Moral distress in undergraduate nursing students
Bibliographic record
Abstract
BACKGROUND: Nurses and nursing students appear vulnerable to moral distress when faced with ethical dilemmas or decision-making in clinical practice. As a result, they may experience professional dissatisfaction and their relationships with patients, families, and colleagues may be compromised. The impact of moral distress may manifest as anger, feelings of guilt and frustration, a desire to give up the profession, loss of self-esteem, depression, and anxiety. OBJECTIVES: The purpose of this review was to describe how dilemmas and environmental, relational, and organizational factors contribute to moral distress in undergraduate student nurses during their clinical experience and professional education. RESEARCH DESIGN: The research design was a systematic literature review. METHOD: The search produced a total of 157 articles published between 2004 and 2014. These were screened with the assessment sheet designed by Hawker and colleagues. Four articles matched the search criteria (one quantitative study and three qualitative), and these were separately read and analyzed by the researchers. The process of review and analysis of the data was supervised by a colleague experienced in moral distress who provided an independent quality check. ETHICAL CONSIDERATION: Since this was a systematic review, no ethical approval was required. FINDINGS: From the analysis, it emerged that inequalities and healthcare disparities, the relationship with the mentor, and students' individual characteristics can all impact negatively on the decisions taken and the nursing care provided, generating moral distress. All these factors condition both the clinical experience and learning process, in addition to the professional development and the possible care choices of future nurses. CONCLUSION: Few studies dealt with moral distress in the setting of nurse education, and there is a knowledge gap related to this phenomenon. The results of this review underline the need for further research regarding interventions that can minimize moral distress in undergraduate nursing students.
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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 | 0.010 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".