Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study (Preprint)

BACKGROUND Less than 10% of the individuals seeking behavioral health care receive measurement-based care (MBC). Technology has the potential to implement MBC in a secure and efficient manner. To test this idea, a mobile health (mHealth) platform was developed with the goal of making MBC easier to deliver by clinicians and more accessible to patients within integrated behavioral health care. Data from over 3000 users of the mHealth platform were used to develop an output severity score, a robust screening measure for depression and anxiety. OBJECTIVE The aim of this study is to compare severity scores with scores from validated assessments for depression and anxiety and scores from clinician review to evaluate the potential added value of this new measure. METHODS The severity score uses patient-reported and passively collected data related to behavioral health on an mHealth platform. An artificial intelligence–derived algorithm was developed that condenses behavioral health data into a single, quantifiable measure for longitudinal tracking of an individual’s depression and anxiety symptoms. Linear regression and Bland-Altman analyses were used to evaluate the relationships and differences between severity scores and Personal Health Questionnaire-9 (PHQ-9) or Generalized Anxiety Disorder-7 (GAD-7) scores from over 35,000 mHealth platform users. The severity score was also compared with a review by a panel of expert clinicians for a subset of 250 individuals. RESULTS Linear regression results showed a strong correlation between the severity score and PHQ-9 (<i>r</i>=0.74; <i>P</i>&lt;.001) and GAD-7 (<i>r</i>=0.80; <i>P</i>&lt;.001) changes. A strong positive correlation was also found between the severity score and expert panel clinical review (<i>r</i>=0.80-0.84; <i>P</i>&lt;.001). However, Bland-Altman analysis and the evaluation of outliers on regression analysis showed that the severity score was significantly different from the PHQ-9. CONCLUSIONS Clinicians can reliably use the mHealth severity score as a proxy measure for screening and monitoring behavioral health symptoms longitudinally. The severity score may identify at-risk individuals who are not identified by the PHQ-9. Further research is warranted to evaluate the sensitivity and specificity of the severity score.