Workplace aggression experienced by frontline staff in dementia care
Bibliographic record
Abstract
AIM: To describe the frequency of aggressive acts experienced by frontline staff working in two models of dementia care: Residential Alzheimer's Care Centers and Secured Dementia Units and to explore the associations between aggressive acts experienced by frontline staff and factors related to the work context and care providers. BACKGROUND: Aggression towards healthcare providers in residential long-term care settings is well documented. However, few studies have examined associations between aggressive behaviours towards care providers and organisational factors. DESIGN: A cross-sectional survey. METHOD: The survey included demographic items and questions about aggressive acts experienced by staff and contextual factors. Analyses included: (1) descriptive statistics, (2) tests of difference (i.e. Student's t-test, Mann-Whitney U-test, chi-squared test and anova), (3) bivariate associations (i.e. Pearson and Spearman rank order correlations) and (4) multivariate linear regression. RESULTS: Ninety-one health care aides and licensed practical nurses working in four nursing units using two models of dementia care participated (response rate 81%). The most frequently reported types of aggression were physical assault (50% of staff, n = 45) and emotional abuse (48% of staff, n = 44). Aggressive acts were significantly associated with working in Secured Dementia Units rather than Residential Alzheimer's Care Centers. CONCLUSIONS: Frontline staff working in Secured Dementia Units were exposed to higher frequencies of various types of aggressive acts mainly initiated by residents. Future research needs to explore modifiable workplace factors associated with aggressive acts in a larger sample across a variety of long-term care settings. RELEVANCE TO CLINICAL PRACTICE: To prevent staff perceived aggressive acts, leaders and managers in dementia care need to acknowledge the complex topic of workplace aggression and encourage an open discussion among frontline staff without assigning blame. Care provider strategies for dealing with aggressive behaviour have to be implemented in policies and clinical practice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".