Determinants of Non-emergency Use of Control Interventions in Older Canadian Psychiatric Inpatients: Analysizing the InterRAI Mental Health Electronic Health Records
Bibliographic record
Abstract
Background: The use of control interventions (CIs; acute control medications, physical/mechanical restraint) is associated with negative physical and psychological outcomes, particularly in older adults who are physically vulnerable. The aims of this study were to: (i) report the rates of CI use in older psychiatric inpatients (age 65 – 84 and age 85+), and compare them with younger age groups (18 – 44, age 45 – 64); and (ii) identify the factors associated with non-emergency CI use in older psychiatric inpatients. Methods: Routinely collected interRAI Mental Health assessments from 2005 – 2018 in Ontario, Canada, were analyzed to determine the rates of CI use. Logistic regression models were used to examine the sociodemographic and clinical determinants of non-emergency and any CI use. Results: There were 226,119 (female: 48.6%) interRAI assessments, and 85% of those assessed were under 65 years of age. The rates of non-emergency CI use in the four age groups were: 18 – 44 = 9.4%, 45 – 64 = 8.3%, 65 – 84 = 9.9%, 85+ = 13.2%. The most significant determinants of non-emergency CI use in older adults were highest impairments in activities of daily living (ADL Short Form score 8–16: OR = 2.72, 95% CI = 2.42 – 3.06), highest levels of aggression (Aggressive Behavior Scale score 4 – 6: OR = 1.76, 95% CI = 1.57 – 1.98), and highest levels of positive psychotic symptoms (Positive Symptoms Scale score 9+: OR = 1.65, 95% CI = 1.43 – 1.90). Delirium, cognitive disorder diagnosis, cognitive impairment, and falls were also associated with increased CI use odds, as were having the reasons for admission be danger to self, danger to others or inability to care for self. Females were less likely to have non-emergency CI use (OR = 0.84, 95% CI = 0.73 – 0.95). Patients admitted from long-term care homes had significantly greater odds of non-emergency CI use compared with community admissions (OR = 1.18; 95% CI = 1.07 – 1.29). Conclusion: The higher rates of non-emergency CI use in older psychiatric inpatients is concerning. Alternative non-pharmacological and person-centered management strategies should be considered to support older psychiatric inpatients with functional impairment, positive symptoms, aggressive behavior, cognitive impairment and delirium. The use of CIs could be incorporated as a quality improvement activity to monitor changes at various service provision levels.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".