Developing HIV Prevention Interventions for Emerging Adult MSM With a History of Being Bullied: A Qualitative Study
Bibliographic record
Abstract
The experience of being bullied in childhood or adolescence affects health into adulthood and is a public health crisis. Particularly affected are sexual minority young adults who are at the greatest risk for severe and violent bullying, HIV seroconversion, and onset of a substance use disorder. Although the scholarly work in the area of bullying victimization has made great gains over the past few years via improved sampling and methodological rigor, most of the focus of health research in this area has been on prevention efforts. The purpose of the current study was to inform the development of a transdiagnostic integrated treatment platform that will focus on mental and physical health outcomes that include sexual risk taking and substance abuse. This study involved conducting four focus groups with HIV-uninfected gay and bisexual men, aged 18 to 26 years, in order to examine treatment needs and preferences and further develop an evidence-based intervention. Four themes emerged from the analysis of transcripts: (a) learning about bullying and psychopathology, (b) coping with bullying, (c) experiencing psychopathology as a consequence of bullying, and (d) tailoring psychosocial interventions to address health sequelae linked with bullying. These themes provided a solid foundation to develop and test an intervention to address key health risks among men who have sex with men (MSM) with a history of being bullied and recent sexual risk taking and substance abuse.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".