Confidence or Control: Using Theory of Planned Behavior to Explore Medical Residents' Intentions to Address Religion and Spirituality in Patient Care
Bibliographic record
Abstract
The purpose of this study was to explore whether subjective norms moderate the relationship between perceived control and behavioral intention and between self-efficacy and behavioral intention to address religion and spirituality (r/s) in patient care among first- through fifth-year medical residents. The study used a non-experimental design and included a sample of medical residents working in a hospital system in southeastern Pennsylvania during the summer of the 2021 were gathered to respond to the survey questionnaire measuring subjective norms, perceived control and behavioral control and behavioral intention, and self-efficacy variables. The instrument used for this study, Assessing Residents' Intentions to Address Religion/Spirituality in Patient Care, was adapted from an instrument used to measure medical residents’ intentions to adopt a comprehensive scope of practice after exposure to Canada’s Triple C curriculum. The results showed that perceived control, self-efficacy, and subjective norms are not significant predictors of intent to address r/s in patient care, and further, that subjective norm does not moderate the relationships between perceived control, self-efficacy, and intention. Recommendations for further research include examining variables across specific demographics, identifying attitudes as a possible moderating variable, and exploring the impact of the hidden medical curriculum on resident behaviors, attitudes, and values related to r/s in patient care. Finally, a future study that examines the physician-chaplain relationship may lead to increased assessment of and engagement in r/s issues.
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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 | 0.015 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".