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Record W4410463331 · doi:10.1177/10731911251337185

Compassion Questionnaires Revised: Scales Development and Validation

2025· article· en· W4410463331 on OpenAlexaff
Bassam Khoury, Rodrigo C. Vergara

Bibliographic record

VenueAssessment · 2025
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyOperationalizationCompassionScale (ratio)Construct (python library)Clinical psychologyReliability (semiconductor)Interpersonal communicationConstruct validityPsychometricsApplied psychologySocial psychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.393
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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