The Power of the Social Environment in Motivating Persons with Dementia to Engage in Occupation: Qualitative Findings
Bibliographic record
Abstract
A key element in persons with dementia's occupational engagement is the degree to which the social environment supports participation. This article summarizes the results of a qualitative study of eight assisted living facility residents, that explored volition in persons with moderate dementia. Extensive interviewing and observation were followed by the primary researcher's engagement and documentation of each resident in therapeutic activity sessions. Data were analyzed using van Manen's phenomenological approach, and three themes emerged. One, potency of the social environment, is the focus of this article. From the eight participants, two case studies are presented, one demonstrating the positive impact of therapeutic communication and social support on volitional behavior and occupational engagement and the other demonstrating the inhibiting effect of lack of therapeutic social interaction. Each case is analyzed using Epp's (2003, Person-centred dementia care: A vision to be refined. The Canadian Alzheimer's Disease Review, 14–18) Person-Centered Care model techniques and interaction modes recommended by Taylor's (2008, The intentional relationship: Occupational therapy and use of self. Philadelphia: F.A. Davis.) Intentional Relationship Model. The article concludes with recommendations for promoting positive social interactions at the client, staff/family, and systems levels.
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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 | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 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".