There is strong rationale to move from disorder-labels of mental health to a transdiagnostic symptom based approach to enhance physiological understanding.

For decades, psychiatry has been defined by disorder-based categories, which are used to label patients according to the degree to which their symptoms align with different sets of diagnostic criteria. However, in recent years, there has been increasing push back on this approach due to issues of heterogeneity and comorbidity, despite its noted clinical utility.

As we’ve discussed previously, trying to categorize diverse sets of symptoms into specific diagnostic categories is fraught with considerable challenges. This starts at the very basic level of how the assessments tools used to assess these disorders are designed, where heterogeneity across assessments evaluating the same disorder, and overlap in assessments evaluating different disorders  adds further confusion to what is already a complex picture [1].

Transdiagnostic approaches to research

To try and address some of these issues, there has been increased traction behind research taking a more transdiagnostic approach. The most high-profile shift has been the introduction of the RDoC [2] framework where researchers are often encouraged to think in terms of neuroscientifically defined constructs which may underlie multiple disorders, rather than in terms of disorders per se.  Other transdiagnostic approaches include the study of comorbid patient groups whose symptom profiles align with multiple diagnostic criteria or looking across groups of patients with differential disorder diagnoses.

Within the research field, disruptions in brain structure and function, cognition and behavior have all been explored from a transdiagnostic perspective, revealing, for example, cross-disorder commonalities in the disruption of resting-state functional connectivity, cognitive control, reward responsivity, gray matter volume, and social cognition, to name a few. For example, a recent review of EEG studies explored abnormalities in error-related negativity, an event-related potential (ERP) component, across multiple disorders (e.g. ADHD, anxiety, depression, schizophrenia) suggesting that it could be a relevant transdiagnostic marker of psychopathology [3]. Other studies have used fMRI to examine patterns of disruption in the circuits important in cognitive control across multiple major psychiatric disorders, finding commonalities and suggesting that these disruptions may also be a transdiagnostic phenotype reflecting difficulties in adaptable and flexible cognition [4].

Transdiagnostic Uses of the MHQ

These issues are what also led us to develop the Mental Health Quotient (MHQ), a transdiagnostic assessment tool which spans the symptoms from 10 major psychiatric disorders [5]. It also includes questions that ask about life experience and demographics, as well as situational factors, to reflect the important contribution of contextual factors to many psychiatric challenges, something that is often excluded in existing mental health assessment tools.

The MHQ is used as part of our public interest project – the Mental Health Million Project – and is also available for academic and not-for-profit researchers to use in their own research studies. For example if you want to compare symptom profiles across different patient groups who may have a diverse range of symptom profiles then the MHQ can provide a standardized view and remove the unwanted noise and bias that comes with using a multiple different tools which are particular to one disorder or another. Although there are other cross-disorder tools available, our analysis [1] showed that none of the ones that we looked at adequately assessed a comprehensive range of symptoms, another reason why we sought to develop the MHQ.

Secondly, there have been considerable efforts to try and identify valid biomarkers for different disorders where patterns of brain activity, acquired using fMRI or EEG, are matched against symptom profiles. Again, the majority of this work has been conducted at the level of the single disorder, but transdiagnostic assessment tools such as the MHQ provide an opportunity for taking a more cross disorder view. The cross-over between several MHQ items with RDoC constructs also means that the MHQ can be used to collect self-report data in combination with brain and behavioral data streams in studies that aim to identify biotypes relevant to psychopathology.

Thirdly the MHQ can be used to evaluate patient outcomes after different treatments or interventions, or to track the trajectory of patient symptoms, and their overall mental wellbeing, over time.  In this way it can be used to map the shifting mental profiles of individuals or groups before and after treatment programs, or during longitudinal studies where measures are collected and compared over multiple time points to identify any relevant changes.

These are just a few examples of how you can use the MHQ in your research. You can find out more about the MHQ for research here or by getting in touch

References

[1] Newson, J., Hunter, D., & Thiagarajan, T. (2020). The Heterogeneity of Mental Health Assessment. Frontiers In Psychiatry, 11. doi: 10.3389/fpsyt.2020.00076

[2] https://www.nimh.nih.gov/research/research-funded-by-nimh/rdoc/index.shtml

[3] Hanna, G., & Gehring, W. (2016). The NIMH Research Domain Criteria initiative and error-related brain activity. Psychophysiology, 53(3), 386-388. doi: 10.1111/psyp.12571

[4] McTeague, L., Huemer, J., Carreon, D., Jiang, Y., Eickhoff, S., & Etkin, A. (2017). Identification of Common Neural Circuit Disruptions in Cognitive Control Across Psychiatric Disorders. American Journal Of Psychiatry, 174(7), 676-685. doi: 10.1176/appi.ajp.2017.16040400

[5] Newson, J., & Thiagarajan, T. (2020). Assessment of Population Well-Being With the Mental Health Quotient (MHQ): Development and Usability Study. JMIR Mental Health, 7(7), e17935. doi: 10.2196/17935