Document Type

Article

Publication Date

8-1-2025

Comments

This article is the author's final published version in Clinical Teacher, Volume 22, Issue 4, 2025, Article number e70102.

The published version is available at https://doi.org/10.1111/tct.70102.

Copyright © 2025 The Author(s)

Abstract

INTRODUCTION: Data are limited as to which factors most strongly impact medical trainees' well-being, and few studies have assessed trainee's wellness at multiple time points during the COVID-19 pandemic. Additionally, much research has not taken an intersectional approach to understanding the ways in which different facets of a resident's identity impact their wellness. Thus, more person-centred, probability-driven statistical approaches that can produce distinct heterogenous groups of individuals are warranted to understand the way in which different identities are associated with resident wellness scores.

METHODS: A latent profile analysis was conducted using institutional data from resident surveys administered from 2019 to 2022. We had a 78.8% response rates for a total of 1101 surveys completed and 1033 retained for data analysis (i.e., 662 medical residents, 204 surgical residents, 48 pharmacy residents and 119 residents who did not specify practice type).

RESULTS: Broadly, findings indicated that having certain identities (i.e., being female, being in a medical or pharmacy programme and length of time in programme) resulted in lower resident wellness scores. However, the degree to which these scores were impacted appeared to be dependent on the intersection of the residents' identities with COVID-19 time point being moderately influential (e.g., advanced medical/pharmacy residents scored lower in latter part of COVID-19; PGY1 medical residents scored lower regardless of COVID-19 time point).

CONCLUSIONS: Results from this study encourage data-driven approaches to wellness initiatives that are tailored by gender, programme type and year of programme.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

PubMed ID

40484703

Language

English

Available for download on Friday, August 01, 2025

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