Peer volunteer perspectives following a complex social cognitive intervention: a qualitative investigation
Bibliographic record
Abstract
BACKGROUND: Peer volunteers can be key to delivering effective social cognitive interventions due to increased potential for social modeling. We consulted peer volunteers who had just taken part in an 8-week social and nutritional mealtime intervention with older adults living alone, to seek their evaluation of the intervention. METHODS: Semi-structured focus groups were used with a total of 21 volunteers (17 female) and two facilitators. Thematic analysis was used to interrogate the data. RESULTS: Six themes (16 sub-themes) are discussed. Peer volunteers described the importance of the socializing aspect of the intervention, of pairing considerations and compatibility in peer interventions, of considering the needs of the participant, of benefits to the volunteers, and of the practical considerations of conducting an intervention. Volunteers also discussed considerations for future research and services for older adults living alone. CONCLUSIONS: Volunteers found their involvement in the intervention to be personally beneficial, and revealed some valuable considerations for the researchers to take forward to future research. Results are pertinent to intervention design and could inform future social cognitive and other peer-oriented interventions for older adults living alone.
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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 | 0.025 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".