Our scientific approach

We undertake the following assessments as part of our programme:

• An adapted mental health assessment

• Medical history, including previous diagnoses and treatment responses

• Mental health screens

• Personality measures

• Cognitive tests

• Brain activity measures at rest and task

We bring together this multi-dimensional information, in line with the Research Domain Criteria, and use this to best suggest suitable interventions for the user. In the future, we hope to publish our outcome data in peer-reviewed journals and contribute to the wider scientific community. In particular, we hope to contribute toward the field of data-driven mental health, utilising machine learning to augment health-related decision making [1, 2].

All our users are given the very explicit option to allow us to use their data for scientific research. All data are confidential and permissions can be revoked at any time within the user's secure Psynergy account.

For more information regarding our evidence-base and vision, get in touch.

References [1] Durstwitz D, Koppe G & Meyer-Lindenberg A (2019) Deep neural networks in psychiatry. Molecular Psychiatry. 24: 1583-1598. https://doi.org/10.1038/s41380-019-0365-9 [2] Chandler C, Foltz PW & Elvevag B. (2019) Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness. Schizophrenia Bulletin. 46(1): 11-14. https://doi.org/10.1093/schbul/sbz105