Clinical trial NCT03490253: Diabetes and Depression Text Messaging Intervention
Official title: Improving Diabetes and Depression Self-management Via Adaptive Mobile Messaging
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Diabetes
Depression
Physical Activity
Lead sponsor: University of California, San Francisco
Sponsor class: OTHER
Collaborators: name: University of California, Berkeley
name: Agency for Healthcare Research and Quality (AHRQ)
First posted: 2018-04-06
Enrollment: 226
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: This study is a randomized, controlled, one-center superiority trial with three-arm groups and a primary endpoint of increase in daily steps during a 6 month intervention by a smartphone app. Randomization will be performed as block randomization with a 1:1:1 allocation. Patients will be automatically randomized into groups trough our secure server during on-boarding of the app. Patients need to be informed of the nature and frequency of the messages they will be receiving and discuss this with investigators during the course of the study. Therefore, investigators and patients will not be blinded. We used the SPIRIT checklist when writing our report.
Primary purpose: OTHER

Brief summary: The main aim of the "Diabetes and Mental Health Adaptive Notification Tracking and Evaluation" trial (DIAMANTE) is to test a smartphone intervention that generates adaptive messaging, learning from daily patient data to personalize the timing and type of text-messages. We will compare the adaptive content to 1. a static messaging intervention with health management and educational messages and 2. a control condition that receives a weekly mood message. The primary outcomes for this aim will be improvements in physical activity at 6-month follow-up defined by daily step counts.

Detailed description: We utilized user-centered design (UCD) methods to iteratively develop the DIAMANTE content and text messaging system through three iterative phases of UCD with ten patients each (total n=30). The first phase consisted of 1.5-hour individual semi-structured interviews. Findings from phase 1 were used to inform content and information delivery decisions of the final intervention, including selecting the thematic message categories and the design. In the second phase, patients tested out an early prototype of the mobile application through usability testing. Patients tested the final DIAMANTE intervention including thematic message content and the application in the third, final UCD phase, in order to address any user-related issues prior to launching the randomized control trial.

In the DIAMANTE Randomized Controlled Trial, we aim to examine the effect of a smartphone app that uses reinforcement learning to predict the most effective messages for increasing physical activity. We will recruit 276 low-income minority patients with depression and diabetes within he San Francisco Health Network. We will compare this intervention to static messages with health management content, and a control group that only receives a weekly mood message.

Eligibility criteria: Inclusion Criteria:

* HbA1c (Hemoglobin A1c) \> 7
* PHQ-8 (Patient Health Questionnaire-8) \> 5

Exclusion Criteria:

* high levels of physical activity (\>30 minutes of moderate to vigorous activity per day)
* pregnancy
* inability to exercise due to physical disability
* serious mental illness
* unable to read and write in English or Spanish
* plans to leave the country for extended periods of time during the trial

Primary outcomes:
measure: Physical Activity
timeFrame: 6 months
Secondary outcomes:
measure: Hemoglobin A1c
timeFrame: 6 months
measure: Patient Health Questionnaire-8 (PHQ-8)
timeFrame: 6 months
Other outcomes:
Locations:
city: San Francisco
country: United States
facility: Zuckerberg San Francisco General Hospital/University of California, San Francisco
state: California
Study officials:
affiliation: University of California, San Francisco
name: Courtney Lyles, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: UC Berkeley
name: Adrian Aguilera, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Aguilera A, Schueller SM, Leykin Y. Daily mood ratings via text message as a proxy for clinic based depression assessment. J Affect Disord. 2015 Apr 1;175:471-4. doi: 10.1016/j.jad.2015.01.033. Epub 2015 Jan 29.
citation: Lyles CR, Ratanawongsa N, Bolen SD, Samal L. mHealth and Health Information Technology Tools for Diverse Patients with Diabetes. J Diabetes Res. 2017;2017:1704917. doi: 10.1155/2017/1704917. Epub 2017 Feb 23. No abstract available.
citation: Nouri SS, Avila-Garcia P, Cemballi AG, Sarkar U, Aguilera A, Lyles CR. Assessing Mobile Phone Digital Literacy and Engagement in User-Centered Design in a Diverse, Safety-Net Population: Mixed Methods Study. JMIR Mhealth Uhealth. 2019 Aug 29;7(8):e14250. doi: 10.2196/14250.
citation: Avila-Garcia P, Hernandez-Ramos R, Nouri SS, Cemballi A, Sarkar U, Lyles CR, Aguilera A. Engaging users in the design of an mHealth, text message-based intervention to increase physical activity at a safety-net health care system. JAMIA Open. 2019 Oct 11;2(4):489-497. doi: 10.1093/jamiaopen/ooz049. eCollection 2019 Dec.
citation: Hernandez-Ramos R, Aguilera A, Garcia F, Miramontes-Gomez J, Pathak LE, Figueroa CA, Lyles CR. Conducting Internet-Based Visits for Onboarding Populations With Limited Digital Literacy to an mHealth Intervention: Development of a Patient-Centered Approach. JMIR Form Res. 2021 Apr 29;5(4):e25299. doi: 10.2196/25299.
citation: Figueroa CA, Aguilera A, Chakraborty B, Modiri A, Aggarwal J, Deliu N, Sarkar U, Jay Williams J, Lyles CR. Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions. J Am Med Inform Assoc. 2021 Jun 12;28(6):1225-1234. doi: 10.1093/jamia/ocab001.
citation: Aguilera A, Figueroa CA, Hernandez-Ramos R, Sarkar U, Cemballi A, Gomez-Pathak L, Miramontes J, Yom-Tov E, Chakraborty B, Yan X, Xu J, Modiri A, Aggarwal J, Jay Williams J, Lyles CR. mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study. BMJ Open. 2020 Aug 20;10(8):e034723. doi: 10.1136/bmjopen-2019-034723.
citation: Figueroa CA, Deliu N, Chakraborty B, Modiri A, Xu J, Aggarwal J, Jay Williams J, Lyles C, Aguilera A. Daily Motivational Text Messages to Promote Physical Activity in University Students: Results From a Microrandomized Trial. Ann Behav Med. 2022 Feb 11;56(2):212-218. doi: 10.1093/abm/kaab028.