JOURNAL ARTICLE
The dermatologist identity crisis: a phenomenological analysis of dermatology trainee professional identity during generalist redeployment.
Published In: Clinical & Experimental Dermatology, 2023, v. 48, n. 4. P. 345 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Guckian, Jonathan; Lee, Natasha; Sutton, Jonathan E; Mayat, Nabilah Y; Morrison, Kirsty; Farquhar, Katherine E L; Singh, Minal 3 of 3
Abstract
This article examines the impact of COVID-19 redeployment on the professional identity of dermatology trainees within the UK National Health Service (NHS), particularly amid broader shifts in medical education towards generalism. Through phenomenological analysis of semistructured interviews with ten dermatology trainees, the study identifies key themes including trainee identity and values, redeployment transitions, and future career clarity, alongside integrative themes of uncertainty, community ("tribes"), and sense of purpose. Findings reveal that trainees associate their professional identity with competence, community support, and lifelong learning, but redeployment to generalist roles during the pandemic led to experiences ranging from reaffirmation of dermatology values to disorienting reflections on career trajectories. The study suggests that fostering supportive communities, minimizing uncertainty, and promoting a clear sense of purpose may help maintain and enrich dermatology trainee identity, which is crucial for sustaining the future dermatology workforce amid evolving healthcare demands.
Additional Information
- Source:Clinical & Experimental Dermatology. 2023/04, Vol. 48, Issue 4, p345
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2023
- ISSN:0307-6938
- DOI:10.1093/ced/llac131
- Accession Number:162824340
- Copyright Statement:Copyright of Clinical & Experimental Dermatology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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