Attitudes towards Risk Prediction in a Help Seeking Population of Early Detection Centers for Mental Disorders—A Qualitative Approach

Pauline Katharina Mantell, Annika Baumeister, Stephan Ruhrmann, Anna Janhsen and Christiane Woopen
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Pauline Katharina Mantell: Research Unit Ethics, Institute for the History of Medicine and Medical Ethics, Faculty of Medicine, University of Cologne and University Hospital of Cologne, 50924 Cologne, Germany
Annika Baumeister: Research Unit Ethics, Institute for the History of Medicine and Medical Ethics, Faculty of Medicine, University of Cologne and University Hospital of Cologne, 50924 Cologne, Germany
Stephan Ruhrmann: Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, 50931 Cologne, Germany
Anna Janhsen: a.r.t.e.s. Graduate School for the Humanities, University of Cologne, 50931 Cologne, Germany
Christiane Woopen: Research Unit Ethics, Institute for the History of Medicine and Medical Ethics, Faculty of Medicine, University of Cologne and University Hospital of Cologne, 50924 Cologne, Germany

IJERPH, 2021, vol. 18, issue 3, 1-13

Abstract: Big Data approaches raise hope for a paradigm shift towards illness prevention, while others are concerned about discrimination resulting from these approaches. This will become particularly important for people with mental disorders, as research on medical risk profiles and early detection progresses rapidly. This study aimed to explore views and attitudes towards risk prediction in people who, for the first time, sought help at one of three early detection centers for mental disorders in Germany (Cologne, Munich, Dresden). A total of 269 help-seekers answered an open-ended question on the potential use of risk prediction. Attitudes towards risk prediction and motives for its approval or rejection were categorized inductively and analyzed using qualitative content analysis. The anticipated impact on self-determination was a driving decision component, regardless of whether a person would decide for or against risk prediction. Results revealed diverse, sometimes contrasting, motives for both approval and rejection (e.g., the desire to control of one’s life as a reason for and against risk prediction). Knowledge about a higher risk as a potential psychological burden was one of the major reasons against risk prediction. The decision to make use of risk prediction is expected to have far-reaching effects on the quality of life and self-perception of potential users. Healthcare providers should empower those seeking help by carefully considering individual expectations and perceptions of risk prediction.

Keywords: health literacy; risk perception; prevention; personalized medicine; help seekers; Big Data (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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