Mental Health Help-Seeking and Associated Factors Among Public Health Workers During the COVID-19 Outbreak in China

She, Rui; Wang, Xiaohui; Zhang, Zhoubin; Li, Jinghua; Xu, Jun; You, Hua; Li, Yan; Liang, Yuan; Li, Shan; Ma, Lina; Wang, Xinran; Chen, Xiuyuan; Zhou, Peien; Lau, Joseph T. F.; Hao, Yuantao; Zhou, Huan; Gu, Jing

doi:10.3389/fpubh.2021.622677

Cited by 27 publications

(37 citation statements)

References 45 publications

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“…However, during the pandemic in China, when small-scale outbreaks occurred in some areas, primary PHWs were on the front line of the fight against the epidemic and were required to respond quickly to their areas of responsibility 42. Consequently, they were exposed to greater workload, physical injuries and mental stress caused by higher work demands, with insufficient work resources, which seriously deteriorated their job satisfaction 43. The results showed that the thriving at work score of primary PHWs was 3.17±0.65.…”

Section: Discussionmentioning

confidence: 99%

Relationships among thriving at work, organisational commitment and job satisfaction among Chinese front-line primary public health workers during COVID-19 pandemic: a structural equation model analysis

Jiang

Wang

et al. 2022

BMJ Open

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ObjectivesThis study aims to explore the mediating effect and influence mechanism of organisational commitment on the association among thriving at work and job satisfaction among frontline primary public health workers (PHWs) in China during the COVID-19 pandemic.DesignThis study is a cross-sectional written survey.SettingWe included 20 primary care units in northern provinces of China.ParticipantsA total of 601 PHWs who worked in primary organisations and against COVID-19 on the front line were included.MethodsWe collected the data from the participants’ written questionnaire (Minnesota Satisfaction Questionnaire, thriving at work scale and organisational commitment scale), and programmed AMOS V.26.0 to develop a structural equation model (SEM) based on the relationships among the three variables.ResultsThe thriving at work scores of the primary PHWs were (M=3.17, SD=0.65), and job satisfaction was (M=3.05, SD=0.69); the scores of their thriving at work, organisational commitment and job satisfaction were all significantly correlated (p<0.01); and the SEM indicated that organisational commitment had a significant partial mediating effect between thriving at work and job satisfaction. The overall effect value was 0.867, and the mediated effect value was 0.422, accounting for 48.7% of the total effect size.ConclusionThe thriving at work and job satisfaction scores of primary PHWs in China are moderate, and thriving at work not only affects job satisfaction directly, but also indirectly through organisational commitment. This study suggests that health policy-makers should promote job satisfaction among PHWs through relative inventions aiming to improve their thriving at work and organisational commitment.

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Section: Discussionmentioning

confidence: 99%

Relationships among thriving at work, organisational commitment and job satisfaction among Chinese front-line primary public health workers during COVID-19 pandemic: a structural equation model analysis

Jiang

Wang

et al. 2022

BMJ Open

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“…Supports from colleagues, supervisors and families were the fundamental, which could encourage HCWs to fight with confidence, help HCWs control negative thoughts and relieve their psychological burden and miss (Blanco‐Donoso et al, 2020 ). Support from society gave a great and warm respect to HCWs' contribution and encouraged HCWs to seek mental help, which might increase HCWs' self‐efficacy and turn the trauma into positive growth (She et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Negative and positive psychological experience of frontline nurses in combatting COVID‐19: A qualitative study

