Front. Organ. Psychol. Frontiers in Organizational Psychology Front. Organ. Psychol. 2813-771X Frontiers Media S.A. 10.3389/forgp.2026.1634851 Original Research Effort-reward imbalance influences perceived patient safety during the COVID-19 pandemic, mediated by work-family conflict: results from the longitudinal VOICE study Jerg-Bretzke Lucia 1 † Writing – original draft Writing – review & editing Platzek Paul 2 * † Writing – review & editing Writing – original draft Jarczok Marc N. 1 Writing – review & editing Writing – original draft Kempf Maximilian 1 Writing – original draft Writing – review & editing Weimer Katja 1 Writing – review & editing Writing – original draft Hirning Christian 1 Writing – review & editing Writing – original draft Kern Sarah 3 Writing – review & editing Writing – original draft Geiser Franziska 4 Writing – original draft Writing – review & editing Baranowski Andreas 4 Writing – original draft Writing – review & editing Erim Yesim 5 Writing – review & editing Writing – original draft Morawa Eva 5 Writing – review & editing Writing – original draft Weidner Kerstin 6 Writing – review & editing Writing – original draft Steudte-Schmiedgen Susann 6 Writing – original draft Writing – review & editing Albus Christian 7 Writing – review & editing Writing – original draft Beschoner Petra 1 Writing – original draft Writing – review & editing Department of Psychosomatic Medicine and Psychotherapy, Ulm University Medical Center, Ulm, Germany Clinic for Neuroradiology, University Hospital Rechts der Isar, TUM University Munich, Munich, Germany Clinic for Psychosomatic and Psychotherapy, Hospital Christophsbad Göppingen, Göppingen, Germany Clinic for Psychosomatic Medicine and Psychotherapy, University Hospital Bonn, University Bonn, Bonn, Germany Department of Psychosomatic Medicine and Psychotherapy, University Hospital of Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany Department of Psychosomatics and Psychotherapy, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany Correspondence: Paul Platzek, paul.platzek@tum.de

These authors have contributed equally to this work and share first authorship

 09 03 2026 2026 4 1634851 11 06 2025 25 01 2026 26 01 2026 Copyright © 2026 Jerg-Bretzke, Platzek, Jarczok, Kempf, Weimer, Hirning, Kern, Geiser, Baranowski, Erim, Morawa, Weidner, Steudte-Schmiedgen, Albus and Beschoner. 2026 Jerg-Bretzke, Platzek, Jarczok, Kempf, Weimer, Hirning, Kern, Geiser, Baranowski, Erim, Morawa, Weidner, Steudte-Schmiedgen, Albus and Beschoner https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Background

The COVID-19 pandemic increased psychosocial burden on healthcare workers, especially related to work-family conflict, leading to significant health consequences. This longitudinal study aimed to investigate the impact of work-family conflict on occupational stress and perceived patient safety among healthcare workers during the pandemic.

 Methods

This multicenter longitudinal study included 1036 healthcare workers at two measurement time points: T1 (spring 2020) and T2 (autumn 2020). We used established questionnaires to assess work-family conflict (WFC), effort-reward imbalance (ERI), and perceived patient safety.

 Results

Significant increases were observed in work-family conflict, effort-reward imbalance, and family-work conflict from T1 to T2. Effort-reward imbalance was significantly associated with perceived patient safety, with work-family conflict partially mediating this relationship.

 Conclusions

Interventions are necessary to improve the mental health of healthcare workers, including strategies to rebalance work-family conflict, especially during a pandemic.

 COVID-19 effort-reward imbalance occupational stress patient safety work-family conflict Bundesministerium für Bildung und Forschung 10.13039/501100002347 The author(s) declared that financial support was received for this work and/or its publication. The online study VOICE was part of the BMBF-funded egePan research project (funding code: 01KX2021) under the National Network Pandemic Management of University Hospitals (NUM), lasting for 2 years. section-at-acceptance Employee Well-being and Health Background

