Precision psychiatry is an emerging field with transformative opportunities for mental health. However, the use of clinical prediction models carries unprecedented ethical challenges, which must be addressed before accessing the potential benefits of precision psychiatry. This critical review covers multidisciplinary areas, including psychiatry, ethics, statistics and machine-learning, healthcare and academia, as well as input from people with lived experience of mental disorders, their family, and carers. We aimed to identify core ethical considerations for precision psychiatry and mitigate concerns by designing a roadmap for research and clinical practice. We identified priorities: learning from somatic medicine; identifying precision psychiatry use cases; enhancing transparency and generalizability; fostering implementation; promoting mental health literacy; communicating risk estimates; data protection and privacy; and fostering the equitable distribution of mental health care. We hope this blueprint will advance research and practice and enable people with mental health problems to benefit from precision psychiatry.

Objective: To investigate gender differences of health literacy in individuals with a migration background. Design: Systematic review and meta-analysis. OVID/MEDLINE, PsycINFO and CINAHL were searched in March 2018 and July 2020. Setting: Studies had to provide health literacy data for adult women and men with a migration background, collected with a standardised instrument, or report results that demonstrated the collection of such data. Health literacy data were extracted from eligible studies or requested from the respective authors. Using a random-effects model, a meta-analysis was conducted to assess standardised mean differences (SMDs) of health literacy in men and women. Two researchers independently assessed risk of bias for each included study using the Appraisal Tool for Cross-Sectional Studies. Results: Twenty-four studies were included in this systematic review. Thereof, 22 studies (8012 female and 5380 male participants) were included in the meta-analyses. In six studies, gender-specific health literacy scores were reported. The authors of additional 15 studies provided their data upon request and for one further study data were available online. Women achieved higher health literacy scores than men: SMD=0.08, 95% CI 0.002 to 0.159, p=0.04, I ² =65%. Another 27 studies reported data on female participants only and could not be included due to a lack of comparable studies with male participants only. Authors of 56 other eligible studies were asked for data, but without success. Conclusion: Men with a migration background—while being much less frequently examined—may have lower health literacy than women. As heterogeneity between studies was high and the difference became statistically insignificant when excluding studies with a high risk of bias, this result must be interpreted with caution. There is a paucity of research on the social and relational aspects of gender in relation to health literacy among people with a migration background, especially for men. PROSPERO registration number: CRD42018085555.

Health literacy (HL) is considered a key concept to positively address relevant decisions concerning physical and mental health. According to an integrated model of a European Consortium, the process to access, understand, appraise and apply health information is at the centre of practising HL. In this study, we examine HL in a population with an early onset of a mental disorder (MD). Results are based on a cross-sectional survey among people with MD (n = 310) who sought help at an early detection centre for MD in Cologne, Dresden or Munich. Help-seekers filled out the European Health Literacy Survey questionnaire (HLS-EU-Q) on perception-based HL, socio-demographic data and general health status. Psychopathology was assessed separately by trained specialists. Data are compared with a representative sample of the German population. Overall, HL was lower in a sample with MD compared with the general population. Disease-specific limitations were present in accessing, appraising and applying health information, whereas understanding was perceived fairly easy. Statistical analysis of limited HL revealed correlations with the diagnosis of affective disorders and anxiety disorders, an increase of depressive symptoms as well as the presence of more than one MD. In line with these findings, low levels of HL were associated with a worse general health status. In a population with MD, accessing, appraising and applying health information seemed to be particularly challenging. Therefore, educational programmes that mainly focus on increasing knowledge might not be sufficient for improving the HL in people with MD. Further research should concentrate on context-specific HL to foster behavioural change and improve overall health.

Predictive and preventive medicine play an increasingly important role in public debates on health, providing cutting-edge technologies with the potential to measure and predict individual risks of getting ill. This leads to an ever-expanding definitional space between being “healthy” and being “ill”, challenging the individual’s everyday life, attitudes and perceptions towards the self and the process of health-related decision-making. “How do the condition of ‘being at risk’ and individual health literacy interrelate?” is the leading question of the current contribution. Drawing on empirical qualitative data, collected by means of narrative interviews with persons at risk in four clinical fields, a bottom-up ethnographic and health sciences perspective on health literacy (with an emphasis on critical health literacy) is employed. The findings will be embedded within theoretical approaches dealing with power relations and communication in healthcare encounters, particularly Habermas’ theory of communicative action. The core outcome of our study is a concept for an overarching model of health literacy in the context of health-related risk prediction across indications, based on empirical insights gained through interpretative analysis of the four clinical domains.