Utilization of Patient-Generated Data Collected Through Mobile Devices: Insights From a Survey on Attitudes Toward Mobile Self-Monitoring and Self-Management Apps for Depression

Background Depression is a severe psychiatric disease with high prevalence and an elevated risk for recurrence and chronicity. A substantial proportion of individuals with a diagnosis of unipolar depressive disorder do not receive treatment as advised by national guidelines. Consequently, self-monitoring and self-management become increasingly important. New mobile technologies create unique opportunities to obtain and utilize patient-generated data. As common adherence rates to mobile technologies are scarce, a profound knowledge of user behavior and attitudes and preferences is important throughout any developmental process of mobile technologies and apps. Objective The aim of this survey was to provide descriptive data upon usage and anticipated usage of self-monitoring and self-management of depression and preferences of potential users in terms of documented parameters and data-sharing options. Methods A Web-based survey comprising 55 questions was conducted to obtain data on the usage of mobile devices, app usage, and participant’s attitudes and preferences toward mobile health apps for the self-monitoring and self-management of depression. Results A total of 825 participants provided information. Moreover, two-thirds of the sample self-reported to be affected by depressive symptoms, but only 12.1% (81/668) of those affected by depression have ever used any mobile self-monitoring or self-management app. Analysis showed that people want personally relevant information and feedback but also focus on handling sensitive data. Conclusions New mobile technologies and smartphone apps, especially in combination with mobile sensor systems, offer unique opportunities to overcome challenges in the treatment of depression by utilizing the potential of patient-generated data. Focus on patient-relevant information, security and safe handling of sensitive personal data, as well as options to share data with self-selected third parties should be considered mandatory throughout any development process.

[1]  G. Andersson Internet-Delivered Psychological Treatments. , 2016, Annual review of clinical psychology.

[2]  Amanda L. Forest,et al.  When Social Networking Is Not Working , 2012, Psychological science.

[3]  Deborah Estrin,et al.  Identifying preferences for mobile health applications for self-monitoring and self-management: Focus group findings from HIV-positive persons and young mothers , 2013, Int. J. Medical Informatics.

[4]  J. Os,et al.  The size and burden of mental disorders and other disorders of the brain in Europe 2010 , 2011, European Neuropsychopharmacology.

[5]  J. Torous,et al.  A Hierarchical Framework for Evaluation and Informed Decision Making Regarding Smartphone Apps for Clinical Care. , 2018, Psychiatric services.

[6]  B. Arroll,et al.  Antidepressants for treatment of depression in primary care: a systematic review and meta-analysis. , 2016, Journal of primary health care.

[7]  L. Piwek,et al.  The Rise of Consumer Health Wearables: Promises and Barriers , 2016, PLoS medicine.

[8]  K. Riekert,et al.  User Preferences and Design Recommendations for an mHealth App to Promote Cystic Fibrosis Self-Management , 2014, JMIR mHealth and uHealth.

[9]  R. de Graaf,et al.  Recurrence and chronicity of major depressive disorder and their risk indicators in a population cohort , 2018, Acta psychiatrica Scandinavica.

[10]  M. Höfler,et al.  Twelve‐month prevalence, comorbidity and correlates of mental disorders in Germany: the Mental Health Module of the German Health Interview and Examination Survey for Adults (DEGS1‐MH) , 2014, International journal of methods in psychiatric research.

[11]  Laurie A. Rudman,et al.  Implicit self-esteem compensation: automatic threat defense. , 2007, Journal of personality and social psychology.

[12]  L. Yardley,et al.  The Person-Based Approach to Intervention Development: Application to Digital Health-Related Behavior Change Interventions , 2015, Journal of medical Internet research.

[13]  E. Schneider,et al.  Patient preferences for outcomes of depression treatment in Germany: a choice-based conjoint analysis study. , 2013, Journal of affective disorders.

[14]  L. Miller,et al.  Self-disclosure and liking: a meta-analytic review. , 1994, Psychological bulletin.

[15]  S. Riedel-Heller,et al.  Prevalence and correlates of DSM-IV-TR major depressive disorder, self-reported diagnosed depression and current depressive symptoms among adults in Germany. , 2016, Journal of affective disorders.

[16]  C. Sedikides,et al.  Self-Enhancement: Food for Thought , 2008, Perspectives on psychological science : a journal of the Association for Psychological Science.

[17]  N. Bauminger,et al.  Intimacy in adolescent friendship: The roles of attachment, coherence, and self-disclosure , 2008 .

[18]  K. Beesdo-Baum,et al.  The Treatment of Depression in Primary Care. , 2017, Deutsches Arzteblatt international.

[19]  J. Crocker,et al.  The costly pursuit of self-esteem. , 2004, Psychological bulletin.

[20]  K. Lohr,et al.  Comparative benefits and harms of second generation antidepressants and cognitive behavioral therapies in initial treatment of major depressive disorder: systematic review and meta-analysis , 2015, BMJ : British Medical Journal.

[21]  M. Höfler,et al.  [Erratum to: Mental disorders in the general population. Study on the health of adults in Germany and the additional module mental health (DEGS1-MH)]. , 2016, Der Nervenarzt.

[22]  Derek Smolenski,et al.  Behavioral Screening Measures Delivered With a Smartphone App: Psychometric Properties and User Preference , 2013, The Journal of nervous and mental disease.

[23]  U. Hapke,et al.  [Prevalence of depressive symptoms and diagnosed depression among adults in Germany: results of the German Health Interview and Examination Survey for Adults (DEGS1)]. , 2013, Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz.

[24]  Stefano Taddei,et al.  Privacy, trust and control: Which relationships with online self-disclosure? , 2013, Comput. Hum. Behav..

[25]  C. Ryan,et al.  Theoretical Perspectives of Adherence to Web-Based Interventions: a Scoping Review , 2018, International Journal of Behavioral Medicine.

[26]  G. Andersson,et al.  The efficacy of psychotherapy and pharmacotherapy in treating depressive and anxiety disorders: a meta‐analysis of direct comparisons , 2013, World psychiatry : official journal of the World Psychiatric Association.

[27]  U. Hegerl,et al.  Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review , 2017, Journal of medical Internet research.