The SARS-CoV-2 outbreak in 2019 had a significant impact on the social life and mental health status of the population (Bäuerle et al., 2020; Petzold et al., 2020). It is already known from previous epidemics, such as the SARS outbreak 2003, the H1N1 pandemic 2009 or the Ebola outbreak in 2014, that these are accompanied by high distress among medical staff (Brooks et al., 2018; Mulfinger et al., 2020; Raven et al., 2018; El Gaafary et al., 2010; Chong et al., 2004). Many studies demonstrated this aspect also in the COVID-19 pandemic (Mulfinger et al., 2020; Bohlken et al., 2020). Outside the health sector, the COVID-19 pandemic had a huge impact worldwide, as most countries' economies ground to a halt, work routines inevitably changed and employment became uncertain (Apouey et al., 2020; Charles et al., 2021; Ceri and Cicek, 2021; Galanti et al., 2021; Sandoval-Reyes et al., 2021; Garbóczy et al., 2021). Extensive meta-analyses and reviews indicated a high prevalence of occupational stress and mental health problems among health care workers (HCWs) treating COVID-19 patients. The pooled prevalence of anxiety and depression in HCWs was estimated to be 23.2–32% and 22.8–28%, respectively (Lai J. et al., 2020; Luo et al., 2020; Pappa et al., 2020). Therefore, mental health should be assigned a high priority, especially since studies have shown that it can have a significant impact on the quality of patient care (Wallace et al., 2009). With respect to the COVID-19 pandemic, the VOICE working group has already published results from a first survey in Germany showing that physicians, nurses and medical technical assistants (MTAs) had higher depression scores than the normal population before the pandemic, shown by (Morawa et al. 2021). A multiple regression analysis by Morawa et al. indicated that insufficient recreation in leisure time, increased alcohol consumption and lower trust in colleagues in difficult situations at work were statistically associated with increased depression symptoms. Increased fear of contracting COVID-19, on the other hand, was positively related to anxiety symptoms. Considering the working conditions of medical staff, HCWs were exposed to an increased workload, a change of tasks and considerable occupational stress. At the same time, there was a shortage of contactor equipment, so their actions were strained. Also, some employees had to decide on further therapy in triage situations. In addition, there was the risk of infection and the fear of infecting relatives. This fear was realistic, as other studies reported that more than 30,000 Chinese doctors had already been reported infected with SARS-CoV-2 in March 2020, of whom more than 30 died from the infection, especially when there has been insufficient protective equipment (Marazziti and Stahl, 2020; Unützer et al., 2020; Adhanom Ghebreyesus, 2020). As most of the studies considering the COVID-19 pandemic were cross-sectional or retrospective study designs, there is a lack of longitudinal studies focusing on the development during consecutive pandemic waves (Magnavita et al., 2020, 2021b; Delamarre et al., 2022). In Italian and French HCWs, longitudinal comparisons during the pandemic (spring 2020 to spring 2021) showed changes in workload, isolation at work and in social life, lack of time for physical activity or meditation and compassion fatigue in physicians, nursing professionals and paramedics (Delamarre et al., 2022; Magnavita et al., 2021a). The balance between work and family is a challenge that affects all occupational groups, but especially those with a high workload, shift work and irregular working hours, such as healthcare workers (Limbrecht-Ecklundt et al., 2015). In relation to this problem, social science research is mainly concerned with the two social roles of family work and gainful employment. Work-family conflict, as used in this study, occurs when the different roles interfere with each other in the performance of their respective tasks (Katharina, 2011). The relationship between work and family and associated with it the inter-role conflict also came into increased focus during the COVID-19 pandemic as school and day-care closures are likely to increase the double burden, presumably affecting primarily female employees (Collins et al., 2021). (Jerg-Bretzke et al. 2020, 2021) showed in two studies, independently of the pandemic, a negative correlation between Work-Family conflict (WFC) and job satisfaction. Another study also found that WFC correlates with workload and related health problems and that WFC is a risk factor for burnout (Jerg-Bretzke et al., 2020, 2021). Because the conflict between work and family is elementary for HCWs, we used a model, the Effort-Reward Imbalance (ERI) model by (Siegrist 2002, 2010, 1996) and (Siegrist et al. 2004), to highlight and analyze this conflict (Netemeyer et al., 1996). The Effort-Reward Imbalance model by (Siegrist 2002, 2010, 1996) and (Siegrist et al. 2004) which describes the development of psychosocial occupational stress due to an imbalance between work effort (e.g., requirements, obligations) and reward received (e.g., wages, recognition, job security) at work. If there is an ERI to the disadvantage of reward (i.e., gratification crisis), there is an empirically well-documented risk of developing psychological and physical stress symptoms and somatic disorders such as cardiovascular diseases (Siegrist, 2010; Siegrist et al., 2004; Eddy et al., 2017; Weigl et al., 2015; Bellingrath et al., 2008). Other studies demonstrated that increased effort alone in HCWs is also associated with increased depressive symptoms (Magnavita et al., 2020; Zhang et al., 2021). Even before the pandemic, it could be shown that occupational groups in the social sector such as police officers, teachers and psychiatrists, have a significantly increased risk of ERI. Particularly high prevalence of ERI are found among medical staff (Janzen et al., 2007; Violanti et al., 2018; De Sousa et al., 2019; Braun et al., 2010; Vu-Eickmann et al., 2018; Diekmann et al., 2020; Hinz et al., 2016). In addition, absenteeism or turnover in the workplace in HCW is attributed to work-life balance or Work-Family conflicts (Webster et al., 2009; Josephson et al., 2008; Schreuder et al., 2010). Previous studies have shown that increased ERI as well as increased WFC can lead to health problems among HCWs. We conducted in this study a longitudinal comparison, for the first time to the best of our knowledge in Germany, and a mediation analysis examining the WFC in detail with regard to mediating perceived patient safety and increased ERI. It is hypothesized that WFC, ERI, and work-related conditions significantly change from the first to the second wave of the COVID-19 pandemic among HCWs and differ between occupational groups, and that higher ERI is negatively associated with perceived patient safety.

The two main questions this study aimed to answer are:

To what extent do WFC, ERI, and specific working conditions change from the first to the second wave of the COVID-19 pandemic in Germany among HCW and are there differences between occupational groups?

What influence does the ERI of HCWs have on perceived patient safety and is this relationship mediated by WFC?

 Methods Statement of ethics/statement artificial intelligence

The listed study was approved by the Ethics Committee of the Medical Faculty of the Friedrich-Alexander University Erlangen-Nürnberg (FAU) and registered at ClinicalTrials, DRKS-ID: DRKS00021268. All study participants consented online. This manuscript was prepared with the assistance of ChatGPT (version: GPT-4) to improve clarity and coherence. The AI was used to assist with language editing and refining specific sections of the text.

