[On the future of prediction modeling for precision psychiatry].

Background: Precision psychiatry is an emerging field focusing on individualized approaches to mental health care, aiming to reduce uncertainty regarding prognosis and treatment response.

Aim: To identify challenges that hinder the implementation of precision psychiatry and to propose directions for future research.

Method: A narrative review of challenges within the field of precision psychiatry.

Results: Significant emphasis has been placed on technical innovation for data-driven predictive models of treatment outcomes. However, the complex and dynamic nature of mental health presents major challenges for successful implementation. Research in representative populations, relevant outcome definitions, and integration of contextual and behavioral factors is essential. Furthermore, validation and implementation currently remain understudied.

Conclusion: A shift is needed from retrospective research based on linear and static disease concepts to prospective research that considers the impact of contextual factors and the dynamic and complex nature of mental health.