Abstract
Drawing on ethnographic fieldwork exploring various head and neck cancer treatment pathways of patients with low socio-economic status being treated with radiation therapy in Denmark, our aim was to explore how and why inequality in this treatment pathway might occur in the encounter between these patients and Danish healthcare. In recent years, inequality in cancer treatment of patients with a low socio-economic status has been a growing concern worldwide. The majority of patients with head and neck cancer have a relatively low socio-economic status and are at risk of experiencing inequality in their cancer treatment. Using a method proposed by Robert Yin, we performed a multiple case study of five treatment pathways of patients with a low socio-economic status. The case studies consisted of participant observations and interviews with patients, relatives and health professionals. We applied Herbert Blumer's theory of symbolic interaction as a framework for our analysis. We identified three concepts that all blocked joint action because patients and health professionals had different perceptions of what interaction required of them in terms of (1) Understanding information; (2) Assuming responsibility for managing practical tasks; and (3) Coordinating one's own treatment pathway. We identified how different situations challenged the patients' abilities to assume participation in their own treatment pathway. In their encounter with patients, healthcare professionals did not know which situational impediments to joint action patients were facing. We argue that being aware of how challenges unfold in the interaction with patients with low socio-economic status may serve as a starting point for changing practice to reduce inequality in the treatment of these patients. This study is reported using consolidated criteria for reporting Qualitative research (SRQR). We used the theory and method of Robert Yin of performing a multi-case study and we applied Herbert Blumer's theory of Symbolic interactionism as a framework for understanding data. No patient or public contribution.
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