Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder
Open accessAbstract
BACKGROUND: Traditionally, assessment of psychiatric symptoms has been relying on their retrospective report to a trained interviewer. The emergence of smartphones facilitates passive sensor-based monitoring and active real-time monitoring through time-stamped prompts; however there are few validated self-report measures designed for this purpose. METHODS: We introduce a novel, compact questionnaire, Mood Zoom (MZ), embedded in a customised smart-phone application. MZ asks participants to rate anxiety, elation, sadness, anger, irritability and energy on a 7-point Likert scale. For comparison, we used four standard clinical questionnaires administered to participants weekly to quantify mania (ASRM), depression (QIDS), anxiety (GAD-7), and quality of life (EQ-5D). We monitored 48 Bipolar Disorder (BD), 31 Borderline Personality Disorders (BPD) and 51 Healthy control (HC) participants to study longitudinal (median±iqr: 313±194 days) variation and differences of mood traits by exploring the data using diverse time-series tools. RESULTS: MZ correlated well (|R|>0.5,p<0.0001) with QIDS, GAD-7, and EQ-5D. We found statistically strong (|R|>0.3,p<0.0001) differences in variability in all questionnaires for the three cohorts. Compared to HC, BD and BPD participants exhibit different trends and variability, and on average had higher self-reported scores in mania, depression, and anxiety, and lower quality of life. In particular, analysis of MZ variability can differentiate BD and BPD which was not hitherto possible using the weekly questionnaires. LIMITATIONS: All reported scores rely on self-assessment; there is a lack of ongoing clinical assessment by experts to validate the findings. CONCLUSIONS: MZ could be used for efficient, long-term, effective daily monitoring of mood instability in clinical psychiatric practice.
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In depression, mobile apps have tracked changes in patient-reported mood.
“In depression, mobile apps have tracked changes in patient-reported mood [27-29] and have been used as part of randomized controlled trials to evaluate treatment efficacy [30].”
From Wearable technology for high-frequency cognitive and mood assessment in major depressive disorder: longitudinal observational study (2019) · cites this paper as [29]
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- Authors
- Tsanas, A., Saunders, K. E. A., Bilderbeck, A. C., Palmius, N., Osipov, M., Clifford, G. D., Goodwin, G. Μ., & De Vos, M.
- Affiliations
- University of Oxford (GB)
- Georgia Institute of Technology (US)
- Corresponding author
- Tsanas, A.
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 205
- Pages
- 225-233
- ISSN
- 0165-0327 (ISSN-L)
- PMC
- PMC5296237
- OpenAlex
- W2466601107
- Cited by
- 162
- References
- 49
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 13 · 2023: 14 · 2022: 17 · 2021: 22 · 2020: 28 · 2019: 16 · 2018: 11 · 2017: 16 · 2016: 1
- FWCI
- 13.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Affective Disorders (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- Wellcome Trust (98,461/Z/12/Z)
- CONBRIO (102,616/Z)
- RCUK Digital Economy Programme (EP/G036861/1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- mood variability, bipolar disorder, borderline personality disorder, mania, depression, anxiety, quality of life, mood instability
- MeSH terms
- Adolescent, Adult, Affect, Anger, Anxiety, Bipolar Disorder, Borderline Personality Disorder, Depression, Female, Humans, Irritable Mood, Male, Middle Aged, Quality of Life, Surveys and Questionnaires, Self-Assessment, Young Adult, Self Report
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