News from the Society for Women's Health Research: Society Workshop Investigates Barriers to Recruitment and Retention of Women in Clinical Research

Greenberger, Phyllis; Knab, Sarah

doi:10.1089/152460900750020838

Cited by 8 publications

(6 citation statements)

References 1 publication

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“…Our findings suggest that there may be a need to support retention in trials for women in particular. This confirms previous evidence [37]. Female adult smokers may have competing family responsibilities—such as having a child mdash;that interfere with their ability to meet trial participation demands or commitment to smoking cessation interventions [37,38].…”

Section: Discussionsupporting

confidence: 87%

“…This confirms previous evidence [37]. Female adult smokers may have competing family responsibilities-such as having a child mdash;that interfere with their ability to meet trial participation demands or commitment to smoking cessation interventions [37,38]. A higher motivation to quit was associated with lower retention rates, contrary to findings in previous studies [39,40].…”

Section: Retention Ratessupporting

confidence: 79%

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

et al. 2021

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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.

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Section: Discussionsupporting

confidence: 87%

Section: Retention Ratessupporting

confidence: 79%

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

et al. 2021

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“…Having at least one child currently living at home was a particularly strong predictor of attrition, while Non-White race predicted early dropout and not having graduated from college predicted late dropout. That having at least one child living at home predicted attrition above and beyond educational attainment and race suggests that this may have been due to the added responsibilities faced by women with children [ 20 ]. The findings for Non-White race are in accordance with the observations of Nevid et al [ 16 ]and the added risk faced by those with lower educational attainment replicates findings reported by Borrelli et al [ 2 ] and Curtin et al [ 3 ].…”

Section: Discussionmentioning

confidence: 99%

“…Other demographic variables that may increase likelihood of attrition include lower education level [ 2 , 3 ], (although Nevid et al [ 16 ] found null results) and a lower Body Mass Index (BMI) [ 2 , 19 ]. Given that female smokers are likely to have competing family responsibilities that may interfere with their commitment to cessation treatment [ 20 ], having children currently living at home may increase likelihood of attrition. There are also findings that point to a relationship between age and attrition.…”

Section: Introductionmentioning

confidence: 99%

Attrition in a Multi-Component Smoking Cessation Study for Females

et al. 2006

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Limiting attrition (i.e., participant dropout before the conclusion of a study) is a major challenge faced by researchers when implementing clinical trials. Data from a smoking cessation trial for females (N = 246) were analyzed in order to identify baseline smoking-related, demographic and psychological characteristics affecting likelihood of early (i.e., before the quit attempt) and late (i.e., after the quit attempt) dropout. There were a number of significant demographic predictors of attrition. Participants with at least one child living at home were at increased risk of both early and late dropout. Non-Whites were at increased risk of early dropout, while not having a college degree put one at increased risk of late dropout. Age was found to be a protective factor in that the older a participant was, the less likely she was to drop out in the early stages of the trial. With respect to psychological variables, weight concerns increased risk of attrition, as did the experience of guilt. In terms of smoking-related variables, mean cigarettes per day was not a significant predictor of attrition, although length of longest prior quit attempt was a significant predictor of early dropout when age was removed from the regression.

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“…On the whole, the association between study retention and other sociodemographic characteristics (e.g. age, [25,29] , education level, [24,28] sex, [30] and number of dependent children) [25] , behavioural/ psychological factors (e.g. weight concerns [25] , feelings of guilt, IQ [31,32] ) and health-related factors (e.g.…”

Section: Introductionmentioning

confidence: 99%

Predictors of retention in a randomised trial of smoking cessation in low-socioeconomic status Australian smokers

Courtney

Clare

Boland

et al. 2017

Addictive Behaviors

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News from the Society for Women's Health Research: Society Workshop Investigates Barriers to Recruitment and Retention of Women in Clinical Research

Cited by 8 publications

References 1 publication

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

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

Attrition in a Multi-Component Smoking Cessation Study for Females

Predictors of retention in a randomised trial of smoking cessation in low-socioeconomic status Australian smokers

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