I 2 ).
For network meta-analyses, ideally sufficient evidence from direct comparisons will be available, and treatment effect estimates along with measures of uncertainty from those analyses will be extracted. However, where little to no evidence from direct comparisons is available and indirect comparison data exist, we will extract both analyses and determine extent of consistency of results and make appropriate interpretations. For indirect comparison analyses, effect estimates and corresponding credible intervals will be collected from indirect comparisons. We will extract and transparently describe if and how authors’ ranking of treatments was used, ensuring appropriateness; ranking may take the form of rank probabilities, mean/median rank, surface under the cumulative ranking (SUCRA) curve, or a P-score [ 96 – 98 ].
For outcomes where a pooled analysis was not performed, how data are extracted will be informed by authors’ reporting. For example, if effect estimates from primary studies are reported, then a range of those effects could be extracted. In the absence of optimal quantitative data, a narrative summary of findings will be extracted from the reviews. Data will be collected for all reported and relevant (see Table 1 ) time points of follow-up.
Where reviews partially overlap with the scope of interest, such that a subset of studies may be conducted in a different population (e.g. adolescents), setting (not relevant to primary care), or other relevant parameter, we will attempt to determine whether the analyses undertaken are sufficiently direct to the overview question by considering the relative contribution of those studies to the analysis, subject to adequate reporting of this information. How these analyses are handled (inclusion versus exclusion) will be reviewed with the WG for their input; those decisions and any accompanying uncertainty in the applicability of the included results will be detailed in the report.
The overview will seek information on various factors that would typically be considered variables for effect modification. In the case of an overview, we expect to encounter reviews that have undertaken subgroup or meta-regression analyses. There may also be reviews through the process of defining scope that would have focused their interest according to a particular factor, such as evaluating the effects of an intervention in a particular setting. Reviews addressing both of these approaches will be included. Variables of interest listed below are those that we have considered as being potentially important effect modifiers that would influence the development of guideline recommendations or implementation considerations. According to guidance, we have restricted subgroup analysis to characteristics that are measured at baseline rather than after randomization [ 99 ].
- Fewer versus more quit attempts (specific groupings will depend on what is found in the literature)
- Opportunistic versus individuals seeking treatment
- Baseline level of nicotine dependence (e.g. using a validated scale or cigarettes per day as a proxy)
- By demographic factors (age, SES, sex, ethnicity, LGBTQ+)
- By comorbid conditions (e.g. mental illness, HIV infection, cardiovascular disease, COPD, obesity, substance use disorder)
- By pregnancy status
- Dose, type, duration, number of sessions
- Specific forms of an intervention (e.g. yoga as a form of exercise)
- KQ1a/b: behavioural change technique (e.g. providing information on consequences of smoking, explaining the importance of abrupt cessation, receiving prompt commitment from the patient)
- Family medicine clinics
- Walk-in clinics
- Smoking cessation clinics
- Urgent care facilities
- Emergency departments
- Public health units
- Dental offices
- Behavioural health/substance use treatment facilities (ambulatory or outpatient)
- Academic research settings
- By industry funding status (subgroup and/or sensitivity analyses performed in eligible reviews will be sought)
While there are both simple (e.g. comparing 95% confidence intervals, statistical test of summary estimates) and complex (e.g. Bucher method, network meta-analysis) methods available for indirect comparisons of treatments across reviews, all approaches are based on the assumption that the primary studies are similar [ 85 , 100 ]. This would require overview authors to be familiar with the primary study literature and not to rely solely on review authors’ reporting of the primary studies [ 85 ]. Given that we will not have opportunity to read and become familiar with the primary study reports themselves, conducting network meta-analyses or informal indirect comparisons of interventions will not be performed. As noted above, any existing network meta-analyses located in the literature will be included and commented on.
Similarly, subgroup analyses within reviews will provide evidence for effect modification. For factors that comprise the focused scope of a given review, as described in the previous section, we will provide the appropriate statements relating to interpretation but be unable to perform comparisons across reviews in the absence of the direct familiarity with the primary studies. Where possible, we will evaluate the credibility of subgroup analyses [ 99 , 101 , 102 ].
Although a narrative synthesis of available evidence to ensure appropriate interpretation will be provided for readers, the use of GRADE tables will facilitate appropriate presentation of this information in tabular form to avoid juxtaposition that may lend to inappropriate comparisons on the part of the reader [ 83 , 85 , 103 ]. Comparisons across reviews with similar scope will be limited to an assessment of the extent of concordance or discordance of the review results and, for discordance, an exploration of a potential explanation.
Reviews that overlap in terms of scope may present discordant results and/or conclusions due to variation in eligibility criteria, data extraction, risk of bias assessment, data synthesis approach, or interpretation of the results [ 104 ]. In those instances, we will investigate the source(s) of discordance using the algorithm developed by Jadad et al. as a guide [ 104 , 105 ].
Where overlapping reviews of similar quality rely on the exact same studies, we will investigate whether discordance was due to differences in data extraction (e.g. reviews may have extracted data at different time points of follow-up or reviews may vary regarding definitions of outcomes or outcome measurement methods), heterogeneity testing (e.g. reviews differ in their investigation of clinical and methodological heterogeneity and the decision in which to conduct a meta-analysis), or the synthesis approach (e.g. quantitative versus qualitative synthesis or in the statistical methods used).
If overlapping reviews do not rely on the exact same studies, we will investigate differences in the eligibility criteria. If similar, we will evaluate whether discordance is attributable to differences in the search strategies (e.g. number and type of databases searched, whether grey literature was searched) or in the application of the eligibility criteria. If reviews use different eligibility criteria, Jadad et al. [ 105 ] recommend comparing the publication status of primary studies (e.g. whether there are differences in the inclusion of unpublished reports), evaluation of the methodological quality of primary studies (e.g. differences across reviews regarding the assessment of quality of primary studies and how quality was used in interpreting the results of the review), language restrictions, and quantitative synthesis [ 105 ].
In addition to exploring sources of discordance, we will categorize discordance as follows: (1) direction of effect (i.e. reviews report results in opposite directions), (2) magnitude of effect (i.e. reviews report results in the same direction but differ in the size of the effect estimate), and (3) statistical significance (i.e. statistical significance reached in one review but not others) [ 105 ].
Quality of the body of evidence
The Task Force endorses the use of GRADE methodology for assessing the quality of the body of evidence for critical and important outcomes [ 106 ]. Currently, there are no methods to evaluate the strength of evidence across systematic reviews [ 83 ]. For each outcome of interest reported in each individual review, we will provide GRADE assessments by intervention/comparison [ 107 ]. We will not evaluate the strength of the evidence across reviews.
For reviews that have used GRADE methods, we will provide results for the overall quality of evidence, including reasons for downgrading. If available, we will also report the ratings for each of the five domains of GRADE (i.e. risk of bias, imprecision, indirectness, inconsistency, publication bias). We will not consult primary studies as a quality control measure.
If GRADE methods were not used in a given review, we will attempt to conduct GRADE assessments using information available in the review (e.g. risk of bias assessments). This will likely be challenging due to reporting issues; therefore, we will provide our best interpretation based on the available information and note any limitations. For systematic reviews that include a network meta-analysis, using information reported in the review, we will evaluate the quality of evidence using the GRADE extension for network meta-analysis [ 108 ]. As above, we will not consult primary studies for the purpose of conducting GRADE assessments. We will make note if it is not possible to conduct GRADE for a given review or outcome.
Stage 2: Updated systematic review on electronic cigarettes for smoking cessation
The search strategy for this update will be developed using the search strategy of the candidate systematic review, once identified. The search strategy of the candidate review will be evaluated and modified as necessary. Databases will be searched from the last search date of the review. Using the OVID platform, we will search Ovid MEDLINE®, Ovid MEDLINE® Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Embase Classic + Embase, and PsycINFO. We will also search the Cochrane Library on Wiley. The final search will be peer-reviewed using the PRESS 2015 guideline [ 86 ]. Results of the PRESS reviews will be provided in an appendix in the final report. The grey literature will be searched using the same approach outlined for the overview of reviews.
Studies will be selected for inclusion using the criteria outlined in Table 3 .
Inclusion and exclusion criteria for an updated review on e-cigarettes
a Nicotine and non-nicotine containing e-cigarettes can serve as either an intervention or comparator
b The outcome “relapse” was initially considered critical based on WG rating. However, based on discussion with WG members, it was decided that this outcome should be considered important. It was also decided that this outcome is most important for KQ1b
c Although initially rated as being of limited importance by the WG, based on discussions with WG members, it was decided that this outcome should be considered as important. Clinical experts and patients rated this outcome as important
Study selection and data extraction
Study selection and data extraction will follow the same process described for the overview of reviews. Where study eligibility is unclear, authors will be contacted by email twice over 2 weeks for additional information.
We will collect both self-report and biochemically validated tobacco abstinence and relapse. Data will be collected for all reported and relevant (see Table 3 ) time points of follow-up. Where needed, we will convert data (e.g. standard error to standard deviation) to facilitate consistent presentation of results across studies. Authors will be contacted by email twice over 2 weeks if any information is missing or unclear. Refer to Additional file 6 for a list of draft items to be collected during data extraction
We will consult studies included in the original review to ensure that all outcomes of interest (Table 3 ) have been captured.
Risk of bias assessment
For consistency, risk of bias assessments/quality appraisal will be performed for all available studies (i.e. studies included in the original review and newly identified studies). The risk of bias of randomized and non-randomized controlled trials will be assessed by one reviewer using the Cochrane risk of bias (ROB) tool [ 109 ] (Additional file 7 ). We will consider industry funding under the “other sources of bias” domain of the tool. A modified version of the Scottish Intercollegiate Guidelines Network critical appraisal tool [ 110 ] (Additional file 8 ), which accounts for potential sources of bias including that arising from industry funding, will be used to evaluate the quality of prospective cohort studies. Verification will be done by a second reviewer. Disagreements will be resolved by consensus or third-party adjudication.
Some domains are outcome-specific and will be assessed at the outcome level. Overall risk of bias for the body of evidence will be evaluated according to the importance of domains, the likely direction of bias, and the likely magnitude of bias [ 109 ]. The Agency for Healthcare Research and Quality guidance will be followed for evaluating risk of bias for outcome and analysis reporting bias [ 111 ].
Study characteristics will be summarized narratively and presented in summary tables. Where possible, relative and absolute effects with 95% confidence intervals will be calculated for the GRADE summary of findings and evidence profile tables. Risk ratios and risk differences will be used to report effects for dichotomous data. For calculating the risk difference from meta-analyzed data, we will use the median baseline risk for the control group in the included studies, although we may perform sensitivity analysis using differing baseline risks if thought to be suitable. For continuous outcomes, mean difference (i.e. difference in means) effect measures will be used for outcomes using the same measure and standardized mean differences for outcomes using different measures, consistent with GRADE guidance [ 112 ].
We will examine the extent of clinical and methodological heterogeneity to determine appropriateness of performing meta-analysis. The Cochrane’s Q (considered statistically significant at p < 0.10) and I 2 statistic will be used to assess the statistical heterogeneity across included studies [ 113 , 114 ]. If appropriate, data from the original systematic review will be meta-analyzed with data from newly identified studies, using random effects models. For time-to-event data, the hazard ratio will be pooled using the generic inverse variance method. Analyses will be stratified by study design. For observational studies, we will use adjusted risk estimates in the meta-analysis.
Should meta-analysis not be appropriate due to considerable heterogeneity, the range of effects will be presented and results will be discussed narratively. Studies will also be presented in a forest plot without a pooled risk estimate. Clinical and methodological sources of heterogeneity will also be explored using subgroup, sensitivity, and/or meta-regression analyses, depending on how data are reported in studies. We will follow previously published guidance for meta-regression [ 115 ].
Sparse binary data and studies with zero events
Results will be synthesized narratively if studies report rare events. The risk difference will be used for outcomes (e.g. serious adverse events) where at least one intervention group contains zero events.
If there are sufficient data, the following subgroup analyses will be conducted:
- By use of other substances (alcohol, cannabis, opioids)
- By setting (e.g. family medicine clinics, walk-in clinics, urgent care facilities)
- Nicotine content (groupings will depend on what is found in the literature)
- Intensity of behavioural therapy (groupings will depend on what is found in the literature)
- Duration of e-cigarette usage as part of the intervention (groupings will depend on what is found in the literature)
- By type or generation of e-cigarette device
- By industry funding
Sensitivity analyses restricted to low risk of bias studies may be performed. Sensitivity analyses may also be performed to explore statistical heterogeneity or to evaluate the impact of various decisions made during the conduct of the review.
Small study effects
To evaluate small study effects, a combination of graphical aids and/or statistical tests will be performed if there are at least 10 studies in the analysis.
The Cochrane Review Manager software version 5.3 [ 116 ] will be used to conduct analyses. Where needed, Comprehensive Meta-Analysis (CMA) or Stata may be used.
Grading the quality of evidence and interpretation
For critical and important outcomes, the GRADE framework [ 106 , 117 ] will be used to assess the quality of the evidence.
Smoking is a leading cause of preventable death and disability, accounting for nearly 20% of all deaths in Canada. It is estimated that the cost of tobacco use in Canada is around $16 billion CDN, when considering factors such as hospital expenditure, physician care, and economic losses associated with premature death and disability. In response to this important public health care issue, the Canadian Task Force on Preventive Health Care will be developing a national tobacco smoking cessation guideline informed by an overview of systematic reviews of the benefits and harms of various stop smoking interventions for adults and relevant subpopulations, where available. This document has outlined the methods for undertaking the overview and an update of e-cigarette evidence for that overview.
PRISMA Statement for Protocols (PRISMA-P) checklist. (DOCX 18 kb)
Search strategy for the overview of reviews. (DOCX 16 kb)
AMSTAR 2 Critical Appraisal Tool. (DOCX 77 kb)
AMSTAR 2 critical domains for assessing overall rating of quality. (DOCX 14 kb)
Draft data extraction items for the overview of reviews. (DOCX 13 kb)
Draft data extraction items for the updated review of e-cigarettes for smoking cessation. (DOCX 12 kb)
Cochrane risk of bias tool. (DOCX 29 kb)
Modified SIGN methodology checklist for cohort studies. (DOCX 26 kb)
Stakeholder feedback. (DOCX 34 kb)
Other members of the Canadian Task Force on Preventive Health Care who provided additional comments: John Leblanc, Guylène Thériault, John Riva. Detailed descriptions of each member are available at https://canadiantaskforce.ca . The authors also acknowledge Marion Doull and Rachel Rodin from the Public Health Agency of Canada for their input and direction during project scoping and refinement.
Funding for this protocol and subsequent evidence review is provided by the Public Health Agency of Canada. This funding will support all phases of conduct of the evidence review, including the search and selection of the evidence, collection of the data, data management, analyses, and writing. The funder was involved in the development of the protocol and will give approval to the final version. For the conduct of the review, the funder will also be given opportunity to comment, but final decisions will be made by the review team. In addition, the funder will not be involved in study selection, data extraction, or analysis.
Availability of data and materials
Abbreviations, authors’ contributions.
MH, GT, AB, and AS drafted the protocol. BS developed the search strategy and provided text for the protocol. JL, BJS, BH, and VW critically reviewed the protocol and provided methodological expertise. SLB, PS, SJO, DM, SP, and JP reviewed the protocol and provided clinical expertise for the review. MM provided a patient perspective for the protocol. Members of the Tobacco Working Group for the Canadian Task Force on Preventive Health Care (BT, SG, EL, DLR, BW) critically reviewed and provided feedback on the protocol. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Consent for publication.
Written informed consent to publish was obtained from the stakeholders who provided feedback on the protocol. A copy of the written consent is available for review by the Editors-in-Chief of this journal. The stakeholder feedback has been anonymized and included as Additional file 9 .
BH has received consultancy fees from Cornerstone Research Group for methodologic advice related to systematic reviews and meta-analysis and is a member of the Editorial team for Systematic Reviews . PS reports grants and research support from Pfizer Inc., Bhasin Consulting Fund, and Patient Centered Outcomes Research Institute; consulting fees from Pfizer Canada Inc., Evidera Inc., Johnson & Johnson Group of Companies, Medcan Clinic, NVision Insight Group, and Myelin & Associates; receival of drugs free of charge or at a discounted rate for study through open tender process from Johnson & Johnson, Novartis, and Pfizer Inc.; assisted in organizing the Pfizer Canada Inc. Advisory Board events; and speaking engagements (content not subject to sponsor approval)/honoraria from Pfizer Inc. The remaining authors declare that they have no competing interests.
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Mona Hersi, Email: ac.irho@isrehm .
Gregory Traversy, Email: [email protected] .
Brett D. Thombs, Email: [email protected] .
Andrew Beck, Email: ac.irho@kceba .
Becky Skidmore, Email: moc.sregor@eromdiksb .
Stéphane Groulx, Email: [email protected] .
Eddy Lang, Email: [email protected] .
Donna L. Reynolds, Email: [email protected] .
Brenda Wilson, Email: ac.num@nosliwb .
Steven L. Bernstein, Email: [email protected] .
Peter Selby, Email: [email protected] .
Stephanie Johnson-Obaseki, Email: moc.liamg@ikesabonosnhojs .
Douglas Manuel, Email: ac.irho@leunamd .
Smita Pakhale, Email: ac.hot@elahkaps .
Justin Presseau, Email: ac.irho@uaesserpj .
Susan Courage, Email: [email protected] .
Brian Hutton, Email: ac.irho@nottuhb .
Beverley J. Shea, Email: ac.irho@aehsb .
Vivian Welch, Email: gro.noitaroballocllebpmac@hclewv .
Matt Morrow, Email: [email protected] .
Julian Little, Email: ac.awattou@elttilj .
Adrienne Stevens, Email: ac.irho@snevetsda .
- Summary of Recommendations
- USPSTF Assessment of Magnitude of Net Benefit
- Practice Considerations
- Update of Previous USPSTF Recommendation
- Supporting Evidence
- Research Needs and Gaps
- Recommendations of Others
- Article Information
See the Figure for a more detailed summary of the recommendations for clinicians. See the Practice Considerations section for more information on recommended behavioral interventions and pharmacotherapy and for suggestions for practice regarding the I statements. USPSTF indicates US Preventive Services Task Force.
