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Phenomenology as a resource for translational research in mental health: methodological trends, challenges and new directions.

Rosa RitunnanoD PapolaM R BroomeB Nelson
Published in: Epidemiology and psychiatric sciences (2023)
This editorial reflects on current methodological trends in translational research in mental health. It aims to build a bridge between two fields that are frequently siloed off from each other: interventional research and phenomenologically informed research. Recent years have witnessed a revival of phenomenological approaches in mental health, often - but not only - as a means of connecting the subjective character of experience with neurobiological explanatory accounts of illness. Rich phenomenological knowledge accrued in schizophrenia, and wider psychosis research, has opened up new opportunities for improving prediction, early detection, diagnosis, prognostic stratification, treatment and ethics of care. Novel qualitative studies of delusions and hallucinations have challenged longstanding assumptions about their nature and meaning, uncovering highly complex subjective dimensions that are not adequately captured by quantitative methodologies. Interdisciplinary and participatory research efforts, informed by phenomenological insights, have prompted revisions of pre-established narratives of mental disorder dominated by a dysfunction framework and by researcher-centric outcome measures. Despite these recent advances, there has been relatively little effort to integrate and translate phenomenological insights across applied clinical research, with the goal of producing more meaningful, patient-valued results. It is our contention that phenomenological psychopathology - as the basic science of psychiatry - represents an important methodology for advancing evidence-based practices in mental health, and ultimately improving real-world outcomes. Setting this project into motion requires a greater emphasis on subjectivity and the structures of experience, more attention to the quality and patient-centredness of outcome measures, and the identification of treatment targets that matter most to patients.
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