Abstract: Nonstandard Work Shifts and Social Workers' Burnout in China during the COVID-19 (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

All in-person and virtual presentations are in Mountain Standard Time Zone (MST).

SSWR 2023 Poster Gallery: as a registered in-person and virtual attendee, you have access to the virtual Poster Gallery which includes only the posters that elected to present virtually. The rest of the posters are presented in-person in the Poster/Exhibit Hall located in Phoenix A/B, 3rd floor. The access to the Poster Gallery will be available via the virtual conference platform the week of January 9. You will receive an email with instructions how to access the virtual conference platform.

Nonstandard Work Shifts and Social Workers' Burnout in China during the COVID-19

Friday, January 13, 2023
Valley of the Sun E, 2nd Level (Sheraton Phoenix Downtown)
* noted as presenting author
Huiying Jin, MSW, Doctoral Student, Rutgers University, NJ
Bin Tu, PhD, Professor and Vice Dean, Guangdong University of Foreign Studies, China
Chien-Chung Huang, PhD, Professor, Rutgers University, New Brunswick, NJ
Background/Purpose: Studies show the adverse effects of nonstandard work shifts (NWS) on well-being and social workers' high level of burnout in western counties. Social workers are acknowledged to be at risk of burnout, and the COVID-19 is putting social workers under increasing pressure. However, less is known about the phenomenon of NWS of Chinese social workers and the reason they work NWS. Furthermore, few studies examine whether NWS affects the burnout of social workers in China. To fill the gap, this study uses primarily collected data from frontline social workers in Guangzhou to provide a 'snapshot' of Chinese social workers' burnout during the pandemic and examine the associations of both NWS and the reason working NWS with social workers' burnout.

Methods: We randomly selected 54 out of 180 social work service stations in Guangzhou and sent the survey link to frontline workers on September 15, 2021. After the initial invitation, reminders were sent to social workers twice after seven and fourteen days. Out of 756 frontline social workers, 537 social workers participated and completed the online survey by October 10, 2021, with a 71% response rate. Burnout was measured by the Oldenburg Burnout Inventory, and Cronbach's alpha value was 0.85. NWS was assessed by a multiple-choice question, "Which of the following nonstandard work hour do you usually work?" with four multiple-choice options: weekdays (beyond 9-6 pm), weekends, legal holidays, and no NWS. We constructed a binary variable to express if they experience any NWS and a six-category variable for different types of NWS, including n NWS, weekdays only, weekends only, legal holidays only, weekdays and weekends, and weekdays/weekends and legal holidays. We used an eight-multiple-choice question to ask the reasons for NWS. Multiple Ordinary Least Squares regression models with robust stand errors were conducted to examine the effects of NWS and what reason for working NWS affects burnout of Chinese social workers.

Results: We find that NWS (91% of our sample) was associated with higher burnout, specifically for working on legal holidays only, both weekdays and weekends, and both weekdays/weekends and legal holidays. In addition, involuntary NWS was associated with a higher level of burnout. Involuntary reasons, more specifically, high workloads and mandatory NWS, are associated with a higher level of burnout.

Conclusions/Implications: Our findings suggest that an overwhelming majority of social workers in Guangdong, and probably in China as a whole, are experiencing NWS during the pandemic. Results show that NWS is associated with a higher level of burnout, and involuntary reason for working NWS matters for social workers' burnout. These findings call for policies to regulate NWS at both institution- and national- levels to reduce social workers' burnout and improve their well-being. Without structural changes, NWS workers will be precariously tied to high burnout and low well-being, especially during the pandemic.