Comparison of the Resilience of the Medical Staff During the COVID-19 Pandemic in Response to The Effects of Yalom Group Psychotherapy and Acceptance and Commitment Group Therapy

Background: The medical staff working on the front-line battle against coronavirus (COVID-19) are more exposed to mental health risks than others. Resilience is the ability to withstand challenging situations that help individuals defend their mental health against stressors. Therefore, the present study aimed to compare the effectiveness of Yalom and acceptance and commitment group psychotherapy on medical staff’s resilience in COVID-19 centers. Methods: The research method was quasi-experimental and pre-test-post-test with a control group. The statistical population includes all 600 medical staff of Hamedan who were caring for patients with COVID-19 in 2021. Among them, 45 people, based on the average variance of resilience obtained from the study of Valizadeh et al. (2020), were selected by convenience sampling and randomly assigned to two experimental groups (each 15) and one control group (15). The experimental groups were divided into Yalom and acceptance and commitment group psychotherapy, and all three groups responded to the Connor-Davidson Resilience scale (CD-RISC) as pre-test and post-test. Data were analysed using analysis of covariance using SPSS software version 25. Results: Yalom group psychotherapy and ACT group therapy have differing effects on the resilience of the participants investigated and are statistically significant since the value of the computational F statistic (106.722) is statistically significant (P = 0.001 and P 0.05, respectively). Therefore, it can be acknowledged that Yalom group psychotherapy has a better rate of improvement than acceptance and commitment group therapy. Conclusion: Considering the significant efficacy of Yalom group psychotherapy and its relative ease of implementation in comparison to ACT, it is possible to employ this intervention to protect the mental health of medical staff during severe epidemics of diseases such as coronavirus.