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1 results

  • Digital assessment of nonverbal behaviors forecasts first onset of depression

  • Sekine Ozturk, Scott Feltman, Daniel N. Klein, Roman Kotov, Aprajita Mohanty
  • Journal:
    Psychological Medicine / Volume 54 / Issue 12 / September 2024
    Published online by Cambridge University Press:
    04 October 2024, pp. 3507-3518
    • Article
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  • Background

    Adolescence is marked by a sharp increase in the incidence of depression, especially in females. Identification of risk for depressive disorders (DD) in this key developmental stage can help prevention efforts, mitigating the clinical and public burden of DD. While frequently used in diagnosis, nonverbal behaviors are relatively understudied as risk markers for DD. Digital technology, such as facial recognition, may provide objective, fast, efficient, and cost-effective means of measuring nonverbal behavior.

    Method

    Here, we analyzed video-recorded clinical interviews of 359 never-depressed adolescents females via commercially available facial emotion recognition software.

    Results

    We found that average head and facial movements forecast future first onset of depression (AUC = 0.70) beyond the effects of other established self-report and physiological markers of DD risk.

    Conclusions

    Overall, these findings suggest that digital assessment of nonverbal behaviors may provide a promising risk marker for DD, which could aid in early identification and intervention efforts.