Investigating the Relationship Between Self-Efficacy and Caring Behaviors in Critical Care Nurses: A Cross-Sectional Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".