Lifetime and Daily Discrimination and Mental Health in Sexual and Gender Diverse Individuals: Examining Risk and Protective Factors
Bibliographic record
Abstract
Lesbian, gay, bisexual, transgender, non-binary, queer, two-spirit, intersex, asexual and other sexual and gender diverse (LGBTQ+) individuals are at increased vulnerability to experience negative mental health outcomes compared to their heterosexual and cisgender counterparts. A large body of scholarly literature suggest that stigma (often in the form of discrimination) contributes to stressors that may account for the increased mental health burden in this population. The Psychological mediation framework (PMF) indicates that emotion regulation and social support may be important mechanisms leading from stigma to mental health outcomes. The objectives of the present studies were to evaluate and expand the PMF by testing the effects of stigma on mental health (i.e., affectivity and depression) through emotion regulation and social support, and to examine the moderating effects of several risk factors (i.e., childhood abuse history, attachment insecurity) and protective factors (i.e., self-compassion). Daily diary data was used in Study 1 while Study 2 used cross-sectional baseline data to carry out objectives. In Study 1, participants (n = 84) submitted 592 daily surveys for an average of 7 days, reporting on their discrimination experiences, social support, emotion regulation, daily affect, and several risk and protective factors. Moderated mediation models were examined using multilevel, conditional process modelling. It was found that both within-person and across-persons, daily discrimination was indirectly related to daily negative affectivity, via emotion dysregulation, but not social support. Childhood abuse history and self-compassion moderated the daily discrimination- emotion dysregulation relationship. In Study 2, conditional process modeling was used to test pathways from lifetime LGBTQ+ discrimination to depression via social support and emotion dysregulation, with attachment insecurity as a moderator using cross-sectional data from 117 LGBTQ+ individuals. As expected, lifetime LGBTQ+ discrimination had an indirect effect on depression, via social support, and this effect was moderated by attachment insecurity. Social support had a direct and indirect effect on depression, via emotion dysregulation. Emotion dysregulation and social support are important mechanisms leading from discrimination to mental health in LGBTQ+ individuals, and understanding specific risk and protective factors can help to inform case conceptualization and treatment planning for LGBTQ+ affirmative interventions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".