# A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder https://www.mdpi.com/2077-0383/10/14/3109/htm Taliaz Ltd., Tel Aviv-Yafo 6801294, Israel 2 EPSYLON—Psychiatric Care Network, 1000 Brussels, Belgium 3 Laboratory of Psychological Medicine and Addictology, Faculty of Medicine, Université Libre de Bruxelles, 1050 Brussels, Belgium * Author to whom correspondence should be addressed. Academic Editor: Michele Roccella J. Clin. Med. 2021, 10(14), 3109; https://doi.org/10.3390/jcm10143109 Received: 13 June 2021 / Revised: 8 July 2021 / Accepted: 10 July 2021 / Published: 14 July 2021 --- [[24-10-2022]] **Psychiatric diagnosis based on observations is not reliable. No two patients are alike. We need a better solution, perhaps with technology.** -Mental health disorders are ambiguously defined and diagnosed. The established diagnosis technique, which is based on structured interviews, questionnaires and data subjectively reported by the patients themselves, leaves the mental health field behind other medical areas. We support these statements with examples from major depressive disorder (MDD). The National Institute of Mental Health (NIMH) launched the Research Domain Criteria (RDoC) project in 2009 as a new framework to investigate psychiatric pathologies from a multidisciplinary point of view. This is a good step in the right direction. Contemporary psychiatry considers mental illnesses as diseases that manifest in the mind and arise from the brain, expressed as a behavioral condition; therefore, we claim that these syndromes should be characterized primarily using behavioral characteristics. We suggest the use of smartphones and wearable devices to passively collect quantified behavioral data from patients by utilizing digital biomarkers of mental disorder symptoms. Various digital biomarkers of MDD symptoms have already been detected, and apps for collecting this longitudinal behavioral data have already been developed. This quantified data can be used to determine a patient’s diagnosis and personalized treatment, and thereby minimize the diagnosis rate of comorbidities. As there is a wide spectrum of human behavior, such a fluidic and personalized approach is essential. **Major Depression Disorder highly prevalent but poorly defined and diagnosed.** MDD is a highly prevalent condition, with 6% of the adult population worldwide affected each year [[4](https://www.mdpi.com/2077-0383/10/14/3109/htm#B4-jcm-10-03109)]. MDD has been recognized as a major risk factor for suicide by the World Health Organization [[5](https://www.mdpi.com/2077-0383/10/14/3109/htm#B5-jcm-10-03109)]. In addition, MDD is associated with other life-threatening conditions, such as stroke [[6](https://www.mdpi.com/2077-0383/10/14/3109/htm#B6-jcm-10-03109)]. As MDD is of particular medical importance, it is unfortunate that experts from the psychiatric community claim that MDD is poorly defined and diagnosed [[7](https://www.mdpi.com/2077-0383/10/14/3109/htm#B7-jcm-10-03109),[8](https://www.mdpi.com/2077-0383/10/14/3109/htm#B8-jcm-10-03109)]. Santor et al. [[8](https://www.mdpi.com/2077-0383/10/14/3109/htm#B8-jcm-10-03109)] mapped over 280 different depression scales to measure MDD. Another study that emphasized the unwanted heterogeneity of MDD was undertaken by Zimmerman et al. [[9](https://www.mdpi.com/2077-0383/10/14/3109/htm#B9-jcm-10-03109)], who found that there are 227 possible ways to meet the DSM-IV diagnostic criteria for MDD, while only 170 different combinations occur among patients. **Diagnosis for MDD is based on patient's subjective and retrospective reporting on questionnaires. Compare to other medical specialty, this doesn't look like a very good diagnostic technique.** This evidence indicates the problematic diagnosis system established by the Diagnostic and Statistical Manual of Mental Disorders (DSM), which is routinely used by psychiatrists. The DSM-5 diagnosis method for MDD includes a list of nine symptoms applied as diagnostic criteria [[10](https://www.mdpi.com/2077-0383/10/14/3109/htm#B10-jcm-10-03109)]. Patients meet the diagnostic criteria based on the number and duration of symptoms and signs. Threshold scores are used to classify and measure depression severity. The conventional way to determine those crucial scores is to use questionnaires completed by the psychiatrist ([Figure 1](https://www.mdpi.com/2077-0383/10/14/3109/htm#fig_body_display_jcm-10-03109-f001)a). Even though psychiatrists aim to determine scores objectively, this diagnosis technique, which is mostly based on data subjectively reported by the patients themselves, leaves the mental health field behind other medical areas. One of the consequences of using this problematic diagnosis technique is also reflected in the low remission rates of MDD patients, even after they are treated with different treatment options [[11](https://www.mdpi.com/2077-0383/10/14/3109/htm#B11-jcm-10-03109),[12](https://www.mdpi.com/2077-0383/10/14/3109/htm#B12-jcm-10-03109)]. Other factors that are also likely to have an influence on remission rates include patients who do not routinely take their prescribed medications. In this article, we provide examples and evidence from the literature discussing MDD, but our ideas are also relevant to other mental health disorders. **Because mental illness are diseases that manifest in the mind and expresses themselves as behavioural conditions, therefore mental syndrome should be characterised primarily using behavioural characteristics. **  **Figure 1.