A Test of Feasibility and Acceptability of Online Mindfulness-Based Stress Reduction for Lesbian, Gay, and Bisexual Women and Men at Risk for High Stress: Pilot Study
Bibliographic record
Abstract
BACKGROUND: In conservative and rural areas, where antidiscrimination laws do not exist, lesbian, gay, and bisexual (LGB) people are at risk for excess stress arising from discrimination. Stress-reducing interventions delivered via innovative channels to overcome access barriers are needed. OBJECTIVE: This study aimed to investigate the feasibility and acceptability of online mindfulness-based stress reduction (OMBSR) with LGB people in Appalachian Tennessee at high risk for stress. METHODS: In 2 pilot studies involving pre-post test designs, participants completed 8 weeks of OMBSR, weekly activity logs, semistructured interviews, and surveys of perceived and minority stress. RESULTS: Overall, 24 LGB people enrolled in the study and 17 completed OMBSR. In addition, 94% completed some form of mindfulness activities daily, including meditation. Participants enjoyed the program and found it easy to use. Perceived stress (Cohen, perceived stress scale-10) decreased by 23% in women (mean 22.73 vs mean 17.45; t10=3.12; P=.01) and by 40% in men (mean 19.83 vs mean 12.00; t5=3.90; P=.01) between baseline and postprogram. Women demonstrated a 12% reduction in overall minority stress (Balsam, Daily Experiences with Heterosexism Questionnaire) from baseline to 12-week follow-up (mean 1.87 vs mean 1.57; t10=4.12; P=.002). Subscale analyses indicated that women's stress due to vigilance and vicarious trauma decreased by 21% and 20%, respectively. CONCLUSIONS: OMBSR may be a useful tool to help LGB people reduce general and minority-specific stress in socially conservative regions lacking antidiscrimination policies.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".