 Data collection

The online survey was conducted over 4 weeks in June 2020 (T1) and in December 2020 (T2) by the psychosomatic departments of the university hospitals of Erlangen, Bonn, Ulm, Cologne, and Dresden. The survey/questionnaire was developed by the VOICE working group during the pandemic and has already resulted in several publications (Morawa et al., 2021; Schmuck et al., 2021; Schug et al., 2021, 2022). The participation link was provided via online platforms or mailing lists. This collaborative project was supported by the Federal Ministry of Education and Research (BMBF) as part of the “egePan Unimed” initiative within the National University Medicine Network (NUM) during the second survey wave. egePan Unimed is a regional project in cooperation with the respective university hospitals for optimal pandemic management. Other hospitals and various professional societies and online platforms advertised participation in the survey. Additional surveys were conducted at different stages of the pandemic in the framework of the VOICE cooperation and will be reported in further publications. The online-survey (77 items) was presented using two academic online survey webpages: Unipark (http://www.unipark.com) and SoSci Survey (http://www.soscisurvey.de). Answering the questionnaire took a total of about 20 min. Inclusion criteria were a minimum age of 18 years, occupation in the health care sector, place of residence or work in Germany and sufficient German language skills. In addition to the variables listed below, other variables were analyzed and published in other studies of the VOICE collaboration (Morawa et al., 2021; Jerg-Bretzke et al., 2020, 2021; Schmuck et al., 2021; Schug et al., 2021, 2022).

 Measures Sociodemographics

The online questionnaire included the following sociodemographic data: age, gender, living alone (or not), children (in household, not in household or no children at all) and migrant background. Occupational characteristics were work environment, profession, years of work experience and employment status.

 Effort-reward imbalance

To assess psychosocial work stress, we used the ERI questionnaire by (Siegrist 2002), (Siegrist et al. 2004), and (Rödel et al. 2004). The ERI measures occupational effort and the consecutive reward received and relates them in a subsequent step. We used three items for occupational effort and a total of seven items for the consecutive reward received. To obtain the ERI-ratios we had to multiply the effort by a correction factor first and divide the effort and the reward then. Answers could be given with a Likert scale. A gratification crisis was present when the ERI-ratios were > 1. The internal consistency of the scales is satisfactory with Cronbachs α (effort) = 0.77 and α (reward) = 0.82 by (Ni et al. 2023). These results can be compared to the sample collected here with α (effort) = 0.74 and α (reward) = 0.72 replicated.

 Work-family/family-work conflict

The Work-Family Conflict Scale (WFC) and the Family-Work Conflict Scale (FWC; Netemeyer et al., 1996) were used in this study to determine the conflict between work and family. These scales were developed by (Netemeyer et al. 1996) and contain a total of four items in the version used here. Answers are given on a five-point Likert scale. The first two items (1–2) refer to the influence that the job has on the family and the other two (3–4) refer to the opposite effect (influence of the family regarding the job). Sum scores are formed separately for the WFC and the FWC. High values indicate an increased inter-role conflict.

 Working conditions, potential problems of the COVID-19 pandemic and especially perceived patient safety

To get a more detailed insight into the “working conditions during the pandemic,” five questions were developed by the VOICE working group. These could then be answered using a Likert scale consisting of 5 items, starting from 0 (“strongly disagree”) to 5 (“strongly agree”). This Likert scale was also used for the survey scale “Potential Problems in the COVID-19 Pandemic.” This survey scale included a total of 15 questions. These items were developed based on the work of (Matsuishi et al. 2012) who examined psychological stress among healthcare workers during the 2009 H1N1 influenza pandemic. They asked the participants 19 stress-related questions and conducted a factor analysis on their responses. We used the results to formulate items for our survey in the most evidence-based manner possible. The working conditions and three selected questions of “Potential Problems in the COVID-19 Pandemic” including the perceived patient safety are listed below (Table 1).

Questionnaire “working conditions” and selected questions from “potential problems in the COVID-19 pandemic.”

Item no. Working conditions Item letter Potential problems in the COVID-19 pandemic
1. There is sufficient protective clothing for the staff. A. I was stressed by the increased workload.
2. I work more than before the COVID-19 pandemic. B. I had problems to sleep.
3. There are sufficient staff for the current workload. C. I felt that patient safety suffered from the increased workload.
4. I can recover sufficiently in my free time.
5. I can rely on my colleagues when things get difficult at work.
Statistics

The statistical analysis was performed with the statistical program SPSS (version 25). Normality of the data was assessed through visual inspection of Q–Q plots and histograms. As the variables showed no relevant deviations from normality, parametric statistical tests were applied. In the context of longitudinal mean comparisons, t-tests for dependent samples were used. To detect gender differences and differences between occupational groups (physicians, nurses, MTAs, psychologists), repeated-measures ANOVAs were made, with occupational groups as the between-subjects factor. Post-hoc tests were calculated according to LSD and Tamhane-T2. Given that the repeated-measures factors involved only two time points, the assumption of sphericity was inherently met. Correlations were calculated according to Pearson and Spearman. Mediation analyses were conducted using Hayes' process macro for SPSS to examine the effects of WFC on perceived patient safety in relation to the ERI. The significance level was set at p = 0.05. Effect sizes were calculated according to Cohen (0.1–0.3 = mild effect; 0.3–0.5 = moderate effect; >0.5 = strong effect) and partial Eta-Square for the ANOVA. The items were evaluated if they were answered completely. Missing responses were not considered. This results in a different number of participants for the respective items. The WFC/FWC scale as well as the ERI scale, as well-established and validated instruments with consistently high reliability in prior research, was deemed appropriate for use in this study, and the study-specific scales were evaluated for conceptual coherence during their development, supporting their adequacy for our analyses.

