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Record W4224937349 · doi:10.5688/ajpe8687

Measuring Empathy in Iranian Pharmacy Students Using the Jefferson Scale of Empathy-Health Profession Student Version

2022· article· en· W4224937349 on OpenAlexaff
Fatemeh Mirzayeh Fashami, Mona Nili, Mina Mottaghi, Ali Vasheghani‐Farahani

Bibliographic record

VenueAmerican Journal of Pharmaceutical Education · 2022
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsMcMaster UniversityImpact
FundersThomas Jefferson University
KeywordsEmpathyConfirmatory factor analysisExploratory factor analysisPharmacyPsychologyConstruct validityScale (ratio)Clinical psychologyValidityMedical educationPsychometricsMedicineFamily medicineSocial psychologyStructural equation modeling

Abstract

fetched live from OpenAlex

<b>Objective.</b> To assess validity of the Farsi-translated version of the Jefferson Scale of Empathy-Health Profession Student version (JSE-HPS) and measure empathy scores of Iranian pharmacy students. <b>Methods.</b> The JSE-HPS questionnaire was administered to 504 Iranian pharmacy students in 2019. Confirmatory factor analysis and exploratory factor analysis were used to explore the underlying components and construct validity. Group comparisons of the empathy scores and the underlying components were conducted using statistical tests. <b>Results.</b> Based on 496 useable survey questionnaires, three domains of empathy among Iranian pharmacy students were confirmed by confirmatory factor analysis: compassionate care, perspective taking, and standing in a patient’s shoes. Two items in the JSE-HPS were removed, as their factor loadings were under the permissible limits in exploratory factor analysis. Empathy scores were significantly higher among female pharmacy students. <b>Conclusion.</b> These findings support the validity and reliability of the Farsi version of the JSE-HPS among Iranian pharmacy students.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.411
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.077
GPT teacher head0.471
Teacher spread0.394 · 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.

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

Citations13
Published2022
Admission routes1
Has abstractyes

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