Using Intervention Mapping to Develop an mHealth Intervention to Support Men Who Have Sex With Men Engaging in Chemsex (Budd): Development and Usability Study
Bibliographic record
Abstract
BACKGROUND: Chemsex refers to the intentional use of drugs before or during sex among men who have sex with men (MSM). Engaging in chemsex has been linked to significant negative impacts on physical, psychological, and social well-being. However, no evidence-based support tools have addressed either these harms or the care needs of MSM who engage in chemsex. OBJECTIVE: The purpose of this paper was to describe the development of a mobile health intervention (named Budd) using the intervention mapping protocol (IMP). Budd aims to support and inform MSM who participate in chemsex, reduce the negative impacts associated with chemsex, and encourage more reasoned participation. METHODS: The IMP consists of 6 steps to develop, implement, and evaluate evidence-based health interventions. A needs assessment was carried out between September 2, 2019, and March 31, 2020, by conducting a literature study and in-depth interviews. Change objectives were selected based on these findings, after which theory-based intervention methods were selected. The first version of the intervention was developed in December 2020 and pilot-tested between February 1, 2021, and April 30, 2021. Adjustments were made based on the findings from this study. A separate article will be dedicated to the effectiveness study, conducted between October 15, 2021, and February 24, 2022, and implementation of the intervention. The Budd app went live in April 2022. RESULTS: Budd aims to address individual factors and support chemsex participants in applying harm reduction measures when taking drugs (drug information, drug combination tool, and notebook), preparing for participation in a chemsex session (articles on chemsex, preparation tool, and event-specific checklist), planning sufficient time after a chemsex session to recover (planning tool), seeking support for their chemsex participation (overview of existing local health care and peer support services, reflection, personal statistics, and user testimonials), taking HIV medication or pre-exposure prophylaxis in a timely manner during a chemsex session (preparation tool), and contacting emergency services in case of an emergency and giving first aid to others (emergency information and personal buddy). CONCLUSIONS: The IMP proved to be a valuable tool in the planning and development of the Budd app. This study provides researchers and practitioners with valuable information that may help them to set up their own health interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/39678.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".