USPSTF indicates US Preventive Services Task Force.
eFigure. US Preventive Services Task Force (USPSTF) Grades and Levels of Evidence
- USPSTF Review: Interventions for Tobacco Cessation in Adults, Including Pregnant Persons JAMA US Preventive Services Task Force January 19, 2021 This systematic review to support the 2021 US Preventive Services Task Force Recommendation Statement on interventions for tobacco cessation in adults summarizes published evidence on the benefits and harms of interventions for tobacco cessation in adults, including pregnant persons. Carrie D. Patnode, PhD, MPH; Jillian T. Henderson, PhD, MPH; Erin L. Coppola, MPH; Joy Melnikow, MD, MPH; Shauna Durbin, MPH; Rachel G. Thomas, MPH
- A Comprehensive Approach to Increase Adult Tobacco Cessation JAMA Editorial January 19, 2021 Brenna VanFrank, MD, MSPH; Letitia Presley-Cantrell, PhD
- Initiating Pharmacologic Treatment in Tobacco-Dependent Adults JAMA JAMA Clinical Guidelines Synopsis January 19, 2021 This JAMA Clinical Guidelines Synopsis summarizes the American Thoracic Society’s 2020 recommendations for treating tobacco dependence with pharmacologic therapy in adults. Atul Jain, MD, MS; Andrew M. Davis, MD, MPH
- USPSTF Recommendation: Interventions to Promote Tobacco Cessation JAMA JAMA Patient Page January 19, 2021 This JAMA Patient Page summarizes the USPSTF 2020 guideline recommending that physicians ask all adults about tobacco use, advise them to stop using tobacco, and provide behavioral interventions and drugs shown effective for stopping cigarette and other tobacco use. Jill Jin, MD, MPH
- COVID-19 and the “Lost Year” for Smokers Trying to Quit JAMA Medical News & Perspectives May 18, 2021 This Medical News article describes a reduction in smoking cessation attempts during the COVID-19 pandemic. Mary Chris Jaklevic, MSJ
- Considerations of Sex and Gender in FDA Tobacco Regulation JAMA Viewpoint June 20, 2023 This Viewpoint discusses how sex and gender subpopulations may be differentially affected by tobacco products and suggests that the FDA formulate regulations in clinically meaningful ways. Danielle R. Davis, PhD; Suchitra Krishnan-Sarin, PhD; Carolyn M. Mazure, PhD
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US Preventive Services Task Force. Interventions for Tobacco Smoking Cessation in Adults, Including Pregnant Persons : US Preventive Services Task Force Recommendation Statement . JAMA. 2021;325(3):265–279. doi:10.1001/jama.2020.25019
Interventions for Tobacco Smoking Cessation in Adults, Including Pregnant Persons : US Preventive Services Task Force Recommendation Statement
- Editorial A Comprehensive Approach to Increase Adult Tobacco Cessation Brenna VanFrank, MD, MSPH; Letitia Presley-Cantrell, PhD JAMA
- US Preventive Services Task Force USPSTF Review: Interventions for Tobacco Cessation in Adults, Including Pregnant Persons Carrie D. Patnode, PhD, MPH; Jillian T. Henderson, PhD, MPH; Erin L. Coppola, MPH; Joy Melnikow, MD, MPH; Shauna Durbin, MPH; Rachel G. Thomas, MPH JAMA
- JAMA Clinical Guidelines Synopsis Initiating Pharmacologic Treatment in Tobacco-Dependent Adults Atul Jain, MD, MS; Andrew M. Davis, MD, MPH JAMA
- JAMA Patient Page USPSTF Recommendation: Interventions to Promote Tobacco Cessation Jill Jin, MD, MPH JAMA
- Medical News & Perspectives COVID-19 and the “Lost Year” for Smokers Trying to Quit Mary Chris Jaklevic, MSJ JAMA
- Viewpoint Considerations of Sex and Gender in FDA Tobacco Regulation Danielle R. Davis, PhD; Suchitra Krishnan-Sarin, PhD; Carolyn M. Mazure, PhD JAMA
Importance Tobacco use is the leading preventable cause of disease, disability, and death in the US. In 2014, it was estimated that 480 000 deaths annually are attributed to cigarette smoking, including second hand smoke exposure. Smoking during pregnancy can increase the risk of numerous adverse pregnancy outcomes (eg, miscarriage and congenital anomalies) and complications in the offspring (including sudden infant death syndrome and impaired lung function in childhood). In 2019, an estimated 50.6 million US adults (20.8% of the adult population) used tobacco; 14.0% of the US adult population currently smoked cigarettes and 4.5% of the adult population used electronic cigarettes (e-cigarettes). Among pregnant US women who gave birth in 2016, 7.2% reported smoking cigarettes while pregnant.
Objective To update its 2015 recommendation, the USPSTF commissioned a review to evaluate the benefits and harms of primary care interventions on tobacco use cessation in adults, including pregnant persons.
Population This recommendation statement applies to adults 18 years or older, including pregnant persons.
Evidence Assessment The USPSTF concludes with high certainty that the net benefit of behavioral interventions and US Food and Drug Associated (FDA)–approved pharmacotherapy for tobacco smoking cessation, alone or combined, in nonpregnant adults who smoke is substantial. The USPSTF concludes with high certainty that the net benefit of behavioral interventions for tobacco smoking cessation on perinatal outcomes and smoking cessation in pregnant persons is substantial. The USPSTF concludes that the evidence on pharmacotherapy interventions for tobacco smoking cessation in pregnant persons is insufficient because few studies are available, and the balance of benefits and harms cannot be determined. The USPSTF concludes that the evidence on the use of e-cigarettes for tobacco smoking cessation in adults, including pregnant persons, is insufficient, and the balance of benefits and harms cannot be determined. The USPSTF has identified the lack of well-designed, randomized clinical trials on e-cigarettes that report smoking abstinence or adverse events as a critical gap in the evidence.
Recommendations The USPSTF recommends that clinicians ask all adults about tobacco use, advise them to stop using tobacco, and provide behavioral interventions and FDA-approved pharmacotherapy for cessation to nonpregnant adults who use tobacco. (A recommendation) The USPSTF recommends that clinicians ask all pregnant persons about tobacco use, advise them to stop using tobacco, and provide behavioral interventions for cessation to pregnant persons who use tobacco. (A recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of pharmacotherapy interventions for tobacco cessation in pregnant persons. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of e-cigarettes for tobacco cessation in adults, including pregnant persons. The USPSTF recommends that clinicians direct patients who use tobacco to other tobacco cessation interventions with proven effectiveness and established safety. (I statement)
Tobacco use is the leading preventable cause of disease, disability, and death in the US. In 2014, it was estimated that 480 000 deaths annually are attributed to cigarette smoking, including second hand smoke. 1 Smoking during pregnancy can increase the risk for miscarriage, congenital anomalies, stillbirth, fetal growth restriction, preterm birth, placental abruption, and complications in the offspring, including sudden infant death syndrome and impaired lung function in childhood. 1 - 4 In 2019 (the most recent data currently available), an estimated 50.6 million US adults (20.8% of the adult population) used tobacco; 14.0% of the US adult population currently smoked cigarettes; and 4.5% of the US adult population used electronic cigarettes (e-cigarettes). 5 According to data from the National Vital Statistics System, in 2016, 7.2% of women who gave birth smoked cigarettes during pregnancy. 6 There are disparities in smoking behaviors associated with certain sociodemographic factors: smoking rates are particularly high in non-Hispanic American Indian/Alaska Native persons; lesbian, gay, or bisexual adults; adults whose highest level of educational attainment is a General Educational Development certificate; persons who are uninsured and those with Medicaid; adults with a disability; and persons with mild, moderate, or severe generalized anxiety symptoms. 5 According to the 2015 National Health Interview Survey, which reported responses from 33,672 adults, 68% of adults who smoked reported that they wanted to stop smoking and 55% attempted quitting in the past year 7 ; only 7% reported having recently quit smoking and 31% reported having used cessation counseling, medication, or both when trying to quit. 7
Quiz Ref ID The USPSTF concludes with high certainty that the net benefit of behavioral interventions and US Food and Drug Administration (FDA)–approved pharmacotherapy for tobacco smoking cessation, alone or combined, in nonpregnant adults who smoke is substantial .
Quiz Ref ID The USPSTF concludes with high certainty that the net benefit of behavioral interventions for tobacco smoking cessation on perinatal outcomes and smoking cessation in pregnant persons is substantial .
Quiz Ref ID The USPSTF concludes that the evidence on pharmacotherapy interventions for tobacco smoking cessation in pregnant persons is insufficient because few studies are available, and the balance of benefits and harms cannot be determined.
Quiz Ref ID The USPSTF concludes that the evidence on the use of e-cigarettes for tobacco smoking cessation in adults, including pregnant persons, is insufficient , and the balance of benefits and harms cannot be determined. The USPSTF has identified the lack of well-designed, randomized clinical trials (RCTs) on e-cigarettes that report smoking abstinence or adverse events as a critical gap in the evidence.
See the Figure , Table 1 , and the eFigure in the Supplement for more information on the USPSTF recommendation rationale and assessment. For more details on the methods the USPSTF uses to determine net benefit, see the USPSTF Procedure Manual. 8
This recommendation applies to adults 18 years or older, including pregnant persons. The USPSTF has issued a separate recommendation statement on primary care interventions for the prevention and cessation of tobacco use in children and adolescents. 9
Key definitions related to tobacco use are reported in the Box . Although tobacco use refers broadly to the use of any tobacco product, cigarette smoking has historically been the most prevalent form of tobacco use in the US, and most of the evidence surrounding cessation of tobacco products relates to quitting combustible cigarette smoking. Thus, the current USPSTF recommendations focus on interventions for tobacco smoking cessation. Additionally, although e-cigarettes are considered a tobacco product that should also be the focus of tobacco prevention and cessation efforts, for this recommendation statement, the evidence on e-cigarettes as a potential cessation aid for cigarette smoking was also evaluated.
Key Definitions Related to Tobacco Use
Tobacco use refers to use of any tobacco product. As defined by the US Food and Drug Administration, tobacco products include any product made or derived from tobacco intended for human consumption (except products that meet the definition of drugs), including, but not limited to, cigarettes, cigars (including cigarillos and little cigars), dissolvables, hookah tobacco, nicotine gels, pipe tobacco, roll-your-own tobacco, smokeless tobacco products (including dip, snuff, snus, and chewing tobacco), vapes, electronic cigarettes (e-cigarettes), hookah pens, and other electronic nicotine delivery systems. 10
Smoking generally refers to the inhaling and exhaling of smoke produced by combustible tobacco products such as cigarettes, cigars, and pipes.
Vaping refers to the inhaling and exhaling of aerosols produced by e-cigarettes. 11 Vaping products (ie, e-cigarettes) usually contain nicotine, which is the addictive ingredient in tobacco. Substances other than tobacco can also be used to smoke or vape. While the 2015 USPSTF recommendation statement used the term “electronic nicotine delivery systems” or “ENDS,” the USPSTF recognizes that the field has shifted to using the term “e-cigarettes” (or “e-cigs”) and uses the term e-cigarettes in the current recommendation statement. e-Cigarettes can come in many shapes and sizes, but generally they heat a liquid that contains nicotine (the addictive drug in tobacco) to produce an aerosol (or “vapor”) that is inhaled (“vaped”) by users. 11
USPSTF indicates US preventive Services Task Force.
All patients should be asked about their tobacco use, whether or not risk factors for use are present, and encouraged to stop using tobacco. When smoking is identified, all patients should be provided interventions to quit smoking. Higher smoking prevalence has been observed in men; persons younger than 65 years; non-Hispanic American Indian/Alaska Native persons; persons who are lesbian, gay, or bisexual; persons whose highest level of educational attainment is a General Educational Development certificate; persons with an annual household income less than $35 000; persons with a disability; and persons with mild, moderate, or severe anxiety symptoms. 5
Common approaches for clinicians to assess patients’ tobacco use include the following.
The 5 As: (1) Ask about tobacco use; (2) Advise to quit through clear, personalized messages; (3) Assess willingness to quit; (4) Assist in quitting; and (5) Arrange follow-up and support. 12
“Ask, Advise, Refer,” which encourages clinicians to ask patients about tobacco use, advise them to quit, and refer them to telephone quit lines, other evidence-based cessation interventions, or both. 12
Vital Sign: Treating smoking status as a vital sign and recording smoking status at every health visit are also frequently used to assess smoking status. 12
Because many pregnant women who smoke do not report it, using multiple choice questions to assess smoking status in this group may improve disclosure. 12
Effective tobacco smoking cessation interventions for nonpregnant adults include behavioral counseling and pharmacotherapy, either individually or in combination. 13 , 14
Combining behavioral and pharmacotherapy interventions has been shown to increase tobacco smoking cessation rates compared with either usual care/brief cessation interventions alone or pharmacotherapy alone. 13 Most combination interventions include behavioral counseling involving several sessions (≥4), with planned total contact time usually ranging from 90 to 300 minutes. 13 The largest effect was found in interventions that provided 8 or more sessions, although the difference in effect among the number of sessions was not significant. 13
Many behavioral counseling interventions are available to increase tobacco smoking cessation in adults. These interventions can be delivered in the primary care setting or can be referred to community settings with feedback to the primary care clinician. Effective behavioral interventions include physician advice, nurse advice, individual counseling with a cessation specialist, group behavioral interventions, telephone counseling, and mobile phone–based interventions. 13 Behavioral counseling interventions used in studies typically targeted individuals who were motivated to quit tobacco smoking. 13 For additional information about behavioral counseling interventions in nonpregnant adults, see Table 2 .
Quiz Ref ID The current pharmacotherapy interventions approved by the FDA for the treatment of tobacco smoking dependence in adults are nicotine replacement therapy (NRT) (including nicotine transdermal patches, lozenges, gum, inhalers, or nasal spray), bupropion hydrochloride sustained-release (SR), and varenicline. 46 All 3 types of pharmacotherapy increase tobacco smoking cessation rates. Using a combination of NRT products (in particular, combining short-acting plus long-acting forms of NRT) has been found to be more effective than using a single form of NRT. 13 Based on a smaller number of studies, varenicline appears to be more effective than NRT or bupropion SR. 13 Information on dosing regimens is available in the package inserts of individual medications or in the 2020 Surgeon General Report on Smoking Cessation. 47
Providing any psychosocial intervention to pregnant persons who smoke tobacco can increase smoking cessation. The behavioral counseling intervention type most often studied in pregnant persons who smoke was counseling. Behavioral interventions were more effective when they provided more intensive counseling, were augmented with messages and self-help materials tailored for pregnant persons, and included messages about the effects of smoking on both maternal and fetal health and strong advice to quit as soon as possible. 12 , 13 Although smoking cessation at any point during pregnancy yields substantial health benefits for the expectant mother and infant, quitting early in pregnancy provides the greatest benefit to the fetus. 12 , 13 Other interventions included feedback, incentives, health education, and social support, although provision of health education alone, without counseling, was not found to be effective. For additional information about behavioral counseling interventions in pregnant persons, see Table 2 .
Primary care clinicians may find the following resources useful in talking with adults and pregnant persons about tobacco smoking cessation.
Centers for Disease Control and Prevention
Health care clinician resources for treatment of tobacco use and dependence https://www.cdc.gov/tobaccoHCP
Tips From Former Smokers https://www.cdc.gov/tobacco/campaign/tips/partners/health/index.html
US Department of Health and Human Services
SmokeFree.Gov Health Professionals Page https://smokefree.gov/help-others-quit/health-professionals
In addition, the following resources may be useful to primary care clinicians and practices trying to implement interventions for tobacco smoking cessation.
Million Hearts tools for clinicians for tobacco cessation https://millionhearts.hhs.gov/tools-protocols/tools/tobacco-use.html
Centers for Disease Control and Prevention state and community resources for tobacco control programs https://www.cdc.gov/tobacco/stateandcommunity/index.htm
The US Department of Veterans Affairs (VA) Primary Care & Tobacco Cessation Handbook https://www.mentalhealth.va.gov/quit-tobacco/docs/IB_10-565-Primary-Care-Smoking-Handbook-PROVIDERS-508.pdf
World Health Organization’s toolkit for delivering brief smoking interventions in primary care http://www.who.int/tobacco/publications/smoking_cessation/9789241506953/en/
In 2020, the Surgeon General issued a Report on Smoking Cessation. 47 The report’s findings were largely similar to that of the USPSTF. The Surgeon General’s report issued some additional findings regarding internet-based interventions for cessation and describes some suggestive but not sufficient evidence about specific e-cigarette use behaviors and increased cessation. Overall, the Surgeon General’s report found that there is inadequate evidence to conclude that e-cigarettes increase smoking cessation. More information on the Surgeon General’s Report on Smoking Cessation is available at https://www.cdc.gov/tobacco/data_statistics/sgr/2020-smoking-cessation/#fact-sheets .
According to data from the National Vital Statistics System, in 2016, 7.2% of women who gave birth smoked cigarettes during pregnancy, 6 and among 1071 pregnant women aged 18 to 44 years, 3.6% reported using e-cigarettes. 48 Smoking during pregnancy reduces fetal growth, increases the risk of preterm birth, and doubles the risk for delivering an infant with low birth weight. It also increases the relative risk for stillbirth death by 25% to 50%. 1 , 2 Quitting smoking early in pregnancy can reduce or eliminate the adverse effects of smoking on fetal growth. 47 For pregnant persons for whom behavioral counseling alone does not work, evidence to support other options to increase smoking cessation during pregnancy are limited. Few clinical trials have evaluated the effectiveness of NRT for smoking cessation in pregnant women. Although most studies were in the direction of benefit, no statistically significant increase in cessation was seen. 13 There is limited evidence on harms of NRT from trials in pregnant persons. Potential adverse maternal events reported in studies of NRT include slightly increased diastolic blood pressure and skin reactions to the patch. 13 Potential adverse events reported in nonpregnant adults include higher rates of low-risk cardiovascular events, such as tachycardia. 13 It has been suggested that NRT may be safer than smoking during pregnancy given that cigarette smoke contains harmful substances in addition to nicotine. The USPSTF identified no studies on bupropion SR or varenicline pharmacotherapy for tobacco smoking cessation during pregnancy.
