Exploring Proximal LGBTQ+ Minority Stressors Within Physical Activity Contexts from a Self-determination Theory Perspective
Bibliographic record
Abstract
BACKGROUND: LGBTQ+ (lesbian, gay, bisexual, transgender, queer, etc.) individuals experience challenges such as discrimination and marginalization (referred to as minority stressors) that are detrimental to their mental and physical health. Specifically, proximal or internalized LGBTQ+ minority stressors may influence motivation for and willingness to participate in physical activity. PURPOSE: To explore whether proximal LGBTQ+ minority stressors relate to the basic psychological needs-motivation-physical activity pathway, as per self-determination theory. METHODS: An online cross-sectional survey was completed by 778 self-identified LGBTQ+ adults. Structural equation modelling analyses were used to examine how proximal LGBTQ+ minority stressors relate to the motivational sequence. RESULTS: Findings support that proximal LGBTQ+ minority stressors are negatively associated with psychological need satisfaction within physical activity (β = -.36), which in turn is positively associated with autonomous motivation (β = .53) and reported physical activity participation (β = .32). Overall, the final model accounted for 13% of variance in need satisfaction (small effect size), 53% of variance in autonomous motivation (moderate-large effect size), and 10% of variance in moderate-to-vigorous physical activity levels (small effect size). CONCLUSIONS: Future research focused on increasing LGBTQ+ participation in physical activity should investigate the effects of (a) reducing proximal LGBTQ+ minority stressors and (b) better supporting LGBTQ+ adults' autonomy, competence, and relatedness within physical activity contexts.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".