 Results Sociodemographics

A total of 1,036 HCWs participated at both measurement time points of this study (T1, T2). Participants were divided into four professional groups. There were 248 physicians (24.1%), 223 nurse practitioners (21.7%), 137 medical technical assistants and medical assistants (13.3%) and 66 psychologists (6.4%) who participated in the questionnaire both at T1 and T2. Another n = 354 (34.2%) of the total sample belong to the HCWs other than the cited groups (e.g., physiotherapists, social workers, pastoral workers, secretarial stuff). As they are part of the healthcare team in hospitals, they were included when the total sample was analyzed. However, due to small numbers, they were not included in comparisons of occupational groups.

Nearly one-third (29%) of the respondents in the total sample were between 51 and 60 years old at the time of the first interview, 21.3% were between 18 and 30 years old, 23.5% were between 31 and 40 years old and 20.9% were between 41 and 50 years old. 5.2% of the respondents were older than 60 years old. In terms of gender 816 female (78.9%) and 218 male (21%) study participants took part. A total of eight individuals did not indicate an occupation (0.8%) and two individuals did not indicate a gender.

 Longitudinal comparisons Effort-reward imbalance

Overall, the ERI-ratio, consisting of a ratio of the sum values for effort and reward, was finally calculated for n = 595 study participants who took part in both measurement time points. The sample size is smaller than the other items because the ERI was not collected at all sites. The mean values of the ERI-ratios of the total sample and the respective occupational groups at T1 and T2 are shown in Table 2. This descriptive analysis shows that medical staff experienced a high imbalance between effort and reward at both measurement time points and that consecutive gratification crises were already present at the beginning of the pandemic. Medical staff experienced a high imbalance between effort and reward already during the first wave of the pandemic, which had increased significantly (p < 0.05) in all occupational groups (except psychologists) in the second wave. Effect sizes are small for all significances. To additionally investigate to what extent the occupational groups differed from each other in the ERI-model, a post-hoc test (Tamhane-T2) was performed. In this regard, nurses showed higher ERI ratios in the post-hoc test than physicians (mean difference = −0.246; p < 0.001) and psychologists (mean difference = 0.376; p < 0.001) and MTAs also showed higher imbalances than psychologists (mean difference = 0.268; p = 0.004; Table 2, Figure 1).

Longitudinal comparison of the ERI-ratios between T1 and T2 of the total sample and selected occupational groups (t-tests).

Alln = 595 Physiciansn = 143 Nursing professionalsn = 128 MTA/MAn = 82 Psychologistsn = 46
ERI-ratios
Mean
T1 1.081 (0.482) 1.078 (0.458) 1.117 (0.474) 1.115 (0.537) 0.936 (0.419)
T2 1.220 (0.562) 1.129 (0.502) 1.462 (0.602) 1.307 (0.604) 0.950 (0.370)
Longitudinal comparison p < 0.001* p = 0.001* p < 0.001* p < 0.001* p = 0.794

*Significant.

Graphic design of the longitudinal group comparison regarding ERI. ERI, Effort-Reward Imbalance; MTA, medical technical assistant; MA, medical assistant; *, significance level; 1, measuring time 1 (spring 2020); 2, measuring time 2 (autumn 2020). *p < 0.05; **p < 0.01; ***p < 0.001.

Line chart comparing ERI values for four professions: physicians (blue), nursing professionals (red), MTA/MA (green), and psychologists (orange). Nursing professionals show the highest increase from ERI 1 to ERI 2, followed by MTA/MA and physicians, while psychologists remain nearly constant. Error bars are present for each data point. Work family conflict/family work conflict

Overall, a longitudinal comparison for WFC and FWC could be calculated for n = 971 study participants.

WFC: A significant increase in the longitudinal comparison of the WFC in the total sample as well as in the subgroups of physicians, nursing professionals and psychologists could be determined (p < 0.05; Table 3, Figure 2).

Longitudinal comparison of the WFC between T1 and T2 of the total sample and the selected occupational groups (t-tests).

Alln = 971 Physiciansn = 241 Nursing professionalsn = 212 MTA/MAn = 127 Psychologistsn = 65
WFC
Mean
T1 5.117 (2.430) 6.174 (2.433) 5.363 (2.347) 4.670 (2.417) 4.570 (2.135)
T2 5.582 (2.382) 6.577 (2.288) 6.146 (2.363) 5.040 (2.358) 5.108 (2.107)
Longitudinal comparison p < 0.001* p = 0.003* p < 0.001* p = 0.057 p = 0.036

*Significant.

Graphic design of the longitudinal group comparison regarding WFC. WFC, work-family conflict; MTA, medical technical assistant; *, significance level; 1, measuring time 1 (spring 2020); 2, measuring time 2 (autumn 2020). *p < 0.05; **p < 0.01; ***p < 0.001.

Line chart comparing four professional groups—physicians, nursing professionals, MTA, and psychologists—showing mean WFC scores at two points. Physicians consistently have the highest scores, psychologists and MTA the lowest. Error bars indicate variability.