Peng

Yang

Gao

et al. 2021

J Nursing Management

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Aims To qualitatively explore potential experience among frontline nurses who had been fighting against the COVID‐19 infection since the outbreak. Background Disasters are often sudden and uncertain. Since the COVID‐19 outbreak in Wuhan city, local frontline nurses had been responsible for treatment of COVID‐19 for several months. Qualitative study was required to assess complex multi‐component psychological experiences among frontline nurses. Methods Twenty local frontline nurses were recruited from a designated hospital of COVID‐19 treatment. We conducted semi‐structured interview using phenomenological method. Descriptive phenomenological method was applied for thematic analysis. Results Twenty female frontline nurses (aged 24 to 43 years old) were interviewed. Two broader themes, negative and positive, were identified. Negative experience included refusal and helpless (refusal to work at frontline, shortage of confidence in working and helpless), fear and anxiety, excessive miss, and other health issues. Positive experience included improved interpersonal relationship, sublimation of personal faith and strength, changes in understanding meaning of life and new possibility. Conclusion Both positive and negative psychological response were observed, which can provide evidence based clues for making essential strategies and policy. Implications for Nursing Management Understand subjective experience of frontline nurses can establish evidence for development of effective psychological intervention. Nursing administrator should consider the nurses' psychological experience comprehensively to promote psychological growth and lower post‐traumatic psychological burden.

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“…Previous studies found that the COVID-19 cases would affect the investment and trust behavior, and the physical activity of the public (20)(21)(22). The OPHS behavior affected by the COVID-19 cases was also investigated among the public workers and college students (23,24). However, how the OPHS behavior of the Chinese public was affected by the COVID-19 cases has not yet been understood.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Online Psychological Help-Seeking Behavior During the COVID-19 Pandemic: An Interpretable Machine Learning Method

Hui

Zhang

Huang

et al. 2022

Front. Public Health

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Online mental health service (OMHS) has been named as the best psychological assistance measure during the COVID-19 pandemic. An interpretable, accurate, and early prediction for the demand of OMHS is crucial to local governments and organizations which need to allocate and make the decision in mental health resources. The present study aimed to investigate the influence of the COVID-19 pandemic on the online psychological help-seeking (OPHS) behavior in the OMHS, then propose a machine learning model to predict and interpret the OPHS number in advance. The data was crawled from two Chinese OMHS platforms. Linguistic inquiry and word count (LIWC), neural embedding-based topic modeling, and time series analysis were utilized to build time series feature sets with lagging one, three, seven, and 14 days. Correlation analysis was used to examine the impact of COVID-19 on OPHS behaviors across different OMHS platforms. Machine learning algorithms and Shapley additive explanation (SHAP) were used to build the prediction. The result showed that the massive growth of OPHS behavior during the COVID-19 pandemic was a common phenomenon. The predictive model based on random forest (RF) and feature sets containing temporal features of the OPHS number, mental health topics, LIWC, and COVID-19 cases achieved the best performance. Temporal features of the OPHS number showed the biggest positive and negative predictive power. The topic features had incremental effects on performance of the prediction across different lag days and were more suitable for OPHS prediction compared to the LIWC features. The interpretable model showed that the increase in the OPHS behaviors was impacted by the cumulative confirmed cases and cumulative deaths, while it was not sensitive in the new confirmed cases or new deaths. The present study was the first to predict the demand for OMHS using machine learning during the COVID-19 pandemic. This study suggests an interpretable machine learning method that can facilitate quick, early, and interpretable prediction of the OPHS behavior and to support the operational decision-making; it also demonstrated the power of utilizing the OMHS platforms as an always-on data source to obtain a high-resolution timeline and real-time prediction of the psychological response of the online public.

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Mental Health Help-Seeking and Associated Factors Among Public Health Workers During the COVID-19 Outbreak in China

Cited by 27 publications

References 45 publications

Relationships among thriving at work, organisational commitment and job satisfaction among Chinese front-line primary public health workers during COVID-19 pandemic: a structural equation model analysis

Relationships among thriving at work, organisational commitment and job satisfaction among Chinese front-line primary public health workers during COVID-19 pandemic: a structural equation model analysis

Negative and positive psychological experience of frontline nurses in combatting COVID‐19: A qualitative study

Prediction of Online Psychological Help-Seeking Behavior During the COVID-19 Pandemic: An Interpretable Machine Learning Method

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