Introduction: While self-administered mobile app-based cognitive behavioral therapy (CBT) has shown efficiency and effectiveness over the past decade, attempts to address automatic and negative beliefs have been lacking. The purpose of this study was to introduce and verify a mobile app that directly intervenes in dysfunctional thoughts. This app-based treatment includes recognizing automatic and negative thoughts of the protagonist of scenarios, writing advice directly to the main character, and sharing advice provided by other participants. Materials and Methods: Thirty-four participants diagnosed with Other Specified Depressive Disorder were recruited and randomly allocated to a CBT-based mobile-app program, the Todac Todac (TT group), or a daily mood chart app program (control group). Participants were asked to use the software for 3 weeks. Assessments for autonomic thoughts and clinical symptoms were administered at baseline and at a follow-up evaluation. Results: After completing the 3-week program, Dysfunctional Attitude Scale (DAS) scores in TT group were lower than they were in the control group. In clinical measures, both TT group and control group showed reduced Beck Depression Inventory-II (BDI-II) scores and situation-dependent trait version of State-Trait Anxiety Inventory (STAI-X2) at follow-up. However, TT group showed significantly reduced STAI-X2 scores compared to control group. For all participants, changes in DAS scores were correlated with BDI-II and STAI-X2 scores. Conclusions: Our preliminary findings provide promising evidence that scenario-based CBT mobile apps can be used to deliver feasible and efficacious cognitive therapy. Long-term research is needed to determine the impact and effectiveness of this new treatment format.

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

BACKGROUND AND PURPOSE: Neurotransmitter changes in youth addicted to the Internet and smartphone were compared with normal controls and in subjects after cognitive behavioral therapy. In addition, the correlations between neurotransmitters and affective factors were investigated. MATERIALS AND METHODS: Nineteen young people with Internet and smartphone addiction and 19 sex- and age-matched healthy controls (male/female ratio, 9:10; mean age, 15.47 ± 3.06 years) were included. Twelve teenagers with Internet and smartphone addiction (male/female ratio, 8:4; mean age, 14.99 ± 1.95 years) participated in 9 weeks of cognitive behavioral therapy. Meshcher-Garwood point-resolved spectroscopy was used to measure γ-aminobutyric acid and Glx levels in the anterior cingulate cortex. The γ-aminobutyric acid and Glx levels in the addicted group were compared with those in controls and after cognitive behavioral therapy. The γ-aminobutyric acid and Glx levels correlated with clinical scales of Internet and smartphone addiction, impulsiveness, depression, anxiety, insomnia, and sleep quality. RESULTS: Brain parenchymal and gray matter volume–adjusted γ-aminobutyric acid-to-creatine ratios were higher in subjects with Internet and smartphone addiction (P = .028 and .016). After therapy, brain parenchymal- and gray matter volume–adjusted γ-aminobutyric acid-to-creatine ratios were decreased (P = .034 and .026). The Glx level was not statistically significant in subjects with Internet and smartphone addiction compared with controls and posttherapy status. Brain parenchymal- and gray matter volume–adjusted γ-aminobutyric acid-to-creatine ratios correlated with clinical scales of Internet and smartphone addictions, depression, and anxiety. Glx/Cr was negatively correlated with insomnia and sleep quality scales. CONCLUSIONS: The high γ-aminobutyric acid levels and disrupted balance of γ-aminobutyric acid-to-Glx including glutamate in the anterior cingulate cortex may contribute to understanding the pathophysiology and treatment of Internet and smartphone addiction and associated comorbidities.

Background: The hyperarousal model demonstrates that instability of sleep-wake regulation leads to insomnia symptoms and various neurophysiological hyperarousal states. Previous studies have shown that hyperarousal states that appear in chronic insomnia patients are not limited to sleep at nighttime but are stable characteristics that extend into the daytime. However, this phenomenon is mainly measured at bedtime, so it hard to determine whether it is maintained throughout a 24 h cycle or if it just appears at bedtime. Methods: We examined the resting state qEEG (quantitative electroencephalogram) and ECG (electrocardiogram) of chronic insomnia patients (n = 24) compared to good sleepers (n = 22) during the daytime. Results: As compared with controls, participants with insomnia showed a clearly high beta band activity in eyes closed condition at all brain areas. They showed a low frequency band at the frontal area; high frequency bands at the central and parietal areas were found in eyes open condition. Significantly higher heart rates were also found in the chronic insomnia group. Conclusion: These findings suggest that chronic insomnia patients were in a state of neurophysiological hyperarousal during the middle of the day due to abnormal arousal regulation.