Physical restraint use among nursing home residents: A comparison of two data collection methods
Bibliographic record
Abstract
BACKGROUND: In view of the issues surrounding physical restraint use, it is important to have a method of measurement as valid and reliable as possible. We determined the sensitivity and specificity of physical restraint use a) reported by nursing staff and b) reviewed from medical and nursing records in nursing home settings, by comparing these methods with direct observation. METHODS: We sampled eight care units in skilled nursing homes, seven care units in nursing homes and one long-term care unit in a hospital, from eight facilities which included 28 nurses and 377 residents. Physical restraint use was assessed the day following three periods of direct observation by two different means: interview with one or several members of the regular nursing staff, and review of medical and nursing records. Sensitivity and specificity values were calculated according to 2-by-2 contingency tables. Differences between the methods were assessed using the phi coefficient. Other information collected included: demographic characteristics, disruptive behaviors, body alignment problems, cognitive and functional skills. RESULTS: Compared to direct observation (gold standard), reported restraint use by nursing staff yielded a sensitivity of 87.4% at a specificity of 93.7% (phi = 0.84). When data was reviewed from subjects' medical and nursing records, sensitivity was reduced to 74.8%, and specificity to 86.3% (phi = 0.54). Justifications for restraint use including risk for falls, agitation, body alignment problems and aggressiveness were associated with the use of physical restraints. CONCLUSIONS: The interview of nursing staff and the review of medical and nursing records are both valid and reliable techniques for measuring physical restraint use among nursing home residents. Higher sensitivity and specificity values were achieved when nursing staff was interviewed as compared to reviewing medical records. This study suggests that the interview of nursing staff is a more reliable method of data collection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".