Abstract
Concepts of disease risk and its management are central to processes of medicalisation and pharmaceuticalisation. Through a narrative perspective, this paper aims to understand how such macro-level developments may (or may not) be experienced individually, and how an algorithm that is used for recruitment into a clinical trial may structure individual notions of being 'at risk' and 'in need of treatment'. We interviewed 31 women participating in the Study of Tamoxifen and Raloxifene (STAR), a chemoprevention trial conducted in the US between 1999 and 2006. Interviews were thematically analysed. Women in the study had experienced the threat of breast cancer and felt vulnerable to developing the disease prior to STAR participation. The diagnosis of 'being at risk' for cancer through an algorithm that determined risk-eligibility for STAR, opened up the possibility for the women to heal. The trial became a means to recognise and collectivise the women's experiences of vulnerability. Through medication intake, being cared for by study coordinators, and the sense of community with other STAR participants, trial participation worked to transform women's lives. Such transformative experiences may nevertheless have been temporary, enduring only as long as the close links to the medical institution through trial participation lasted.
| Original language | English |
|---|---|
| Pages (from-to) | 1373-1387 |
| Number of pages | 15 |
| Journal | Sociology of Health and Illness |
| Volume | 37 |
| Issue number | 8 |
| DOIs | |
| State | Published - Nov 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Adult
- Breast Neoplasms/prevention & control
- Estrogen Antagonists/therapeutic use
- Female
- Humans
- Interviews as Topic
- Middle Aged
- Narration
- Qualitative Research
- Raloxifene Hydrochloride/therapeutic use
- Randomized Controlled Trials as Topic/psychology
- Risk Assessment
- Sociology, Medical
- Tamoxifen/therapeutic use
- Uncertainty
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