Predictors of recruitment and retention in randomized controlled trials of behavioural smoking cessation interventions: a systematic review and meta‐regression analysis

Abstract

Aim To investigate predictors of participant eligibility, recruitment and retention in behavioural randomized controlled trials (RCTs) for smoking cessation. Method Systematic review and pre‐specified meta‐regression analysis of behavioural RCTs for smoking cessation including adult (≥ 18‐year‐old) smokers. The pre‐specified predictors were identified through a literature review and experts’ consultation and included participant, trial and intervention characteristics and recruitment and retention strategies. Outcome measures included eligibility rates (proportion of people eligible for the trials), recruitment rates, retention rates and differential retention rates. Results A total of 172 RCTs with 89 639 participants. Eligibility [median 57.6%; interquartile range (IQR) = 34.7–83.7], recruitment (median 66.4%; IQR = 42.7–85.2) and retention rates (median 80.5%; IQR = 68.5–89.5) varied considerably across studies. For eligibility rates, the recruitment strategy appeared not to be associated with eligibility rates. For recruitment rates, use of indirect recruitment strategies (e.g. public announcements) [odds ratio (OR) = 0.30, 95% confidence interval (CI) = 0.11–0.82] and self‐help interventions (OR = 0.14, 95% CI = 0.03–0.67) were associated with lower recruitment rates. For retention rates, higher retention was seen if the sample had ongoing physical health condition/s (OR = 1.66, 95% CI = 1.04–2.63), whereas lower retention was seen amongst primarily female samples (OR = 0.83, 95% CI = 0.71–0.98) and those motivated to quit smoking (OR = 0.74, 95% CI = 0.55–0.99) when indirect recruitment methods were used (OR = 0.60, 95% CI = 0.38–0.97) and at longer follow‐up assessments (OR = 0.83, 95% CI = 0.79–0.87). For differential retention, higher retention in the intervention group occurred when the intervention but not comparator group received financial incentives for smoking cessation (OR = 1.35, 95% CI = 1.02–1.77). Conclusions In randomized controlled trials of behavioural smoking cessation interventions, recruitment and retention rates appear to be higher for smoking cessation interventions that include a person‐to‐person rather than at‐a‐distance contact; male participants, smokers with chronic conditions, smokers not initially motivated to quit and shorter follow‐up assessments seems to be associated with improved retention; financial incentive interventions improve retention in groups receiving them relative to comparison groups.

Low carbohydrate and psychoeducational programs show promise for the treatment of ultra-processed food addiction

“…Retention at the end of the group sessions (~3 months) was 82.5, 48, and 70% for UK, NA, and SE, respectively. This is similar to other addiction programs such as those for smoking cessation where a meta-analysis showed an interquartile range of 68.5–89.5% for retention ( 36 ). NA retention is somewhat lower at this point.…”

The Usability of an Online Tool to Promote the Use of Evidence-Based Smoking Cessation Interventions

“…Another advantage of the so-called blended care is that it allows the combination of personal attention and synchronous communication with the online advantages of high accessibility [80,81]. Given that the primary care setting prominently reaches smokers who are more motivated to quit [79,82], using a mass media approach might reach a greater absolute number of smokers, even those who are still in the (pre-)contemplating phase [79], as was also the case in this study.…”

Effects of an Explicit Value Clarification Method With Computer-Tailored Advice on the Effectiveness of a Web-Based Smoking Cessation Decision Aid: Findings From a Randomized Controlled Trial

“…A way of achieving this would be to embed DAs (such as VISOR ) in a counseling pathway as the involvement of a professional has been shown to positively influence time spent on websites aimed at improving healthy lifestyles [ 61 ]. Concurrently, this might also positively influence retention rates in studies (ie, people returning for follow-up measurements) in which digital DAs are evaluated [ 62 , 63 ]. There could be multiple ways of accomplishing this in the context of VISOR (or other digital DAs for that matter): (1) VISOR could be used together with a health care professional (eg, a practice nurse) or could be sent to participants before or after a health care consultation in which (the result of) VISOR is discussed, or (2) a digital form of counseling could be included in VISOR (eg, through the form of videocalls [ 64 ] or an automated chatbot [ 65 ]).…”