The Effect of a Brief Video-Based Intervention to Improve AIDS Prevention in Older Men: Randomized Controlled Trial
Bibliographic record
Abstract
Background: The AIDS epidemic among older people is becoming more serious. Evidence-based, acceptable, and effective preventive interventions are urgently needed. Video-based interventions have become an innovative way to change behaviors, and we have developed a brief video-based intervention named Sunset Without AIDS. Objective: In this study, we tested the effectiveness of a brief video-based intervention targeting older men's understanding of AIDS prevention. Methods: A randomized controlled trial was conducted from June 20 to July 3, 2023. In total, 100 older men were randomly divided into the intervention group (n=50) and the control group (n=50) using the envelope extraction method. The intervention group was shown the Sunset Without AIDS video; the control group viewed a standard AIDS education video. A questionnaire was used to measure the effect of Sunset Without AIDS after 2 interventions. AIDS-related high-risk behaviors were followed up 1 and 3 months after the intervention. The difference was statistically significant at P≤.05. Results: After 2 interventions, the total awareness rates (%) of AIDS-related knowledge in the intervention and control groups were 84% (42/50) and 66% (33/50), respectively (P=.04). The mean stigma attitude scores of the 2 groups were 2.53 (SD 0.45) and 2.58 (SD 0.49), respectively (P=.55), but there was a statistically significant difference in the first dimension (fear of infection) between the 2 groups (P<.001). The mean positive scores of attitudes of AIDS-related high-risk behaviors of the 2 groups were 83.33 (SD 21.56) and 75.67 (SD 26.77), respectively (P=.58). In addition, 82% reported that they were satisfied with the educational content within the Sunset Without AIDS video. At 1- and 3-month follow-ups conducted after the intervention, participants in the 2 groups did not report AIDS-related high-risk behaviors. After watching the 2 videos, more people accepted and were satisfied with Sunset Without AIDS. Conclusions: Sunset Without AIDS could improve the ability of older men in China to follow best practices for AIDS prevention and provide a certain basis for the innovation of AIDS education in the older adult population.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| 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 | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".