FWC: A significant difference in FWC in the longitudinal comparison could be found here for the total sample and when looking at the individual occupational groups only for the nursing professionals between T1 and T2 (p < 0.05; Table 4, Figure 3). Cohen's effect sizes were small. A difference between occupational groups could not be detected for both, WFC and FWC. The individual occupational groups can be seen in Tables 3, 4 as well as in Figures 2, 3.

Longitudinal comparison of the FWC between T1 and T2 of the total sample and the selected occupational groups (t-tests).

Alln = 971 Physiciansn = 241 Nursing professionalsn = 212 MTA/MAn = 127 Psychologists n = 65
WFC
Mean
T1 4.162 (2.159) 4.813 (2.330) 4.212 (2.032) 4.000 (2.152) 3.908 (2.234)
T2 4.400 (2.058) 5.017 (2.471) 4.764 (2.042) 4.197 (2.097) 3.785 (1.700)
Longitudinal comparison p < 0.001* p = 0.108 p < 0.001* p = 0.301 p = 0.585

*Significant.

Graphic design of the longitudinal group comparison regarding FWC. WFC, family-work conflict; MTA, medical technical assistant; *, significance level; 1, measuring time 1 (spring 2020); 2, measuring time 2 (autumn 2020). *p < 0.05; **p < 0.01; ***p < 0.001.

Line chart comparing four professional groups—physicians, nursing professionals, MTA, and psychologists—on an FWC scale at two time points, showing mean values with error bars for each group. Working conditions

Looking at the questionnaire (question nrs. 2–4, total sample n = 679) dealing with working conditions, it became clear that all of the occupational groups studied, with the exception of psychologists, indicated a worsening in conditions at time T2. These included workload during the pandemic, sufficient staff to handle the workload, and sufficient time for rest and recovery. The only exception reported was a significantly improved supply of personal protective clothing, with psychologists again being an exception. Individual occupational group comparisons of the respective questions revealed that nurses were significantly more satisfied with the provision of protective clothing than psychologists (mean difference = −0.420; p = 0.004*), for which no difference was found between the two pandemic waves.

 Potential problems of the COVID-19 pandemic

The total sample (n = 983) as well as the individual occupational groups reported a significant increase in stress by the reported workload in the longitudinal comparison (question A). Regarding the sleep problems suffered (question B), there was also a significant increase in the total sample as well as in the individual occupational groups. Particularly physicians, nurses, medical technical assistants felt that patient safety increasingly suffered during the pandemic. Looking at perceived patient safety (question C) the post-hoc test also found significant differences between the occupational groups. Physicians showed a significant difference in the longitudinal comparison compared to nurses (mean difference = −0.44; p < 0.001) and compared to psychologists (mean difference = 0.59; p < 0.001). The nursing professionals showed a significant difference in the post-hoc test compared to the medical technical assistants and medical assistants (mean difference = 0.40; p < 0.001) and compared to the psychologists (mean difference = 1.03; p < 0.001). The medical technical assistants also still showed a significant difference in the longitudinal comparison to the psychologists (mean difference = 0.63; p < 001; Table 5).

Longitudinal comparison of the questions regarding “working conditions” (1–5) and selected questions from the survey item “potential problems in the COVID-19 pandemic” (A–C; t-tests).

Questions All n = 679 Physicians n = 162 Nursing professionals n = 143 MTA/MA n = 95 Psychologists n = 58
1. Protective clothing
Mean
T1 3.45 (1.303) 3.35 (1.278) 3.20 (1.269) 3.28 (1.350) 3.93 (1.057)
T2 4.14 (1.024) 4.23 (0.992) 4.01 (1.045) 4.18 (1.000) 4.12 (1.077)
Longitudinal comparison p < 0.001* p < 0.001* p < 0.001* p < 0.001* p = 0.345
2. More work
Mean
T1 2.53 (1.301) 2.52 (1.247) 2.37 (1.214) 2.38 (1.273) 2.71 (1.338)
T2 3.05 (1.354) 3.11 (1.347) 3.13 (1.358) 3.12 (1.304) 2.98 (1.291)
Longitudinal comparison p < 0.001* p < 0.001* p < 0.001* p < 0.001* p = 0.214
3. Sufficient staff
Mean
T1 3.41 (1.304) 3.59 (1.279) 3.20 (1.323) 3.57 (1.252) 3.53 (1.260)
T2 2.67 (1.289) 2.58 (1.194) 2.20 (1.308) 2.75 (1.352) 3.07 (1.153)
Longitudinal comparison p < 0.001* p < 0.001** p < 0.001** p < 0.001* p = 0.024*
4. Sufficient recovery
Mean
T1 3.06 (1.262) 2.86 (1.265) 2.94 (1.246) 3.18 (1.345) 3.22 (1.060)
T2 2.67 (1.169) 2.48 (1.116) 2.49 (1.137) 2.74 (1.197) 3.10 (1.119)
Longitudinal comparison p < 0.001* p < 0.001* p < 0.001* p < 0.001* p = 0.447
5. Rely on colleagues
Mean
T1 3.93 (1.069) 4.04 (0.912) 3.98 (1.078) 3.89 (1.134) 4.03 (1.059)
T2 2.89 (1.071) 3.95 (1.045) 3.92 (1.132) 3.78 (1.011) 4.24 (1.127)
Longitudinal comparison p = 0.374 p = 0.184 p = 0.508 p = 0.294 p = 0.051
A. Stress due to increase in workload n = 983 n =242 n = 216 n = 130 n = 66
Mean
T1 2.39 (1.228) 2.33 (1.262) 2.48 (1.193) 2.28 (1.196) 2.36 (1.132)
T2 3.01 (1.268) 3.02 (1.249) 3.39 (1.264) 3.05 (1.334) 2.88 (1.196)
Longitudinal comparison p < 0.001* p < 0.001* p < 0.001** p < 0.001** p = 0.003*
B. Sleeping problems
Mean
T1 2.40 (1.349) 2.34 (1.342) 2.47 (1.364) 2.55 (1.474) 2.21 (1.183)
T2 2.63 (1.340) 2.57 (1.277) 2.78 (1.353) 2.79 (1.396) 2.15 (1.243)
Longitudinal comparison p < 0.001* p = 0.004* p < 0.001* p = 0.038 p = 0.716
C. Perceived patient safety
Mean
T1 1.98 (1.126) 2.05 (1.150) 2.29 (1.181) 1.94 (1.160) 1.62 (0.924)
T2 2.56 (1.333) 2.55 (1.269) 3.17 (1.355) 2.73 (1.346) 1.79 (0.985)
Longitudinal comparison p < 0.001* p < 0.001* p < 0.001* p < 0.001* p = 0.257

