Ending PJ paralysis for hospitalised patients: a quality improvement initiative
Bibliographic record
Abstract
INTRODUCTION: PJ paralysis refers to the negative effects experienced by hospitalised patients who remain inactive and dressed in hospital clothing, and is a serious problem, affecting one-third of hospitalised older adults. This study evaluated the impact of a multicomponent hospital-based intervention to get patients out of bed, dressed in non-hospital attire, and moving around/mobilised. METHODS: A 3-month quality improvement initiative was conducted at one hospital unit in Western Canada, which aimed for 50% of all patients to be dressed in their own clothing by midday, sitting up in a chair for all meals and mobilising to activities. Healthcare providers, patients and family members received PJ paralysis education, and a new patient dress code care standard and physician patient care order were implemented. Measures included: daily percentage of patients dressed and up for meals, weekly mobilisation rates, patient and provider satisfaction, and complication rates. Descriptive statistics were completed. RESULTS: From July to October 2019, 70 patients participated. Approximately 14.3% of patients were dressed in their own clothing daily, 6.4% were sitting for all three meals, and the weekly mean number of patients mobilising to activities was 0.9 (SD 0.7) and mobilising for other reasons was 4.5 (SD 1.3). Five physician care orders were written. A trend was observed towards decreased falls, with minimal change in the number of staff, nursing assessment time and complication rates. Patient feedback revealed improvement in their self-identity. CONCLUSION: Alleviating PJ paralysis in hospitalised older patients requires a complex multifactorial approach. Despite not achieving the project aim, the intervention demonstrated positive impacts without complications or additional workload, and ease of implementation suggests feasibility and (potential) long-term sustainability. Further research is needed to explore the experiences and perceptions of patients and healthcare providers to identify facilitators and barriers, which may aid in enhancing and implementing future interventions.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".