Social science & medicine (1982) · 2025
Longitudinal network analysis of resilience factors and mental health symptoms among healthcare workers during a public health emergency.
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Zainal Nur Hani, Foo Cheryl Yunn Shee, Teo Irene, Sung Sharon C
Аннотация
BACKGROUND: Healthcare workers (HCWs) experience various stressors that can adversely weaken mental health and self-perceived resilience, potentially spilling over to compromised patient care. However, the sequela of this phenomenon is not well understood. Therefore, we tested how shifts in resilience factor strength (self-perceived resilience and job dedication) might precede, co-occur, or be a consequence of mental health symptoms among HCWs during a public health emergency.
METHOD: A three-wave survey was conducted across two years, each wave about a year apart. HCWs (N = 634) recruited in Singapore self-reported on anxiety and depression symptoms, perceived stress, job dedication, and resilience during each wave. Prospective network analysis determined within-person, cross-lagged temporal relationships between constructs from time t to t + 1, adjusting for autoregressions and other within-person and between-person associations.
RESULTS: Increased stress predicted future weakened job dedication (Cohen's d = -3.93) and resilience factors (d = -2.96). Likewise, increased depression symptoms predicted subsequent weakened job dedication (d = -0.64) and resilience factors (d = -0.44). Parameter estimates examining resilience factors as a predictor and anxiety symptoms were unstable across the 1,000 network bootstrap iterations. Results remained similar after adjusting for age, sex, chronic illness, social support, being a nurse vs. another HCW, and managerial role status.
DISCUSSION: HCWs with higher stress and depression severity may experience weaker long-term job dedication and self-perceived resilience, supporting the scar theory and not the vulnerability model of mental health. Interventions targeting high-stress occupations might benefit from focusing on alleviating mental health problems before building resilience.
METHOD: A three-wave survey was conducted across two years, each wave about a year apart. HCWs (N = 634) recruited in Singapore self-reported on anxiety and depression symptoms, perceived stress, job dedication, and resilience during each wave. Prospective network analysis determined within-person, cross-lagged temporal relationships between constructs from time t to t + 1, adjusting for autoregressions and other within-person and between-person associations.
RESULTS: Increased stress predicted future weakened job dedication (Cohen's d = -3.93) and resilience factors (d = -2.96). Likewise, increased depression symptoms predicted subsequent weakened job dedication (d = -0.64) and resilience factors (d = -0.44). Parameter estimates examining resilience factors as a predictor and anxiety symptoms were unstable across the 1,000 network bootstrap iterations. Results remained similar after adjusting for age, sex, chronic illness, social support, being a nurse vs. another HCW, and managerial role status.
DISCUSSION: HCWs with higher stress and depression severity may experience weaker long-term job dedication and self-perceived resilience, supporting the scar theory and not the vulnerability model of mental health. Interventions targeting high-stress occupations might benefit from focusing on alleviating mental health problems before building resilience.