In the absence of clear evidence on the balance of benefits and harms of pharmacotherapy in pregnant women, clinicians are encouraged to consider the severity of tobacco dependence in each patient and engage in shared decision-making to determine the best individual treatment course.
No tobacco product use is risk-free, including the use of e-cigarettes. Tobacco smoking cessation can be difficult for many individuals; thus, having a variety of tools available to help persons quit smoking would potentially be helpful. Findings from small surveys and qualitative data report mixed findings on whether physicians are recommending e-cigarettes to patients to help them quit smoking. 13 , 49 - 51 Few randomized trials have evaluated the effectiveness of e-cigarettes to increase tobacco smoking cessation in nonpregnant adults, and no trials have evaluated e-cigarettes for tobacco smoking cessation in pregnant persons. 13 Overall, results were mixed on whether smoking cessation increased with e-cigarettes; however, continued e-cigarette use after the intervention phase of trials remained high, indicating continued nicotine dependence. Trial evidence on harms of e-cigarettes used for smoking cessation is also limited. The most commonly reported adverse effects from e-cigarette use reported in trials included coughing, nausea, throat irritation, and sleep disruption. 13 Generally, no significant difference in short-term serious adverse events associated with e-cigarette use was reported. 13 Evidence on potential harms of e-cigarette use in general (whether for tobacco smoking cessation or not) has been reviewed in the National Academies of Science, Engineering, and Medicine report Public Health Consequences of E-Cigarettes. 52 For example, the report found conclusive evidence that in addition to nicotine, most e-cigarette products contain and emit numerous potentially toxic substances. Additionally, an outbreak of e-cigarette, or vaping product, use–associated lung injury (EVALI) that occurred in the US in late 2019 also suggests potential harms of e-cigarette use. The vast majority of cases have been associated with tetrahydrocannabinol (THC)–containing e-cigarettes. 53
Given the high rates of e-cigarette use in children and adolescents currently in the US, 54 the USPSTF recognizes that an overall public health question remains on whether the potential use of e-cigarettes as a tobacco smoking cessation aid (if ever proven effective) could be balanced with the high rates of e-cigarette use in youth as a driver for increasing overall tobacco use. The USPSTF has issued a separate recommendation statement on the prevention of tobacco use, including e-cigarettes, in children and adolescents. 9 The current USPSTF recommendation statement for adults evaluated the evidence on the benefits and harms of e-cigarettes to increase tobacco cessation; the USPSTF found this evidence to be insufficient. Given the proven effectiveness of behavioral counseling interventions in both nonpregnant and pregnant adults, and of pharmacotherapy in nonpregnant adults, the USPSTF recommends that clinicians focus on offering behavioral counseling and pharmacotherapy to increase smoking cessation in nonpregnant adults, and behavioral counseling to increase smoking cessation in pregnant persons.
In 2020, the USPSTF recommended that primary care clinicians provide interventions, including education or brief counseling, to prevent the initiation of tobacco use (including e-cigarettes) in school-aged children and adolescents. 9 The USPSTF found the evidence on primary care interventions for the cessation of tobacco use in youth to be insufficient.
This recommendation statement replaces the 2015 USPSTF recommendation statement on behavioral and pharmacotherapy interventions for tobacco smoking cessation in adults, including pregnant women. 55 The current recommendation statement has been updated to reflect newer evidence and language in the field of tobacco cessation and includes a description of the 2019 EVALI outbreak in the US. However, the recommendations on the services primary care clinicians should provide for tobacco cessation are the same as in 2015.
The USPSTF commissioned a systematic review to evaluate the benefits and harms of primary care interventions on tobacco use cessation in adults, including pregnant persons. 13 , 14 The USPSTF considered evidence on the benefits and harms of behavioral counseling interventions, pharmacotherapy interventions, and e-cigarettes in nonpregnant adults and pregnant persons. The vast majority of evidence identified focused on cigarette smoking cessation.
The USPSTF reviewed evidence on the benefits of behavioral counseling interventions on tobacco use cessation in general adults primarily from 20 systematic reviews that covered approximately 830 RCTs and more than 500 000 participants. 13 The evidence almost exclusively evaluated interventions for cessation of cigarette smoking. Physician advice, nurse advice, individual counseling with a cessation specialist, group behavioral interventions, telephone counseling, and mobile phone–based interventions have all been found to be effective to increase cessation of cigarette smoking. 13
Based on a 2013 systematic review that pooled 26 trials (n = 22 239), rates of smoking cessation at 6 months or more were an average of 8.0% in groups that received physician advice compared with 4.8% in groups that received no advice or usual care (risk ratio [RR], 1.76 [95% CI, 1.58-1.96]). 13 , 56 When stratified by intensity level, both minimal advice (defined as a single session lasting <20 minutes with ≤1 follow-up sessions) and intensive advice (defined as a single session lasting ≥20 minutes or >1 follow-up session) from a physician was associated with significantly increased cessation rates compared with no advice. Although not definitive, some subgroup analyses suggest that more intensive physician counseling (>20 minutes for initial consult, use of additional materials, or >1 follow-up visit) may be associated with an increase in cessation rates, particularly in patients who have smoking-related disease. 13 , 56
Based on a 2017 systematic review that pooled 44 trials evaluating nurse advice, 14.2% of participants who received interventions from nurses achieved smoking cessation at 6 months or more compared with 12.2% of those who received usual care or minimal intervention (RR, 1.29 [95% CI, 1.21-1.38]). 13 , 57 No evidence of effect modification was found when comparing higher- or lower-intensity counseling provided by nurses.
A systematic review from 2017 that pooled 33 trials (n = 13 762) found that an average of 11.4% of participants who received individual counseling with a cessation specialist achieved smoking cessation, compared with 7.7% of those who received minimal contact of less than 15 minutes of advice (RR, 1.48 [95% CI, 1.34-1.64]). 13 , 58 The review found some evidence suggesting that more intensive counseling was associated with higher cessation rates. Another systematic review published in 2017 that pooled 13 trials (n = 4395) also found that participants receiving group behavioral interventions had higher cessation rates compared with those who received a self-help program (10.4% cessation rate in intervention group vs 5.8% cessation rate in control group; RR, 1.88 [95% CI, 1.52-2.33]). 13 , 59
A 2019 review on telephone counseling interventions found that proactive telephone counseling (where telephone counselors called participants directly either to initiate counseling or in response to a participant calling a quitline) was associated with increased cessation rates. 13 , 60 If the telephone counseling was a “cold call” from telephone counselors to initiate counseling, smoking cessation rates were 11.0% in control participants and 13.9% in telephone counseling recipients (RR, 1.25 [95% CI, 1.15-1.35]; 65 trials; n = 41 233). 13 , 60 If telephone counseling occurred in response to a participant contacting a quitline, cessation rates were 7.8% in control participants and 10.8% in intervention recipients (RR, 1.38 [95% CI, 1.19-1.61]; 14 trials; n = 32 484). 13 , 60
A 2019 review that pooled 13 trials (n = 14 133) found higher cessation rates associated with mobile phone–based interventions. 13 , 61 All studies primarily used text messaging as the main intervention component, although a limited number of studies looked at individual mobile phone applications. Smoking cessation rates were an average of 5.6% in participants receiving usual or minimal care and 9.5% in those receiving mobile phone–based interventions (RR, 1.54 [95% CI, 1.19-2.00]).
The USPSTF considered evidence on other behavioral counseling interventions such as print-based, nontailored self-help materials, internet-based interventions, motivational interviewing, biofeedback, exercise, acupuncture, and hypnotherapy 13 ; however, limited evidence was available on these interventions.
The USPSTF reviewed evidence from 4 systematic reviews on pharmacotherapy that reported smoking cessation at 6 months or more. 13
A 2018 review on NRT (133 studies; n = 64 640) 62 found that 16.9% of participants taking any form of NRT achieved smoking abstinence at 6 months or more compared with 10.5% of participants receiving placebo or taking no NRT (RR, 1.55 [95% CI, 1.49-1.61]). All forms of NRT (patch, gum, inhaler, intranasal, and tablets) were found to be effective. Another review found that using combination NRT (patch plus a fast-acting form) was associated with higher smoking cessation rates than using a single form of NRT (16.9% vs 13.9%; RR, 1.25 [95% CI, 1.15-1.36]). 63
A 2020 systematic review on the use of antidepressants for smoking cessation (46 studies; n = 17 866) found that bupropion SR was associated with a significantly higher rate of smoking abstinence at 6 months or more than placebo or no bupropion SR (19.0% vs 11.0%; RR, 1.64 [95% CI, 1.52-1.77]). 64
Based on pooled analyses of 27 studies (n = 12 625), a 2016 systematic review found that varenicline was associated with higher rates of smoking cessation over placebo (25.6% vs 11.1%; RR, 2.24 [95% CI, 2.06-2.43]). 65
Smaller subsets of studies from these reviews directly compared types of pharmacotherapy for smoking cessation. Eight studies (n = 6264) compared varenicline and NRT and found that varenicline was associated with a greater smoking cessation rate over any form of NRT. 65 Six studies (n = 6286) evaluated varenicline vs bupropion SR and found that varenicline was associated with a higher cessation rate. 64 , 65 Smoking cessation rates among participants using NRT vs bupropion SR at 6 months or more did not significantly differ (10 studies; n = 9230). 64
Combinations of behavioral counseling and pharmacotherapy for smoking cessation were also effective, and potentially more effective than behavioral counseling or pharmacotherapy alone. 13 A 2016 systematic review (52 studies; n = 19 488) 66 found that participants who received combination pharmacotherapy and intensive behavioral counseling had a higher abstinence rate at 6 months or more compared with control participants who received usual care, self-help materials, or brief advice on quitting (which was less intensive than the counseling or support given to the intervention groups) (15.2% vs 8.6%; RR, 1.83 [95% CI, 1.68-1.98]). These combination interventions often have behavioral components delivered by specialized smoking cessation counselors or trained staff; however, no difference in effectiveness was seen in studies in which a nonspecialist provided the counseling. 13 Most studies used NRT as the pharmacotherapy. The intensity and format of the behavioral counseling component of the intervention varied greatly, with the majority of studies offering at least 4 behavioral counseling sessions, with a total planned contact time generally ranging from 90 to 300 minutes. Most of the behavioral counseling was delivered by a specialized smoking cessation counselor or trained trial staff.
Another systematic review, 67 which pooled analyses of 65 studies (n = 23 331), found that cessation rates at 6 months or more were modestly higher in participants who received behavioral support as an adjunct to pharmacotherapy than in those who received pharmacotherapy alone. Most studies offered NRT as the pharmacotherapy. Participants in the control group may have also received some counseling or support, but it was less intensive than in the intervention group. The addition of behavioral support to pharmacotherapy was associated with significantly higher cessation rates, approximately 17% in persons using pharmacotherapy alone vs 20% in those using a combination of pharmacotherapy and behavioral support (RR, 1.15 [95% CI, 1.08-1.22]). 13
For benefits of tobacco use cessation interventions in pregnant persons, the USPSTF reviewed evidence from an existing systematic review on behavioral counseling interventions 68 and from primary studies of pharmacotherapy. As with the evidence base in nonpregnant adults, the available evidence primarily addressed smoking cessation.
Based on a systematic review from 2017, 68 the USPSTF found that behavioral counseling interventions in pregnant women were effective at improving rates of smoking cessation as well as some perinatal health outcomes. Pooled analyses from 97 studies (n = 26 637) found that use of any psychosocial intervention was associated with higher smoking cessation rates in late pregnancy relative to control groups (an average quit rate of 12.2% in control groups and 16.4% in intervention groups) (RR, 1.35 [95% CI, 1.23-1.48]). The majority of studies used counseling interventions, and analyses of only counseling interventions (51 studies; n = 18 276) found a significant increase in smoking cessation rates late in pregnancy, from 10.8% in control groups to 14.5% in intervention groups (RR, 1.31 [95% CI, 1.16-1.47]). Studies of other intervention types (health education, feedback, incentives, social support, and exercise) were much fewer, with fewer total participants. Findings of smoking cessation effectiveness by intervention type were all in the direction of benefit, although not all were statistically significant. No subgroup differences by intervention type were found. The same systematic review also assessed the association of behavioral counseling interventions with perinatal outcomes and found lower rates of low birth weight (RR, 0.83 [95% CI, 0.72-0.94]; 18 trials; n = 9402) and increased mean birth weight (mean difference, 55.6 g [95% CI, 29.82-81.38]; 26 trials; n = 11 338). No statistically significant difference in rates of preterm births or stillbirths was found.
The USPSTF identified 5 placebo-controlled trials on NRT during pregnancy. 13 All 5 trials included behavioral counseling or support in addition to NRT. One trial used NRT gum as the intervention, one used an inhaler, while the other 3 trials used a NRT patch. Adherence to NRT in studies was low (<10% in 1 study). Findings of the 5 trials were all generally in the direction of benefit with NRT; however, none of the studies, either individually or when pooled, found a statistically significant difference in smoking cessation (11.9% in NRT intervention groups vs 10.1% in control groups; RR, 1.11 [95% CI, 0.79-1.56]; 5 trials; n = 2033). 13 Seven trials (the 5 placebo-controlled trials previously mentioned plus 2 additional non–placebo-controlled trials) reported on perinatal and health outcomes with NRT during pregnancy 13 ; findings were inconsistent and imprecise. No studies on bupropion SR or varenicline for smoking cessation during pregnancy were identified.
The FDA classifies e-cigarettes as a tobacco product and to date, no e-cigarettes have been approved as a smoking cessation aid. Approximately 4.5% of adults 5 , 69 and 3.6% of pregnant women 48 report using e-cigarettes. Higher e-cigarette use is reported among young adults aged 18 to 24 years (7.6%) 70 and has been increasing in recent years. 70 In addition to young adults, e-cigarette use among adults is higher in men; non-Hispanic White adults and other non-Hispanic adults; lesbian, gay, or bisexual 5 persons; and persons with chronic illnesses (such as cardiovascular disease, diabetes, cancer, asthma, chronic obstructive pulmonary disease, chronic kidney disease, and depression). 13 , 71 Most adult e-cigarette users report that quitting smoking and health improvement are major reasons why they started using e-cigarettes. 72 , 73 This is in contrast to youth, where it has been found that e-cigarette use increases risk of ever smoking cigarettes. 52 Nineteen percent of tobacco users use 2 or more tobacco products, the most common combination being cigarettes and e-cigarettes. 74
The USPSTF identified 5 RCTs (n = 3117) on e-cigarettes for smoking cessation in nonpregnant adults 13 , 75 - 80 and no studies in pregnant persons. 13 All 5 studies were conducted outside of the US (2 in New Zealand, 1 in Italy, 1 in Korea, and 1 in the UK). Four of the studies included participants who either wanted to stop smoking or were attending a stop smoking service. The type of e-cigarette interventions (nicotine content, whether NRT was also given, nicotine cartridge vs e-liquid, and whether behavioral support was also provided) and control interventions (NRT vs nonnicotine e-cigarette) varied across studies, making comparisons difficult. Only 3 of the e-cigarettes used in the studies are currently available in the US. Study size ranged from 150 to 1124 participants.
Reported trial findings were mixed. The 2 largest and most recent trials reported a statistically significant increase in smoking cessation at 6 months; 1 study reported smoking cessation rates of 4% in control groups vs 7% 79 in intervention groups; the second trial reported smoking cessation rates of 25% in control groups vs 35% 78 in intervention groups. The 3 remaining trials reported no statistically significant differences in smoking cessation rates. Three of the studies reported on continued e-cigarette use after achievement of smoking cessation in intervention groups at 6 months to 1 year, with continued e-cigarette use ranging from 38% to 80%. One study reported that 26.9% of all study participants were using e-cigarettes at 1 year. 77
The USPSTF identified limited evidence on harms from behavioral counseling interventions for tobacco cessation. Three systematic reviews (1 on internet-based interventions, another on incentives, and 1 on hypnotherapy) did not find evidence of serious adverse events associated with interventions. 13
The USPSTF identified 4 systematic reviews on NRT that reported on harms 13 : 3 reviews compared harms of NRT vs placebo 62 , 81 , 82 and 1 compared harms from various types of NRT. 63 Twelve to 21 studies (n = 10 234 to 11 647) reported on cardiovascular harms. Statistically significantly more cardiovascular adverse events (in particular, heart palpitations and chest pain) were found for participants randomized to NRT vs placebo (RR, 1.81 [95% CI, 1.35-2.43]; 21 trials; n = 11 647). 82 However, when analyses focused on major cardiovascular adverse events (combined outcome of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke), findings were no longer statistically significant (RR, 1.38 [95% CI, 0.58-3.26]; 21 trials; n = 11 647). 82 Other reported harms associated with NRT included nausea, vomiting, gastrointestinal symptoms, and insomnia. Localized increased skin irritation at the NRT patch site has also been reported. No statistically significant increase in headaches, dizziness, anxiety, or depression were found. Cardiac adverse events and other serious adverse events did not differ by type of NRT. 63
The USPSTF considered evidence on harms from bupropion SR for tobacco smoking cessation from 4 systematic reviews. 13 No difference in serious adverse events (RR, 1.30 [95% CI, 1.00-1.69]; 33 trials; n = 9631), 83 cardiovascular adverse events (RR, 1.03 [95% CI, 0.71-1.50]; 27 trials; n = 10 402), 82 or major cardiovascular events (RR, 0.57 [95% CI, 0.31-1.04]; 27 trials; n = 10 402) 82 were found with bupropion SR (compared with placebo or no bupropion SR). No difference in moderate and severe neuropsychiatric events, including rates of suicidal behavior and ideation, were found with bupropion SR (compared with varenicline or NRT) in the recent Evaluating Adverse Events in a Global Smoking Cessation Study (EAGLES) trial. 84 , 85
Evidence on harms of varenicline for tobacco cessation are available from 3 systematic reviews on varenicline in unselected smokers, 4 systematic reviews of varenicline among persons with severe mental illness, and 1 review on varenicline for cessation of smokeless tobacco. 13 Common adverse effects reported with varenicline include nausea, insomnia, abnormal dreams, headache, and fatigue. 13 One review found an increase in serious adverse events with varenicline in unselected smokers (RR, 1.25 [95% CI, 1.04-1.49]; 29 trials; n = 15 370); however, many of these events included comorbidities that were mostly considered by the study authors to be unrelated to the treatments. 65 Across 3 systematic reviews (encompassing 18 to 38 studies; n = 8587 to 12 706), no statistically significant difference in cardiovascular adverse events or cardiovascular severe adverse events was found. 13 Additionally, no statistically significant increase in neuropsychiatric adverse events (including depression, suicidal ideation, and suicide attempt) was found across several systematic reviews. 13
The USPSTF did not identify any reports of adverse events related to combinations of behavioral counseling interventions and pharmacotherapy. Any harms of combined therapy are assumed to be similar to those of the pharmacotherapy being used.
