Volunteers' Experiences Visiting the Cognitively Impaired in Nursing Homes: A Friendly Visiting Program
Bibliographic record
Abstract
Two challenges facing nursing-home care today are understanding the concept of quality of life as it relates to cognitively impaired residents and finding effective ways to ensure that it is achieved. Canadian director Allan King's documentary, Memory for Max, Claire, Ida and Company , filmed at Baycrest, captures a method for enhancing the quality of life of six cognitively impaired residents. While the film suggests an intervention model implemented by volunteers, there are challenges unique to institution-based programs (i.e., the recruitment and retention of volunteers). One of the challenges is the fear that volunteers may experience when interacting with the cognitively impaired. We conducted a pilot study of a model for training volunteers to provide friendly visiting and evaluated the impact on the participating residents. Observational accounts of volunteer-resident interactions and seven volunteer interviews were analysed and yielded several themes-(a) relationship building, (b) contribution of the environment, (c) preserving personhood, (d) resident-centred presence and the quality of the moment-and several themes related to the volunteers' role and their perceived impact on the residents. Discussed are the implications for volunteer programs in long-term health care settings.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".