Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis

Abstract

Background: Over the last decade, there has been considerable development in precision psychiatry, especially in the development of novel prediction tools that can be used for early prediction of the risk of developing a severe mental disorder such as schizophrenia, depression, bipolar disorder. Although the clinical efficiency of those tools is still unclear it is crucial to consider the future ethical and social consequences of their clinical use before they are used in clinical practice. The literature on this issue is rapidly growing and represents input from scholars from different fields-psychiatrists, bioethicists etc. However, to our knowledge, nobody has produced a review addressing these issues. Therefore, the present study aims to bridge the gap.

Methods: We conducted a scoping review, allowing integration of both empirical and non-empirical studies. The research question addressed is: what are the ethical and social issues raised by the potential use of predictive tools for the risk of developing of severe mental disorder identified in the existing empirical and theoretical literature? After developing the search terms, we conducted a search in three electronic databases: Scopus, Web of Science and PubMed. For the included articles bibliometric analysis and inductive thematic coding was performed. To ensure the transparency and rigour of this scoping review we followed he Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). A qualitative inductive thematic analysis of the included articles was performed using Atlas.ti.

Results: After screening, evaluation for eligibility and citation tracing 129 publications were included in the scoping review. The articles represent a wide range of fields of research-clinical psychology, general medicine, neuroscience, genetics, clinical genetics, psychiatry and mental health, philosophy, ethics, etc. The majority of the articles (83) are theoretical studies, 35 papers report results of empirical research and 11 are review papers. Qualitative thematic analysis of the included articles revealed four main themes: 1) Potential benefits and harms; 2) Rights and responsibilities; 3) Counselling, education and communication; 4) Ethical issues in different applications.

Conclusions: The articles included in the review cover a wide variety of concerns that might be raised when implementing predictive tools for the risk of developing of severe mental disorder. However, some important gaps in the literature are indicated. First, there are issues that should deserve more attention than they have received thus far (clinical utility, extensive or mandatory use). In several cases there is no empirical knowledge that determines whether particular concerns are justified (stigmatisation, use of machine learning algorithms).

Keywords: Artificial intelligence; Ethics; Intergenerational transmission; Mental illness; Risk prediction.

Fig. 1

Map of bibliographical coupling relations between the documents. Fractional counting was used and the minimum number of citations of a document was set to 5. Nodes (dots) and edges (lines) reflect the strength of the links between the items. Colour indicates membership into different clusters

Fig. 2

Results of word frequencies analysis