The primary review that informed the USPSTF on the benefits of behavioral counseling interventions for smoking cessation during pregnancy also summarized evidence on harms of behavioral counseling interventions. 68 Based on analyses of 13 trials (n = 5831), no increase in adverse effects from psychosocial interventions was seen.
Nicotine in general has been shown in animal studies to cause fetal harms. However, NRT does not contain many harmful substances, such as hydrogen cyanide and carbon monoxide, that are present in cigarette smoke. 86 Evidence on harms of NRT during pregnancy is limited; the USPSTF identified 5 placebo-controlled trials (n = 3117), 2 non–placebo-controlled trials (n = 233), and 3 cohort studies (n = 306 721). 13 Findings on potential harms of NRT on birth outcomes from trial evidence is mixed, although most studies reported findings in the direction of benefit rather than harm. Observational evidence from cohort studies generally did not indicate an increase in stillbirth or low birth weight with NRT. Based on observational evidence, there was no evidence of increased risk of premature delivery, small for gestational age, stillbirth, or congenital anomalies associated with the use of NRT, bupropion, and varenicline vs smoking. According to FDA labeling, some fetal harms with bupropion were noted in animal studies, but currently, no adequate, well-controlled studies of bupropion SR use during pregnancy (for any indication) in humans are available. 87 Labeling for varenicline states that available studies cannot definitively establish or exclude varenicline-associated risk during pregnancy. 88
The USPSTF identified 9 RCTs (n = 3942) that reported on harms of e-cigarette interventions for tobacco smoking cessation in nonpregnant adults 13 (the 5 trials previously described that reported cessation rates at 6 months or more, as well as an additional 4 trials that reported on cessation rates at less than 6 months). No trials on harms of e-cigarettes for smoking cessation in pregnant persons was identified. The most commonly reported adverse effects from e-cigarette use reported in trials include coughing, nausea, throat irritation, and sleep disruption. 13 Generally, no significant difference in short-term serious adverse events associated with e-cigarette use was reported. 13 Data on potential long-term harms of e-cigarette use are currently lacking.
Additional evidence on harms from e-cigarette use (whether used for tobacco cessation or not) considered by the USPSTF included data of the 2019 EVALI outbreak in the US 53 and the 2018 report Public Health Consequences of E-Cigarettes by the National Academies of Sciences, Engineering, and Medicine. 52 In late 2019, an outbreak of EVALI occurred in the US. Symptoms of EVALI include cough, shortness of breath, chest pain, nausea, vomiting, stomach pain, diarrhea, fever, chills, and weight loss. As of February 2020, more than 2800 cases of EVALI were reported, with 68 deaths. 53 Based on testing of bronchoalveolar lavage fluid samples of patients with EVALI 89 and testing of products used by patients with EVALI, 53 vitamin E acetate (an additive in some THC-containing e-cigarettes) was found to be strongly linked to EVALI. 53 However, evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either THC- or non–THC–containing products, in some reported EVALI cases. 53
The National Academies of Sciences, Engineering, and Medicine report found that in youth and young adults, there is substantial evidence that e-cigarette use increases risk of ever using combustible tobacco and moderate evidence that e-cigarette use increases the frequency and intensity of subsequent cigarette smoking. 52 The report also found conclusive evidence that e-cigarettes contain and emit potentially toxic substances, although substantial evidence shows that other than nicotine, there is significantly lower exposure to potentially toxic substances from e-cigarettes compared with combustible tobacco cigarettes. 52
A draft version of this recommendation statement was posted for public comment on the USPSTF website from June 2, 2020, to June 29, 2020. Several comments expressed concern about the insufficient evidence statement on e-cigarettes for cessation. Some respondents wanted the USPSTF to recommend against e-cigarettes for tobacco cessation, while others wanted the USPSTF to recommend in favor of e-cigarettes. Based on the evidence reviewed, the USPSTF could not determine whether e-cigarettes are effective in helping persons to quit smoking cigarettes, nor could it determine what the potential long-term harms of e-cigarette use are; thus, it cannot recommend for or against their use. Some comments were also received requesting that the USPSTF recommend NRT for smoking cessation during pregnancy. Too few trials were identified for the USPSTF to determine whether NRT during pregnancy provides overall more benefits or harms, and the USPSTF calls for more research on NRT and other pharmacotherapy to help pregnant persons quit using tobacco. Last, edits to clarify language, as well as additional information from the recent 2020 Surgeon General’s Report on Smoking Cessation, have been provided in response to comments.
Because of the well-established health benefits of smoking cessation, 1 , 12 , 47 most of the research on interventions for smoking cessation focuses on cessation (rather than health outcomes) as a primary outcome. The current review identified 1 study 90 of middle-aged men at high risk for cardiorespiratory disease that found lower (although not statistically significant) total mortality, fatal coronary disease, and lung cancer death at 20 years of follow-up in participants who received advice from medical practitioners. 91 The study also found some reduction in all-cause mortality, coronary disease mortality, and lung cancer incidence and mortality at 20 years of follow-up, although these outcomes were not significant. 91
Although not zero, less toxins have been found to be released by e-cigarettes than by cigarettes. It is hypothesized that health outcomes may be improved in adults who completely switch from cigarette smoking to e-cigarette use, although long-term data are not available yet to support this. Evidence on long-term harms of e-cigarette use in general is lacking and is needed. Additionally, emerging evidence suggests that toxicant levels in dual users of e-cigarettes and cigarettes may be higher than in conventional cigarette–only users. 92
The greatest research needs are to gain a better understanding of the effectiveness of e-cigarettes for smoking cessation, as well as potential short- and long-term harms of e-cigarette use, and to understand whether there are effective pharmacotherapy options for pregnant persons.
e-Cigarettes: Given the potential negative effect that increasing e-cigarette use in youth is having on overall tobacco control efforts, there is an urgent need for research that provides both a clearer understanding of whether e-cigarettes may increase adult tobacco smoking cessation, as well as the potential harms of e-cigarette use as a tobacco product. Future research on e-cigarettes for smoking cessation in adults should address the following:
Studies must be well-designed RCTs that compare e-cigarette interventions with placebo, as well as established, effective combinations of pharmacotherapy and behavioral support.
Studies should be adequately powered to detect differences in continued smoking abstinence rates at 6 months or more.
Given the high rate of continued e-cigarette use after smoking cessation, research on both the short- and long-term harms of e-cigarette use is needed, as well as the harms in dual users of e-cigarettes and conventional cigarettes. More research is needed on smoking relapse rates in adults who have used e-cigarettes for smoking cessation and how to help with cessation of e-cigarette use once smoking abstinence has been achieved.
Given the rapidly evolving landscape of e-cigarettes, trials should include current generations of e-cigarettes. Additionally, to successfully conduct these types of studies, standardization of how to quantify e-cigarette use and levels of nicotine exposure from e-cigarettes is needed.
More research is needed to understand the patterns of e-cigarette use in youth and the risk factors for their transition from e-cigarette use to conventional cigarette smoking.
More research is also needed to better understand patterns of e-cigarette use in pregnant persons and potential harms of e-cigarette use to both pregnant persons and their offspring.
More research is needed on understanding how to help adults quit e-cigarettes.
Pharmacotherapy in pregnant persons: Although behavioral counseling interventions have been found to be effective in improving smoking cessation during pregnancy, additional research is needed on pharmacotherapy options, in particular NRT, for pregnant persons for whom behavioral counseling interventions alone are not effective.
Larger studies adequately powered to detect an effect on both smoking cessation rates (during pregnancy and postpartum) and changes in perinatal and child health outcomes are needed.
A better understanding of why adherence rates to NRT during pregnancy is so low would also be helpful.
Although the benefits of behavioral counseling interventions and pharmacotherapy in nonpregnant adults and the benefits of behavioral counseling interventions in pregnant adults are well established, additional research on effective components of behavioral counseling and who to target specific interventions to would be informative. More research on newer modalities and remotely delivered interventions (mobile phone apps, internet-based interventions) would also be helpful. Additionally, the effectiveness of interventions for cessation of other forms of tobacco and whether interventions need to be tailored to individual tobacco product types are also needed. Last, more research is needed on interventions to prevent relapse of tobacco use.
Numerous professional societies and health organizations, including the American Academy of Family Physicians, 93 American College of Physicians, 94 and American College of Obstetricians and Gynecologists (ACOG), 95 recommend that clinicians screen for tobacco use and provide interventions to patients who smoke.
For pregnant persons, ACOG recommends brief behavioral counseling and the use of evidence-based smoking cessation aids as effective strategies for achieving smoking cessation, even for very heavy smokers. 96 ACOG also recommends that NRT should be considered only after a detailed discussion with the patient of the known risks of continued smoking, the possible risks of NRT, and need for close supervision. 95
The American Academy of Pediatrics also has a policy statement recommending that pediatricians screen for the tobacco exposure of children during pediatric care visits and recommend nicotine dependence treatment, including behavioral interventions and pharmacotherapy, to tobacco-dependent parents. 97
More recently some organizations have addressed e-cigarette use in their tobacco use guidelines. The American Academy of Family Physicians, 98 the American College of Preventive Medicine, 99 and the American Heart Association 100 recommend that clinicians screen for e-cigarette use. Organizations vary somewhat in terms of whether they recommend e-cigarettes for smoking cessation. ACOG recommends against use of e-cigarettes in pregnant and postpartum individuals. 95 , 101 The American Cancer Society does not recommend e-cigarettes as a smoking cessation method, 102 and the American Heart Association 100 states that there is not enough evidence for clinicians to counsel patients on using e-cigarettes as a primary smoking cessation aid.
Corresponding Author: Alex H. Krist, MD, MPH, Virginia Commonwealth University, One Capitol Square, 6th Flr, 830 E Main St, Richmond, Virginia 23219 ( [email protected] )).
Accepted for Publication: December 4, 2020.
The US Preventive Services Task Force (USPSTF) members: Alex H. Krist, MD, MPH; Karina W. Davidson, PhD, MAS; Carol M. Mangione, MD, MSPH; Michael J. Barry, MD; Michael Cabana, MD, MA, MPH; Aaron B. Caughey, MD, PhD; Katrina Donahue, MD, MPH; Chyke A. Doubeni, MD, MPH; John W. Epling Jr, MD, MSEd; Martha Kubik, PhD, RN; Gbenga Ogedegbe, MD, MPH; Lori Pbert, PhD; Michael Silverstein, MD, MPH; Melissa A. Simon, MD, MPH; Chien-Wen Tseng, MD, MPH, MSEE; John B. Wong, MD.
Affiliations of The US Preventive Services Task Force (USPSTF) members: Fairfax Family Practice Residency, Fairfax, Virginia (Krist); Virginia Commonwealth University, Richmond (Krist); Feinstein Institute for Medical Research at Northwell Health, Manhasset, New York (Davidson); University of California, Los Angeles (Mangione); Harvard Medical School, Boston, Massachusetts (Barry); University of California, San Francisco (Cabana); Oregon Health & Science University, Portland (Caughey); University of North Carolina at Chapel Hill (Donahue); Mayo Clinic, Rochester, Minnesota (Doubeni); Virginia Tech Carilion School of Medicine, Roanoke (Epling Jr); George Mason University, Fairfax, Virginia (Kubik); New York University, New York, New York (Ogedegbe); University of Massachusetts Medical School, Worcester (Pbert); Boston University, Boston, Massachusetts (Silverstein); Northwestern University, Evanston, Illinois (Simon); University of Hawaii, Honolulu (Tseng); Pacific Health Research and Education Institute, Honolulu, Hawaii (Tseng); Tufts University School of Medicine, Boston, Massachusetts (Wong).
Author Contributions: Dr Krist had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The USPSTF members contributed equally to the recommendation statement.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Authors followed the policy regarding conflicts of interest described at https://www.uspreventiveservicestaskforce.org/Page/Name/conflict-of-interest-disclosures . All members of the USPSTF receive travel reimbursement and an honorarium for participating in USPSTF meetings. Dr Barry reported receiving grants and personal fees from Healthwise.
Funding/Support: The USPSTF is an independent, voluntary body. The US Congress mandates that the Agency for Healthcare Research and Quality (AHRQ) support the operations of the USPSTF.
Role of the Funder/Sponsor: AHRQ staff assisted in the following: development and review of the research plan, commission of the systematic evidence review from an Evidence-based Practice Center, coordination of expert review and public comment of the draft evidence report and draft recommendation statement, and the writing and preparation of the final recommendation statement and its submission for publication. AHRQ staff had no role in the approval of the final recommendation statement or the decision to submit for publication.
Disclaimer: Recommendations made by the USPSTF are independent of the US government. They should not be construed as an official position of AHRQ or the US Department of Health and Human Services.
Additional Contributions: We thank Tina Fan, MD, MPH (AHRQ), who contributed to the writing of the manuscript, and Lisa Nicolella, MA (AHRQ), who assisted with coordination and editing.
Additional Information: The US Preventive Services Task Force (USPSTF) makes recommendations about the effectiveness of specific preventive care services for patients without obvious related signs or symptoms. It bases its recommendations on the evidence of both the benefits and harms of the service and an assessment of the balance. The USPSTF does not consider the costs of providing a service in this assessment. The USPSTF recognizes that clinical decisions involve more considerations than evidence alone. Clinicians should understand the evidence but individualize decision-making to the specific patient or situation. Similarly, the USPSTF notes that policy and coverage decisions involve considerations in addition to the evidence of clinical benefits and harms.
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- Published: 18 July 2021
Factors motivating smoking cessation: a cross-sectional study in a lower-middle-income country
- Russell Seth Martins 1 ,
- Muhammad Umer Junaid 1 ,
- Muhammad Sharjeel Khan 2 ,
- Namrah Aziz 1 ,
- Zoha Zahid Fazal 1 ,
- Mariam Umoodi 3 ,
- Fatima Shah 2 &
- Javaid Ahmed Khan 4
BMC Public Health volume 21 , Article number: 1419 ( 2021 ) Cite this article
Only one-quarter of smokers in Pakistan attempt to quit smoking, and less than 3% are successful. In the absence of any literature from the country, this study aimed to explore factors motivating and strategies employed in successful smoking cessation attempts in Pakistan, a lower-middle-income country.
A survey was carried out in Karachi, Pakistan, amongst adult (≥ 18 years) former smokers (individuals who had smoked ≥100 cigarettes in their lifetime but who had successfully quit smoking for > 1 month at the time of survey). Multivariable logistic regression, with number of quit attempts (single vs. multiple) as the dependent variable, was performed while adjusting for age, sex, monthly family income, years smoked, cigarettes/day before quitting, and having suffered from a smoking-related health problem.
Out of 330 former smokers, 50.3% quit successfully on their first attempt with 62.1% quitting “cold turkey”. Only 10.9% used a cessation aid (most commonly nicotine replacement therapy: 8.2%). Motivations for quitting included self-health (74.5%), promptings by one’s family (43%), and family’s health (14.8%). Other social pressures included peer-pressure to quit smoking (31.2%) and social avoidance by non-smokers (22.7%). Successful smoking cessation on one’s first attempt was associated with being married (OR: 4.47 [95% CI: 2.32–8.61]), employing an abrupt cessation mode of quitting (4.12 [2.48–6.84]), and telling oneself that one has the willpower to quit (1.68 [1.04–2.71]).
In Pakistan, smoking cessation is motivated by concern for self-health and family’s health, family’s support, and social pressures. Our results lay a comprehensive foundation for the development of smoking-cessation interventions tailored to the population of the country.
Little is known about the patterns and strategies employed by smokers who are attempting to quit smoking, especially in lower-middle-income countries like Pakistan. Likewise, there are very few smoking cessation programs designed to assist in quitting. Our study will allow for a better understanding of the culture-specific motivating factors and strategies that most contributed to successful quit attempts. Based on these results, evidence based smoking cessation interventions can be developed tailored to the socioeconomic demographic of our country and region, including smoking cessation clinics and public outreach and media campaigns highlighting key elements of successful smoking cessation.
Peer Review reports
Smoking, with an average of 7 million deaths per year, is currently the leading cause of preventable death in the world [ 1 ], and causes a significant burden of oral and other cancers [ 2 ]. Literature pertaining to smoking cessation has shown that around two thirds of cigarette smokers are interested in quitting, with more than 50% reporting making a quit attempt in the past year [ 3 ]. However, fewer than one third of smokers who tried to quit used proven cessation methods, with only one in 10 smokers being able to quit successfully [ 3 ]. A UK based study showed that one third of quitting attempts were not preplanned and around half of those were made without the use of any support and thus were less likely to be successful [ 4 ]. Documented and validated support-based methods, and thus by extension a plan beforehand, contribute towards the success of any quit attempt [ 4 ].
To facilitate those with the intention to quit smoking, it is imperative to identify factors motivating successful cessation in former smokers and use these to support others’ quit attempts [ 5 ]. Cessation-aid interventions that are designed according to specific motivations to quit smoking are likely to increase chances of successful cessation [ 6 ]. Factors motivating smoking cessation range from internal/individual factors (such as a smokers emotional state and willpower) and external factors (such as advice on why and how to quit from health professionals, environmental smoking restrictions, and expectations about the benefits of quitting) [ 7 ]. The importance of internal/individual factors must not be undermined, as they have been shown to affect the efficacy of smoking cessation programs [ 7 , 8 ].
