SOCIAL NETWORKING SITE USE AND MENTAL HEALTH IN OLDER LGB CANADIANS IN THE CLSA
Bibliographic record
Abstract
Abstract The Internet has historically been an important avenue for social connection between lesbian, gay, and bisexual (LGB) people. Social networking sites (SNS) may have positive mental health impacts for LGB people. Limited research has explored SNS use in older LGB adults. The purpose of this study was to examine SNS use by sexual orientation in a sample of heterosexual and LGB Canadians using data collected from Follow-up 1 of the Canadian Longitudinal Study on Aging (n=21,836; 583 LGB). Participants completed self-report measures of SNS use, depression symptoms (CESD-10), and loneliness (UCLA 3-item Loneliness Scale). After adjusting for age, gender, income, and education, a significant difference remained in the odds of LGB participants using SNS to make new friends (OR = 1.82, p<.001) and promote themselves or their work (OR = 1.34, p=.005) in comparison to heterosexual participants. In terms of mental health, the linear regression treating depression as the outcome variable showed an interaction between being LGB and using SNS to stay in touch with friends (B=-1.23, p=.012), such that using SNS to stay in touch with friends as an LGB person was associated with fewer depression symptoms. The linear regression treating loneliness as the outcome variable showed an interaction between being LGB and using SNS to make new friends (B=.44, p=.013), indicating that LGB people who use SNS to make new friends report more loneliness than heterosexual people who use SNS to make new friends. This study adds to the growing literature on how older LGB adults use SNS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".