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Record W4415288052 · doi:10.2196/86055

Developing a shared understanding of humanism: Protocol for critical review, empirical exploration and modified e-Delphi study. (Preprint)

2025· article· en· W4415288052 on OpenAlexvenueaboutno aff
Diane Guay, Annie Turcotte, Marie-Josée April, Véronique Foley, Jacinthe Beauchamp, Nicole Marquis, Michèle Héon-Lepage

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)Experiential learningThematic analysisProtocol (science)HumanismConstruct (python library)CompassionExperiential knowledgeConceptual framework

Abstract

fetched live from OpenAlex

BACKGROUND Humanism is central to the practice of health care professionals but remains poorly defined and inconsistently applied. Amid growing system pressures and dehumanization, this study aims to develop consensus-based conceptual and operational definitions of humanism to support education, evaluation, practice, and policy. OBJECTIVE This study aims to formulate consensus-based conceptual and operational definitions of humanism in health care, based on the integration of theoretical perspectives with the experiences and expertise of clinician-educators, students, and members of the public. METHODS A 2-phase mixed methods design was implemented to ensure methodological rigor and analytical depth. In phase I, a critical review of the literature was conducted and systematically analyzed using content analysis. Concurrently, focus groups were conducted with learners, clinician-educators, and members of the public. The resulting qualitative data were subjected to thematic analysis to capture both the theoretical and experiential dimensions of humanism in health care. Phase 2 will involve a modified e-Delphi technique, in which the generated statements will be submitted to an interdisciplinary and cross-sectoral panel of experts for iterative refinement and validation. This approach is intended to strengthen construct validity and support consensus building. RESULTS This project is funded by the Research Chair in Compassion Science at the Université de Sherbrooke, with additional support from the Office of Social Accountability. The study is currently progressing through phase 1. In step 1 (critical literature review), the initial screening of studies based on titles and abstracts has been completed, and full-text screening is nearing completion. To date, 51 studies have been selected, and data extraction and analysis are underway. In step 2, analysis of data collected from 3 focus groups (N=18) has been completed. The process of converting critical review and focus group findings into Delphi statements is expected to be completed by the end of summer 2026. Phase 2 will consist of a modified e-Delphi process. The launch of this phase, involving the submission of the developed statements to an interdisciplinary and cross-sectoral panel of experts, is scheduled for fall 2026. CONCLUSIONS This study is expected to contribute to the development of a conceptually grounded and operationally relevant definition of humanism in health care, informed by both theoretical foundations and lived experiences. This process will support the harmonization of educational practices, the development of assessment tools, and the integration of humanistic values into health policy. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/86055

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.210
metaresearch head score (Gemma)0.276
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.210
Threshold uncertainty score0.974

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2100.276
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0090.009
Science and technology studies0.0060.007
Scholarly communication0.0060.008
Open science0.0050.008
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0560.016

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 head0.932
GPT teacher head0.768
Teacher spread0.163 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes2
Has abstractyes

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