Background and aims Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta‐analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions. Methods A systematic review and meta‐regression was conducted including 172 randomised controlled trials with at least 6 months follow‐up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta‐regression was used to create a model predicting smoking cessation outcomes. This model was used to re‐estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta‐regression models and smoking cessation differences and ratios to compare relative effectiveness. Results The meta‐regression model predicted smoking cessation rates well (pseudo R2 = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a ‘no support comparator’, self‐help was 1.33 times (95% CI = 1.16–1.49), brief physician advice 1.61 times (95% CI = 1.31–1.90), nurse individual counselling 1.76 times (95% CI = 1.62–1.90), psychologist individual counselling 2.04 times (95% CI = 1.95–2.15) and group psychologist interventions 2.06 times (95% CI = 1.92–2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness. Conclusions Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
BACKGROUND: Web-based interventions are thought to overcome barriers to treatment, such as accessibility and geographical location, which can undermine the effectiveness of traditional face-to-face interventions. Owing to these features, researchers are increasingly testing the efficacy of web-based interventions as ways to reduce alcohol misuse, binge eating, and gambling. However, many web-based interventions have poorly defined mechanisms of action; therefore, it is often uncertain how they propose to bring about behavior change.
OBJECTIVE: This systematic review aims to identify effective behavior change techniques (BCTs) present in web-based interventions aimed at reducing alcohol consumption, binge eating, or gambling.
METHODS: This systematic review covered research conducted in the last 20 years. Inclusion criteria for interventions were web-based administration; targeting alcohol use, binge eating, and/or gambling; and reporting on baseline and postintervention measures of behavior. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines were followed. We coded intervention effectiveness, study quality, and BCTs present in the interventions.
RESULTS: Following removal of 4152 ineligible articles, 45 were included in the review: 32 (71%) targeted alcohol misuse, 6 (13%) targeted binge eating, and 7 (16%) targeted gambling. In total, 5 frequency counts were performed to identify the most commonly used BCTs: all studies, effective interventions, high-quality studies at 2 thresholds, and both high quality and effective studies. The results obtained from this were integrated to identify 7 BCTs. These 7 BCTs were problem solving, feedback on behavior, self-monitoring of behavior, self-monitoring of outcomes, instruction on how to perform a behavior, information about social and health consequences, and social comparison. A total of 4 BCTs were found in all frequency counts: feedback on behavior, self-monitoring of behavior, instruction on how to perform a behavior, and social comparison. Self-monitoring of outcomes of behavior was found in 3 of the 5 frequency counts, problem solving was found in 2 frequency counts, and information about social and health consequences was found in 1 frequency count.
CONCLUSIONS: This systematic review identified 7 of the most frequently used BCTs used in web-based interventions focused on alcohol misuse, binge eating, and gambling. These results can inform the development of evidence-based eHealth interventions that have the potential to lead to effective, positive behavior changes in all 3 areas.
BACKGROUND: Young adulthood has become synonymous with the development of poor lifestyle behaviours associated with an increased risk of preventable chronic disease in later years. Interventions aiming to improve health behaviours may be more engaging and effective if they are targeted to males or females than interventions with a gender-neutral approach. This review will examine the outcome effectiveness of gender-targeted and gender-neutral interventions targeting nutrition, physical activity or overweight/obesity in young adults (17-35 years).
METHODS: Six electronic databases were searched for randomised controlled trials (RCTs) published up to December 2019 that evaluated nutrition, physical activity and/or overweight/obesity interventions in young adults (17-35 years). An effective intervention was one where the change in one or more primary outcome was positive and statistically significantly different from baseline, compared with control, or if no control comparator, compared with another active intervention. Effectiveness of outcomes was compared between gender-targeted and gender-neutral studies.
