Clinical evaluation questionnaire in advanced cancer: a psychometric study of a novel measure of healthcare provider interactions
Bibliographic record
Abstract
OBJECTIVES: The Clinical Evaluation Questionnaire (CEQ) is a patient-reported experience measure (PREM) that assesses the perceived benefit of therapeutic interactions of patients with advanced cancer with their healthcare providers concerning issues relevant to their illness. It was developed for a randomised controlled trial of Managing Cancer and Living Meaningfully (CALM), a brief supportive-expressive therapy for patients with advanced cancer. The present study evaluates the preliminary psychometric properties of the CEQ. METHOD: Patients in the CALM and usual care groups completed the CEQ 3 (n=195) and 6 (n=186) months after randomisation. The CEQ's internal consistency, factor structure and concurrent validity were evaluated, and CEQ scores in the treatment groups were compared. RESULTS: The CEQ demonstrated high internal consistency for both treatment arms (Cronbach's α=0.94 to 0.95), and a single factor was consistently found in exploratory factor analyses. CEQ scores correlated significantly with satisfaction with the relationship with healthcare providers (r=0.23 to 0.61, p≤0.02) and life completion (r=0.24 to 0.37, p≤0.02) in both groups and with spiritual well-being in the CALM group (meaning: r=0.23 to 0.24, p=0.01 to 0.02; faith: r=0.24 to 0.34, p=0.001 to 0.02). The CALM group showed higher CEQ total scores than usual care at 6 months (CALM: 18.19±6.59; usual care: 14.36±7.67, p<0.001). CONCLUSIONS: The CEQ is a reliable and valid PREM of the benefit perceived by patients with advanced cancer from their interactions with healthcare providers. Further study is needed to establish its value as a measure of perceived intervention benefit across different clinical and research 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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".