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OBJECTIVES: To determine the compliance and clinical utility of weekly and daily electronic mood symptom monitoring in adolescents and young adults at risk for mood disorder. METHODS: Fifty emerging adult offspring of bipolar parents were recruited from the Flourish Canadian high-risk offspring cohort study along with 108 university student controls. Participants were assessed by KSADS/SADS-L semi-structured interviews and used a remote capture method to complete weekly and daily mood symptom ratings using validated scales for 90 consecutive days. Hazard models and generalized estimating equations were used to determine differences in summary scores and regularity of ratings. RESULTS: Seventy-eight and 77% of high-risk offspring and 97% and 93% of controls completed the first 30 days of weekly and daily ratings, respectively. There were no differences in drop-out rates between groups over 90 days (weekly P = 0.2149; daily P = 0.9792). There were no differences in mean summary scores or regularity of weekly anxiety, depressive or hypomanic symptom ratings between high-risk offspring and control groups. However, high-risk offspring compared to controls had daily ratings indicating lower positive affect, higher negative affect and lower self-esteem (P = 0.0317). High-risk offspring with remitted mood disorder compared to those without had more irregularity in weekly anxiety and depressive symptom ratings and daily ratings of lower positive affect, higher negative affect, and higher shame and self-doubt (P = 0.0365). CONCLUSIONS: Findings support that high-resolution electronic mood tracking may be a feasible and clinically useful approach in monitoring emerging psychopathology in young people at high-risk offspring of mood disorder onset or recurrence.

Original publication

DOI

10.1111/bdi.12721

Type

Journal article

Journal

Bipolar Disord

Publication Date

13/11/2018

Keywords

affect, bipolar disorder, compliance, high-risk offspring, offspring, online, regularity, remote capture, self-esteem, self-report symptoms, symptom monitoring