BackgroundAnxiety disorders are among the most prevalent mental health problems worldwide, and access to effective treatment is not always available. Preventive interventions need to be scalable and cost-effective, which can be achieved through communication and information technologies. However, recruiting participants for digital prevention trials remains a major methodological challenge.AimTo evaluate the performance of different approaches to recruiting participants for a digital preventive intervention for anxiety (the prevANS trial), and to assess participants’ motivations for enrolling in the trial.MethodsDescriptive analyses were conducted to evaluate the performance of each recruitment strategy (number of potential participants attracted per week). Quantitative data were obtained from website records of individuals initiating the online screening process while each strategy was active, and self-reported information on how participants learned about the study. Baseline group differences between the intervention and control groups were examined using chi-square and Mann–Whitney U-tests. Reflexive inductive thematic analysis was used to analyze qualitative data on participants’ main motivations for enrolling, collected through an open-ended survey question.ResultsOver a 26-month recruitment period, 6,017 individuals initiated screening and 1,054 participants were enrolled (17.5% conversion rate). The most effective strategies for attracting potential participants were social media and university dissemination. Self-reported data also indicated that word of mouth had a notable impact on recruitment. The final sample was mainly composed of women and highly educated participants, and the intervention and control groups were balanced across all variables except for age. Thematic analysis revealed three main motivations for enrollment: helping others, health related issues, and own benefits.ConclusionRecruitment strategies should be tailored to the target population, as their performance may vary across groups. Involving users through co-design and co-creation can enhance both the intervention and the identification of effective recruitment channels in digital trials.
Adapting DeepLabV3+ for biopsy cervical cancer lesion segmentation
IntroductionCervical cancer remains a leading cause of cancer mortality in resource-constrained settings, where access to advanced digital pathology equipment is severely limited. Automated histopathological image



