Acceptability of a Self-Guided Lifestyle Intervention Among Young Men: Mixed Methods Analysis of Pilot Findings
Bibliographic record
Abstract
BACKGROUND: Young men are vastly underrepresented in lifestyle interventions, suggesting a need to develop appealing yet effective interventions for this population. OBJECTIVE: This study aimed to determine the acceptability of a self-guided lifestyle intervention designed specifically for young men (age: 18-35 years old). METHODS: Semistructured interviews and surveys were completed by 14 men following completion of a remotely delivered, 12-week lifestyle intervention. The intervention included 1 virtual group session, digital tools, access to self-paced web- and mobile-based content, and 12 weekly health risk text messages. We quantitatively and qualitatively examined young men's experiences with the intervention components of a remotely delivered, self-guided lifestyle intervention targeting weight loss. Data were integrated using convergent mixed methods analysis. RESULTS: . The self-guided aspect was not acceptable, and a majority preferred more check-ins. Participants expressed a desire for a social aspect in future lifestyle interventions. All men found the focus on health risks appealing. A majority of men found the study-issued, Bluetooth-enabled scale acceptable. CONCLUSIONS: Acceptability of the self-guided lifestyle intervention was perceived as suboptimal by young men. The findings highlight the need to add intervention components that sustain motivation and provide additional social support for young men. TRIAL REGISTRATION: ClinicalTrials.gov NCT04267263; https://www.clinicaltrials.gov/study/NCT04267263.
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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 | 0.044 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".