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Record W4367668976 · doi:10.2196/44241

Measurement of Humanity Among Health Professionals: Development and Validation of the Medical Humanity Scale Using the Delphi Method

2023· article· en· W4367668976 on OpenAlexvenueno aff
Jawdat Ataya, Issam Jamous, Mayssoon Dashash

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaLikert scaleScale (ratio)EmpathyPsychologyHumanityDelphi methodCompassionClinical psychologyHealth careMedicineSocial psychologyPsychometricsStatisticsDevelopmental psychologyMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the importance of humanism in providing health care, there is a lack of valid and reliable tool for assessing humanity among health professionals. OBJECTIVE: The aim of this study was to design a new humanism scale and to assess the validity of this scale in measuring humanism among Syrian health professional students. METHODS: The Medical Humanity Scale (MHS) was designed. It consists of 27 items categorized into 7 human values including patient-oriented care, respect, empathy, ethics, altruism, and compassion. The scale was tested for internal consistency and reliability using Cronbach α and test-retest methods. The construct validity of the scale was also tested to assess the ability of the scale in differentiating between groups of health professional students with different levels of medical humanity. A 7-point Likert scale was adopted. The study included 300 participants including 97 medical, 78 dental, 82 pharmacy, and 43 preparatory-year students from Syrian universities. The Delphi method was used and factors analysis was performed. Bartlett test of sphericity and the Kaiser-Meyer-Olkin measure of sample adequacy were used. The number of components was extracted using principal component analysis. RESULTS: The mean score of the MHS was 158.7 (SD 11.4). The MHS mean score of female participants was significantly higher than the mean score of male participants (159.59, SD 10.21 vs 155.48, SD 14.35; P=.008). The MHS mean score was significantly lower in dental students (154.12, SD 1.45; P=.005) than the mean scores of medical students (159.77, SD 1.02), pharmacy students (161.40, SD 1.05), and preparatory-year students (159.05, SD 1.94). However, no significant relationship was found between humanism and academic year (P=.32), university type (P=.34), marital status (P=.64), or financial situation (P=.16). The Kaiser-Meyer-Olkin test (0.730) and Bartlett test of sphericity (1201.611, df=351; P=.01) were performed. Factor analysis indicated that the proportion of variables between the first and second factors was greater than 10%, confirming that the scale was a single group. The Cronbach α for the overall scale was 0.735, indicating that the scale had acceptable reliability and validity. CONCLUSIONS: The results of this study suggest that the MHS is a reliable and valid tool for measuring humanity among health professional students and the development of patient-centered care.

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)0.054
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.005
Research integrity0.0010.001
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 head0.446
GPT teacher head0.602
Teacher spread0.157 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations9
Published2023
Admission routes1
Has abstractyes

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