Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial

Abstract

Background: Developing effective, widely useful, weight management programs is a priority in health care because obesity is a major health problem.

Objective: This study developed and investigated a new, comprehensive, multifactorial, daily, intensive, psychologist coaching program based on cognitive behavioral therapy (CBT) modules. The program was delivered via the digital health care mobile services Noom Coach and InBody.

Methods: This was an open-label, active-comparator, randomized controlled trial. A total of 70 female participants with BMI scores above 24 kg/m2 and no clinical problems besides obesity were randomized into experimental and control groups. The experimental (ie, digital CBT) group (n=45) was connected with a therapist intervention using a digital health care service that provided daily feedback and assignments for 8 weeks. The control group (n=25) also used the digital health care service, but practiced self-care without therapist intervention. The main outcomes of this study were measured objectively at baseline, 8 weeks, and 24 weeks and included weight (kg) as well as other body compositions. Differences between groups were evaluated using independent t tests and a per-protocol framework.

Results: Mean weight loss at 8 weeks in the digital CBT group was significantly higher than in the control group (-3.1%, SD 4.5, vs -0.7%, SD 3.4, P=.04). Additionally, the proportion of subjects who attained conventional 5% weight loss from baseline in the digital CBT group was significantly higher than in the control group at 8 weeks (32% [12/38] vs 4% [1/21], P=.02) but not at 24 weeks. Mean fat mass reduction in the digital CBT group at 8 weeks was also significantly greater than in the control group (-6.3%, SD 8.8, vs -0.8%, SD 8.1, P=.02). Mean leptin and insulin resistance in the digital CBT group at 8 weeks was significantly reduced compared to the control group (-15.8%, SD 29.9, vs 7.2%, SD 35.9, P=.01; and -7.1%, SD 35.1, vs 14.4%, SD 41.2, P=.04). Emotional eating behavior (ie, mean score) measured by questionnaire (ie, the Dutch Eating Behavior Questionnaire) at 8 weeks was significantly improved compared to the control group (-2.8%, SD 34.4, vs 21.6%, SD 56.9, P=.048). Mean snack calorie intake in the digital CBT group during the intervention period was significantly lower than in the control group (135.9 kcal, SD 86.4, vs 208.2 kcal, SD 166.3, P=.02). Lastly, baseline depression, anxiety, and self-esteem levels significantly predicted long-term clinical outcomes (24 weeks), while baseline motivation significantly predicted both short-term (8 weeks) and long-term clinical outcomes.

Conclusions: These findings confirm that technology-based interventions should be multidimensional and are most effective with human feedback and support. This study is innovative in successfully developing and verifying the effects of a new CBT approach with a multidisciplinary team based on digital technologies rather than standalone technology-based interventions.

Trial registration: ClinicalTrials.gov NCT03465306; https://ichgcp.net/clinical-trials-registry/NCT03465306.

Keywords: cognitive behavioral therapy; digital health care; mobile phone; obesity.

Conflict of interest statement

Conflicts of Interest: YK is an employee of Noom.

©Meelim Kim, Youngin Kim, Yoonjeong Go, Seokoh Lee, Myeongjin Na, Younghee Lee, Sungwon Choi, Hyung Jin Choi. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 30.04.2020.

Figures

Figure 1

Digital cognitive behavioral therapy (CBT) CONSORT (Consolidated Standards of Reporting Trials) flow diagram. SIMS: Situational Motivation Scale.

Figure 2

Diagram of the digital cognitive behavioral therapy (CBT) process.

Figure 3

Screenshots of the digital platform (ie, mobile apps) for the participants (top) and screenshots of the digital platform (ie, dashboard) for the therapist (ie, clinical psychologist) (bottom).

Figure 4

Patterns of changes in mean body weight (A), BMI (B), body fat mass (C), and lean body mass (LBM) (D). CBT: cognitive behavioral therapy. *P<.05; **P<.01.

Figure 5

Weight change based on individual data from the experimental group at the 8-week follow-up (A), from the experimental group at the 24-week follow-up (B), from the control group at the 8-week follow-up (C), and from the control group at the 24-week follow-up (D). CBT: cognitive behavioral therapy.

Figure 6

Changes in meal calories between experimental and control groups during the intervention period, as well as the contrast of mean energy intake between groups. *P<.05; ** P<.01.

Figure 7

Patterns of changes in engagement rate of the experimental and control groups during the intervention period. *P<.05.

Figure 8

The correlation between weight change at the long-term follow-up period (24 weeks) and the level of motivation, self-esteem, depression, and anxiety at baseline. Also shown are the correlation between BMI change at the long-term follow-up and the level of motivation at baseline, and the correlation between fat mass change at the long-term follow-up and lean body mass at baseline. K-BDI: Korean version of the Beck Depression Inventory; RSES: Rosenberg Self-Esteem Scale; SIMS: Situational Motivation Scale; TAI: Trait Anxiety Inventory.

Figure 9

The clinical efficacy of digital cognitive behavioral therapy (CBT) by applying the optimal cutoff scores of the predictive markers in the clinical setting. The pink line represents the threshold for successful weight loss.