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Record W4412589435 · doi:10.1177/10784535251357968

Investigating the Relationship Between Self-Efficacy and Caring Behaviors in Critical Care Nurses: A Cross-Sectional Study

2025· article· en· W4412589435 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCreative Nursing · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsSelf-efficacyCross-sectional studyCompetence (human resources)NursingPsychological interventionSocial supportPsychologyScale (ratio)Health careDescriptive statisticsMedicineFamily medicineSocial psychology

Abstract

fetched live from OpenAlex

This descriptive-analytical cross-sectional study investigated the relationship between self-efficacy and self-reported caring behaviors of 198 nurses working in intensive care units of hospitals affiliated with Tehran University of Medical Sciences in Tehran, Iran in 2023. The tools used were a Sociodemographic Information Form, the Nursing Profession Self-Efficacy Scale, and the Caring Behaviors Inventory. In the multiple linear regression model, the support situation subscale of self-efficacy was significantly associated with the total caring behavior scores of nurses ( β = 1.9, 95% CI = 1.74–2.07, p = 0.001). In the multiple linear regression model, 70% of the variance in caring behaviors among nurses was explained ( R 2 = 0.73). By recognizing the role of social support in fostering nurses’ confidence and competence, healthcare organizations can implement targeted interventions to promote a supportive work environment and enhance patient care outcomes.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.192
GPT teacher head0.559
Teacher spread0.367 · 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