The Impact of Peer Mentoring on Loneliness, Depression, and Social Engagement in Long-Term Care
Bibliographic record
Abstract
Loneliness, depression, and social isolation are common among people living in long-term care homes, despite the activities provided. We examined the impact of a new peer mentoring program called Java Mentorship on mentees’ loneliness, depression, and social engagement, and described their perceptions of the visits. We conducted a mixed-methods approach in 10 homes in Ontario, Canada, and enrolled residents as mentees ( n = 74). We used quantitative surveys and qualitative interviews to understand their experience. After 6 months, mentees ( n = 43) showed a 30% reduction in depression ( p = .02, d = .76), a 12% reduction in loneliness ( p = .02, d = .76), and a 60% increase in the number of monthly programs attended ( p = .01, d = .37), with small-to-medium effect sizes. The analysis of mentee’s interviews revealed positive perceptions. This program offers an innovative, nonpharmacological alternative to the treatment of loneliness and depression.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".