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Cited by 56Digital Mental Health InterventionsMobile Health and mHealth ApplicationsObesity, Physical Activity, Diet

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

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Kim, Meelim, Kim, Youngin, Go, Yoonjeong, Lee, Seokoh, Na, Myeongjin, Lee, Younghee, Choi, Sungwon, Choi, Hyung Jin·2020·JMIR mHealth and uHealth
DOI 10.2196/14817PMC PMC7226050

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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://clinicaltrials.gov/ct2/show/NCT03465306

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  • A multidimensional approach with human feedback and support based on elements of CBT and SCT is most effective in the treatment of depression symptoms in individuals with obesity.

    “The outcomes of studies conducted by Chang et al. (45), Kim et al. (47), and Young et al. (42) showed that a multidimensional approach with human feedback and support based on elements of the CBT and SCT are most effective in the treatment of depression symptoms in individuals with obesity.”

    From Efficacy of eHealth interventions to reduce depression symptoms in individuals with obesity: a systematic review of randomized controlled trials (2024) · cites this paper as Kim et al. (47)

    The Abstract Conclusions say the multidimensional digital CBT intervention is most effective with human feedback and support, but the study frames that conclusion around obesity treatment. The Results (Secondary Outcomes: Metabolic and Psychological Outcomes; no page given) report a significant within-group change in depression scores at 24 weeks, but no significant between-group difference in psychological outcomes other than emotional eating. The cited paper therefore does not establish that this approach is most effective for treating depression symptoms, and the passages do not identify SCT as part of the intervention. (LLM, conf=0.88)

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  • Baseline depression symptoms significantly predicted long-term clinical outcomes.

    “Baseline depression symptoms significantly predicted long-term clinical outcomes.”

    From Efficacy of eHealth interventions to reduce depression symptoms in individuals with obesity: a systematic review of randomized controlled trials (2024) · cites this paper as Kim et al. (47)

  • Digital CBT improved the level of depression symptoms.

    “The findings of the study by Kim et al. (47) which investigated a new, comprehensive, multifactorial, daily, intensive psychologist coaching based on CBT modules, showed that digital CBT improved the level of depression symptoms.”

    From Efficacy of eHealth interventions to reduce depression symptoms in individuals with obesity: a systematic review of randomized controlled trials (2024) · cites this paper as Kim et al. (47)

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Research works printed but not linked: 1

  1. [6]Brennan L Cognitive Behavioural Evaluation and Treatment of Adolescent Overweight and Obesity [doctoral thesis] 2006 8 31 2006-08-31 Melbourne, Australia RMIT University http://researchbank.rmit.edu.au/eserv/rmit:6333/Brennan.pdf

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Authors
Kim, M., Kim, Y., Go, Y., Lee, S., Na, M., Lee, Y., Choi, S., & Choi, H. J.
Affiliations
  • Seoul National University (KR)
  • Duksung Women's University (KR)
Corresponding author
Choi, Hyung Jin
ORCID
Venue
JMIR mHealth and uHealth
Publisher
JMIR Publications Inc.
Published
2020-04-30
Volume
8
Issue
4
Pages
e14817
ISSN
2291-5222 (ISSN-L)
DOI
10.2196/14817
PMC
PMC7226050
OpenAlex
W3005776191
Cited by
56
References
55
Citations by year
2026: 6 · 2025: 10 · 2024: 14 · 2023: 10 · 2022: 8 · 2021: 7 · 2020: 1
FWCI
5.87
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • YUHSpace (Yonsei University Medical Library) (submittedVersion, cc-by-nc-nd)
  • Seoul National University Open Repository (Seoul National University) (submittedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords
obesity, cognitive behavioral therapy, digital health interventions, weight loss, mobile health, fat mass reduction, leptin, insulin resistance, emotional eating, body composition, weight management interventions, dietary habits, eating disorders, eating disorders in children and adolescents, eating disorders in adults
MeSH terms
Feeding Behavior, Female, Humans, Obesity, Weight Loss, Cognitive Behavioral Therapy

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