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Which lane are we in? Driving toward adaptive expertise in clinical practice

Published online by Cambridge University Press:  15 June 2026

Adrienne H. Simonds*
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
Mary Lou Galantino
Affiliation:
Program in Physical Therapy, Stockton University, Galloway, NJ, USA University of Pennsylvania, Philadelphia, PA, USA University of the Witwatersrand, Johannesburg, South Africa
Todd Levin
Affiliation:
Jefferson Health - Northeast, Philadelphia, PA, USA
Pamela Rothpletz-Puglia
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
James Scott Parrott
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
Richard Ferraro
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
Andrew Lynch
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
Judith Barberio
Affiliation:
School of Nursing, Rutgers Health, Newark, NJ, USA
David M. Kietrys
Affiliation:
School of Health Professions, Rutgers Health , Newark, NJ, USA
*
Corresponding author: A. H. Simonds; Email: adrienne.simonds@rutgers.edu
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Abstract

Mpox infection causes fever, rash, painful lesions, and flu-like symptoms and disproportionately impacts people living with HIV disease. The Mpox outbreak in 2022 afforded an opportunity to explore how learners adapted to emergent circumstances. We conducted a quality improvement project using a qualitative focus group exploring how medical residents demonstrated characteristics of a Master Adaptive Learner, including caring for a stigmatized LGBTQIA+ population and people living with HIV. Five medical residents agreed to participate and showed evidence of adaptive expertise on the continuum. Development of healthcare learners who continuously reflect and adapt within complex, ever-changing healthcare environments is critical.

Information

Type
Brief Report
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Association for Clinical and Translational Science
Figure 0

Table 1. Results of coding using the Master Adaptive Learner (MAL) framework[2]

Figure 1

Figure 1. Frequency of counts in coding using Master Adaptive Learner (MAL) Framework [2]. C = characteristics; S = skills; AEC = advanced expertise continuum.