Cancer Symptom Help‐Seeking Behaviors of Breast Cancer Patients: A Grounded Theory Study

ABSTRACT Objective This study aimed to explore the complex dynamics of help‐seeking behaviors among breast cancer patients in China through developing an explanatory theoretical model. Methods A Constructivist Grounded Theory (CGT) approach was employed to investigate breast cancer patients' help‐seeking behaviors. Data collection occurred at a tertiary hospital in Zhejiang, China, from September 2024 to February 2025. We used a two‐phase CGT design: Phase 1 inductively generated the preliminary model from patient interviews; Phase 2 employed theoretical sampling with nurses and non‐participant observations to test negative cases, triangulate covert decision dynamics, and achieve category saturation. Sample size was based on theoretical saturation audit checks for coding consistency. Data analysis utilized NVivo 12.0 software following Strauss and Corbin's three‐level coding paradigm. Results Analysis generated the Motivate‐Response‐Feedback Model (MRFM), outlining the dynamics of breast cancer help‐seeking behavior. Intrinsic motivators included cognitive biases, perceived disease severity, and coping strategies, whereas extrinsic motivators encompassed cultural stigma, healthcare resource allocation, and family responsibilities. Patients' behavioral responses manifested as active (multi‐source symptom verification, cross‐regional care‐seeking) or passive (delayed consultations, condition concealment). Feedback processes were categorized as positive (enhanced social support, reduced psychological stress) and negative (economic strain, negative emotional states), further influencing subsequent help‐seeking behaviors. Conclusions This study provides a nuanced understanding of the complex interplay between intrinsic and extrinsic motivators, behavioral responses, and feedback loops shaping breast cancer help‐seeking behaviors in China. We propose a culture‐specific MRFM that explains intention–behavior gaps via dynamic feedback loops rather than static determinants. The developed MRFM highlights the need for culturally tailored interventions to reduce stigma, improve resource allocation, and enhance psychological and social support. Further quantitative validation and research exploring the role of digital health interventions in facilitating timely help‐seeking behaviors are recommended.