*Significant.

 Mediation analysis

A mediation analysis was calculated at T1 and T2 to test whether the ERI predicted the perceived suffering of patient safety and whether the direct pathway was consecutively mediated by the WFC.

Mediation analysis at T1

An effect of the ERI on perceived patient safety was found (B = 0.9382, p < 0.001). Consequently, higher ERI ratios were associated with reduced subjective patient safety. After the mediator (=WFC) was included in the model, the ERI significantly predicted the mediator (B = 2.2886, p < 0.001) which in turn significantly predicted perceived patient safety, B = 0.1061, p < 0.001. Thus, we were able to conclude that the relationship between ERI and subjective suffering of patient safety was partially mediated by WFC, indirect effect (ab = 0.2427, 95% CI [0.1521, 0.3371]; Figure 4).

Mediation analysis at T1 involving the factors WFC, ERI, and perceived patient safety. ERI, effort-reward imbalance; WFC, work-family conflict. *p < 0.05; **p < 0.01; ***p < 0.001.

Diagram featuring a blue triangle with labeled arrows representing relationships among ERI, WFC, and perceived patient safety; coefficients are displayed on arrows, indicating strength and significance of connections between variables. Mediation analysis at T2

A further mediation analysis was calculated to analyze whether the ERI predicted suffering of perceived patient safety also at T2 and if the direct path was again mediated by the WFC. An effect of ERI on patient safety was also found (B = 1.1621, p < 0.001), higher ERI ratios were associated with reduced subjective patient safety. After the mediator (=WFC) was again included in the model, the ERI significantly predicted the mediator (B = 2.1424, p < 0.001) which in turn significantly predicted the perceived patient safety (B = 0.1188, p < 0.001).

In the final step, we were again able to demonstrate that the relationship between ERI and perceived patient safety was at least partially mediated by the WFC again, indirect effect (ab = 0.2545, 95% CI [0.1551, 0.3514]; Figure 5).

Mediation analysis at T2 involving the factors WFC, ERI, and perceived patient safety. ERI, effort-reward imbalance; WFC, work-family conflict. *p < 0.05; **p < 0.01; ***p < 0.001.

Conceptual diagram featuring a blue triangle in the center with labeled relationships: ERI links to WFC with a coefficient of two point one four two four, WFC links to perceived patient safety with zero point one one eight eight, and ERI links directly to perceived patient safety with coefficient C equal to one point one six two one and C’ equal to zero point nine zero seven five. Discussion Effort-reward imbalance

A significant increase in ERI-ratios was found between the first and second pandemic wave for all occupational groups, except psychologists. In addition to the change over time, a significant difference was also found between the occupational groups, showing that nurses were particularly affected by an exceptional large increase in psychosocial workload. This finding is underlined by an Italian prospective study regarding intensive care employees, in which a longitudinal comparison of ERI-ratios between the first and second corona pandemic waves was also performed. These authors described an increase in ERI-ratios > 1 from 77 to 83%. However, in contrast to our results, this increase was not significant and no occupational group comparison was performed (Magnavita et al., 2021b). (Delamarre et al. 2022) also described a worsening of the ERI for medical staff and paramedics between the first and second lockdown, matching our measurement time points, with a worsening of ERI scores. However, no comparison of occupational groups was made in this study either (Delamarre et al., 2022). An increase in stress during the pandemic does not only affect medical staff (Charles et al., 2021; Sandoval-Reyes et al., 2021; Li et al., 2022), but was also observed in non-medical occupational groups, like college-students or remote workers in general and police officers. This proves, that this is also a problem of the present time and does not only affect medical staff (Charles et al., 2021; Sandoval-Reyes et al., 2021; Li et al., 2022).

As another consideration, a Greek study found a significant correlation between sleep problems and high ERI-ratios in HCWs during the COVID-19 pandemic. As mentioned, we observed significant increase in both ERI-ratios and sleep problems. However, we have not carried out any investigation to this effect ourselves (Tzenetidis et al., 2021).