RESULTS: In total 21,582 manuscripts were identified and 107 RCTs were included; 30 gender-targeted studies (28%) and 77 gender-neutral (72%). Most gender-targeted studies were female targeted (n = 22, 73%). Primary outcome/s were adiposity (n = 36, 34%), nutrition (n = 29, 27%), physical activity (n = 28, 26%), or a combination of (n = 14, 14%). A greater proportion of gender-targeted than gender-neutral studies were effective in improving nutrition (n = 6, 100% and n = 17, 74% of studies respectively) and physical activity outcomes (n = 6, 86% and n = 14, 67% respectively), where as a greater proportion of gender-neutral studies were effective in improving adiposity outcomes (n = 13, 59% and n = 5, 36% respectively). None of these differences were statistically significant. Meta-analyses for weight found no significant differences between gender-targeted and gender-neutral studies for weight loss or weight gain prevention studies. Meta-analysis for fruit and vegetable intake demonstrated a significantly greater increase in intervention participants in gender-targeted studies of +158 g/day for > 3 months.
CONCLUSIONS: Although differences in outcome effectiveness were identified between gender-targeted and gender-neutral studies, these were not significantly different. This is likely due to an insufficient number of studies to detect a difference. The meta-analysis for fruit and vegetable intake findings should be interpreted with caution due to including only two gender-targeted studies. The findings collectively are suggestive of a potential difference requiring further investigation. To truly determine the effectiveness of gender-targeted interventions, well-designed RCTs comparing gender-targeted interventions with gender-neutral and control are needed.
REGISTRATION: This systematic review is a secondary analysis of studies included in a systematic review examining the effectiveness of interventions targeting nutrition, physical activity, or overweight/obesity in young adults, for which a predefined protocol was registered with PROSPERO (CRD42017075795).
Although the role of shoe constructions on running injury and performance has been widely investigated, systematic reviews on the shoe construction effects on running biomechanics were rarely reported. Therefore, this review focuses on the relevant research studies examining the biomechanical effect of running shoe constructions on reducing running-related injury and optimising performance. Searches of five databases and Footwear Science from January 1994 to September 2018 for related biomechanical studies which investigated running footwear constructions yielded a total of 1260 articles. After duplications were removed and exclusion criteria applied to the titles, abstracts and full text, 63 studies remained and categorised into following constructions: (a) shoe lace, (b) midsole, (c) heel flare, (d) heel-toe drop, (e) minimalist shoes, (f) Masai Barefoot Technologies, (g) heel cup, (h) upper, and (i) bending stiffness. Some running shoe constructions positively affect athletic performance-related and injury-related variables: 1) increasing the stiffness of running shoes at the optimal range can benefit performance-related variables; 2) softer midsoles can reduce impact forces and loading rates; 3) thicker midsoles can provide better cushioning effects and attenuate shock during impacts but may also decrease plantar sensations of a foot; 4) minimalist shoes can improve running economy and increase the cross-sectional area and stiffness of Achilles tendon but it would increase the metatarsophalangeal and ankle joint loading compared to the conventional shoes. While shoe constructions can effectively influence running biomechanics, research on some constructions including shoe lace, heel flare, heel-toe drop, Masai Barefoot Technologies, heel cup, and upper requires further investigation before a viable scientific guideline can be made. Future research is also needed to develop standard testing protocols to determine the optimal stiffness, thickness, and heel-toe drop of running shoes to optimise performance-related variables and prevent running-related injuries.
Self-efficacy is an important determinant of health behaviour. Digital interventions are a potentially acceptable and cost-effective way of delivering programmes of health behaviour change at scale. Whether behaviour change interventions work to increase self-efficacy in this context is unknown. This systematic review and meta-analysis sought to identify whether automated digital interventions are associated with positive changes in self-efficacy amongst non-clinical populations for five major health behaviours, and which BCTs are associated with that change. A systematic literature search identified 20 studies (n = 5624) that assessed changes in self-efficacy and were included in a random effects meta-analysis. Interventions targeted: healthy eating (k = 4), physical activity (k = 9), sexual behaviour (k = 3), and smoking (k = 4). No interventions targeting alcohol use were identified. Overall, interventions had a small, positive effect on self-efficacy ([Formula: see text] 0.190, CI [0.078; 0.303]). The effect of interventions on self-efficacy did not differ as a function of health behaviour type (Q-between = 7.3704 p = 0.061, df = 3). Inclusion of the BCT 'information about social and environmental consequences' had a small, negative effect on self-efficacy ([Formula: see text]= -0.297, Q = 7.072, p = 0.008). Whilst this review indicates that digital interventions can be used to change self-efficacy, which techniques work best in this context is not clear.
