Process Models to Understand Resident-to-Resident Aggression Among Residents With Dementia in Long-Term Care
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Resident-to-resident aggression (RRA) is a prevalent form of interpersonal violence in long-term care (LTC) settings. Research to guide preventive interventions is limited. Using social-ecological and need-driven dementia-compromised behavior perspectives, we sought to generate process models representing common RRA pathways in dementia-specific LTC units. RESEARCH METHODS: = 36) exposed to everyday resident interactions at two urban LTC facilities in Toronto, Canada. Semistructured interviews were audio-recorded and transcribed. Two independent raters coded the transcripts using iterative, constant comparison analytic processes. RESULTS: Two distinct RRA process models in dementia-specific LTC units were developed. Models reflect sequential pathways driven by residents' benign or responsive behaviors and cognitive processing limitations, with escalation points within resident dyads or groups. IMPLICATIONS: This study furthers RRA conceptualization as a process rather than an aggressive event. Models capture unique RRA manifestations in dementia-specific LTC units and entrypoints for prevention or management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".