A Multilevel Analysis of Teachers' Compassion Fatigue and Compassion Satisfaction During the COVID-19 Pandemic

• In Event: Supporting the Well-Being of School Community During the COVID-19 Pandemic: Perspectives From Different School Stakeholders

Abstract

Objectives
The COVID-19 pandemic and its subsequent school disruptions have drastically shift teachers' perception of their efficacy as individual teachers and members of the school community; it has also provided teachers with opportunities to utilize social-emotional learning (SEL) practices to cope with the continuously changing demands and new challenges and support students. However, we have a limited scientific understanding of how these new challenges and opportunities interact with their diverse demographic contexts to influence their mental health wellbeing during the pandemic. To address this research gap, this paper aims to understand how teachers’ self-efficacy, collective efficacy, and SEL competencies, as well as diverse demographic factors across teacher level and school level, influence their compassion fatigue and compassion satisfaction during the pandemic and distance learning from a multilevel perspective.

Theoretical Perspectives and Framework
The study is guided by the Jobs Demands – Resources (JD-R) model, which argues that job demands and job resources concurrently and interactively influence individuals' wellbeing and performance through the motivational process and the health impairment process, respectively (Bakker & Demerouti, 2007; Bakker & Demerouti, 2017). Although researchers argue that job demands and resources could exist at both the individual level and organization levels, there is a lack of empirical studies examining the multilevel influence of self-efficacy, collective efficacy, SEL competencies, and teachers' and schools' demographic factors across teacher and school levels. This study aims to expand the JD-R model from the ecological system perspective.

Methods and Data Sources
Participants included 1,619 teachers recruited from PreK-12 schools in a large urban school district in Northern California. Teachers’ online teaching self-efficacy was measured by the modified Teacher Subjective Well-being Questionnaire (Renshaw et al., 2015). A self-developed Teacher collective scale measured teachers' collective efficacy. Compassion fatigue and compassion satisfaction were measured by a modified subscale of the Professional Quality of Life Scale (Stamm, 2010). Teachers and their schools’ demographic information were also collected from the district’s administrative data system. Reliability analyses and confirmatory factor analyses showed that all Likert scale/subscales achieved adequate construct validity and reliability. Regression analyses were conducted using hierarchical linear regression modeling in HLM to estimate the multilevel main and moderation effects.

Results
Based on the multilevel analyses results, female teachers reported a higher level of compassion fatigue and lower level of compassion satisfaction than male teachers. Upon controlling for teachers' and schools' demographic factors, teachers’ perception of self-efficacy and SEL competencies at the teacher level and collective efficacy at the school level were positively associated with compassion satisfaction and negatively associated with compassion fatigue. Moderating analysis showed that the preventing effect of SEL competencies on teachers' compassion fatigue was mitigated in schools with a higher level of school-level collective efficacy.

Significance
The findings highlight the importance of fostering teachers' efficacy at both the individual level and collective level to promote teachers' wellbeing and prevent compassion fatigue; it also shows that schools' demographic and psychological contexts play an important role in influencing individual teachers' wellbeing and adjustment. Practical implications for conducting research-practice partnerships during the pandemic will also be discussed.

Authors

• Chunyan Yang, University of California, Berkeley

• Meg Stomski, University of California - Berkeley

• Xueqin Lin, University of California - Berkeley