Trajectories of Mental Distress and Resilience During the COVID-19 Pandemic Among Healthcare Workers

<b>Background/Objectives</b>: The recent COVID-19 pandemic posed a significant psychological challenge for healthcare workers. Resilience and the extent of psychological stress varied across professional groups and individual circumstances. This study aims to longitudinally capture the trajectories of psychological stress and resilience among medical personnel during the pandemic and identify various contributing factors. <b>Methods</b>: Over a period of three years, healthcare workers from five locations (Bonn, Cologne, Ulm, Erlangen, and Dresden) were surveyed regarding their psychological stress (PHQ-4) and other aspects of mental health. Data were collected at five different points during the pandemic. Using Growth Mixture Modeling (GMM), various stress trajectories during the crisis were modeled without initial adjustment for covariates to allow for an unbiased identification of latent classes. Differences in demographic and occupational factors (e.g., age, gender, profession) were analyzed across the identified trajectory groups in subsequent steps. <b>Results</b>: The application of GMM revealed three distinct profiles of psychological stress and resilience among the respondents, largely consistent with the literature. The largest group was the 'resilience' group (81%), followed by the 'recovery' (10%) and 'delayed' groups (9%). Group membership was consistent with self-reported trajectories over the course of the pandemic. It was not possible to predict individual trajectories based on the results of a short resilience questionnaire (RS-5). <b>Conclusions</b>: The COVID-19 pandemic had multiple psychological impacts on healthcare workers, manifesting in clearly differentiated group trajectories of distress over time. While a majority of respondents in this sample exhibited a stable trajectory with low distress, other groups showed varying stress responses over time. These findings highlight the necessity of longitudinal approaches to understand the complex interplay of stressors and coping mechanisms during prolonged crises.

Authors

Institutions

Publication Details

Journal
Healthcare
Published
2025-03-06
DOI
https://doi.org/10.3390/healthcare13050574
Citations
1
Primary Topic
Resilience and Mental Health
Type
article
Field-Weighted Citation Impact
2.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trajectories of Mental Distress and Resilience During the COVID-19 Pandemic Among Healthcare Workers

Katja Maus, Franziska Geiser, Lucia Jerg‐Bretzke, Eva Morawa et al.
1 citations
Healthcare
Resilience and Mental Health
2.31
article

Trajectories of Mental Distress and Resilience During the COVID-19 Pandemic Among Healthcare Workers

Katja Maus, Franziska Geiser, Lucia Jerg‐Bretzke, Eva Morawa, Kerstin Weidner, Andreas Baranowski, Petra Beschoner, Lukas Radbruch, Yeşim Erim, Simone C. Tüttenberg, Anna C. Culmann, Julia-K. Matthias, Cornelia Richter, Rebecca M. Blank, Christian Albus
article en
1 citations

Abstract

<b>Background/Objectives</b>: The recent COVID-19 pandemic posed a significant psychological challenge for healthcare workers. Resilience and the extent of psychological stress varied across professional groups and individual circumstances. This study aims to longitudinally capture the trajectories of psychological stress and resilience among medical personnel during the pandemic and identify various contributing factors. <b>Methods</b>: Over a period of three years, healthcare workers from five locations (Bonn, Cologne, Ulm, Erlangen, and Dresden) were surveyed regarding their psychological stress (PHQ-4) and other aspects of mental health. Data were collected at five different points during the pandemic. Using Growth Mixture Modeling (GMM), various stress trajectories during the crisis were modeled without initial adjustment for covariates to allow for an unbiased identification of latent classes. Differences in demographic and occupational factors (e.g., age, gender, profession) were analyzed across the identified trajectory groups in subsequent steps. <b>Results</b>: The application of GMM revealed three distinct profiles of psychological stress and resilience among the respondents, largely consistent with the literature. The largest group was the 'resilience' group (81%), followed by the 'recovery' (10%) and 'delayed' groups (9%). Group membership was consistent with self-reported trajectories over the course of the pandemic. It was not possible to predict individual trajectories based on the results of a short resilience questionnaire (RS-5). <b>Conclusions</b>: The COVID-19 pandemic had multiple psychological impacts on healthcare workers, manifesting in clearly differentiated group trajectories of distress over time. While a majority of respondents in this sample exhibited a stable trajectory with low distress, other groups showed varying stress responses over time. These findings highlight the necessity of longitudinal approaches to understand the complex interplay of stressors and coping mechanisms during prolonged crises.

HealthcareVol. 13(5)
University of Bonn (DE), University Hospital Bonn (DE), Universitätsklinikum Erlangen (DE), Klinik und Poliklinik für Psychosomatik und Psychotherapie (DE), Klinik und Poliklinik für Psychosomatische Medizin und Psychotherapie (DE), Klinik und Poliklinik für Psychosomatische Medizin und Psychotherapie (DE), University Hospital Ulm (DE), Klinik und Poliklinik für Psychotherapie und Psychosomatik (DE)
Deutsche Forschungsgemeinschaft, Rheinische Friedrich-Wilhelms-Universität Bonn
Good health and well-being
Openalex Percentile: Top 17%
Resilience and Mental Health
2.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.