Compassion Questionnaires Revised: Scales Development and Validation
Bibliographic record
Abstract
The Compassion Questionnaires for Self and Others were developed to measure compassion as a multifaceted construct encompassing affective, cognitive, behavioral, and interpersonal dimensions. However, the original versions had limitations such as item number and coverage of the underlying concepts, unidirectional item wording, lack of a global latent variable, and validation only among women. This study aimed to address these shortcomings by revising the questionnaires to improve their psychometric properties. The revised Compassion Questionnaires for Self and Others underwent significant modifications. A large-scale validation study involving both women and non-women participants was conducted to evaluate the revised questionnaires. The final versions of the revised compassion questionnaires comprised 39 items for self-compassion and 33 items for compassion toward others, incorporating both positive and negative wording. Psychometric analysis indicated excellent reliability and validity, with evidence supporting the existence of global latent variables. The revised questionnaires represent a significant improvement over the original versions, offering a comprehensive operationalization of compassion constructs suitable for diverse populations. The study findings underscore the theoretical and practical significance of these questionnaires in assessing and cultivating compassion. However, certain limitations warrant consideration, and the implications for research and clinical practice are thoroughly discussed.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".