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Record W3165667765 · doi:10.1111/ppc.12854

The effect of affective learning on alexithymia, empathy, and attitude toward disabled persons in nursing students: A randomized controlled study

2021· article· en· W3165667765 on OpenAlexaboutno aff
Berna Dinçer, Demet İnangil

Bibliographic record

VenuePerspectives In Psychiatric Care · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaEmpathyPsychologyToronto Alexithymia ScaleRandomized controlled trialIntervention (counseling)Transformative learningClinical psychologyScale (ratio)NursingMedicineDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the effect of affective learning on alexithymia, empathy, and attitude toward disabled persons in nursing students. DESIGN AND METHODS: This prospective, randomized, controlled trial study was implemented among 70 nursing students. Based on transformative learning theory, the affective learning method was applied to the intervention group. Toronto Alexithymia Scale (TAS), Empathic Tendency Scale (ETS), and Attitudes Toward Disabled Person Scale (ATDPS) were administered to both groups. RESULTS: The intervention group showed a statistically and significantly lower score at TAS and higher score at ATDPS compared to the control group, whereas no statistically significant difference was found in ETS score. PRACTICE IMPLICATIONS: Affective learning methods could be implemented in the nursing course for improving students' attitude toward disabled persons, and reducing alexithymia.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.008
GPT teacher head0.379
Teacher spread0.371 · 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 designRandomized trial
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

Citations14
Published2021
Admission routes1
Has abstractyes

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