Alcohol misuse is a common, disabling and costly issue worldwide. Internet-delivered cognitive behavior therapy (ICBT) has the potential to reduce the harms of alcohol misuse, particularly for individuals who are unable or unwilling to access face-to-face therapy. A systematic review was conducted using Medline, CINAHL, EMBASE and PsycINFO databases for all relevant articles published from 1980 to January 2019. Randomized controlled trials (RCTs) were included if (i) an ICBT intervention targeting alcohol misuse was delivered; (ii) participants were aged 18 years or older; and (iii) primary outcomes were quantity of drinking. A qualitative analysis was conducted on the content of the ICBT programs. Fourteen studies met inclusion criteria. Most studies included participants from the general population, while studies conducted within clinic settings with diagnosed individuals were rare. The programs were similar in terms of included modules. Small effects were seen in studies on self-guided ICBT, while therapist-guided ICBT rendered small to large effects. The current review indicates that ICBT has a significant effect in reducing alcohol consumption. Larger studies evaluating ICBT compared to active control groups especially within clinic settings are warranted. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
BACKGROUND: A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.
OBJECTIVES: To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.
SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in May 2019 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords.
SELECTION CRITERIA: Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.
DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane.
MAIN RESULTS: We included 81 studies (69,094 participants), five of which are new to this update. We judged 22 studies to be at high risk of bias, 53 to be at unclear risk of bias, and six studies to be at low risk of bias. Fifty studies included abstainers, and 30 studies helped people to quit and then tested treatments to prevent relapse. Twenty-eight studies focused on special populations who were abstinent because of pregnancy (19 studies), hospital admission (six studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy. We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I2 = 82%; moderate-certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I2 = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I2 = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I2 = 0%; low-certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I2 = 0%; moderate-certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I2 = 66%; low-certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at the end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I2 = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I2 = 3%), studies in hospital inpatients (5 studies, n = 1385, RR 1.10, 95% CI 0.82 to 1.47, I2 = 58%), and studies in assisted abstainers (11 studies, n = 5523, RR 0.98, 95% CI 0.87 to 1.11, I2 = 52%; moderate-certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I2 = 1%) from the general population.
AUTHORS' CONCLUSIONS: Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.
Background and aims There has been no comprehensive evaluation of the efficacy of transcutaneous electric nerve stimulation (TENS) for acute low back pain (LBP). The aim of this systematic review was to investigate the efficacy and safety of TENS for acute LBP. Methods We searched MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, CINAHL and PsycINFO (inception to May 2018) for randomised placebo controlled trials. The primary outcome measure was pain relief in the immediate term (within 2-weeks of administration) assessed using the 100 mm visual analogue scale. A mean difference of at least 10 points on the 100-point pain scale was considered clinically significant. Methodological quality of the eligible studies was assessed using the PEDro scale and overall quality assessment rating was assessed using GRADE. Results Three placebo controlled studies (n = 192) were included. One low quality trial (n = 63) provides low quality evidence that ~30 min treatment with TENS in an emergency-care setting provides clinically worthwhile pain relief for moderate to severe acute LBP in the immediate term compared with sham TENS [Mean Difference (MD) - 28.0 (95% CI - 32.7, -23.3)]. Two other studies which administered a course of TENS over 4-5 weeks, in more usual settings provide inconclusive evidence; MD -2.75 (95% CI -11.63, 6.13). There was limited data on adverse events or long term follow-up. Conclusions The current evidence is insufficient to support or dismiss the use of TENS for acute LBP. Implications There is insufficient evidence to guide the use of TENS for acute LBP. There is low quality evidence of moderate improvements in pain with a short course of TENS (~30 min) during emergency transport of patients to the hospital. Future research should evaluate whether TENS has an opioid sparing role in the management of acute LBP.
