Critical care nurses' decisions regarding physical restraints in two Canadian ICUs: A prospective observational study.
Bibliographic record
Abstract
BACKGROUND: Legislation, guidelines and accreditation standards cal for the minimization of physical restraints, yet their use remains common in intensive care units (ICUs) both in Canada and internationally. In Canada, physical restraints are prescribed by physicians. However, assessment of their need, application, and removal are primarily the responsibility of ICU nurses. OBJECTIVES: We sought to describe Canadian ICU nurses' decision-making and practices of physical restraint application and discontinuation, as well as alternative measures attempted prior to their use for critically ill adults. METHODS: We conducted a prospective, observational study in two medical-surgical ICUs (tertiary academic and large community teaching hospital) of physical restraint use. RESULTS: We collected physical restraint data from the medical records of 141 patients from October 2011 to September 2012. Most restrained patients were mechanically ventilated (n = 118, 84%). Of the 247 reasons for restraint application identified for these 141 patients, agitation (n = 107, 43%), restlessness (n = 42, 17%) and use as a precautionary measure (n = 42, 17%) were the most commonly documented. Of the 167 behaviours observed and documented by nurses as indicative of agitation, pulling at the endotracheal tube or other lines/tubes (n = 111, 66%) was most commonly cited. Nurses documented the use of various strategies as an alternative to physical rest raint prior to their use for 46 (33%) patients. Of the 96 alternative strategies attempted, communication comprising reorientation and reminders was the most frequently documented (n = 26, 27%). Nurses reported having considered removing restraints during their shift for 61 (43%) patients. The criterion most commonly deemed essential for restraint removal was a calm patient (51 of the 104 reasons listed, 49%). CONCLUSIONS: Our study suggests that patient behaviour indicative of agitation was the most common reason for physical restraint application. Use as a precautionary measure and in situations where nurses' ability to be present at the bedside was reduced, as well as the limited use of alternative measures prior to physical restraint suggest restraint minimization may not be optimal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".