Effect of Integrating Patient-Generated Digital Data Into Mental Health Therapy: A Randomized Controlled Trial.

OBJECTIVE The authors sought to determine whether providing summaries of patients' social media and other digital data to patients and their clinicians improves patients' health-related quality of life (HRQoL) measured by the RAND 36-Item Short Form Health Survey (SF-36). METHODS The authors randomly assigned 115 adults receiving outpatient mental health therapy to usual care or to periodic sharing of summaries of their digital data with their clinician providing psychosocial therapy. The study was conducted October 2020-December 2021. RESULTS Patients' mean±SD age was 31.3±10.5 years, and 82% were women. At 60 days after enrollment, no statistically significant change was detected in SF-36 scores for patients randomly allocated to the intervention (mean difference=-0.39, 95% CI=-4.17, 3.39) or to usual care (mean difference=-1.98, 95% CI=-5.74, 1.77), and no significant between-arm difference was observed (between-arm difference=1.60, 95% CI=-3.67, 6.86). CONCLUSIONS Collecting and summarizing digital data for use in mental health treatment was feasible for patients but did not significantly improve their HRQoL or other measures of mental health.

[1]  R. Merchant,et al.  Perspectives of Patients and Therapists on Social Media and Digital Data Use in Mental Health Therapy: Thematic Analysis , 2022, JMIR formative research.

[2]  K. Ressler,et al.  Measuring and Quantifying Collateral Information in Psychiatry: Development and Preliminary Validation of the McLean Collateral Information and Clinical Actionability Scale , 2021, JMIR mental health.

[3]  Dong Whi Yoo,et al.  Clinician Perspectives on Using Computational Mental Health Insights From Patients’ Social Media Activities: Design and Qualitative Evaluation of a Prototype , 2020, JMIR mental health.

[4]  C. Botella,et al.  Affect Recall Bias: Being Resilient by Distorting Reality , 2020, Cognitive Therapy and Research.

[5]  Richard Bruggeman,et al.  Insights of Patients and Clinicians on the Promise of the Experience Sampling Method for Psychiatric Care. , 2019, Psychiatric services.

[6]  S. Rauch,et al.  Incorporating Information From Electronic and Social Media Into Psychiatric and Psychotherapeutic Patient Care: Survey Among Clinicians , 2019, Journal of medical Internet research.

[7]  Sharath Chandra Guntuku,et al.  Evaluating the predictability of medical conditions from social media posts , 2019, PloS one.

[8]  D. Asch,et al.  Facebook language predicts depression in medical records , 2018, Proceedings of the National Academy of Sciences.

[9]  Brian W. Powers,et al.  The digital phenotype , 2015, Nature Biotechnology.

[10]  B. Löwe,et al.  A brief measure for assessing generalized anxiety disorder: the GAD-7. , 2006, Archives of internal medicine.

[11]  R. Spitzer,et al.  The PHQ-9 , 2001, Journal of General Internal Medicine.

[12]  S. Sabourin,et al.  Client satisfaction and social desirability in psychotherapy , 1992 .

[13]  C. Sherbourne,et al.  The MOS 36-Item Short-Form Health Survey (SF-36) , 1992 .

[14]  A. Horvath,et al.  Development and validation of the Working Alliance Inventory. , 1989 .