BACKGROUND: Taking regular exercise, whether cardiovascular-type exercise or resistance exercise, may help people to give up smoking, particularly by reducing cigarette withdrawal symptoms and cravings, and by helping to manage weight gain.
OBJECTIVES: To determine the effectiveness of exercise-based interventions alone, or combined with a smoking cessation programme, for achieving long-term smoking cessation, compared with a smoking cessation intervention alone or other non-exercise intervention.
SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialised Register for studies, using the term 'exercise' or 'physical activity' in the title, abstract or keywords. The date of the most recent search was May 2019.
SELECTION CRITERIA: We included randomised controlled trials that compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme alone or another non-exercise control group. Trials were required to recruit smokers wishing to quit or recent quitters, to assess abstinence as an outcome and have follow-up of at least six months.
DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods. Smoking cessation was measured after at least six months, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of comparison, as either smoking cessation or relapse prevention. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models.
MAIN RESULTS: We identified 24 eligible trials with a total of 7279 adult participants randomised. Two studies focused on relapse prevention among smokers who had recently stopped smoking, and the remaining 22 studies were concerned with smoking cessation for smokers who wished to quit. Eleven studies were with women only and one with men only. Most studies recruited fairly inactive people. Most of the trials employed supervised, group-based cardiovascular-type exercise supplemented by a home-based exercise programme and combined with a multi-session cognitive behavioural smoking cessation programme. The comparator in most cases was a multi-session cognitive behavioural smoking cessation programme alone. Overall, we judged two studies to be at low risk of bias, 11 at high risk of bias, and 11 at unclear risk of bias. Among the 21 studies analysed, we found low-certainty evidence, limited by potential publication bias and by imprecision, comparing the effect of exercise plus smoking cessation support with smoking cessation support alone on smoking cessation outcomes (RR 1.08, 95% CI 0.96 to 1.22; I2 = 0%; 6607 participants). We excluded one study from this analysis as smoking abstinence rates for the study groups were not reported. There was no evidence of subgroup differences according to the type of exercise promoted; the subgroups considered were: cardiovascular-type exercise alone (17 studies), resistance training alone (one study), combined cardiovascular-type and resistance exercise (one study) and type of exercise not specified (two studies). The results were not significantly altered when we excluded trials with high risk of bias, or those with special populations, or those where smoking cessation intervention support was not matched between the intervention and control arms. Among the two relapse prevention studies, we found very low-certainty evidence, limited by risk of bias and imprecision, that adding exercise to relapse prevention did not improve long-term abstinence compared with relapse prevention alone (RR 0.98, 95% CI 0.65 to 1.47; I2 = 0%; 453 participants).
AUTHORS' CONCLUSIONS: There is no evidence that adding exercise to smoking cessation support improves abstinence compared with support alone, but the evidence is insufficient to assess whether there is a modest benefit. Estimates of treatment effect were of low or very low certainty, because of concerns about bias in the trials, imprecision and publication bias. Consequently, future trials may change these conclusions.
BACKGROUND: Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.
OBJECTIVES: To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.
SEARCH METHODS: For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.
SELECTION CRITERIA: Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.
DATA COLLECTION AND ANALYSIS: We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.
MAIN RESULTS: This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I2 = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.
AUTHORS' CONCLUSIONS: There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.
Background and aims Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta‐analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions. Methods A systematic review and meta‐regression was conducted including 172 randomised controlled trials with at least 6 months follow‐up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta‐regression was used to create a model predicting smoking cessation outcomes. This model was used to re‐estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta‐regression models and smoking cessation differences and ratios to compare relative effectiveness. Results The meta‐regression model predicted smoking cessation rates well (pseudo R2 = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a ‘no support comparator’, self‐help was 1.33 times (95% CI = 1.16–1.49), brief physician advice 1.61 times (95% CI = 1.31–1.90), nurse individual counselling 1.76 times (95% CI = 1.62–1.90), psychologist individual counselling 2.04 times (95% CI = 1.95–2.15) and group psychologist interventions 2.06 times (95% CI = 1.92–2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness. Conclusions Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