While there is extensive literature exploring factors motivating smoking cessation amongst populations in developed countries [ 9 ], such research is scarce from lower-middle-income countries (LMICs) such as Pakistan. Around 19.1% of Pakistan’s adult population are tobacco users, with the majority being smokers [ 10 ], and approximately 10% of deaths in Pakistan annually are attributable to smoking [ 11 ]. Apart from devastating consequences on population health, smoking also costs Pakistan approximately Rs. 192 billion (1.37 billion United States Dollars) annually due to costs associated with smoking-associated cancers, respiratory disease, and cardiovascular disease [ 12 ]. However, according to the World Health Organization (WHO) Global Adult Tobacco Survey (GATS), a much lower percentage (24.7%) of smokers in Pakistan make attempts to quit smoking, as compared to other countries (40–50%) [ 13 , 14 ]. In addition, the success rates of quit attempts are also lower for smokers in Pakistan (2.6%), as compared to those reported by international literature [ 13 ]. Almost half of the smokers attempting to quit did so without assistance (49.2%) and were hence less likely to be successful, with only 9.1% making use of pharmacotherapy and 14.7% of counseling [ 14 ]. The huge gap between the number of smokers attempting to quit and those actually successful highlights the ineffectiveness or absence of adequate motivators of smoking cessation and interventions designed to motivate and support successful cessation attempts in Pakistan [ 15 ]. The GATS survey also found that almost two-thirds (63.9%) of smokers were individuals without any education and around 59.8% were not interested in quitting [ 14 ]. This calls into question the benefit of mass media campaigns for smoking cessation, particularly those using a textual medium, in a country where the majority of smokers are illiterate [ 14 ]. In addition, since most smokers in Pakistan belong from lower socioeconomic backgrounds [ 16 ], cessation aids such as pharmacotherapy and counseling may be out of the financial reach of many individuals. Lastly, cultural and religious influences on smoking practices [ 17 ] may contribute to cessation patterns that differ from those seen in Western countries.
Although the 2014 GATS survey [ 14 ] provides highly generalizable national-level data regarding the sociodemographic distribution of ex-smokers and their use of cessation aids, it did not explore factors driving cessation itself. This gap in knowledge represents a niche that invites further research. Moreover, though the GATS survey reported that 29.7% of current smokers thought of quitting because of warning labels on cigarette packages [ 14 ], the impact of other public health interventions to promote cessation was largely unexplored. Thus, this study aims to describe factors motivating successful smoking cessation attempts in Pakistan, so that these may be incorporated towards the development of smoking cessation interventions that are targeted to the population of the country. In addition, this study also aims to identify motivators and strategies that are associated with successful cessation on one’s first attempt. Lastly, our study also reports the perceived usefulness of public health interventions in motivating cessation and resisting relapse amongst ex-smokers.
Study setting and population
This cross-sectional survey was carried out in Karachi, Pakistan, after approval from the institutional review board at the Aga Khan University Hospital (AKUH). The target population for this survey was adult former smokers, who were defined as adult (≥ 18 years) individuals who had smoked at least 100 cigarettes in their lifetime but who had successfully quit smoking at the time of survey [ 18 ]. A quit attempt was defined as deliberately stopping smoking for > 1 week, while successful quitting was defined as having deliberately stopped smoking for > 1 month [ 18 ]. A quit attempt was categorized as unsuccessful if any smoking relapse (≥ 1 cigarette smoked) took place after a quit attempt.
Data was collected by means of a questionnaire that was available in both English and Urdu, the national language of Pakistan. In the absence of a prior questionnaire suitable for our population, a comprehensive questionnaire was developed using elements from various sources [ 9 , 19 , 20 ] in close association with faculty with expertise in tobacco cessation research at the Section of Pulmonary and Critical Care Medicine at AKUH and the University of York. Content validity was assessed by calculating a content validity index (CVI) for relevance and clarity based on the ratings of three subject experts and a biostatistician. A CVI for relevance of 0.92 and for clarity of 0.89 indicated good content validity for the tool. The English questionnaire was then translated to Urdu, which is the national language of Pakistan, by an independent translator fluent in both languages and with experience in questionnaire translation. To ensure face validity, the English and Urdu versions of the survey underwent pilot testing amongst 30 respondents, and any ambiguous questions were subsequently modified as appropriate. The final survey contained the following five sections:
Demographics and Job Characteristics : Age, sex, marital status, and monthly family income.
History of Smoking and Smoking Cessation : Age at starting smoking, duration of smoking, number of quit attempts, cigarettes/day before cessation, time since quitting, age at cessation, difficulty of cessation (5-point Likert Scale consisting of 5 = very difficult ; 4 = difficult ; 3 = neither difficult nor easy ; 2 = easy ; and 1 = very easy ), and perceived self-efficacy in quitting (Question: “ Do you believe you have quit definitively ? Responses: Yes/ No/Unsure ) [ 9 ].
Strategies Employed in Smoking Cessation : Mode of quitting used in successful attempt ( abrupt cessation/cold turkey vs. gradual reduction ), use of a cessation aid (checklist of different available cessation aids) [ 9 ], strategies for self-discipline ( Yes/No for each strategy using a checklist) [ 20 ], strategies for self-distraction from smoking ( Yes/No for each strategy using a checklist), and positive reinforcement strategies ( Yes/No for each strategy using a checklist) [ 20 ].
Factors Motivating Smoking Cessation : Major reasons for quitting smoking ( Yes/No for each reason using a checklist), sources of awareness regarding need to quit smoking ( Yes/No for each source using a checklist) [ 19 ], social factors motivating cessation ( Yes/No for each factor using a checklist), factors related to self-image ( Yes/No for each factor using a checklist) [ 20 ], and existence of smoking-related health problems [ 9 ].
Usefulness of Public Health Interventions in Aiding Smoking Cessation : The helpfulness of public health interventions in motivating cessation and resisting relapse (multiple choice responses: not helpful at all , helpful to a small extent or helpful to a great extent ).
The survey was preceded by a consent form (available in both English and Urdu) explaining the nature and scope of the survey. In addition, preliminary screening questions based on current smoking status ensured that current smokers or those who had quit for < 1 month were not allowed to proceed with answering the survey.
Sample size calculation
Since no published literature reports factors motivating smoking cessation in Pakistan, it was assumed that approximately 75% of former smokers will have quit for health purposes (to protect present or future health), which will be the most common reason. This figure is based on a study by Gallus et al. in 2013 that was conducted amongst 3075 former smokers in a European population [ 21 ]. The sample size required for our study was calculated using OpenEpi. Using a 95% confidence level, the minimum required sample size was determined to be 288 adult former smokers.
In order to achieve a representative sample for this study, data collection was conducted on the premises of five tertiary care hospitals (three government-owned and two privately-owned) in Karachi, including AKUH. Non-probability convenience sampling was used to recruit participants for the survey. Data collectors approached patients’ attendants (persons accompanying patients) for participation in the survey. Individuals who had presented to the hospital for reasons pertaining to their own health were not considered for inclusion. Patients’ attendants are assumed to be representative of the general population. After initially introducing the study and obtaining consent from the individual, the data collectors screened potential participants according to the inclusion criteria and exclusion criteria. If the individual were suitable for inclusion, an informed consent was obtained. A copy of the consent form was provided to the participant. Next, the data collectors verbally administered the survey in English or Urdu, according to the participant’s preference.
To ensure privacy, the interaction of administering the survey took place in the nearest quiet location (empty room) on the hospital premises, according to the participant’s comfort. Moreover, to maintain anonymity, the questionnaire did not record respondents’ names. There were no risks, immediate benefits, or incentives for participation in the survey.
Statistical analysis was performed using IBM SPSS version 23. Continuous data was presented using mean and standard deviation/ median (interquartile range), and compared using independent sample t-tests/Mann Whitney tests, as appropriate. Categorical data was presented using frequencies and percentages, and compared using chi-squared tests/Fischer’s Exact tests. Content validity indices (CVI) were calculated for clarity and relevance based on the ratings of three content experts and a biostatistician. Multivariable logistic regression, age, sex, monthly family income, years smoked, cigarettes/day before quitting, and having suffered from a smoking-related health problem, was performed with number of quit attempts as the dependent variable (dichotomized as single attempt/successful on first attempt and multiple attempts/one or more unsuccessful attempts before a successful attempt ). A p -value < 0.05 was considered statistically significant for all analyses.
A total of 330 former smokers were included, with the majority male (92.7%) and aged between 18 and 30 years (43%) and 31–45 year (27.9%). Monthly family income was < Rs. 25,000 in 49.7% of respondents and > Rs. 75,000 in 18.2%. The mean age at which respondents at started smoking was 18.05 years, while the mean age at successful quitting was 31.37 years. Around half of the respondents reported having successfully quit smoking in their first attempt (50.3%), while 17.9% reported > 6 quit attempts. Most respondents reported smoking < 10 cigarettes a day (68.2%) at the time they began their successful quit attempt (Table 1 ).
The majority of respondents reported that they had abruptly stopped smoking (quit “cold turkey”; 62.1%). However, only 36 (10.9%) of respondents reported using a cessation aid during their successful quit attempt. Nicotine replacement therapy was the most common cessation aid used ( n = 27; 8.2%). Additionally, 3 (0.9%) respondents reported using mint gums, while only 2 (0.6%) reported using pharmacological cessation therapy and 1 (0.3%) reported having attended psychotherapy/ counselling sessions for smoking cessation. Respondents also reported avoiding social company that encouraged smoking (46.4%), as well as triggers that caused an urge to smoke (28.5%). The majority of respondents believed that they had quit smoking definitively (83.9%), although the majority felt that giving up smoking was very difficult/difficult (63.9%). Respondents reported using a variety of ways to discipline or distract themselves when they felt the urge to smoke, as well as various positive reinforcement strategies to aid cessation (Table 2 ).
The most frequently reported reason for quitting smoking was to improve or protect one’s own health (74.5%), which also served to justify our earlier estimate of 75% for sample size calculation. Other common reasons included promptings by one’s family (43%), and to improve/protect the health of family members (14.8%). 38.8% of respondents reported suffering from a smoking-related health problem (38.8%). Common sources of awareness regarding the need to quit smoking included family/friends/colleagues (37.6%), doctors (24.8%) and social media/online platforms (20.6%). Certain social pressures to quit smoking, such as peer-pressure to quit smoking (31.2%) and social avoidance by non-smokers (22.7%), were also reported. Respondents also reported having felt the need to give up smoking to be content with themselves (33.3%) and having felt upset whenever they felt the urge to smoke (30.9%). The various factors that encouraged smoking cessation are shown in Table 3 .
The majority of respondents felt that anti-smoking public health interventions were not helpful at all. Consumer warnings on cigarette packs (4.5%), increased prices/taxes on cigarettes (4.5%), and smoke-free public recreational places (4.2%) were most commonly reported to be helpful to a great extent in motivating cessation. Similarly, increased prices/taxes on cigarettes (4.8%) and consumer warnings on cigarette packs (4.2%) were most frequently reported to be help to a great extent in resisting relapse (Table 4 ).
On multivariable logistic regression (Table 5 ), successful smoking cessation on one’s first attempt was associated with being married (OR: 4.47 [95% CI: 2.32–8.61]), employing an abrupt cessation mode of quitting (4.12 [2.48–6.84]), the belief that smoking contradicted ones view of being caring and responsible (2.69 [1.52–4.77]), telling oneself that one has the willpower to quit (1.68 [1.04–2.71]), telling oneself that one can resist the urge to smoke if one tries hard enough (2.65 [1.45–4.84]), and consciously diverting ones thoughts to other matters when faced by the urge to smoke (2.22 [1.35–3.65]). Use of a cessation aid (0.20 [0.08–0.48]) and reporting family’s promptings as a major reason for quitting smoking (0.51 [0.32–0.82]) were inversely associated with successful cessation on first attempt (i.e., associated with one or more failed quit attempts before a successful attempt).
This study was conducted to explore factors associated with successful smoking cessation in former smokers in Pakistan, a lower-middle-income country (LMIC) in South Asia. Our study identified personal health, promptings from one’s family, and one’s family’s health, as the most important motivating factors. Social pressures to quit smoking included peer-pressure to quit and social avoidance by non-smokers. Lastly, successful cessation on one’s first quit attempt was associated with being married, quitting cold turkey, having a negative self-image of oneself due to smoking, and having strong willpower to quit.
The commonest reasons for quitting smoking were to improve/protect own health (74.5%), family’s promptings (43%), to improve/protect the health of family members (14.8%), and to save money (14.5%). Respondents reported receiving awareness regarding the need to quit smoking most commonly from their family, friends, and colleagues (37.6%). Moreover, social pressures, such as peer-pressure to quit smoking (31.2%), social avoidance by non-smokers (22.7%), and non-smokers asserting rights to smokeless public spaces (9.1%), were also major deterrents. Studies from the United States, Poland and France have demonstrated similar results, with health concerns, discouragement of smoking at home, and the high cost of cigarettes being important deterrents [ 22 , 23 , 24 ]. In addition, social pressure, such as having a smoke-free social network that pressurizes towards cessation, has also been found to be a strong motivator of cessation across different populations [ 23 , 24 , 25 ]. It is interesting that promptings by doctors were reported as being a reason for quitting by only 13% of respondents, and only one quarter (24.8%) of respondents received cessation-related awareness from their doctors. A study from the United Kingdom revealed that most patients were skeptical about doctors smoking cessation advice, which was often generic and of a preaching nature, and suggested that doctors should practice a more personalized approach to cessation counseling [ 26 ].
Around half (50.3%) of the respondents in our study reported quitting successfully on their first attempt, while the remaining reported needing 2–5 attempts (31.8%) and > 6 attempts (17.9%). These findings are in great contrast with what is usually suggested by smoking cessation programs. These vary from 8 to 14 attempts, as suggested by The American Cancer Society, the Australian Cancer Council, and the Centers for Disease Control [ 27 , 28 , 29 ]. However, there is some literature that aligns with our findings, as it has been suggested that though the number of quit attempts may be quite high on average, between 40 and 52% may be successful on their first serious attempt [ 30 , 31 ].
On multivariable regression, successful cessation on first attempt was associated with being married, quitting cold turkey, having a negative self-image on oneself because of being a smoker, telling oneself they have the willpower to resist the urge to smoke and quit definitively, and consciously diverting one’s thoughts to distract oneself from smoking. While the concept of willpower has been debated for a long time for its actual contribution to smoking cessation [ 32 ], it has been demonstrated to be an important factor in Pakistan previously [ 13 ]. Moreover, personal willpower is an essential feature of the “5A’s” model in “Treating Tobacco Use and Dependence” [ 33 ], of which the first three A’s build towards willingness to quit and the last two A’s facilitate those willing to quit to take the final decision to quit. This concept of personal willpower being an important factor in single-attempt cessation is strengthened by how family’s promptings as a major reason for cessation was negatively associated with single-attempt cessation in our study. This suggests how personal motivation that arises from within the individual is more likely to lead to successful cessation than when it arises externally. Additionally, quitting cold turkey has been recommended as more successful in smoking cessation, as compared to gradually tapering off cigarette use [ 34 ]. Interestingly in our study, use of a smoking cessation aid was negatively associated with quitting on the first attempt, a finding corroborated by a survey by Manis et al. in Switzerland [ 35 ]. With regards to self-image, while having a negative self-image due to one’s addiction may cause distress to the smoker [ 36 ], it can also function as a powerful motivator to quit smoking as it negates the perceived benefits of smoking [ 37 ]. Lastly, being with a spouse or partner who is a non-smoker, a former smoker, or who encourages and motivates quitting, is associated with a greater likelihood of success on cessation attempts [ 38 , 39 , 40 ].
Self-distraction by consciously diverting one’s thoughts to other matters (37.3%), trying to keep one’s hands and fingers occupied (34.5%), and engaging in work (28.8%), were useful strategies reportedly used by respondents. Moreover, consciously diverting one’s thoughts to other matters was significantly associated with single-attempt cessation on multivariable regression. These are encouraging findings, as they are simple yet effective. More technological methods of distraction, such as mobile phone applications and games [ 41 , 42 ], that have been piloted in the setting of developed countries may not be feasible for a resource-constrained like Pakistan. In addition, positive reinforcement strategies, such as expecting rewards (23.6%) and receiving rewards (19.1%) from others for resisting the urge to smoke, were also employed by respondents. Rewards and incentives, often monetary, are helpful in motivating smoking cessation, especially when individualized [ 43 , 44 ].
Lastly, none of the public health interventions mentioned in our survey were perceived by respondents as particularly useful for helping smoking cessation or resisting relapse, with less than 5% of respondents rating any intervention as helpful to a great extent. This is in direct contrast with studies from developed countries, such as the United States [ 45 , 46 ], and may be explained by several reasons. Firstly, interventions such as government or private sector mass media anti-smoking campaigns, anti-smoking advertisements, and health warnings preceding/during films, may not effectively be effective amongst those of lower socioeconomic and less educated backgrounds. Secondly, although Pakistan subscribes to the MPOWER model of tobacco control outlined by the World Health Organization [ 47 ], it is possible that these interventions are not practically implemented in an optimal manner. Thirdly, since our results highlight how former smokers predominantly attribute the success of their cessation to personal factors, such as willpower, self-discipline, and distraction strategies, they are perhaps unable or hesitant to acknowledge the potentially subconscious impact of external motivators. Nevertheless, further studies are required to determine the efficacy of such large-scale public health interventions in the setting of a LMIC like Pakistan, in terms of both improving cessation and cost-effectiveness.
