A life history intervention for individuals with dementia: a randomised controlled trial examining nursing staff empathy, perceived patient personhood and aggressive behaviours
Bibliographic record
Abstract
ABSTRACT Behaviours of concern (e.g.aggression) are often present in residents of long-term care (LTC) facilities diagnosed with dementia and may impact quality of life. Prior uncontrolled research has shown that an intervention involving sharing resident life histories may be effective in reducing aggressive behaviours and improving quality of life, perhaps by increasing staff empathy. We used a randomised controlled design, involving a considerably larger sample than previous investigations. We also examined staff perceptions of LTC resident personhood in relation to aggressive behaviour. Seventy-three residents were randomised to either a life history intervention (N = 38) or a control condition (N = 35). Ninety-nine nurses and care aides answered questionnaires about their own attitudes and the residents' behaviours and quality of life at baseline, post-intervention and at follow-up. Results of mixed-effects modelling indicated significant differences between groups in personhood perception and resident quality of life. Personhood perception mediated the relationship between the intervention and improved quality of life. We identified significant negative correlations between resident cognitive impairment and staff perceptions of resident personhood. Qualitative findings suggested that staff primarily changed their verbal interactions with residents following the intervention, which may be particularly helpful for residents with the most severe dementia. Our results indicate that LTC residents benefit when life histories are constructed with their families and shared with nursing staff.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".