Older adults can re-appraise loneliness using a social connectivity app: a mixed method intervention study
Bibliographic record
Abstract
OBJECTIVES: Older adults face an elevated risk of social isolation, loneliness, and poor psychological health. This mixed methods study evaluates a trial of an intervention app designed to protect against loneliness by raising older adults' awareness of their social relationships. METHOD: = 99, Mean Age = 68) completed a survey at three timepoints (baseline, two, and four weeks) reporting loneliness, depression, and anxiety. Forty-five post-trial interviews were conducted with the app users and analysed using reflexive thematic analysis. RESULTS: A significant interaction effect was found; participants using the app reported a significant reduction in depression scores between baseline and four-week follow-up. There was no significant effect on loneliness or anxiety scores. Interviews revealed ways app users were (1) Holding up a mirror to feelings about their social groups, (2) Re-appraising loneliness; and (3) Acting as analysts. CONCLUSION: The digital intervention reduced reported depression by enhancing positive appraisal of social groups. Further work is required to understand how to overcome risks of reflection-based apps for loneliness.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".