Despite the major burden of tobacco consumption in the country, Pakistan lacks any major smoking cessation programs or clinics facilitating rehabilitation, which along with the low cost and easy availability of tobacco, can prove the difficult task of quitting even more challenging [ 13 ]. The results of our study provide a comprehensive and unique understanding of the factors that motivate smoking cessation in Pakistan. However, despite the varied distribution of socio-demographic characteristics achieved by targeting five different settings for data collection, the convenience sampling methodology used may limit the degree of generalizability of our findings to other populations in Pakistan. Nevertheless, our findings can help guide the development of evidence-based programs for smoking cessation in Pakistan and lay the foundation for similar larger-scale national research. Other potential limitations include the self-reported nature of our data as well as the possibility of social desirability bias. Future research must investigate motivators, strategies, and patterns specific to sex, age, socioeconomic status, education level, and other demographics.
Major motivations for smoking cessation in a Pakistani population include to protect the health of oneself or family members, and due to promptings from family members. Self-discipline, personal willpower, distraction strategies, and positive reinforcement play an important role in a population where smoking cessation aids may be inaccessible to many. Moreover, peer-pressure to quit and social exclusion also motivate smokers towards quitting, as does the negative self-image one associates with themselves because of their addiction to smoking. Lastly, most public health interventions, such as mass media campaigns and anti-tobacco advertisements, were not perceived as being helpful for motivating cessation.
Availability of data and materials
Saw the data is available from the authors on reasonable request, and is not available to be shared publicly due to constraints of the institutional review board at the Aga Khan University.
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The authors would like to acknowledge the Research and Development Wing of the Society for Promoting Innovation in Education (SPIE) for providing valuable research mentorship to authors MUJ, NA, and ZZF. SPIE is involved in innovation, education, and research in the academic and public health sectors. In addition, the authors would like to acknowledge Shamsa Ali and Muhammad Maisam Ali for their role in data collection.
This study received no financial support from any funding body or grant agency.
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Medical College, Aga Khan University Hospital, Stadium Road, Karachi, 74800, Pakistan
Russell Seth Martins, Muhammad Umer Junaid, Namrah Aziz & Zoha Zahid Fazal
Altamash Institute of Dental Medicine, Block 3 Clifton, Karachi, 75500, Pakistan
Muhammad Sharjeel Khan & Fatima Shah
Darul Sehat Hospital, Gulistan-e-Johar, Karachi, 74200, Pakistan
Section of Pulmonary and Critical Care Medicine, Department of Medicine, Aga Khan University Hospital, Stadium Road, Karachi, 74800, Pakistan
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RSM conceptualized and supervised the investigation, along with devising the methodology and analyzing the data. RSM was a major contributor in writing and editing the manuscript. MUJ conceptualized the investigation, along with devising the methodology and analyzing the data. MUJ was a major contributor in writing and editing the manuscript. MSK supervised the investigation, along with devising the methodology and analyzing the data. MSK was a major contributor in writing the manuscript. NA collected the data by verbally administering the survey. NA also contributed to analyzing the data and writing the manuscript. ZZF collected the data by verbally administering the survey. ZZF also contributed writing the manuscript. MU collected the data by verbally administering the survey. MU also contributed to analyzing the data. FS collected the data by verbally administering the survey and supervised the investigation. JAK supervised the investigation and contributed to editing the manuscript. The author(s) read and approved the final manuscript.
Correspondence to Javaid Ahmed Khan .
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Martins, R.S., Junaid, M.U., Khan, M.S. et al. Factors motivating smoking cessation: a cross-sectional study in a lower-middle-income country. BMC Public Health 21 , 1419 (2021). https://doi.org/10.1186/s12889-021-11477-2
Received : 07 January 2021
Accepted : 28 June 2021
Published : 18 July 2021
DOI : https://doi.org/10.1186/s12889-021-11477-2
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Effect of quitting immediately vs progressively on smoking cessation for smokers at emergency department in Hong Kong: A posteriori analysis of a randomized controlled trial
Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing
* E-mail: [email protected]
Affiliation Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong, Hong Kong
Roles Conceptualization, Data curation, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing
Affiliation School of Nursing, Sun Yat-Sen University, Guangzhou, China
Roles Conceptualization, Methodology, Writing – review & editing
Affiliation School of Nursing, The University of Hong Kong, Hong Kong, Hong Kong
Roles Project administration, Resources, Writing – review & editing
Affiliation United Christian Hospital, Hospital Authority, Hong Kong, Hong Kong
Roles Data curation, Formal analysis, Writing – review & editing
Affiliation Department of Pharmacology and Pharmacy & Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, Hong Kong
Roles Conceptualization, Methodology, Supervision, Writing – review & editing
- William Ho Cheung Li,
- Wei Xia,
- Man Ping Wang,
- Derek Yee Tak Cheung,
- Kai Yeung Cheung,
- Carlos King Ho Wong,
- Tai Hing Lam
- Published: January 26, 2023
- Peer Review
- Reader Comments
A progressive approach to quitting smoking has been a popular strategy for motivating smokers who are reluctant to quit. However, whether this strategy can effectively achieve complete cessation or is as successful as quitting immediately remains unresolved. This study aimed to determine whether quitting immediately or progressively was more effective in achieving complete cessation among smokers in Hong Kong who presented at emergency departments.
Methods and findings
A posteriori analysis of a single-blinded, multicenter, randomized controlled trial was performed. The original trials was conducted at emergency departments of four major acute hospitals in different districts of Hong Kong. In total, 1571 smokers 18 years or older who presented at 4 major emergency departments between July 4, 2015 and March 17, 2017 were randomized into an intervention group (n = 787) and a control group (n = 784). The intervention group received brief advice (about 1 minute) and could choose their own quit schedules (immediate or progressive, labeled QI and QP, respectively). The control group received a smoking cessation leaflet. Follow-ups were conducted at 1, 3, 6 and 12 months. The primary outcomes, by intention-to-treat, were biochemically validated abstinence between the QI subgroup and control group; between the QP subgroup and control group, and between the QI subgroup and QP subgroup at 6 months. After the propensity sore matching, the biochemically validated abstinence was statistically significantly higher in the QI subgroup than the control group at 6 months (12.1% vs 3.4%, P = 0.003; adjusted odds ratio [aOR] 4.34, 95% CI 1.63–11.52) and higher in the QP subgroup than the control group at 6 months (9.8% vs 3.4%, P = 0.02; aORs 2.95, 95% CI: 1.04–8.39). No statistically significant differences of biochemically validated abstinence at both 6 month (12.1% vs 9.8%, P = 0.49; aORs 1.50, 95% CI: 0.71–3.19) were found in the comparison between QI and QP subgroups.
This study demonstrates that the strategy of quitting progressively is effective, especially for smokers who lack motivation or find it difficult to quit. If adopted routinely, such an approach can help achieve a greater level of smoking abstinence in the community.
ClinicalTrials.gov: NCT02660957 .
Citation: Li WHC, Xia W, Wang MP, Cheung DYT, Cheung KY, Wong CKH, et al. (2023) Effect of quitting immediately vs progressively on smoking cessation for smokers at emergency department in Hong Kong: A posteriori analysis of a randomized controlled trial. PLoS ONE 18(1): e0280925. https://doi.org/10.1371/journal.pone.0280925
Editor: Yann Benetreau, Public Library of Science, UNITED STATES
Received: February 9, 2021; Accepted: December 22, 2022; Published: January 26, 2023
Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data belong to the funder (Health and Medical Research Fund, Food and Health Bureau, Hong Kong Special Administrative Region). The data can be accessed only with the permission by the Bureau ( https://rfs2.fhb.gov.hk/english/welcome/welcome.html ). The authors did not have any special access privileges that others would not have.
Funding: This research was funded by Health and Medical Research Fund, Food and Health Bureau, Hong Kong Special Administrative Region (Dr Li: grant No. 12133111). The funder sources had no role in the design and conduct of the study; collection; management; analysis; and interpretation of the data; preparation; review; or approval of the manuscript; and decision to submit the manuscript for publication.
Competing interests: The authors have declared that no competing interests exist.
Cigarette smoking is addictive, and quitting the practice is very difficult [ 1 , 2 ]. Our previous studies have found that many smokers recruited from outpatient clinics and the community were reluctant to quit, but showed an interest in reducing the number of cigarettes smoked per day [ 3 – 5 ]. Therefore, a potential strategy would be to allow or motivate smokers to quit progressively, with the ultimate goal of complete cessation of smoking. The progressive approach to quitting smoking has been used for a long time, following the assumption that smokers who reduce cigarette consumption and nicotine dependence will find it easier to further reduce the number of cigarettes smoked or quit smoking altogether [ 6 , 7 ]. Nevertheless, whether the progressive approach can eventually lead to complete cessation or is as effective as abruptly quitting smoking remains controversial. Many previous studies have incorporated the strategy of quitting progressively in addition to nicotine replacement therapy, and their findings support the effectiveness of this strategy in achieving complete cessation in smokers who initially lacked the motivation to quit [ 3 , 8 ]. However, not all smokers opt for pharmacotherapy to manage nicotine dependence. It has been reported that adherence to nicotine replacement therapy is low among Chinese smokers [ 9 , 10 ]. It remains unclear whether using the progressive quitting strategy in such a population will help achieve long-term cessation [ 5 , 7 ]. A previous trial conducted by our research group showed that quitting immediately was more effective than quitting progressively, although nicotine replacement therapy was not used. The outcomes of smokers were assessed at the 6-month medical follow-up in an outpatient clinic [ 4 ]. Another trial on smokers recruited from community settings showed that both the immediate and progressive approaches had similar 7-day point prevalence abstinence rates when assessed at the 6-month follow-up [ 5 ]. A Cochrane systematic review from 2019, which analyzed data from 22 randomized controlled trials (9219 participants) on quitting smoking immediately vs. progressively, found that neither approach was superior to the other in terms of long-term quitting rates [ 8 ]. Our previous trial examined the effectiveness of a brief self-determination theory-based smoking cessation intervention adopted for 1571 smokers who presented at emergency departments. We found that giving the smokers the option to either quit immediately or gradually doubled the quitting rates, compared to a control group that only received a smoking cessation pamphlet [ 11 ]. In this study, we aimed to conduct a posteriori analysis of the data from this published randomized controlled trial to determine whether the smokers who chose to quit immediately or progressively had higher quitting rates than the smokers in the control group. In addition, the analysis aimed to determine which option (immediate or progressive) was more effective in achieving complete cessation.
Materials and methods
Study design and intervention.
We analyzed the archived data from our previously published randomized controlled trial of a brief self-determination theory-based smoking cessation intervention adopted for smokers recruited from emergency departments [ 11 ]. Ethical approval was obtained from the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW14-528). The trial protocol has been published elsewhere [ 11 ]. Participants provided written informed consent.
Participants who presented at the emergency departments of four major acute care hospitals in different districts of Hong Kong were considered eligible if they were current smokers (occasional or daily) aged 18 years or older and triaged as either semi-urgent (level 4) or non-urgent (level 5) [ 12 ]. Exclusion criteria included an impaired mental status, cognitive impairment, communication barriers, or enrollment in other smoking cessation projects.
The sample size was calculated according to a previous trial [ 3 ] of a smoking reduction plus nicotine replacement therapy intervention involving 1154 Chinese adult smokers unwilling to quit smoking (biochemically validated quit rate of 4.4% [10 of 226] in the control group and 8.0% [74 of 928] in the intervention group at 6months). To detect a two-sided significant difference between groups by a chi-square test for comparing proportions with a power of 80% and significance level of 5%, the required sample size was estimated to be 1088 participants (544 in each group). Given an expected attrition rate of approximately 30% at the 6-month follow-up, the target was at least 1554 individuals (777 in each group). Between July 4, 2015 and March 17, 2017, 1571 smokers who presented at 4 major emergency departments consented to participate in this randomized controlled trial and were randomized into an intervention group (n = 787) and a control group (n = 784). Participants in the intervention group received brief advice and were given the option to either quit immediately (QI) or progressively (QP). Participants in the control group received a smoking cessation leaflet. Other details of the trial have been reported elsewhere [ 11 ]. Table 1 shows the characteristics of participants in the QI, QP, and the control groups. A Consolidated Standards of Reporting Trials (CONSORT) flowchart is presented in Fig 1 .
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The primary outcome measures of this posterior analysis consisted of biochemically validated abstinence comparisons between the QI subgroup and control group, between the QP subgroup and control group, and between the QI and QP subgroups as assessed at the 6-month follow-up.
The secondary outcomes included differences in biochemically validated abstinence as assessed at the 12-month follow-up, the self-reported 7-day point prevalence of abstinence as assessed at the 6- and 12-month follow-ups, and a self-reported reduction of at least 50% in daily cigarette consumption as assessed at the 6- and 12-month follow-ups between the QI subgroup and control group, between the QP subgroup and control group, and between the QI and QP subgroups.
Data analysis was performed using the IBM Statistical Package for Social Sciences (SPSS) for Windows (version 25.0; IBM). To minimize the effects of potential confounding factors (demographic characteristics and smoking history of participants) on the primary and secondary outcome measures, a three-way propensity matched analysis was performed. To estimate the propensity scores, all demographic and smoking variables were included in the multinomial regression to maximally inform the propensity of the dependent variables [ 13 ]. The QI subgroup vs. control group and QP subgroup vs. control group were matched 1:1 using a nearest-neighbor approach with caliper restrictions [ 14 ]. A three-way matched data set was then created without replacement by extracting participants from the QI or QP subgroup who had common matches with participants in the control group [ 14 , 15 ]. The standardized differences in demographic and smoking variables were compared to diagnose the balancing of the matched groups [ 16 ]. For continuous and dichotomous variables, the standardized difference used is shown in the S1 and S2 Figs, respectively [ 17 ].
The baseline characteristics of the participants in the QI, QP, and control groups were compared using an analysis of variance (ANOVA) for continuous variables, the chi-square test for categorical variables, and the two-tailed Fisher’s exact test based on the group cell size. For the variables showing significant difference in ANOVA, the Tukey’s honestly significant difference post-hoc test the Games -Howell post-hoc test and were performed when the assumption of equal variances was met and not met, respectively. All analyses were performed based on intention-to-treat, in which participants lost to follow-up were assumed to be active smokers with no changes with respect to the baseline. For primary analysis, the differences in biochemically validated quit rates, as assessed at the 6-month follow-up, between the QI, QP, and control groups were analyzed using the propensity score matched samples. A similar approach was used to analyze the differences in secondary outcomes.
Univariate logistic regression was performed to examine the crude odds ratios (ORs) for primary and secondary outcomes using both the original unmatched and matched samples. A Generalized Logistic Mixed Model (GLMM) was then used to calculate the adjusted odds ratios (aORs) for primary and secondary outcomes after adjusting for characteristics at baseline and the random effect of hospitals using the matched sample. A P value < 0.05 was considered to be statistically significant.
In addition, a posteriori analysis was performed to examine the association between the quantity of smoking reduction across all follow-ups and abstinence at the final follow-up. The percentage reduction was calculated by dividing the difference in daily cigarette consumption between the baseline and a given follow-up by the number of cigarettes consumed at baseline. Multiple logistic regression models were used to examine the predictive power of the absolute and percentage reductions on 12-month abstinence in participants who had not quit by the time of the follow-ups. Each model examined the reduction quantity at a given follow-up as either the absolute or percentage reduction to predict the 12-month abstinence. All models were adjusted for the treatment condition (QI, QP, and control group), demographic and smoking characteristics at the baseline, and the random effect of hospitals. The observed power (1-β) of quitting immediately and quitting progressively on the biochemically validated quit rate, the self-reported quit rate, and self-reported reduction of cigarette consumption were then calculated using G*power. A scatterplot and fitted line analysis were then used to demonstrate the linear association between the absolute or percentage cigarette reduction at 1-, 3-, and 6-month follow-ups and biochemically validated abstinence as assessed at the 12-month follow-up. Given the discrepancies in smoking profiles between the QI and QP subgroups, a two-group propensity matching between the QP and control group was conducted to provide more information on the outcomes in smokers who chose to quit smoking progressively. Similar analyses as described above were also additionally performed.
Fig 1 shows that in the intervention group, 242 participants (30.7%) chose to quit smoking immediately and 545 participants (69.3%) chose to quit smoking progressively. Compared with the QI subgroup, the QP subgroup had a significantly higher mean rate of daily cigarette consumption (QP vs. QI: 15.0 vs. 12.8), more moderate to heavy nicotine dependence (QP vs. QI: 55.6% vs. 39.3%), and a higher number of participants who had not previously attempted to quit smoking (QP vs. QI: 34.5% vs. 20.7%). After propensity score matching, 174 pairs of subjects in the QI, QP, and control groups were matched and analyzed. In the matched sample shown in Table 2 , the absolute standardized differences in all covariates were less than 0.10, and the means and prevalence of baseline covariates were similar in the two matched samples, indicating good balance between the groups [ 18 ].
Tables 3 and 4 showed that after propensity score matching, the biochemically validated abstinence was significantly higher in the QI subgroup than in the control group as assessed at the 6-month (12.1% vs. 3.4%, P = 0.003; aOR = 4.34, 95% CI: 1.63–11.52) and 12-month follow-ups (10.9% vs. 4.0%, P = 0.01; aOR = 3.23, 95% CI: 1.24–8.43). The number needed to treat (NNT) for the QI subgroup was 11.5 [1/(0.121–0.034)]. Compared with the control group, the QI subgroup showed a significantly higher self-reported 7-day point prevalence of abstinence as assessed at the 6-month (21.8% vs. 7.5%, P < 0.001; aOR: 4.34, 95% CI: 1.63–11.52) and 12-month follow-ups (20.7% vs 6.3%, P < 0.001; aOR: 3.23, 95% CI: 1.24–8.43). After excluding those participants who completely ceased smoking, the number of participants who self-reported a reduction in smoking of at least 50% was found to be significantly higher in the QI subgroup than control group at both the 6-month (19.9% vs. 10.6%, P = 0.03; aOR = 2.15, 95% CI: 1.10–4.24), and 12-month follow-ups (18.8% vs. 10.4%, P = 0.04; aOR = 1.95, 95% CI: 0.96–3.93). However, after adjusting for demographics and smoking characteristics at the baseline and the random effect of hospitals, the aOR as assessed at the 12-month follow-up was no longer significantly different between the two groups ( P = 0.07; aOR = 1.95, 95% CI: 0.96–3.93).
