Criticism of the biomedical model of psychiatry that regards mental illness as brain disease has been labelled ‘anti-psychiatry’. Critical psychiatry arises out of so-called anti-psychiatry, but has additional roots in transcultural psychiatry, its alliance with psychiatric user/survivor groups, and the methodological critique of the neuroscientific basis of mental health problems and psychiatric treatment effectiveness. It is not opposed to psychiatry as such and argues for a person-centred shift for practice and research. This article discusses how a more truly biopsychosocial model, which critiques the biomedical model to produce a more relational practice, is needed not only for psychiatry but also for medicine in general.
Duncan What real hope for relational psychiatry? This is on the coll of psychs website Susanne
ReplyDeleteThe British Journal of Psychiatry
Call for Papers: Precision Medicine and Personalised Healthcare in Psychiatry
Submission Due Date: 1st August 2021
The past few years has seen a rapid increase in the use of data science in psychiatry research across the lifespan- including the use of data driven and model based approaches for diagnostic, prognostic, and treatment response predictions. Data science is also being used to identify new illness subgroups using questionnaire data, biomarker or brain imaging data, or combinations therein, that transcend traditional diagnostic groups for potential use in the development for new targeted treatments. Statistical models have been developed across data types to highlight the possibility of machine learning used throughout the care pathway, from app-based community interventions, electronic health records for patient allocation and through to genetic and brain imaging in secondary and tertiary care.
These approaches are coming closer and closer to real world translation and clinical implementation, however significant challenges will be raised. These include the standards of statistical models, replicability and reproducibility in real world settings and the infrastructure for practical implementation. There are also clear issues raised when potentially giving model based prognoses in psychiatry, the right ‘not to know’, when to use data science and how such models may impact resource usage.
We would welcome papers across the lifespan from the arena of youth mental health to dementia, and across multiple data modalities including symptoms, neuroimaging, proteomics and genomics: with the emphasis on papers close to the challenge of real-world implementation and clinician interaction.