Search

Abstract The nature of data obtainable from the commercial smartphone – bolstered by a translational model emphasizing the impact of social and physical zeitgebers on circadian rhythms and mood – offers the possibility of scalable and objective vital signs for major depression. Our objective was to explore associations between passively sensed behavioral smartphone data and repeatedly measured depressive symptoms to suggest which features could eventually lead towards vital signs for depression. We collected continuous behavioral data and bi-weekly depressive symptoms (PHQ-8) from 131 psychiatric outpatients with a lifetime DSM-5 diagnosis of depression and/or anxiety over a 16-week period. Using linear mixed-effects models, we related depressive symptoms to concurrent passively sensed behavioral summary features (mean and variability of sleep, activity, and social engagement metrics), considering both between- and within-person associations. Individuals with more variable wake-up times across the study reported higher depressive symptoms relative to individuals with less variable wake-up times (B [95% CI] = 1.53 [0.13, 2.93]). On a given week, having a lower step count (−0.16 [−0.32, −0.01]), slower walking rate (−1.46 [−2.60, −0.32]), lower normalized location entropy (−3.01 [−5.51, −0.52]), more time at home (0.05 [0.00, 0.10]), and lower distances traveled (−0.97 [−1.72, −0.22]), relative to one’s own typical levels, were each associated with higher depressive symptoms. With replication in larger samples and a clear understanding of how these components are best combined, a behavioral composite measure of depression could potentially offer the kinds of vital signs for psychiatric medicine that have proven invaluable to assessment and decision-making in physical medicine. Clinical Trials Registration: The data that form the basis of this report were collected as part of clinical trial number NCT03152864.

We conducted a 16-week randomized controlled trial in psychiatric outpatients with a lifetime diagnosis of a mood and/or anxiety disorder to measure the impact of a first-of-its-kind precision digital intervention software solution based on social rhythm regulation principles. The full intent-to-treat (ITT) sample consisted of 133 individuals, aged 18–65. An exploratory sub-sample of interest was those individuals who presented with moderately severe to severe depression at study entry (baseline PHQ-8 score ≥15; N = 28). Cue is a novel digital intervention platform that capitalizes on the smartphone's ability to continuously monitor depression-relevant behavior patterns and use each patient's behavioral data to provide timely, personalized “micro-interventions,” making this the first example of a precision digital intervention of which we are aware. Participants were randomly allocated to receive Cue plus care-as-usual or digital monitoring only plus care as usual. Within the full study and depressed-at-entry samples, we fit a mixed effects model to test for group differences in the slope of depressive symptoms over 16 weeks. To account for the non-linear trajectory with more flexibility, we also fit a mixed effects model considering week as a categorical variable and used the resulting estimates to test the group difference in PHQ change from baseline to 16 weeks. In the full sample, the group difference in the slope of PHQ-8 was negligible (Cohen's d = −0.10); however, the Cue group demonstrated significantly greater improvement from baseline to 16 weeks (p = 0.040). In the depressed-at-entry sample, we found evidence for benefit of Cue. The group difference in the slope of PHQ-8 (Cohen's d = −0.72) indicated a meaningfully more rapid rate of improvement in the intervention group than in the control group. The Cue group also demonstrated significantly greater improvement in PHQ-8 from baseline to 16 weeks (p = 0.009). We are encouraged by the size of the intervention effect in those who were acutely ill at baseline, and by the finding that across all participants, 80% of whom were receiving pharmacotherapy, we observed significant benefit of Cue at 16 weeks of treatment. These findings suggest that a social rhythm-focused digital intervention platform may represent a useful and accessible adjunct to antidepressant treatment (https://clinicaltrials.gov/ct2/show/NCT03152864?term=ellen+frank&draw=2&rank=3).

OBJECTIVE: This article describes the adaptation of a rating scale of interpersonal psychotherapy problem areas to include a fifth problem area appropriate to bipolar disorder and an interrater agreement study in identifying interpersonal problem areas and selecting a primary treatment focus if patients were to engage in treatment. METHOD: Five research interpersonal psychotherapists assessed nine audiotapes of a single interview with five bipolar and four unipolar patients in which the interpersonal inventory and identification of problem areas were undertaken. RESULTS: Raters agreed on presence and absence of problem areas in seven tapes. Kappas for identification of problem areas were 1.00 (grief), 0.77 (role dispute), 0.61 (role transition), 0.57 (interpersonal deficits) and 1.00 (loss of healthy self). Kappa for agreement on a primary clinical focus if patients were to engage in interpersonal psychotherapy treatment was 0.64. CONCLUSIONS: The adaptation of the original scale to include an area pertinent to bipolar disorder proved to be applicable and relevant for use with this population. The results show substantial interrater agreement in identifying problem areas and potential treatment focus.OBJETIVO: Este artigo descreve a adaptação de uma escala de avaliação de áreas problema da psicoterapia interpessoal que inclui uma área própria ao transtorno bipolar e um estudo de concordância em identificar áreas problema e selecionar um foco primário de tratamento caso os pacientes fossem participar de tratamento. MÉTODO: Cinco terapeutas interpessoais avaliaram nove audiotapes de uma única entrevista com cinco pacientes bipolares e quatro pacientes unipolares em que o inventário interpessoal e identificação de áreas problema foram empreendidos. RESULTADOS: Os avaliadores concordaram na presença e ausência de áreas problema em sete fitas. Kappas para identificação de áreas problema foram 1,00 (luto), 0,77 (disputa de papel), 0,61 (transição de papel), 0,57 (déficits interpessoais) e 1,00 (perda do self sadio). Kappa para concordância num foco de tratamento clínico foi 0,64. CONCLUSÕES: A adaptação da escala original para incluir área pertinente ao transtorno bipolar mostrou-se relevante para o uso com tal população. Os resultados demonstram uma concordância substancial entre avaliadores na identificação de áreas problema e foco de tratamento.