Examining Longitudinal Risk and Strengths-Based Factors Associated with Depression Symptoms Among Sexual Minority Men in Canada
Bibliographic record
Abstract
Sexual minority men (SMM) experience anti-SMM stressors and have elevated rates of mental health issues compared to heterosexual men, such as depression. Importantly, strengths-based factors may directly increase wellbeing and provide a buffer against the detrimental effects of such stressors. In the present study, we integrated risk and strengths-based models to examine predictors of depression symptoms in a sample of 465 Canadian SMM across three time points using multilevel modeling. Higher scores on a measure of childhood physical abuse at baseline, and greater within-person (i.e., deviation from individual's average) and between-person (i.e., deviation from group average) internalized homonegativity and heterosexist discrimination were associated with higher depression scores. Higher within- and between-person scores on measures of self-esteem, social support, and hope were associated with lower depression scores. Social support buffered the effects of between-person heterosexist discrimination on depression symptoms: at mean and high levels of social support, heterosexist discrimination was not associated with depression symptoms. This is the first study to disaggregate between-person and within-person effects of both risk factors and strengths-based factors among SMM, which has critical importance for the development of tailored individual-level interventions that target internalized homonegativity, hope, social support, and self-esteem to alleviate symptoms of depression among SMM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".