Validation of a short patient-reported compassion measure: the Sinclair Compassion Questionnaire-Short Form (SCQ-SF)
Bibliographic record
Abstract
BACKGROUND: The criticality of compassion in healthcare is recogniszed by governments, healthcare organisations, providers, researchers and most importantly patients. There have been calls for the development and evaluation of tools for the routine measurement of compassion, as compassion has been found to be a critical predictor of quality care. However, there has been a paucity of validated and reliable psychometrics to assess this construct. OBJECTIVE: We assessed the reliability, factor structure and validity of the Sinclair Compassion Questionnaire-Short Form (SCQ-SF). METHODS: The SCQ-SF was embedded in a large administration survey (N=2236) aimed at assessing Canadians in facility-based continuing care contexts. Reliability analysis and confirmatory factor analysis (CFA) were conducted on the SCQ-SF data. RESULTS: Data from 2236 residents were analysed. Cronbach's alpha (α =0.91) indicated that the SCQ-Short had excellent reliability. CFA indicated a well-fitting unidimensional model of compassion. The standardised factor loadings for the 5-items ranged between 0.76 and 0.87. Global indicators of fit were largely excellent (root-mean-squared residuals = 0.06, comparative fit index <0.99, standardised root-mean squared residual = 0.01, χ2 =35.66, p<0.001). CONCLUSION: The SCQ-SF is a short psychometric tool, with excellent internal consistency, strong factor loadings and good fit. The SCQ-SF is suitable for use by clinicians, researchers and health system analysts.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".