The Perspective of Nurses and Healthcare Providers on the use of Television Videos with People with Moderate to Severe Dementia
Bibliographic record
Abstract
BACKGROUND: Nurses and healthcare providers need practical tools to deliver person-centred care in hospitals and long-term care homes. Few non-pharmacological interventions are designed to meet the needs of people with moderate to severe dementia. Dementia-friendly television videos (TV videos) offer a familiar stimulation with the potential for meaningful engagement in the relational space of technology. TV videos refer to moving visuals with audio that can be shown on TV and other devices. They can be used for different purposes for people with dementia, such as stimulating memories and facilitating expressions. PURPOSE: This study aims to understand the perspectives of nurses and healthcare providers on the potential function and practice considerations of using TV videos for people with moderate to severe dementia. METHODS: We conducted five focus groups with 23 nurses and healthcare providers in a long-term care home and a geriatric hospital unit. Data were analyzed using reflexive thematic analysis and guided by Kitwood's person-centred care model. RESULTS: Our analysis identified five themes about the use of TV videos: (1) calm the person with dementia who is in emotional distress, (2) form connections with the person with dementia, (3) bring people with dementia together, (4) facilitate the Person's Activities of Daily Living (ADLs), (5) help the person connect with their past. CONCLUSION: TV videos should be designed to match the person's cognitive abilities, interests, and cultural and linguistic backgrounds. Our findings supplemented Kitwood's model by identifying the person's cultural and language needs.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".