Managing Agitation Using Nonpharmacological Interventions for Seniors With Dementia
Bibliographic record
Abstract
Approximately 36 million people have Alzheimer's disease worldwide, and many experience behavioral issues such as agitation. The purpose of this study was to investigate the perceptions of long-term care (LTC) staff regarding the current use of nonpharmacological interventions (NPIs) for reducing agitation in seniors with dementia and to identify facilitators and barriers that guide NPI implementation. Qualitative methods were used to gather data from interviews and focus groups. A total of 44 staff from 5 LTC facilities participated. Findings showed that both medications and NPIs are used for the management of agitation. The use of NPIs was facilitated by consistency in staffing, and the ability of all the staff members to implement them. Common barriers to NPI use included the perceived lack of time, low staff-to-resident ratios, and the unpredictable and short-lasting effectiveness of NPIs. This study offers insight into perceived factors that influence implementation of NPIs and the perceived effectiveness of NPIs.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".