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Record W2299577948 · doi:10.1111/inm.12198

Nurses' caring and empathy in Jordanian psychiatric hospitals: A national survey

2016· article· en· W2299577948 on OpenAlexaboutno aff
Majdi Alhadidi, Maysoon S. Abdalrahim, Mahmoud Al‐Hussami

Bibliographic record

VenueInternational Journal of Mental Health Nursing · 2016
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyMental healthPsychologyNursingPsychiatryClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Nurses working in psychiatric hospitals need to acquire the skills of therapeutic communication and empathy, and have higher levels of caring. The present study aims to investigate the level of caring and empathy among nurses working in psychiatric hospitals. A cross-sectional survey was utilized to collect data from 205 nurses recruited from three psychiatric hospitals in Jordan. The Background Information Questionnaire, Modified Caring Dimensions Inventory, and Toronto Empathy Questionnaire were administered to the recruited participants. The findings revealed that the sampled nurses had a high level of caring and empathy. Significant correlations were found between caring and having a specialized training in mental health nursing, and having organizational and managerial support. However, no significant correlations were found between empathy and participants' characteristics. Specialized training in mental health nursing, having organizational and managerial support, and empathy were found predictors for caring.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.026
GPT teacher head0.404
Teacher spread0.378 · 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 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

Citations24
Published2016
Admission routes1
Has abstractyes

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