“Becoming a Person Who Does Self-Care”: How Health Care Trainees Naturalistically Develop Successful Self-Care Practices
Bibliographic record
Abstract
OBJECTIVES: Self-care is an ethical imperative for health professionals as it can mitigate the adverse effects of stress on professional functioning and health. Yet, there tends to be a lack of self-care among healthcare trainees and an insufficient focus on self-care in medical education. The objective of this study was to develop a grounded theory of how health trainees become successful self-care users. METHODS: Semi-structured interviews were conducted with 17 students in a variety of healthcare disciplines. Data were analyzed using grounded theory methodology. RESULTS: Health trainees underwent 4 iterative phases to become successful at self-care: Having a Wake-Up Call, Building Skills, Gaining Confidence, and Building an Identity. Our model also explained why some trainees were unsuccessful at developing self-care practices. CONCLUSION: We offer the first theory to explain how health trainees develop effective self-care habits. Understanding how self-care practices naturalistically develop has critical implications for developing interventions and curricula: By basing curricula about self-care on knowledge of what works, we have an opportunity to be more successful as educators. Indeed, other researchers have noted a lack of success in self-care and anti-burnout interventions for healthcare professionals. We conclude by discussing implications and recommendations for medical training and curriculum for health professions, including augmenting naturally occurring processes, linking self-care to personalized values, providing opportunities for deliberate practice, focusing on persistence with self-care, and faculty promotion and acceptance of trainee self-care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".