Developing a Research Agenda on Resident-to-Resident Aggression: Recommendations From a Consensus Conference
Bibliographic record
Abstract
This article provides an overview of the development of a research agenda on resident-to-resident aggression (RRA) in long-term care facilities by an expert panel of researchers and practitioners. A 1-day consensus-building workshop using a modified Delphi approach was held to gain consensus on nomenclature and an operational definition for RRA, to identify RRA research priorities, and to develop a roadmap for future research on these priorities. Among the six identified terms in the literature, RRA was selected. The top five priorities were: (a) developing/assessing RRA environmental interventions; (b) identification of the environmental factors triggering RRA; (c) incidence/prevalence of RRA; (d) developing/assessing staff RRA education interventions; and (e) identification of RRA perpetrator and victim characteristics. Given the significant harm RRA poses for long-term care residents, this meeting is an important milestone, as it is the first organized effort to mobilize knowledge on this under-studied topic at the research, clinical, and policy 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 | 0.530 | 0.381 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.025 | 0.038 |
| Open science | 0.018 | 0.037 |
| Research integrity | 0.046 | 0.048 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".