Why was this study done?

The Chicagoland CEAL program is made up of academic researchers and community organizations collaborating to improve equity in health outcomes and engagement in research for historically marginalized communities in the Chicago metro area. We set out to explore capacity-building initiatives launched by six community–academic partnerships of the Chicagoland CEAL program to understand their core components and barriers and facilitators faced during implementation.

What did we do?

We conducted seven virtual focus group discussions with 26 community organization representatives and researchers representing six capacity-building initiatives. We used a rapid qualitative analysis approach, summarizing the initiatives according to Juckett et al.’s typology and grouping the barriers and facilitators according to the Exploration, Preparation, Implementation, Sustainment (EPIS) implementation science framework.

What does this paper add?

Our findings echo the literature on the importance of mutually beneficial relationships, clear goals, trust, initiative tailoring, and adaptability for achieving equitable implementation of capacity-building initiatives delivered through community–academic partnerships. Our study’s emphasis on health equity and focus on context answers recent calls in the implementation science literature. We also add to the evidence base on the increasingly popular EPIS framework.

Successful implementation of evidence-based interventions—Factors to be considered

David Victor Fiedler, David H Peters, Laurence Moore, Paul Estabrooks, Claudio R Nigg

Lay Summary

Many programs designed to encourage healthy habits, like better eating or regular exercise, work well in controlled settings like research studies. However, they often struggle to succeed when introduced into the real world. This is because people’s needs and circumstances vary widely, and different environments can lead to unexpected outcomes. To overcome these challenges, it’s important to carefully plan and test these programs from the start. This involves using clear strategies, considering cultural differences, and actively involving the people who will use them. By understanding how the program’s methods lead to its results, researchers can avoid common mistakes and improve its chances of success. Ultimately, this approach can help experts in health and behavior to achieve a big goal: making these programs a lasting part of systems, policies, and communities. This would create long-term changes that help people live healthier lives.

Annals of Behavioral Medicine

Daily, prospective associations between sleep architecture and affect: insights from Bayesian multilevel compositional data analysis

Flora Le, PhD; Yang Yap, PhD; Dorothea Dumuid, PhD; Joshua F Wiley, PhD

Lay Summary

Most people have limited sleep opportunities each night. Thus, time spent in different sleep stages (total wake time in bed, light sleep [non-rapid eye movement stages 1 and 2], slow wave sleep, and rapid eye movement sleep) are often constrained within time in bed. When time in bed is fixed, time spent in one sleep stage can only be increased by reducing time spent in one or more of the other stages. We applied a novel statistical method addressing the multilevel compositional nature of sleep architecture to examine the daily, prospective association between sleep architecture and post-sleep affect. In 96 healthy, young adults across 15 consecutive days, sleep architecture was measured at night using an electroencephalography device (Z-Machine Insight+) and affect was self-reported at awakening. Our Bayesian multilevel compositional data analysis revealed various reallocations of sleep stages, particularly longer slow wave sleep and rapid eye movement sleep, at the expense of either light sleep or total wake time, predicted better affect. These findings highlight the importance of considering sleep architecture as an integrated composition to offer new insights into distinct constellations of sleep architecture associated with affect in everyday life.

Cannabinoid content on product labels influences cannabis health perceptions

Joshua L Stanz, MA, MS; Benjamin O Ladd, PhD; Renee E Magnan, PhD

Lay Summary

Features of cannabis product labels communicate product content and may influence health perceptions and decisions to use cannabis. Cannabis product labels typically feature cannabinoid potency including tetrahydrocannabinol (THC) and cannabidiol (CBD). We tested different THC and CBD content and inclusion of a visual aid to communicate their potency. The visual aid was a traffic light showing high, medium, and low potencies of both THC and CBD. People who use cannabis were randomly assigned to evaluate three cannabis products (THC-dominant, equal THC:CBD, and CBD-dominant) that included THC/CBD content with or without the traffic light visual. The THC-dominant product was evaluated as most harmful and least beneficial to health but also most likely to be purchased and used. The opposite pattern occurred for the CBD-dominant product. THC-dominant content was associated with less perceived benefit, which in turn, was associated with less likelihood of use. The inclusion of a cannabinoid potency visual did not influence perceptions of cannabis. THC and CBD potency on product labels likely contribute to health perceptions of the product and more research is needed to determine the extent to which such perceptions drive decisions to use.