We could show that nurses have a significantly higher ERI imbalance than other occupational groups, this aspect could be related to the higher prevalence rate of depression and anxiety in nurses compared to other health care workers reported in the literature (Pappa et al., 2020). Studies have shown that even before the pandemic, an increased ERI in nurses leads to more days off work and increased turnover in the workplace. Consequently, the intensification of this conflict should be taken seriously (Webster et al., 2009; Schreuder et al., 2010; Stordeur and D'Hoore, 2007; Gräske et al., 2023). However, these counteractions are complicated by the fact that already before the pandemic there was a shortage of skilled HCW, especially nurses, in Germany. The higher workload in the pandemic led to low-skilled temporary workers being hired most of whom were on temporary contracts. Interestingly, these temporary workers showed higher levels of occupational stress, presumably due to the abrupt assumption of responsibility (Pappa et al., 2020).

 Work family and family work conflict

Physicians and nursing professionals showed a significant increase of the conflicting influence of family on working life (WFC) from the first to the second wave of the pandemic. For FWC, only a significant increase was observed among nurses. A significant occupational group difference could not be found for both the WFC and the FWC. The psychosocial relevance of these conflicts is described in the literature with an impairment of mental health, such as an increase in burnout symptoms and depression (Zhou et al., 2020; Zhang et al., 2017; Cotel et al., 2021). The WFC was also observed in other social occupational groups during the pandemic, a study among police officers in Hong-Kong showed that conflicts between family and work as well as between work and family can lead to work stress and turnover intentions, furthermore a Malaysian study of physicians also showed that increased Work-Family conflict leads to increased intention to leave the job (Li et al., 2022; Harun et al., 2022). This circumstance was already proven in a large meta-analysis before the pandemic, exemplarily for nursing staff (Yildiz et al., 2021). Before the pandemic strong reconciliation compatibility conflicts with consecutive psychological, musculoskeletal and cardiovascular impairments were evident in medical staff (Zhou et al., 2020; Berkman et al., 2015; Kim et al., 2013). In this work, we have demonstrated that these conflicts have been significantly exacerbated during the course of the pandemic. These results should urgently give rise to appropriate interventions. A general resolution of the conflict should be top priority, as a functioning social environment, such as family, has a positive influence on the subjective workload and the development of mental illnesses, shown by (Schmuck et al. 2021).

 Working conditions during the pandemic

In the second wave of the pandemic, the proportion of study participants who experienced sleep problems, observed an increase in workload, observed a lack of patient safety and rest, perceived staff to be inadequate, and observed a lack of rest had increased significantly.

In line with our findings, other studies have already shown an increase in workload and inadequate time for recovery for example through physical activity and time for meditation (Magnavita et al., 2021a,b; Delamarre et al., 2022). We were also able to show an increase in perceived sleep problems. In contrast to our results, the study by (Magnavita et al. 2020, 2021b) could not show a significant difference regarding sleep problems. However, a difference could be found regarding sleep quality, which then supports our results. The study also highlights that the time for rest was significantly reduced, which is also in line with our results. However, again, no continuative occupational group difference was conducted. This study also supported our results regarding the increase in the amount of work (Magnavita et al., 2021a,b). Studies found that excessive workload or lack of support at work significantly increased mental stress in healthcare workers (Marvaldi et al., 2021; Cabarkapa et al., 2020). This was also shown by previously published data from the VOICE study group that describes inadequate recreation in leisure time, increased alcohol consumption and lower trust in colleagues in difficult situations at work were statistically associated with increased depression symptoms. In this work, particularly a worsening in terms of inadequate rest was found (Morawa et al., 2021). This is significant because studies have shown the relationship between this increasing and persistent state of stress in medical staff has a negative consequence for the quality of patient care and patient safety (Tawfik et al., 2018; Poghosyan et al., 2010). Consequently, the subjective deterioration shown in our work is striking and could be related to the deterioration of working conditions. More recovery time could consequently provide a starting point for possible strategies to protect the mental health of healthcare workers. We observed a significant deterioration in subjectively perceived patient safety over time. This construct reflects healthcare professionals' individual assessments of safety rather than objectively measured outcomes. Perceived patient safety was negatively associated with psychosocial workload, with work–family conflict emerging as an important mediating variable at both measurement points. Although subjective, perceived patient safety is relevant because it may influence clinical behavior, decision-making, and risk awareness. Nursing professionals reported a stronger decline in perceived patient safety during the pandemic than other occupational groups, possibly because they spend more direct time with patients. Staff shortages, insufficiently trained personnel, missing protocols, and rapidly changing recommendations may further increase psychological strain, thereby negatively affecting patient safety perceptions (Wang and Tsai, 2014; Pani and Chariker, 2004; Adám et al., 2009). In addition, the fact that the WFC also influences patient safety has already been demonstrated in the literature (Wang and Tsai, 2014; Pani and Chariker, 2004; Adám et al., 2009). Furthermore, the WFC also proved to be a mediator in another study, but in this case between the associations of workload with job stress and job dissatisfaction (Sadiq, 2022).