The biochemically validated abstinence was also significantly higher in the QP subgroup than the control group when it was measured at the 6-month (9.8% vs. 3.4%, P = 0.02; aOR = 2.95, 95% CI: 1.04–8.39) and 12-month follow-ups (10.3% vs. 4.0%, P = 0.02; aOR = 2.85, 95% CI: 1.11–7.33). The NNT for the QP subgroup was 15.6 [1/(0.098–0.034)]. Compared with the control group, the QP subgroup showed a significantly higher self-reported 7-day point prevalence of abstinence when measured at the 6-month (14.4% vs. 7.5%, P = 0.04; aOR = 1.96, 95% CI: 1.12–4.08) and 12-month follow-ups (19.0% vs. 6.3%, P < 0.001; aOR = 3.10, 95% CI: 1.52–6.79). After excluding those participants who completely ceased smoking, the number of participants who self-reported a reduction in smoking of at least 50% was significantly higher in the QP subgroup than in the control group as measured at the 6-month (24.2% vs. 10.6%, P = 0.001; aOR = 2.70, 95% CI: 1.40–5.23) and 12-month follow-ups (29.8% vs. 10.4%, P < 0.001; aOR = 3.42, 95% CI: 1.76–6.64). A comparison of the baseline characteristics and smoking profiles between the QP and control groups after two-group propensity score matching is presented in the S1 Table . The cessation outcomes showed that the biochemically validated and self-reported abstinence rates among subjects in the matched QP group were significantly higher than those in the matched control group as assessed at both the 6- and 12-month follow-ups ( S2 Table ). After excluding those participants who completely ceased smoking, participants who self-reported a reduction in smoking of at least 50% was higher in the QP subgroup than in the control group. This increase was significantly different when measured at the 12-month follow-up, but not at the 6-month follow-up.
There were no significant differences in biochemically validated abstinence between the QI and QP subgroups at when assessed at the either 6-month (12.1% vs. 9.8%, P = 0.49; aOR = 1.50, 95% CI: 0.71–3.19) or 12-month follow-up (10.9% vs. 10.3%, P = 0.86; aOR = 1.22, 95% CI: 0.57–2.59). Higher self-reported abstinence was reported in the QI subgroup than in the QP subgroup, but this difference was not significant as assessed at either the 6-month (21.8% vs. 14.4%, P = 0.07; aOR = 1.67, 95% CI: 0.93–2.99) or 12-month follow-up (20.7% vs. 19.0%, P = 0.69; aOR = 1.08, 95% CI: 0.62–1.87). Excluding those participants who completely ceased smoking, the number of participants who self-reported a reduction in smoking of at least 50% was lower in the QI subgroup than in the QP subgroup. This reduction was significantly different between the two groups when assessed at the 12-month follow-up (18.8% vs. 29.8%, P = 0.03; aOR = 0.60, 95% CI: 0.31–3.98), but not at the 6-month follow-up (19.9% vs. 24.2%, P = 0.38; aOR = 0.77, 95% CI: 0.42–1.39). Table 5 presented that the powers of the quitting immediately had a and quitting progressively on the biochemically validated quit rate, the self-reported quit rate, and self-reported reduction of cigarette consumption were acceptable (all larger than 0.80) to detect the hypothesis in this study.
The scatterplot and fitted line analysis showed that the values of both the absolute and percent cigarette reduction at the 1-, 3-, and 6-month follow-ups were associated with the biochemically validated abstinence as assessed at the 12-month follow-up ( Fig 2 ). The R 2 showed that the percent cigarette reduction (a-2, b-2, c-2) could better predict the 12-month abstinence than the absolute cigarette reduction (a-1, b-1, c-1).
The results of this a posteriori analysis showed that the number of smokers in the intervention group who chose to quit smoking progressively outnumbered that of smokers who chose to quit smoking immediately by more than two folds (progressive vs. immediate: 69.3% vs. 30.7%). The results also indicated that smokers in the QP subgroup had significantly higher rates of daily cigarette consumption and nicotine dependency and had made fewer attempts to quit previously than those in the QI subgroup. The findings of this study provide support to existing reports in the literature which show that many heavy smokers are reluctant to quit smoking immediately. Therefore, smoking and the quitting histories of smokers should be considered when recommending different types of smoking cessation interventions. For heavy or hard-core smokers who are reluctant to quit, intervention strategies that enforce immediate quitting may be perceived as being too harsh and be ineffective in helping them to cease smoking. In contrast, those who smoke a few cigarettes a day with mild nicotine dependence may deem the progressive quitting approach unnecessary or superfluous and consequently undermine the effectiveness of the approach.
The subgroup analyses showed that smokers in both the QI and QP subgroups had significantly higher biochemically validated abstinence and self-reported 7-day point prevalence of abstinence rates at the 6- and 12-month follow-ups than those in the control group. The results demonstrated that offering a brief smoking cessation intervention to smokers and allowing them to choose the quitting schedules effectively promoted the cessation of smoking. In addition, a significantly higher proportion of smokers who had not quit in the QP subgroup achieved at least 50% reduction in cigarette consumption by the 12-month follow-up, compared to those in the QI subgroup. Though the ultimate goal of quitting progressively is the complete cessation of smoking, it is anticipated that these smokers will find it much easier to gradually reduce their cigarette consumption or quit smoking altogether in the near future, given that they have already initiated the process and reduced their nicotine dependence [ 6 , 7 ]. The fitted line analysis supported the potential of using the rates of reduction in cigarette consumption to predict future abstinence from smoking. These findings imply that progressive quitting is a useful alternative approach for smokers who lack motivation and experience difficulty in quitting smoking [ 19 ].
Given the discrepancies in the smoking profiles of smokers who choose to quit either immediately or progressively, it is difficult to compare the smoking cessation outcomes between the QI and QP groups. Therefore, three-group and two-group propensity score matching analyses were conducted. This study conducted a posteriori analysis of data from a previous trial, which could not provide sufficient evidence for a causal relationship between a reduction in smoking and abstinence from smoking. In future, a randomized controlled trial should be conducted in which smokers with similar smoking profiles should be recruited to test the differences in reduction and abstinence for longer follow-up periods.
Implications for clinical practice
This study addresses the important question of whether the approach to quitting smoking in a progressive manner is or is not effective. Our findings also addressed existing gaps in the field by demonstrating that quitting progressively is effective, especially for chronic smokers who lack motivation or find it difficult to quit. A measured application of these results can help achieve a greater level of abstinence from smoking and make important contributions to evidence-based practice. Most importantly, the outcomes of this original study can inform future researchers and policymakers on designing effective smoking cessation interventions and policies for smokers who are reluctant to quit smoking immediately. Thus, the study has important implications for clinical practice and the improvement of public health. In future, we will explore the means to retain smokers in gradual cessation programs as they reduce their frequency of smoking, develop more successful methods to encourage reduction in smoking, and find ways to prevent a perception of failure by participants, which usually causes them abandon their attempts to reduce the number of cigarettes smoked and quit smoking. Finally, in Hong Kong, which is a region with a low prevalence of smoking yet has many hard-core smokers, our results can guide future strategies toward a total ban on tobacco sales.
This secondary analysis of a randomized controlled trial provides further support to a previous study that allowed smokers to choose their quitting schedules, which was essential in motivating them to quit smoking. This study supplements the previous trial by determining that the progressive quitting approach is effective, especially for smokers who lack motivation or find it difficult to quit.
S1 checklist. consort 2010 checklist of information to include when reporting a randomized trial a ..
S1 Fig. Calculation formula of the standardized difference for continuous variables.
S2 Fig. Calculation formula of the standardized difference for dichotomous variables.
S1 Table. Comparison of baseline characteristics and smoking profiles among subjects in the QP group and control group in the original unmatched sample and the propensity-score matched sample.
S2 Table. Cessation outcomes of subjects in the QP group vs. control group original trial protocol and statistical analysis plan.
S1 File. Trial protocol with statistical analysis plan.
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- Published: July 1992
Reasons for quitting and predictors of cessation among medical patients
- Carol L. Duncan RD, MPH, Ms. 1 ,
- Steven R. Cummings MD 1 , 2 ,
- Esther Sid Hudes PhD, MPH 1 , 2 ,
- Elaine Zahnd PhD 1 &
- Thomas J. Coates PhD 1 , 2
Journal of General Internal Medicine volume 7 , pages 398–404 ( 1992 ) Cite this article
Objective: To describe why medical patients quit smoking and the methods they use .
Design: Cross-sectional and prospective cohort design. Patient smokers were enrolled in a study of physician counseling about smoking. One year later, 2,581 of the patients were asked about quit attempts and methods used. Of those, 245 former smokers whose quitting had been biologically validated were interviewed about why and how they had quit .
Setting: Offices of internists and family practitioners in private practice and a health maintenance organization .
Subjects: Consecutive sample of ambulatory patients who smoked .
Measurements and main results: Baseline questionnaires included demographic data, smoking history, and symptoms and diagnoses related to smoking. After one year, subjects were interviewed about smoking status and methods used in attempting to quit. Cessation was confirmed by biochemical testing. Those who had quit were asked about reasons for quitting. Seventy-seven percent of successful quitters gave health-related reasons for quitting and the quitters ranked “harmful to health” as the most important reason for quitting. In a multivariate analysis, those who had a college education, who had social pressures to quit, and who had greater confidence in being able to quit were more likely to have quit smoking one year later, while those who smoked their first cigarette within 15 minutes of awakening and who had more diagnoses related to smoking were less likely to have quit smoking one year later. Participation in a treatment program and having been counseled by a physician or nurse practitioner were positively related to successful quitting, while use of filters or mouthpieces was negatively related .
Conclusions: Concerns about health are the most common reason patients give for quitting, and addiction is the most important barrier to quitting. Education, social pressure, provider advice, and formal programs, but not over-the-counter devices, appear to increase the chances that smokers will quit .
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the Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
Carol L. Duncan RD, MPH, Ms., Steven R. Cummings MD, Esther Sid Hudes PhD, MPH, Elaine Zahnd PhD & Thomas J. Coates PhD
the Department of Epidemiology, International Health, University of California, San Francisco, San Francisco, California
Steven R. Cummings MD, Esther Sid Hudes PhD, MPH & Thomas J. Coates PhD
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Supported by grant #CA38374 from the National Cancer Institute. Dr. Cummings’ work is supported in part by the Henry J. Kaiser Faculty Fellowship in General Internal Medicine.
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Duncan, C.L., Cummings, S.R., Hudes, E.S. et al. Quitting smoking. J Gen Intern Med 7 , 398–404 (1992). https://doi.org/10.1007/BF02599155
Issue Date : July 1992
DOI : https://doi.org/10.1007/BF02599155
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npj Primary Care Respiratory Medicine volume 32 , Article number: 50 ( 2022 ) Cite this article
- Chronic obstructive pulmonary disease
We explored past-year quit attempts, cessation methods used, and associations with sociodemographic, smoking, and health-related characteristics among smoking patients with chronic obstructive pulmonary disease (COPD) in Germany. Cross-sectional survey data of 509 past-year smokers (current smokers and ≤12 months abstinent) with COPD (ICD-10 code J44.x and FEV1/FVC <0.70) from 19 pulmonary primary care practices were used. Associations were explored between age, sex, educational qualification, lung function, urges to smoke, psychological distress, and (a) ≥1 past-year quit attempt (yes/no), (b) use of ≥1 evidence-based smoking cessation method (yes/no). Of all patients, 48.5% ( n = 247, 95% confidence interval (CI) 44.2–52.9) reported ≥1 past-year quit attempt. Such an attempt was positively associated with the male sex (Odds Ratio (OR) = 1.50, 95% CI 1.01–2.24) and negatively associated with time spent with urges to smoke (OR = 0.69, 95% CI 0.52–0.91). During the most recent past-year quit attempt, one-third of the patients used ≥1 evidence-based smoking cessation method (31.2%, 95% CI 25.4–37.0), which was positively associated with the strength of urges to smoke (OR = 1.62, 95% CI 1.09–2.41). Combined behavioural and pharmacological treatments were used by 4.0% ( n = 10, 95% CI 1.6–6.5). Electronic cigarettes were used most frequently (21.5%, 95% CI 16.3–26.6). Although a high proportion of COPD patients in German pulmonary primary care attempt to quit smoking, only a few of them use evidence-based methods as assistance for quitting.
Tobacco smoking is the leading risk factor for the development of chronic obstructive pulmonary disease (COPD) 1 , and continued smoking can accelerate COPD progression 2 . Among patients with COPD, smoking cessation is the most effective treatment that reduces the excessive decline in lung function 3 , 4 , 5 , improves respiratory symptoms 5 , 6 , decrease the risk of exacerbations 7 and hospital admission 8 , and improves survival rates 3 , 9 , 10 . Nevertheless, a previous German cohort study showed a high smoking prevalence of 38% among COPD patients 11 .
Tobacco dependence and psychological distress influence persistent tobacco consumption 12 and affect quitting behaviour 13 , 14 . In turn, smokers with COPD report higher levels of tobacco dependence than smokers without COPD 15 , 16 , 17 . Anxiety and depression are common comorbidities of COPD 18 , and COPD patients experience more psychological distress compared to the general population 19 . As a result, quitting smoking seems to be more difficult for smokers with COPD than for healthy smokers 16 .
According to international research, between 48–65% of smokers with COPD attempted to quit smoking in the past year 20 , 21 , 22 , 23 . Quit attempts were positively associated with younger age 21 , female gender 22 , and higher educational qualification 23 . To our knowledge, data on quit attempts and on associated characteristics among patients with COPD in Germany are missing.
To support quitting smoking, the German guidelines for the diagnosis and treatment of COPD recommend various evidence-based methods, including pharmacological (e.g., nicotine replacement therapy (NRT), varenicline, bupropion) and behavioural (e.g., brief physician advice, individual, group or telephone counselling) treatments, which increase the chances of successful long-term abstinence compared with unassisted quitting 24 , 25 . The guidelines especially recommend the combination of behavioural and pharmacological treatments as the most effective approach to assist smoking cessation 24 , 25 . Alternative methods, such as electronic cigarette (EC), acupuncture, or hypnotherapy, currently have no clarified evidence and therefore find no recommendation in the guidelines 24 , 25 . A former cross-sectional, web-based survey on smokers with lung conditions (70% of them with COPD) across Europe showed that, in this population, the most frequently used method to support smoking cessation was NRT (31%), followed by EC (20%) 26 . Usage rates of other evidence-based and alternative methods were reported as follows: evidence-based varenicline (13%), bupropion (9%), and telephone quitlines (3%), and alternative methods such as acupuncture (7%) and hypnotherapy (5%) 26 . In Germany, there is a lack of information on the use of evidence-based and alternative smoking cessation methods among smokers with COPD, and it remains unclear whether sociodemographic, smoking, and health-related characteristics are associated with the use of evidence-based cessation methods in this smoking population.
Therefore, among a clinical sample of the adult (≥18 years) current smokers and recent ex-smokers (≤12 months since quitting) with clinically diagnosed COPD, we aimed to estimate:
the prevalence of self‐reported past-year quit attempts, and to characterise these quit attempts (i.e. number of attempts, whether the most recent attempt was made abruptly or by cutting down first, and whether it was planned or unplanned);
the prevalence of the use of evidence-based and alternative methods to assist the most recent past-year quit attempt;
associations between sociodemographic characteristics, percentage of predicted forced expiratory volume in 1 s (FEV1% predicted) as a parameter of COPD severity 1 , time spent with urges to smoke, the strength of urges to smoke, psychological distress, and the presence of ≥1 self‐reported past-year quit attempt;
associations between sociodemographic characteristics, FEV1% predicted, time spent with urges to smoke, the strength of urges to smoke, psychological distress, and the use of ≥1 evidence-based method to assist the most recent past-year quit attempt.
Design, setting and participants
We used data from the ‘Use and real-world effectiveness of smoking cessation methods in patients with COPD’ (RESPIRO) study. This cross-sectional survey among COPD patients was conducted in 19 pulmonary practices across the German federal state of North Rhine-Westphalia (NRW) between September 2018 and June 2020. The RESPIRO study was prospectively registered at the German Clinical Trials Register ( DRKS00011322 ) and approved by the ethics committee of the Medical Faculty of the Heinrich-Heine-University Duesseldorf, Germany (ID 5680 R).
Pulmonary practices were recruited through the scientific information network of the Scientific Institute for Health Care Research in Pneumology ‘WINPNEU’ ( https://winpneu.de ), initiated by the German federal association of pulmonologists, sleep and respiratory physicians. A contact person within the practice (i.e. the pulmonologist, or a study nurse) carried out the recruitment of patients aged ≥18 with the diagnosis of COPD according to the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10 code: J44.x) 27 . The contact person also documented the clinical characteristics of participating patients in the study questionnaire, including the ICD-10 code for COPD and lung function parameters of the most recent spirometry: forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1% predicted. Eligible patients received all study materials (questionnaire, informed consent form, and a small non-financial incentive) to take home with them and were asked to send the completed documents back to the study centre.
Of 4377 distributed questionnaires, 2012 questionnaires were sent back (46%). Six responders withdrew their informed consent to participate afterwards. Among the remaining 2006 responders, 2004 responders had a valid ICD-10 code for COPD entered in their questionnaire. Of these, 653 (32.6%) had reported to be current smokers of cigarettes or other combustible tobacco products (e.g. pipe, cigars), 142 (7.1%) had reported to be recent ex-smokers (≤12 months since quitting), 957 (47.8%) had reported to be long-term ex-smokers (>12 months since quitting), and 162 (8.1%) had reported to be never smokers (4.5%, n = 90 no answer).
For the present study, we conservatively included only past-year smokers (current smokers and recent ex-smokers) with a post-bronchodilator ratio of FEV1/FVC < 0.70, which we calculated according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria for the diagnosis of COPD 1 . Of all 795 past-year smokers listed as COPD patients in the practices according to ICD-10 27 , 286 (36%) had an FEV1/FVC ≥0.70 and were thus excluded from final statistical analyses. This resulted in a final study sample of 509 past-year smokers with a spirometry-confirmed COPD diagnosis.
