Mood instability in patients with unipolar depression measured using smartphones and the association with measures of wellbeing, recovery and functioning

Abstract

Objective

While mood instability is strongly linked to depression, its ramifications remain unexplored. In patients diagnosed with unipolar depression (UD), our objective was to investigate the association between mood instability, calculated based on daily smartphone-based patient-reported data on mood, and functioning, quality of life, perceived stress, empowerment, rumination, recovery, worrying and wellbeing.

Methods

Patients with UD completed daily smartphone-based self-assessments of mood for 6 months, making it possible to calculate mood instability using the Root Mean Squared Successive Difference (rMSSD) method. A total of 59 patients with UD were included. Data were analyzed using mixed effects regression models.

Results

There was a statistically significant association between increased mood instability and increased perceived stress (adjusted model: B: 0.010, 95% CI: 0.00027; 0.021, p = 0.044), and worrying (adjusted model: B: 0.0060, 95% CI: 0.000016; 0.012, p = 0.049), and decreased quality of life (adjusted model: B: −0.0056, 95% CI: −0.011; −0.00028, p = 0.039), recovery (adjusted model: B: −0.032, 95% CI: −0.0059; −0.00053, p = 0.019) and wellbeing. There were no statistically significant associations between mood instability and functioning, empowerment, and rumination (p’s >0.09).

Conclusion

These findings underscore the significant influence of mood instability on patients’ daily lives. Identification of mood fluctuations offer potential insights into the trajectory of the illness in these individuals.

Keywords:

• Unipolar depression
• mood instability
• smartphone

Acknowledgements

The authors would like to thank the patients for participating in the trials, and the nurses involved in the trials.

Disclosure statement

DR, JoB, and MLT have no competing interests. LVK has been a consultant for Lundbeck and Teva within the past 3 years. MFJ has been a consultant for Jannsen Cilag within the past 3 years. MF and JEB are co-founders and shareholders in Monsenso.

Additional information

Funding

The RADMIS trial was funded by Innovation Fund Denmark [5164-00001B9]. MFJ was funded by The Danish Council for Independent Research, Medical Sciences [DFF—0134-00027B].

Notes on contributors

Lars Vedel Kessing

Lars Vedel Kessing, Professor, MD, DMSc in psychiatry University of Copenhagen with a special focus on affective disorders and the course of illness.

Morten Lindberg Tønning

Morten Lindberg Tønning, MD, PhD, resident in psychiatry, Mental Health Services, Capital Region of Denmark. Research focus is mainly on unipolar disorder.

Jonas Busk

Jonas Busk, PhD, Scientific Software Developer. Danish Technical University, Denmark. Main focus is on machine learning models and data analysis.

Darius Rohani

Darius Rohani, PhD. Co-founder of Kuatro group and head of AI. Mads Frost: PhD. Co-founder of Monsenso A/S.

Jakob Eyvind Bardram

Jakob Eyvind Bardram, Professor in computer science at the Danish Technical University, Denmark. He directs the Copenhagen Center for Health Technology (CACHET).

Maria Faurholt-Jepsen

Maria Faurholt-Jepsen, MD, DMSc, Ass. Res. Prof. in psychiatry University of Copenhagen with a special focus on affective disorders and the use of digital tool for monitoring and treatment.