Social networking site use, sexual orientation, and associations with mental health: Findings from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
The number of older adults using online social networking sites (SNS) to maintain social connections is rising. SNS use may contribute both negatively and positively to the mental health of older adults, and these associations may vary by sexual orientation. The purpose of this study was to explore SNS use in older adults by sexual orientation, and to examine associations between SNS use and mental health using participants from the Canadian Longitudinal Study on Aging ( n = 21,836). We found that lesbian, gay, and bisexual (LGB) participants had greater odds of using SNS than heterosexual participants. Additionally, LGB participants who used SNS to stay in touch with friends reported fewer depressive symptoms than their heterosexual peers, and LGB participants who used SNS to make new friends reported more loneliness than heterosexual participants who used SNS for the same reason. This study adds to the growing literature on how older adults, and LGB older adults in particular, use SNS. • LGB older adults had greater odds of using SNS than heterosexual older adults. • Associations between mental health and SNS use varied by sexual orientation. • The reason for using SNS (e.g., to make new friends) may impact mental health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".