Belonging in dual roles: exploring professional identity formation among disabled healthcare students and clinicians
Bibliographic record
Abstract
The development of a robust professional identity is a pivotal aspect of every healthcare professional's educational journey. Critical social perspectives are increasingly influencing the examination of professional identity formation within healthcare professions. While understanding how disabled students and practitioners integrate a disability identity into their professional identity is crucial, we have limited knowledge about the actual formation of their professional identity. This study aims to investigate how disabled students and clinicians in healthcare professions actively shape their professional identity during their educational and professional journeys. We conducted in-depth semi-structured interviews with 27 students and 29 clinicians, conducting up to three interviews per participant over a year, resulting in 124 interviews. Participants represented five healthcare professions: medicine, nursing, occupational therapy, physical therapy, and social work. Employing a constructivist grounded theory approach, our data analysis revealed two prominent dimensions: (a) The contextualization of identity formation processes and (b) The identity navigation dimension in which the professional identity and disability identity are explored. This emerging model sheds light on the dynamic processes involved in identity formation, emphasizing the significance of a supportive environment for disabled students and practitioners. Such an environment fosters the negotiation of both professional and disability identities. Moreover, this study recognizes the importance of a re-examination of the concepts of professionalism and professional identity in healthcare professions. In conclusion, this research underscores the importance of understanding and supporting the multifaceted identity formation processes among disabled individuals within healthcare professions.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| 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".