Effectiveness of interventions on conscience: Findings of a systematic review
Bibliographic record
Abstract
Research indicates that conscience is an asset to healthcare professional's personal and professional practice. However, little work has been done to support healthcare professionals to use and understand their conscience for moral decision-making. Disparity exists between international and national bodies that value conscience for healthcare professionals and the paucity of practice supports available to formally assist healthcare professionals to openly discuss and then navigate their moral decisions arising from their conscience. Therefore, the purpose of this systematic review was to examine the effectiveness of existing interventions aimed at supporting healthcare professionals to understand and use their conscience for healthcare practice. This review was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Metanalyses. International, interdisciplinary databases including Medline, Embase, PsycINFO, CINAHL, Academic Search Complete, ATLA Religion, Religion and Philosophy Collection, PhilPapers, Scopus and Cochrane Controlled Register of Trials were searched and quantitative as well as qualitative outcomes were reported. We found 11 studies that met the inclusion criteria and underwent data extraction and synthesis. Five interventions were identified that aimed to address aspects of HCP's conscience. No interventions were identified that aim to support healthcare professionals to understand or use their conscience for moral decision-making in practice. Empirical and humanities research indicates that conscience is essential to healthcare practice, but issues of conscience remain a polarizing experience for many HCPs. Intervention and education-based research are therefore needed to support HCP's understanding and use of conscience for practice.
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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 | 0.033 | 0.167 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".