Resilience changes and occupational resilience factors among healthcare workers during and after the COVID-19 pandemic: A 2-year prospective cohort study

Abstract

Healthcare workers (HCWs) in COVID-19 pandemic hotspots were exposed to heightened workplace stressor load. Structural occupational resilience factors could prevent work-related stressor exposure from translating into mental health problems but remain poorly understood. This study identifies resilience factors actionable at the workplace and examines the impact of prior stressor exposure early in the pandemic on the later development of depressive and general distress symptoms. We prospectively followed a convenience sample of HCWs working in Spain during the pandemic using a 3-wave online survey conducted in 2020 (wave 1, n = 2,422), 2021 (wave 2, n = 1,827), and 2022 (wave 3, n = 538). We operationalised resilience as low stressor reactivity (SR), quantified as individual deviations from the normative relation between stressors exposure and either depressive or distress symptoms. Mental health problems and stressor exposure both decreased over time, whereas stressor reactivity remained stable. Stressor exposure at baseline was inversely associated with resilience at follow-up. The structural occupational factors support from colleagues, trust in the workplace, and perceived ability to recover from stress were prospectively associated with resilience and thus identified as resilience factors. These results show that resilient responses of HCWs in times of crisis could be supported by promoting structural occupational resilience factors and mitigating cumulative stressor exposure. Future research should test this association in studies that allow causal inferences.

Keywords: Depression; Mental health; Occupational health; Social support; Stress; Trust.

Fig. 1

Number of respondents across waves. The survey was open to new respondents for each wave and the respondents could drop out at any point. This explains the differences in the observations across waves and outcomes. To calculate stressor reactivity (SR) scores, both a stressor exposure (E) score, and a mental health score, as measured by the Patient Health Questionnaire PHQ-9 (SR_dep) or the General Health Questionnaire GHQ-12 (SR_dis), were required.

Fig. 2

Changes in mental health problems (P), depression symptoms (PHQ-9), and psychological distress (GHQ-12 or PHQ-9). Exposure to stressors (E), and stressor reactivity (SR) over time in the complete-cases sample (N_{complete-cases} = 332). SR scores were computed using the 9-item Patient Health Questionnaire (PHQ-9) for depressive symptoms (SR_dep, panel A) and the 12-item General Health Questionnaire (GHQ-12) for psychological distress (SR_dis, panel B). To compute SR scores, E and P had to be available for each individual at all waves (panel A: n = 222, panel B: n = 234), hence the slight differences in E scores between panels.

Fig. 3

Association between stressor exposure (E) at baseline and stressor reactivity (SR) scores at follow-up in the full sample. Depression SR scores (SR_dep, panel A) are computed using the 9-item Patient Health Questionnaire (PHQ-9) and general distress SR scores (SR_dis, panel B) are computed using the 12-item General Health Questionnaire (GHQ-12).

Fig. 4

Association between the resilience factors in the full sample. Social support from colleagues (panel A), trust in the workplace (panel B), and the perceived ability to recover from stress (REC, panel C), and the stressor reactivity scores (SRs) computed using self-reported depressive symptoms (SR_dep, left) and symptoms of psychological distress (SR_dis, right). To show the moderation effects of baseline stressor exposure (E), we present the linear regression estimates and standard errors for respondents with E scores that are one standard deviation (SD) above (purple line) or below (yellow line) the sample mean. Interactions between resilience factors and baseline E are significant (p < 0.05) in panel B (SR_dep: B = − 0.003, p = 0.03; SR_dis: 0.003, p = 0.03) and panel C, right (SR_dis: B = 0.004, p = 0.02). The full model results are in Supplementary Table 5.