Effect of Community Support on the Implementation of Primary Health Care-Based Measurement of Alcohol Consumption

Alcohol measurement delivered by health care providers in primary health care settings is an efficacious and cost-effective intervention to reduce alcohol consumption among patients. However, this intervention is not yet routinely implemented in practice. Community support has been recommended as a strategy to stimulate the delivery of alcohol measurement by health care providers, yet evidence on the effectiveness of community support in this regard is scarce. The current study used a pre-post quasi-experimental design in order to investigate the effect of community support in three Latin American municipalities in Colombia, Mexico, and Peru on health care providers’ rates of measuring alcohol consumption in their patients. The analysis is based on the first 5 months of implementation. Moreover, the study explored possible mechanisms underlying the effects of community support, through health care providers’ awareness of support, as well as their attitudes, subjective norms, self-efficacy, and subsequent intention toward delivering the intervention. An ANOVA test indicated that community support had a significant effect on health care providers’ rates of measuring alcohol consumption in their patients (F (1, 259) = 4.56, p = 0.034, ηp2 = 0.018). Moreover, a path analysis showed that community support had a significant indirect positive effect on providers’ self-efficacy to deliver the intervention (b = 0.07, p = 0.008), which was mediated through awareness of support. Specifically, provision of community support resulted in a higher awareness of support among health care providers (b = 0.31, p < 0.001), which then led to higher self-efficacy to deliver brief alcohol advice (b = 0.23, p = 0.010). Results indicate that adoption of an alcohol measurement intervention by health care providers may be aided by community support, by directly impacting the rates of alcohol measurement sessions, and by increasing providers’ self-efficacy to deliver this intervention, through increased awareness of support. Trial Registration ID: NCT03524599; Registered 15 May 2018; https://clinicaltrials.gov/ct2/show/NCT03524599

Motivational Factors and Barriers Towards Initiating and Maintaining Strength Training in Women: a Systematic Review and Meta-synthesis

Strength training (ST) or resistance training is important in the development and maintenance of musculoskeletal and cardiovascular health in women of all ages; however, uptake of ST amongst women is low. To improve female musculoskeletal health, it is vital that more women are encouraged to participate in ST to maintain musculoskeletal integrity. This systematic review aimed to identify motivators and barriers to women initiating and maintaining ST. Following protocol registration and systematic search, studies were included if they were primary qualitative or mixed-method studies reporting participant verbatim quotes, included adult women, and focused on motivators and barriers for ST. Searches generated 2534 articles from 3 databases, with 20 studies (N = 402 participants) meeting eligibility criteria. Participant quotes and authors’ interpretations were analysed using thematic synthesis. The most frequently observed barriers were gender-based stigmas, discouragement, and negative comments, particularly in women currently engaging in ST. Other factors associated with poor adherence included boredom, poor knowledge of ST, poor gym accessibility, lack of supervision or routine, and difficulty in balancing work and family life. Social support from friends and family, words of affirmation, and accompaniment facilitated ST, particularly in older women. Women who saw expected results such as weight loss were motivated to continue ST. Interventions aimed at increasing participation in ST amongst women should focus on the specific benefits valued by women and the dissemination of accurate information to counter misconceptions and increase knowledge. The adaptation of gym environments to make them more welcoming to women, and reduce gender-focused criticism, is especially important.

Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis

Mediation analysis is an important statistical method in prevention research, as it can be used to determine effective intervention components. Traditional mediation analysis defines direct and indirect effects in terms of linear regression coefficients. It is unclear how these traditional effects are estimated in settings with binary variables. An important recent methodological advancement in the mediation analysis literature is the development of the causal mediation analysis framework. Causal mediation analysis defines causal effects as the difference between two potential outcomes. These definitions can be applied to any mediation model to estimate natural direct and indirect effects, including models with binary variables and an exposure–mediator interaction. This paper aims to clarify the similarities and differences between the causal and traditional effect estimates for mediation models with a binary mediator and a binary outcome. Causal and traditional mediation analyses were applied to an empirical example to demonstrate these similarities and differences. Causal and traditional mediation analysis provided similar controlled direct effect estimates, but different estimates of the natural direct effects, natural indirect effects, and total effect. Traditional mediation analysis methods do not generalize well to mediation models with binary variables, while the natural effect definitions can be applied to any mediation model. Causal mediation analysis is therefore the preferred method for the analysis of mediation models with binary variables.