Prevalence and Risk Factors of Resident to Staff Aggression in Long Term Care Facilities in Hong Kong
Bibliographic record
Abstract
Abstract Resident-to-staff aggression (RSA) is common in long-term care facilities. It is associated with adverse physical and psychological consequences for staff, deteriorates resident-staff relationships, and greater staff turnover intention. Drawing on a sample of 703 care workers from 70 long-term care facilities, this study sought to determine the prevalence and risk factors of RSA in Hong Kong. RSA is common in this sample: 97.6% reported verbal aggression, 10.7% physical assault, 8.5% sexual violence, 13.7% annoying behaviors. Logistic regression analyses were conducted to determine factors associated with physical assaults, sexual violence, and annoying behaviors, controlling for duration (minutes) and location (common area vs resident rooms) of RSA. Physical assaults was associated with perpetrator behavioral problems (OR = 1.08, p<.001), resident male gender (OR = 2.40, p<.05), dementia (OR = 21.87, p<.001), staff lack of experience in dementia care (OR = 17.59, p<.001), need to provide dementia care (OR = 15.89, p<.01), lack of training (OR = 10.06, p<.01, and perceived insufficient training (OR = 2.97, p<.01). Sexual violence was associated with perpetrator male gender (OR = 22.51, p<.001), staff younger age (OR=.93. p<.05) and female gender (OR=.14, p<.01). Annoying behaviors was associated with perpetrator behavioral problems (OR = 1.07, p<.001), younger age (OR=.94, p<.95), male gender (OR = 3.04, p<.01), dementia (OR = 2.31, p<.01), staff female gender (OR=.32, p<.01), lack of experience in dementia care (OR = 3.56, p<.05), needs to provide dementia care (OR = 12.31, p<.01), lack of training (OR = 11.52, p<.001), and perceived insufficient training (OR = 2.52, p<.01). Addressing resident behavioral problems and providing sufficient staff training may help prevent RSA
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".