Past-year quit attempts were measured by asking about serious attempts to stop smoking in the past year; full details are provided in Table 1 . For statistical analyses, the number of attempts was recoded into a dichotomous variable ‘past-year quit attempt’ (yes, ≥1 attempt versus no attempt). To characterise these attempts, the absolute number of attempts was categorised into four groups: one attempt, two attempts, three attempts, and four or more attempts.
Furthermore, smokers with ≥1 past-year quit attempt were asked, whether their most recent quit attempt was made abruptly or by cutting down first, and whether it was planned or initiated spontaneously. This group was also asked about the use of evidence-based and alternative smoking cessation methods to assist their most recent past-year quit attempt (multiple answers were allowed). Evidence-based methods were chosen according to the current German guidelines for the diagnosis and treatment of COPD patients 24 , 25 : behavioural (brief physician advice, individual, group or telephone counselling) and pharmacological (NRT with/without a prescription, varenicline, and bupropion) methods. For regression analyses, we coded a new dichotomous variable, ‘use of ≥1 evidence-based smoking cessation method’ (yes versus no). Alternative methods were chosen according to frequently used methods in the German general smoking population 28 .
Sociodemographic characteristics measured were: age, sex (male, female), and educational qualification (low = 9 years of education or no graduation, medium = 10 years, high ≥11 years).
The FEV1% predicted was used to categorise COPD severity for descriptive statistics: FEV1 ≥80% predicted = mild (GOLD 1), 50% ≤FEV1 <80% predicted = moderate (GOLD 2), 30% ≤ FEV1 <50 % predicted = severe (GOLD 3), and FEV1 <30% predicted = very severe (GOLD 4) COPD 1 . For regression analyses, the FEV1% predicted was used as a continuous variable.
Time spent with urges to smoke and strength of urges to smoke were measured by using the German version of the Strength of Urges to Smoke Scale (SUTS) 29 assessing tobacco dependence; full details are provided in Table 1 . Both items were included as continuous variables (range 0 to 5) for regression analyses.
Psychological distress was measured using the validated, ultra-brief German version of the Patient Health Questionnaire-4 (PHQ-4) 30 , 31 assessing symptoms of major depression and generalised anxiety; full details are provided in Table 1 . The total PHQ-4 score ranges from 0 to 12, with a score of 6 or above representing psychological distress. For descriptive statistics, the PHQ-4 was used as a dichotomous variable by using this cut-off. For regression analyses, the PHQ-4 was used as a continuous variable.
The study protocol and analysis plan were written prior to analysing data and pre‐registered on the Open Science Framework: https://osf.io/a24t3/ . All statistical analyses were conducted using IBM SPSS Statistics Version 28.0.
To assess research aims 1 and 2, we used complete case data and presented prevalence data together with 95% confidence intervals (95% CI).
A multivariable logistic regression model was used to assess the association between age, sex, educational qualification, FEV1% predicted, time spent with urges to smoke, the strength of urges to smoke, psychological distress and the dichotomous outcome ‘past-year quit attempt’ (1 = yes, ≥1 attempt versus 0 = none) among all 509 past-year smokers (research aim 3). Among past-year smokers with ≥1 quit attempt, we repeated this analysis with the dichotomous outcome ‘use of ≥1 evidence-based smoking cessation method’ (1 = yes versus 0 = none) during the most recent past-year attempt (research aim 4).
Since questionnaires were self-completed, missing data was relatively high and occurred in the total study sample in educational qualification (10.0%, n = 51), time spent with urges to smoke (5.1%, n = 26), the strength of urges to smoke (4.9%, n = 25), psychological distress (9.4%, n = 48), and past-year quit attempt (13.2%, n = 67). Therefore, we used multiple imputations to impute missing data of all variables of interest included in regression models. Imputations were based on logistic regression models (for dichotomous and categorical variables) and predictive mean matching (for continuous variables) using the multivariate imputation by chained equations (MICE) algorithm 32 . Ten imputed datasets with ten iterations per dataset were created 33 . Results of analyses across the imputed datasets were combined using Rubin’s rules 34 and presented as odds ratio (OR) with 95% CI and p value.
Regressions were repeated in the total sample of all 795 past-year smokers listed as COPD patients in the practices according to ICD-10 27 (including those with an FEV1/FVC ≥0.70 calculated by us) (Supplementary Table 1 ).
In the sample of current smokers with COPD (FEV1/FVC < 0.70), we conducted a post-hoc descriptive analysis of a current motivation to stop smoking, measured using the validated German version of the Motivation To Stop Scale (MTSS) 35 , 36 (Supplementary Table 2 ).
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Sociodemographic, smoking, and health-related characteristics of the study sample are presented in Table 2 . The patients had a mean age of 62.8 years (standard deviation (SD) = 8.4 years, range 35–87 years), and 56.2% of them were male.
Prevalence and characteristics of quit attempts
Of all past-year smokers, 48.5% ( n = 247, 95% CI 44.2–52.9) reported ≥1 past-year quit attempt. Among this group, 43.3% ( n = 107) reported a single past-year attempt, 29.1% ( n = 72) reported two attempts, 14.2% ( n = 35) reported three attempts, and 13.4% ( n = 33) reported four or more attempts. Just over half of patients (52.6%, n = 130, 95% CI 46.4–58.9) reported that they had attempted to quit by cutting down first, whereas 37.7% ( n = 93, 95% CI 31.6–43.7) reported that they had stopped abruptly (9.7%, n = 24 no answer). Half of the patients (50.2%, n = 124, 95% CI 44.0–56.4) reported that their most recent quit attempt was initiated spontaneously, whereas 37.7%, ( n = 93, 95% CI 31.6–43.7) had planned their attempt in advance (12.1%, n = 30 no answer).
Use of smoking cessation methods
The prevalence of the use of various smoking cessation methods to support the most recent past-year quit attempt is presented in Table 3 . From all presented methods, 46.2% ( n = 114) of the patients had used one method, 22.7% ( n = 56) had used two methods, 11.3% ( n = 28) had used three methods, and 6.4% ( n = 16) had used four or more methods. Around one-third (31.2%, n = 77, 95% CI 25.4–37.0) reported the use of ≥1 evidence-based method, of whom 19.0% ( n = 47, 95% CI 14.1–23.9) used ≥1 behavioural, and 16.2% ( n = 40, 95% CI 11.6–20.8) used ≥1 pharmacological method. Combined behavioural and pharmacological methods were used by 4.0% ( n = 10, 95% CI 1.6–6.5).
The most commonly used evidence-based cessation method was NRT with/without prescription (14.6%, n = 36, 95% CI 10.2–19.0), followed by brief physician advice (13.8%, n = 34, 95% CI 9.5–18.1) and behavioural counselling (individual or group therapy) (6.1%, n = 15, 95% CI 3.1–9.1). EC with/without nicotine was the most commonly used method among all investigated methods (21.5%, n = 53, 95 % CI 16.3–26.6).
Characteristics associated with ≥1 past-year quit attempt
Multivariable associations between sociodemographic, smoking, and health-related characteristics of the study sample and the presence of ≥1 past-year quit attempt (= yes) are shown in Table 4 . Being male was positively associated with reporting ≥1 past-year quit attempt (OR = 1.50, 95% CI 1.01–2.24), while time spent with urges to smoke was negatively associated with such ≥1 attempt (OR = 0.69 per level on the 6-level scale, 95% CI 0.52–0.91) (see (a) in Table 4 ). No statistically significant association was found for age, educational qualification, FEV1% predicted, the strength of urges to smoke, and psychological distress. Regressions in the total sample of all 795 past-year smokers listed as COPD patients in the practices showed similar results with the exception that the association with male versus female sex became weaker (see (a) in Supplementary Table 1 ).
Characteristics associated with the use of ≥1 evidence-based smoking cessation method
Multivariable associations between sociodemographic, smoking and health-related characteristics of the study sample and the use of ≥1 evidence-based smoking cessation method during the most recent past-year quit attempt are shown in Table 4 . The strength of urges to smoke was positively associated with the use of ≥1 evidence-based smoking cessation method (OR = 1.62 per level on the six-level scale, 95% CI 1.09–2.41) (see (b) in Table 4 ). No statistically significant association was found for age, sex, educational qualification, FEV1% predicted, time spent with urges to smoke, and psychological distress. Regressions in the total sample of all 795 past-year smokers listed as COPD patients in the practices yielded similar results (see (b) in Supplementary Table 1 ).
Ancillary analysis of current motivation to stop smoking
In the total of 416 current smokers with COPD (FEV1/FVC <0.70), 2.6% did not answer the question, 33.4% ( n = 139, 95% CI 28.9–37.9) was unmotivated to quit (response 1 and 2), and 64.0% ( n = 266, 95% CI 59.3–68.6) was motivated to stop smoking (response 3–7), including 15.7% of those with a clear intention to do so in the next 1 to 3 months (response 6 and 7) (see Supplementary Table 2 ).
Among adult past-year smokers with spirometry-confirmed COPD from pulmonary practices in Germany, almost every second patient reported at least one past-year attempt to quit tobacco smoking. The most recent quit attempt was made rather by cutting down first and spontaneously. One-third of patients reported the use of at least one evidence-based method to support their most recent past-year quit attempt. Only 4% of attempts were supported by a combination of behavioural and pharmacological treatments. EC was the most commonly used cessation method. Male sex was positive, and time spent with urges to smoke was negatively associated with reporting at least one past-year quit attempt. The strength of urges to smoke was positively associated with the use of at least one evidence-based smoking cessation method.
The prevalence of past-year quit attempts among adult smokers with COPD determined in our study is comparable to two former international population-based household surveys (Canada: 48% 20 ; US: 52% 21 ), whereas two recent population-based telephone surveys from the US reported slightly higher rates of 60–65% 22 , 23 . However, it is notable to mention that the prevalence of quit attempts in the general smoking population is already higher in the US compared with data from Germany (56–57% 37 versus 19% 28 ).
Compared with smokers of the general population in Germany, the prevalence of reporting a past-year quit attempt determined among the COPD patients in our study is substantially higher (49 versus 19% 28 ), and more current smokers with COPD want to stop smoking (64.0 versus 38.8% 35 ). In a population-based study from the US, quit attempt rates among smokers with COPD were also significantly higher than in smokers without COPD 21 . These results suggest that smokers with COPD are highly motivated to quit harmful tobacco smoking.
Evidence on associations between individual characteristics and quit attempts in smokers with COPD is ambiguous. While our study found a positive association with being male and a negative association with time spent with urges to smoke, international studies reported positive associations with younger age 21 , female gender 22 and higher educational qualification 23 . However, it is notable to mention methodological differences between studies, such as the use of partially different exposure variables.
The association between increasing time spent with urges to smoke and less odds of quit attempts shown in our study may be explained by the fact that tobacco dependence reduces self-efficacy 13 , 38 , which plays an important role in smoking cessation 39 . Thus, smokers with COPD who feel constant urges to smoke probably tend not to attempt to quit harmful smoking because they don’t believe in their ability to stop.
The usage of evidence-based smoking cessation methods determined in our study is substantially lower than in international COPD populations 17 , 23 , and only a small fraction of smokers with COPD (4%) report the use of combined behavioural and pharmacological treatments as recommended in the German COPD guidelines 24 , 25 . This underuse is probably because this population does not receive adequate information about evidence-based smoking cessation methods and sufficient advice to use them 40 , 41 . Smokers with lung conditions not only need clear advice to quit but also extensive and target-group-specific information on effective treatment options 26 . However, health professionals in Germany experience a lack of training in how to deliver such smoking cessation counselling effectively and efficiently to their patients 42 , as such training is not standard in undergraduate and postgraduate medical training 43 . In addition, there are other, more structural deficits in the German healthcare system, including the lack of reimbursement of evidence-based smoking cessation methods and the lack of availability of professional smoking cessation services across the country 40 , although such access is particularly important for smokers with lung conditions 26 . The lack of reimbursements of costs for important therapies may represent a huge financial barrier towards the use of such methods, particularly towards the use of combined behavioural and pharmacological treatments. The fact that patients seem to underestimate the effectiveness of evidence-based smoking cessation methods 44 may also be a barrier to the use of these treatments.
Compared with past-year smokers from the German general population, about twice as many smokers with COPD in our study reported the use of evidence-based smoking cessation methods during the most recent past-year quit attempt (31 versus 13% 28 ). Comparable results were found in studies from the Netherlands and the US when assessing the ever use of these methods 17 and the use during the last quit attempt 23 among smokers with and without COPD. Previous population-based studies from Germany and England found an increase in the use of evidence-based smoking cessation methods with increasing levels of tobacco dependence 28 , 45 . Probably, smokers with greater tobacco dependence and associated withdrawal symptoms experience greater difficulties when quitting without any assistance and are therefore more likely to seek support 28 . In our study, increasing the strength of urges to smoke was comparably associated with higher odds of the use of such methods. Considering the fact that smokers with COPD already have a higher level of tobacco dependence compared with other smokers 15 , 16 , 17 , higher usage rates of evidence-based smoking cessation methods among the COPD population are as expected.
A relatively large number of smokers with COPD in our study (22%) reported the use of EC to support their most recent past-year quit attempt, and the usage was about twice as high as in the German general smoking population 28 . Although the effectiveness of EC for smoking cessation in smokers with COPD is still discussed 24 , 25 , previous findings suggest that the use of EC helps smokers with COPD to reduce cigarette consumption or prevent relapse 46 .
Our study provides detailed data on quit attempts and the use of smoking cessation methods, as well as data on associations with sociodemographic, smoking, and health-related characteristics in patients with COPD in a pulmonary primary care setting in Germany. As data collection took place in this setting, it was possible to recruit a broad patient collective, which included both routine control patients and ‘emergency’ patients who had current symptoms of (respiratory) infection and/or mild or moderate exacerbation. Data on lung function parameters of patients were delivered by the practices and are therefore less error-prone and more reliable than patients’ self-reports. Based on this data, we included only patients with a post-bronchodilator ratio of FEV1/FVC <0.70 and thus only patients with a valid COPD diagnosis according to the most recent GOLD guidelines 1 .
However, all other data were self-reported, increasing the risk of missing data. Some variables of interest in our study contained missingness, and it remained unclear if respondents skipped questions intentionally, by mistake, or because of an inability to provide an answer. Missing data were therefore imputed. Data on quit attempts were collected retrospectively, increasing the risk of recall bias that may have affected the prevalence estimates, as short-lasting or occurring further in the past quit attempts may fail to be reported 47 . Moreover, due to the conservative inclusion criterion of a post-bronchodilator ratio of FEV1/FVC <0.70, a relatively high number of past-year smokers (36%) were excluded from our analyses. This led to a relatively small sample size in our study, and the statistical power was probably too low to detect meaningful associations between exposure variables and determined outcomes. Furthermore, our data did not allow an investigation of adherence to smoking cessation methods.
In conclusion, around every second smoking patient with COPD in the German pulmonary primary care setting reports a past-year quit attempt, mainly independent of individual sociodemographic or health-related characteristics. Quit attempts are rarely supported by evidence-based smoking cessation methods, and hardly ever under the application of combined behavioural and pharmacological treatments, although recommended in COPD Guidelines. Urges to smoke seem to play an important role in attempting to quit and using evidence-based methods. EC is the most commonly used cessation method, although the effectiveness and safety of EC as a cessation method should be further investigated among smokers with COPD who do not want to use recommended evidence-based treatments. These quitting characteristics should be taken into account by physicians while helping their COPD patients to quit harmful smoking.
The data underlying this study are available to researchers from the corresponding author ([email protected]). All proposals requesting data access will need to specify how it is planned to use the data, and all proposals will need approval from the RESPIRO study team before the data release.
The code (i.e. SPSS syntax) for the statistical analyses is available to researchers from the corresponding author ([email protected]).
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The authors thank Prof. Dr. Antonius Schneider (Director of the Institute of General Practice, Technical University of Munich) and Dr. med. Thomas Hering (Specialist in pulmonary and bronchial medicine/pneumology, allergology and sleep medicine) for their valuable support with the ethics application of the RESPIRO study, Michael Horst (Head of the Institute Office of the Scientific Institute for Health Care Research in Pneumology (WINPNEU)) and Sebastian Böing (Specialist in internal medicine, pneumology, sleep medicine and allergology, Member of the Federal Board of the Professional Association of Pneumologists, Sleep and Respiratory Physicians (BdP), Deputy regional chairman of regional association Nordrhein, Member of the board of the WINPNEU) for their support with the recruitment of pulmonary practices, belonging to the scientific information network of WINPNEU. The authors also thank all pulmonary practices and patients who supported the RESPIRO study by participating. The RESPIRO study was funded by the Research Commission of the Medical Faculty at the Heinrich-Heine-University Duesseldorf, Germany.
Open Access funding enabled and organized by Projekt DEAL.
Authors and affiliations.
Institute of General Practice (ifam), Centre for Health and Society (chs), Addiction Research and Clinical Epidemiology Unit, Medical Faculty, Heinrich‐Heine‐University Duesseldorf, Duesseldorf, Germany
Yekaterina Pashutina, Daniel Kotz & Sabrina Kastaun
Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
Institute of General Practice (ifam), Centre for Health and Society (chs), Patient-Physician-Communication Research Unit, Medical Faculty, Heinrich‐Heine‐University Duesseldorf, Duesseldorf, Germany
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S.K. conceived the RESPIRO study, supervised the analyses, and critically revised the manuscript and the study protocol and the analysis plan. D.K. provided expert advice on the study protocol, and critically revised the manuscript and the analysis plan. Y.P. conceptualised and drafted the study protocol and the analysis plan, drafted the manuscript, and collected, analysed and interpreted the data. All named authors contributed substantially to the manuscript and agreed on its final version.
Correspondence to Sabrina Kastaun .
The authors declare no competing interests.
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Pashutina, Y., Kotz, D. & Kastaun, S. Attempts to quit smoking, use of smoking cessation methods, and associated characteristics among COPD patients. npj Prim. Care Respir. Med. 32 , 50 (2022). https://doi.org/10.1038/s41533-022-00316-5
Received : 23 June 2022
Accepted : 21 October 2022
Published : 10 November 2022
DOI : https://doi.org/10.1038/s41533-022-00316-5
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