Nursing perspectives on the confusion assessment method: a qualitative focus group study
Bibliographic record
Abstract
Background: the Confusion Assessment Method (CAM) is commonly used to detect delirium. Although accurate when administered by trained researchers, its sensitivity is low when performed by nurses in clinical practice. We aimed to understand the perspectives of nurses who used the CAM on orthopaedic wards. Design: qualitative focus group study. Setting: two academic hospitals in Hamilton, Ontario, Canada. Participants: forty-three nurses who worked on orthopaedic inpatient units and used the CAM daily participated in one of eight focus group sessions. Measurements: structured focus groups explored nurses' perception of delirium and the use of the CAM. Each transcript was coded and sampling continued until theme saturation. Results: the participants (84% female, mean age 40 years, mean years in practice 12.8) had mixed feelings about the CAM. Some nurses praised its simplicity, while others preferred a narrative description of the delirium episode. Only 35% recalled receiving training to administer the CAM. Across the groups, disorientation was inappropriately used to evaluate level of consciousness and inattention. Objective testing was reportedly rarely used for assessing inattention. Most nurses retrospectively completed the CAM at the end of their shift by extrapolating from earlier observations rather than formally administering the tool. Reported challenges included differentiating delirium from dementia, assessing non-verbal patients and those with language barriers, time constraints, discrepancy with physicians' assessments and pressure to diagnose delirium. Conclusion: despite its widespread use, the CAM was poorly understood by orthopaedic nurses at two academic institutions. The CAM may be difficult to implement in practice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".