** Stages toward a paradigm shift: (**a**) Today, established diagnoses of mental disorders are based on interviews. Different disciplines (smaller circles) are investigated separately. Some of those investigated areas contribute (unidirectional dashed arrows) to the diagnosis. (**b**) At the first stage, behavioral data should become the field’s pillar. Data from other relevant areas (smaller circles) will be cross-referenced (dashed bidirectional arrows) with behavioral data. (**c**) At the second stage, a substantial understanding of the behavioral component could lead to finding correlations (red lines) between behavioral markers and markers from other areas (smaller circles). This would promote crosstalk (dashed bidirectional arrows) between the different areas and consequently expand our knowledge in those areas. From a historical viewpoint, we can observe the conceptual changes that the classification system for mental conditions has undergone. The first DSM versions were focused on collecting statistical data [[13](https://www.mdpi.com/2077-0383/10/14/3109/htm#B13-jcm-10-03109)]. In the DSM-III, there was a paradigm shift to include empirically based data with the goal of producing non-biased diagnosis criteria [[13](https://www.mdpi.com/2077-0383/10/14/3109/htm#B13-jcm-10-03109)]. The DSM-5 combines etiological and neurobiological research results into the definitions of mental disorders in order to improve the diagnosis process [[14](https://www.mdpi.com/2077-0383/10/14/3109/htm#B14-jcm-10-03109),[15](https://www.mdpi.com/2077-0383/10/14/3109/htm#B15-jcm-10-03109)]. This approach is consistent with the Research Domain Criteria (RDoC) project of the National Institute of Mental Health (NIMH). The NIMH launched the RDoC project in 2009, which proposed a new framework to investigate psychiatric pathologies [[16](https://www.mdpi.com/2077-0383/10/14/3109/htm#B16-jcm-10-03109)]. The project’s idea is that the integration of data from different disciplines, such as genomics, neuroimaging and the clinical field, can provide a better understanding of psychiatric pathologies. Thomas R. Insel [[17](https://www.mdpi.com/2077-0383/10/14/3109/htm#B17-jcm-10-03109)] explained that today’s diagnostic systems, ICD and DSM, create a common language in psychiatry but rely on observable symptoms. This approach limits physicians from performing examinations to obtain a specific diagnosis, an option that exists in other medical fields [[17](https://www.mdpi.com/2077-0383/10/14/3109/htm#B17-jcm-10-03109)]. This approach also leads physicians to routinely diagnose comorbidities within patients [[18](https://www.mdpi.com/2077-0383/10/14/3109/htm#B18-jcm-10-03109),[19](https://www.mdpi.com/2077-0383/10/14/3109/htm#B19-jcm-10-03109)]. In addition, Thomas R. Insel [[17](https://www.mdpi.com/2077-0383/10/14/3109/htm#B17-jcm-10-03109)] mentioned that medical diagnoses that rely only on symptoms, which are reported by the patients themselves, are not only heterogeneous and imprecise, but the subsequent treatment focuses on symptom relief and prevention. Addressing these problems that accompany the conservative and common practice of psychiatric diagnosis requires a paradigm shift. Although it is known that various aspects (e.g., genetics, chronic medical conditions and deprivation) influence the development of a mental disorder within an individual [[20](https://www.mdpi.com/2077-0383/10/14/3109/htm#B20-jcm-10-03109)], mental disorders—including MDD—are behavioral conditions. It is also known that contemporary psychiatry considers mental illnesses as diseases that manifest in the mind and arise from the brain, expressing themselves as behavioral conditions [[21](https://www.mdpi.com/2077-0383/10/14/3109/htm#B21-jcm-10-03109)]. Therefore, we claim that mental syndromes should be characterized primarily using behavioral characteristics. This approach does not fully correspond with the RDoC project’s view since we argue that behavioral data should be the field’s pillar. Data from other areas, such as emotional regulation and genetics, are also essential for understanding the core of the psychiatric disorder, and must therefore be cross-referenced with behavioral data ([Figure 1](https://www.mdpi.com/2077-0383/10/14/3109/htm#fig_body_display_jcm-10-03109-f001)b). As we will emphasize in the following sections, we support the use of digital devices to collect behavioral data for the purpose of psychiatric assessment. ## The Digital Revolution in Mental Health **[[Ecological Momentary Assessments]] - advantage, short period, asked in natural setting. ==But it is still subjective report?== Therefore better to use sensors for passive monitoring.** To overcome these limitations, we suggest the use of smartphones and wearable devices to collect quantified behavioral data from patients passively. This process falls under the definition of digital phenotyping, as defined in 2016 by Onnela and Rauch [[26](https://www.mdpi.com/2077-0383/10/14/3109/htm#B26-jcm-10-03109)]. The utilization of smartphones and wearable devices exists in many other medical areas. For example, the monitoring of glucose levels among diabetes patients was revolutionized by developing and producing low-cost continuous glucose monitoring sensors [[27](https://www.mdpi.com/2077-0383/10/14/3109/htm#B27-jcm-10-03109)]. Recently, decision-making using data recorded by these devices was approved by the FDA [[27](https://www.mdpi.com/2077-0383/10/14/3109/htm#B27-jcm-10-03109)]. Another example of data collection via wearable devices is that done with the Apple Watch or other fitness bands that can passively measure pulse rate and detect pulse irregularity, which can signal atrial fibrillation or flutter [[28](https://www.mdpi.com/2077-0383/10/14/3109/htm#B28-jcm-10-03109)]. Embracing smartphones and wearable devices as sensors for collecting quantified behavioral data could generate a quantified, continuous and objective database of patients’ behavior. --- OK. I gave up reading this article mid way. Just about idea of using digital phenotyping, and the potential it has for psychiatry. Did not say HOW.