 Possible solutions

The observed increase in effort–reward imbalance (ERI), work–family conflict (WFC), and adverse working conditions during the COVID-19 pandemic highlights the importance of organizational measures to support healthcare workers' wellbeing. Previous research suggests that interventions such as sleep hygiene, relaxation techniques, physical activity, mindfulness-based approaches, and psychological support during periods of high strain may reduce exhaustion and disruptions to family and social life and strengthen manageability and coherence (Schmuck et al., 2021; Kramer et al., 2021; Lai K. S. P. et al., 2020; Pérez-Fuentes et al., 2020). In addition, a supportive social environment and optimism have been shown to facilitate coping with pandemic-related stressors (Schug et al., 2021). Our findings indicate that psychosocial stressors such as ERI and WFC are closely linked to staff perceptions and may indirectly affect patient care. Measures addressing work–family reconciliation, including sufficient leisure and recovery time, may help reduce WFC and improve work–family balance. The relevance of rebalancing ERI is supported by interventional evidence demonstrating reduced anxiety and depressive symptoms when adequate rewards are provided (Barrech et al., 2017) while mindfulness-based and online interventions may further strengthen resilience (Lai K. S. P. et al., 2020; Pérez-Fuentes et al., 2020). Finally, the subjectively perceived deterioration of staffing conditions identified in this study points to organizational factors as potential intervention targets. Financial incentives and professional recognition have been associated with reduced absenteeism and turnover intentions (Webster et al., 2009; Josephson et al., 2008; Schreuder et al., 2010), and VOICE data indicate increased staff turnover related to ERI during the first pandemic wave (Schug et al., 2022) underscoring the need to reduce psychosocial stress to prevent further workforce shortages.

 Study design and limitations

To the best of our knowledge, this study is the first longitudinal investigation in Germany to examine four occupational groups during the COVID-19 pandemic. The longitudinal design allowed us to track changes in psychosocial occupational stress among healthcare workers across the first two pandemic waves and to identify developmental trends with potential relevance for future crises. In a second analytical step, we quantified the associations between psychosocial workload, work–family conflict, and subjectively perceived patient safety. The multicenter design and large overall sample strengthen the relevance of the findings for the German healthcare sector.

The creation of a longitudinal dataset resulted in a reduced sample size, which was further limited by the incomplete availability of certain instruments, particularly effort–reward imbalance (ERI), which was not assessed at all study sites. Nevertheless, the final sample size can still be considered substantial.

The two measurement points represent exceptional situations characterized by extreme organizational and psychosocial stress. While repeated assessments during these pandemic waves constitute a key strength of the study, the findings should be interpreted in light of this extraordinary context. Accordingly, the generalizability of the results to non-crisis conditions may be limited, although the findings provide important insights for managing future pandemics or comparable high-strain situations.

Data collection in the VOICE study was anonymous, which likely reduced response burden and social desirability bias and thereby enhanced data reliability. However, selection bias cannot be excluded. Participation may have been higher either among particularly burdened healthcare workers seeking engagement or among those with sufficient remaining resources, potentially leading to an underrepresentation of the most highly stressed individuals. In addition, lower stress levels observed at some sites may reflect existing employee support programs. Finally, as no formal a priori power analysis was conducted, potential limitations related to statistical power should be considered when interpreting the results.

 Conclusions

In our study, we closely investigated the course of psychosocial stress during the pandemic. HCWs showed a significant increase in ERI and inter-role conflicts, and a decrease in perceived patient safety. High levels of the ERI were associated with lower perceived patient safety, and this association was mediated by the WFC as an outstanding finding.

The picture that emerges from the findings of this study is primarily that support programs related to improving WFC, as well as more rewards, such as compensatory time off for rest, benefits, or even monetary rewards, could be a solution approach to the problems outlined to counteract this trend of increasing psychosocial workload, WFC, and decreasing perceived patient safety.

 Data availability statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

 Ethics statement

The studies involving humans were approved by Ethics Committee of the Faculty of Nuremberg (FAU), and registered at ClinicalTrials (DRKS-ID: DRKS00021268). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

 Author contributions

LJ-B: Writing – original draft, Writing – review & editing. PP: Writing – review & editing, Writing – original draft. MJ: Writing – review & editing, Writing – original draft. MK: Writing – original draft, Writing – review & editing. KWeim: Writing – review & editing, Writing – original draft. CH: Writing – review & editing, Writing – original draft. SK: Writing – review & editing, Writing – original draft. FG: Writing – original draft, Writing – review & editing. AB: Writing – original draft, Writing – review & editing. YE: Writing – review & editing, Writing – original draft. EM: Writing – review & editing, Writing – original draft. KWeid: Writing – review & editing, Writing – original draft. SS-S: Writing – original draft, Writing – review & editing. CA: Writing – review & editing, Writing – original draft. PB: Writing – original draft, Writing – review & editing.

 Acknowledgments

We would like to thank everyone who supported and motivated the VOICE team during the preparation of this project. Our sincere gratitude also goes to our funding partners for their valuable support.

 Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. This manuscript was prepared with the assistance of ChatGPT (version: GPT-4) to improve clarity and coherence, with the AI helping in language editing and refining specific sections of the text.

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Edited by: Sasho Stoleski, Saints Cyril and Methodius University of Skopje, North Macedonia

Reviewed by: Guilherme Liberato Da Silva, University of Vale do Taquari, Brazil

Aleksandar Racz, University of Applied Health Sciences, Croatia

ERI, Effort-Reward Imbalance; FWC, Family-Work Conflict; HCW, Health care workers; MA, Medical assistant; MTA, Medical technical assistant; T1, Measurement point 1, spring 2020; T2, Measurement point 2, autumn 2020; WFC, Work-Family Conflict.