Nonverbal behaviors are associated with increased vagal activity in major depressive disorder: Implications for the polyvagal theory

Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review

BACKGROUND

Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful.

OBJECTIVE

We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common.

METHODS

We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma.

RESULTS

A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes.

CONCLUSIONS

Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.

Heart Rate Variability in Individual Psychotherapy: Associations With Alliance and Outcome

Heart rate variability (HRV) can be conceptualized as a marker of an individual's capability to adaptively respond to its environment and has been linked with mental health. Although conceptually and empirically linked to social behavior and thus relevant in the therapeutic setting, HRV is seldom investigated directly within therapy sessions. In the present examination, we aimed at addressing this research gap by assessing patients' and therapists' HRVs both ambulatory within therapy sessions and under resting conditions. Drawing on polyvagal theory, we hypothesized that higher in-session HRV is accompanied with higher therapeutic alliance ratings. Further, we expected baseline HRV to predict symptomatic outcome and to increase over the course of therapy. In a sample of 53 outpatients receiving 25 sessions of cognitive behavioral therapy, we measured HRV, therapeutic alliance and depressive symptoms on four occasions. Multilevel modeling analyses demonstrated that patients with higher in-session high-frequency HRV rated the therapeutic alliance higher. Baseline HRV predicted symptomatic outcome and increased over the course of therapy. Possible explanations involve a link between in-session HRV and in-session behavior and should be investigated in future studies. The results highlight the usefulness of in-session HRV as a promising process variable in psychotherapy research.