SOCIAL SUPPORT, MENTAL HEALTH, AND SEXUAL ORIENTATION: A STUDY OF THREE TIME POINTS IN THE CLSA
Bibliographic record
Abstract
Abstract Lesbian, gay, and bisexual (LGB) older adults exhibit mental health disparities stemming from a lifetime accumulation of minority stress experiences. Psychological resources like social support may buffer against these poor mental health outcomes. The purpose of this study was to examine indicators of depression and social support by sexual orientation over time in a sample of Canadian adults ages 45-85. We used data collected at three time points in the Canadian Longitudinal Study on Aging (CLSA; baseline, 2011-2015; follow-up 1, 2015-2018; and follow-up 2, 2018-2021). Depression was measured using the Center for Epidemiologic Studies Depression scale (CESD-10) and social support was measured using the Medical Outcomes Study Social Support Survey (MOS-SSS). For depression symptoms (n=38,244; 830 LGB), results indicated a significant effect of sexual orientation (F(2, 38242)=35.93, p<.001) such that LGB participants had more depression symptoms than heterosexual participants. There was also a significant effect of time on depression symptoms (F(2, 38242)=26.07, p<.001); mean depression scores decreased over time. For social support (n=35,795; 770 LGB), results indicated a significant effect of sexual orientation (F(2, 35794)=45.31, p<.001) such that LGB participants reported lower levels of social support than heterosexual participants. There was also a significant effect of time (F(2, 35794)=5.98, p=.003); the mean scores for social support increased over time. The potential role of social support in moderating depression symptoms will be discussed. This study adds to our understanding of potential protective factors influencing the mental health of older LGB people.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".