A Pilot and Feasibility Study on a Mindfulness-Based Intervention Adapted for LGBTQ+ Adolescents
Bibliographic record
Abstract
(1) Background: Lesbian, gay, bisexual, transgender, queer and other gender and sexual minority-identified (LGBTQ+) adolescents face mental and physical health disparities compared to their heterosexual and cisgender counterparts. Mindfulness-based interventions (MBIs) may be a potential method to intervene upon health disparities in this population. This pilot study explores the initial acceptability and feasibility, along with the descriptive health changes of an online MBI, Learning to Breathe-Queer (L2B-Q), which was adapted to meet the needs of LGBTQ+ adolescents. (2) Methods: Twenty adolescents completed baseline and post-intervention assessments of mental health, stress-related health behaviors, physical stress, and LGBTQ+ identity indicators. In addition, the adolescents participated in a post-intervention focus group providing qualitative feedback regarding the acceptability of L2B-Q. (3) Results: L2B-Q demonstrated feasible recruitment and assessment retention, acceptability of content with areas for improvement in delivery processes, and safety/tolerability. From baseline to post-intervention, adolescents reported decreased depression and anxiety and improved intuitive eating, physical activity, and LGBTQ+ identity self-awareness with moderate-to-large effects. (4) Conclusions: These findings underscore the need and the benefits of adapted interventions among LGBTQ+ youth. L2B-Q warrants continued optimization and testing within the LGBTQ+ adolescent community.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".