Applying a Novel Approach to Understanding Social Worker Job Retention during the Pandemic.

Area of Science:

• Social Work
• Organizational Psychology
• Public Health

Background:

• The job demands-resources (JD-R) theory previously explained social worker burnout.
• The COVID-19 pandemic presented unique challenges to social workers, yet many remained in their roles, resisting turnover.
• Identifying factors that promote job retention is crucial for the social work profession.

Purpose of the Study:

• To explore factors facilitating job retention among U.S. Department of Veterans Affairs (VA) outpatient social workers during the COVID-19 pandemic.
• To apply the JD-R theory to understand how social workers managed job demands and utilized resources for retention.
• To inform strategies that support social worker retention in healthcare settings.

Main Methods:

• Qualitative, cross-sectional study utilizing semistructured interviews with 13 U.S. VA outpatient social workers.
• Content analysis of interview data to identify themes related to job retention.
• Application of the JD-R theory to interpret findings on the interplay between job demands and resources.

Main Results:

• Six key themes facilitated social worker retention: commitment to serving veterans, job flexibility, supportive colleagues, leadership support, maintaining routines, and trust in evidence-based practices.
• The JD-R theory effectively illustrated how social workers leveraged resources to balance demands, thereby enhancing job retention.
• Findings highlight the importance of organizational and professional factors in mitigating pandemic-related occupational stress.

Conclusions:

• Commitment, flexibility, collegial and leadership support, routine, and trust in science are vital for social worker retention, particularly during crises.
• Policy implications include the permanent adoption of telework and flexible work options to support social workers.
• Further research should compare retention factors across different social work sectors and sample sizes.