Preventing social isolation and loneliness among older people: a systematic review of health promotion interventions
Bibliographic record
Abstract
Preventing and alleviating social isolation and loneliness among older people is an important area for policy and practice, but the effectiveness of many interventions has been questioned because of the lack of evidence. A systematic review was conducted to determine the effectiveness of health promotion interventions that target social isolation and loneliness among older people. Quantitative outcome studies between 1970 and 2002 in any language were included. Articles were identified by searching electronic databases, journals and abstracts, and contacting key informants. Information was extracted and synthesised using a standard form. Thirty studies were identified and categorised as ‘group’ (n=17); ‘one-to-one’ (n=10); ‘service provision’ (n=3); and ‘community development’ (n=1). Most were conducted in the USA and Canada, and their design, methods, quality and transferability varied considerably. Nine of the 10 effective interventions were group activities with an educational or support input. Six of the eight ineffective interventions provided one-to-one social support, advice and information, or health-needs assessment. The review suggests that educational and social activity group interventions that target specific groups can alleviate social isolation and loneliness among older people. The effectiveness of home visiting and befriending schemes remains unclear.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".