ArticleFrontiers in public health2026
Development and validation of the quiet quitting behavior scale: a mixed-methods study with primary healthcare workers in China.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Affective Organizational Commitment Links Job Satisfaction to Quiet Quitting in Healthcare Workers: The Amplifying Role of Career Engagement.Healthcare (Basel, Switzerland) · 2026Article
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Authors and funding
3 authors.
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Abstract
Background: The growing prevalence of quiet quitting behavior (QQB) poses a significant challenge to workforce mental health and organizational sustainability. However, progress in this field has been hindered by the absence of culturally adapted and behaviorally anchored measurement instruments. This study aimed to develop a Quiet Quitting Behavior Scale (QQBS) tailored to the Chinese context and to validate the scale among primary healthcare workers. Method: The QQBS was developed and validated using an exploratory sequential mixed-methods design. The development process included item generation through grounded-theory analysis, content validation via Delphi consultation, instrument refinement through a pilot survey, and psychometric evaluation in a formal survey. Results: The final 15-item QQBS consists of two dimensions: Role Contraction and Behavioral Inertia (8 items) and Cognitive Collapse and Psychological Detachment (7 items). Content validity was established through expert review. Exploratory factor analysis identified a clear two-factor structure, which was subsequently confirmed by confirmatory factor analysis, indicating excellent model fit (CFI = 0.959, IFI = 0.960, RMSEA = 0.065). The scale showed excellent reliability, with high internal consistency (Cronbach's Conclusion: The QQBS is a theoretically grounded, reliable, and valid instrument. It serves as a critical instrument for identifying QQBs among primary healthcare workers in China and demonstrates strong potential for application in other high-stress sectors.
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