Optimizing a Smartphone Application for Individuals With Eating Disorders
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|ClinicalTrials.gov Identifier: NCT02503098|
Recruitment Status : Unknown
Verified February 2017 by Recovery Record Research.
Recruitment status was: Recruiting
First Posted : July 20, 2015
Last Update Posted : February 20, 2017
|Condition or disease||Intervention/treatment||Phase|
|Eating Disorders Binge Eating Disorder Bulimia Nervosa||Behavioral: Recovery Record adaptive smartphone application Behavioral: Recovery Record standard smartphone application||Not Applicable|
Eating Disorders (ED) are common and serious psychological disorders. Anorexia Nervosa (AN) has a prevalence estimated at between 0.48% and 0.70% among young females. Bulimia Nervosa (BN) is a serious mental health problem, with a prevalence of between 1-2% of young women while clinically significant bulimic behaviors occur in an additional 2-3%. There are significant barriers to access of evidence-based treatments and current models of individual psychotherapy will likely never meet the enormous need for psychological services for ED. Unfortunately, even with treatment, rates of recovery are modest with the best performing treatments achieving remission in only about 50% of cases while relapse rates are high, especially if the ED becomes chronic. It is widely acknowledged that a major shift in intervention practice is needed and that smartphone apps will almost certainly play a role due to their reach and breadth of functionality.
As the first commercially available smartphone app for EDs, Recovery Record (RR) has established wide reach and user acceptability. The app provides users with meal and ED symptom self-monitoring and coping skill strategies in an evidence-based CBT format. Preliminary pilot data suggest that for a proportion of RR users, using RR is associated with clinically significant symptom reduction. However, a limitation of the current app is that it is a "one-size-fits-all" product that does not account for the heterogeneity of ED symptoms. Genetic, personality and neurocognitive data support distinct clusters of ED presentations that also differ according to response to treatment, course and outcome. Pilot data confirm that clinical response to RR is not homogenous across groups and that extent of cognitive distortions is the most potent factor to predict outcome. There is considerable opportunity to increase RR's effectiveness across a range of ED symptoms and behaviors by creating adaptive and tailored content focused on remediation of cognitive distortions.
During Phase 1 of this study screening algorithm will be validated against an unseen, prospective test dataset of approximately 2,000 users. All candidate predictor variables will be entered into a Signal Detection Analysis to confirm the sensitivity and specificity of the screen. Informed by the resultant algorithms, adaptive content will be developed that targets ED-specific cognitive distortions. To evaluate acceptability, adapted content will be piloted with approximately 200 individuals for a period of one month. Participant feedback and utilization data will inform content acceptability and feasibility. By the end of the first phase tailored content that is acceptable to individuals with specific symptom presentations will be developed.
Phase 2 will focus on an evaluation of whether an adaptive app offering tailored content addressing eating related cognitive distortions in a stepped way can outperform the current standard app. The adaptive content will be integrated into a new, dynamic version of the app (RR-A) that will then be evaluated against the current app (RR-S). Approximately 5,000 registered users of RR will be randomized to receive either RR augmented with targeted content (RR-A), or RR in its current standard format (RR-S) over a two-month period. Outcome data will be measured at baseline, one month, end of treatment, and at six-month follow-up. At the end of the study period it is predicted that the resultant evidence-based product will have demonstrated ability to bring about clinically significant reduction in symptoms in more users than the current app, and thus will have potential to make a substantial public health impact.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||5000 participants|
|Intervention Model:||Parallel Assignment|
|Official Title:||Optimizing a Smartphone Application for Individuals With Eating Disorders|
|Actual Study Start Date :||November 23, 2016|
|Estimated Primary Completion Date :||March 23, 2018|
|Estimated Study Completion Date :||May 23, 2018|
Experimental: Recovery Record adaptive smartphone application (RR-A)
Participants will have access to all Recovery Record standard functions and will additionally receive tailored, algorithm-generated content targeting cognitive distortions.
Behavioral: Recovery Record adaptive smartphone application
Active Comparator: Recovery Record standard smartphone application (RR-S)
Participants will have access to all Recovery Record standard functions, including meal monitoring, motivational enhancement, social support, and coping skill strategies.
Behavioral: Recovery Record standard smartphone application
- Changes in Eating Disorder Severity [ Time Frame: Measured at the start of treatment (baseline), week 4, week 8 and 6 months follow-up ]Self-reported eating disorder symptom severity. To measure changes in eating disorder severity over time, the Eating Disorder Evaluation Questionnaire (EDE-Q) will be used.
- Binge eating and purging episode frequency [ Time Frame: Measured at the start of treatment (baseline), week 4, week 8 and 6 months follow-up ]Self-reported disordered behavior frequency will be assessed via behaviors self-monitored in the application in addition to symptom frequency questions in the Eating Disorder Evaluation Questionnaire.
- Changes in Clinical Impairment Severity [ Time Frame: Measured at the start of treatment (baseline), week 4, week 8 and 6 months follow-up ]To measure changes in eating disorder related clinical impairment over time, the self-reported Clinical Impairment Assessment (CIA) will be used.
- Participant Satisfaction [ Time Frame: Participants will be followed for the duration of the 8-week trial ]Self-reported satisfaction
- Adherence to the mobile application intervention [ Time Frame: Measured from the start of application utilization (baseline) to 8-weeks ]Adherence will be measured via dichotomous outcome of drop-out (an individual will be considered a system drop-out if they fail to login to the app at all for a period of 14 consecutive days). Adherence will be assessed through application usage data.
- Adherence to self-monitoring tasks [ Time Frame: Measured from the start of application utilization (baseline) to 8-weeks ]Frequency of self-monitoring entries will be tracked automatically through the program server.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02503098
|Contact: Jenna P Tregarthenemail@example.com|
|Contact: Alison M Darcy, PhD||650 736 firstname.lastname@example.org|
|United States, California|
|Recovery Record Research||Recruiting|
|San Francisco, California, United States, 94107|
|Contact: Jenna P Tregarthen 650-404-7098 email@example.com|
|Principal Investigator: Jenna P Tregarthen, PgDip|
|Stanford University School of Medicine, Department of Psychiatry and Behavioral Sciences||Recruiting|
|Stanford, California, United States, 94304|
|Contact: Alison Darcy, PhD 650-736-7972 firstname.lastname@example.org|
|Principal Investigator: James Lock, M.D., PhD|
|Sub-Investigator: Alison Darcy, PhD|
|Sub-Investigator: Kim J Piak, PhD|