Capturing patients' views on communication with anaesthetists: the CARE Measure
Bibliographic record
Abstract
Purpose The purpose of this paper is to determine the relevance and reliability of the ten-item Consultation and Relational Empathy (CARE) Measure as a tool for measuring patients' views of anaesthetists during preoperative assessment consultations. Design/methodology/approach Self-completed patient questionnaire containing the ten-item CARE Measure. Consecutive adult patients were asked to complete the ten-item CARE questionnaire immediately after their pre-operative assessment consultation with the anaesthetist and return it to a designated local co-ordinator. Reliability co-efficient of the overall measure, and relevance of each item to patients' concerns were measured. Findings Using the Measure, 31 consultant anaesthetists were assessed by 1,582 patients (559 male, 952 female). The total number of “not applicable” responses was 1,086, (6.8 per cent of the total number of possible “not applicable” responses). The overall number of missing values was 0.6 per cent. The measure effectively discriminated between doctors (reliability co-efficient of the average score per doctor provided by 40 patients was above 0.8) and had high internal consistency (Cronbach's alpha, 0.93). Originality/value The present study presents evidence of a tool which may have utility in anaesthetics and other settings.
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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 | 0.012 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".