A Novel Feed-Forward Modeling System Leads to Sustained Improvements in Attention and Academic Performance

Analysis of the Status and Future Direction for Digital Therapeutics in Children and Adolescent Psychiatry

Digital therapeutics based on software, such as artificial intelligence, virtual reality, games, and smartphone applications, are in the spotlight as new therapeutic alternatives in child and adolescent psychiatry. It draws attention to overcoming conventional therapeutics' limitations, such as toxicity, cost, and accessibility, and encourages patients to participate in the treatment attractively. The growth potential of the digital therapeutics market for psychiatric disorders in children and adolescents in Korea and abroad has been highlighted. Clinical studies and Food and Drug Administration approvals for digital therapeutics have increased, and cases approved by the Ministry of Food and Drug Safety have emerged in Korea. As seen above, digital transformation in child and adolescent psychiatry will change treatment paradigms significantly. Therefore, as this new field has just begun to emerge, it is necessary to verify the effectiveness and scope of the application of digital therapeutics and consider preparing a compensation system and institutional arrangements. Accordingly, this study analyzed the development trends and application status of digital therapeutics in children and adolescents and presented limitations and development directions from the perspective of application in healthcare. Further, the study is expected to identify the utility and limitations of digital therapeutics for children and adolescents and establish effective application measures.

Efficacy of Online Intervention for ADHD: A Meta-Analysis and Systematic Review

Background

With the popularity of computers, the internet, and the global spread of COVID-19, more and more attention deficit hyperactivity disorder (ADHD) patients need timely interventions through the internet. At present, there are many online intervention schemes may help these patients. It is necessary to integrate data to analyze their effectiveness.

Objectives

Our purpose is to integrate the ADHD online interventions trials, study its treatment effect and analyze its feasibility, and provide reference information for doctors in other institutions to formulate better treatment plans.

Methods

We searched PubMed, EMBASE and Cochrane libraries. We didn't limit the start date and end date of search results. Our last search was on December 1, 2021. The keyword is ADHD online therapy. We used the Cochrane bias risk tool to assess the quality of included studies, used the standardized mean difference (SMD) as an effect scale indicator to measure data. Random effects model, subgroup analysis were used to analyze the data.

Results

Six randomized controlled trials (RCTs) were identified, including 261 patients with ADHD. These studies showed that online interventions was more effective than waiting list in improving attention deficit and social function of adults and children with ADHD. The attention deficit scores of subjects were calculated in six studies. The sample size of the test group was 123, the sample size of the control group was 133, and the combined SMD was −0.73 (95% confidence interval: −1.01, −0.44). The social function scores of subjects were calculated in six studies. The sample size of the experimental group was 123 and the control group was 133. The combined SMD was −0.59 (95% confidence interval: −0.85, −0.33).

Conclusions

The results show that online interventions of ADHD may be an effective intervention. In the future, we need more online intervention researches to improve the symptoms of different patients, especially for some patients who have difficulties in accepting face-to-face treatment.

Game-based digital therapeutics for children and adolescents: Their therapeutic effects on mental health problems, the sustainability of the therapeutic effects and the transfer of cognitive functions

Mental health problems in childhood and adolescence (e. g., attention deficits, problems in emotional understanding and subclinical levels of anxiety) are reported to develop further in adulthood and/or to increase the risk of developing mental health disorders in adulthood. Although it is important to provide treatment or prevention interventions for children and adolescents in order to reduce the risk of the further development of mental health problems, the pharmacological and behavioral treatments for this age group have limitations (e.g., limited access, unsustainable treatment effects and the lack of engagement in intervention). In order to overcome the limitations of conventional treatments, the use of digital technology, especially video games for this age group, is suggested. In order to be accepted as clinical interventions, objective evidence for the therapeutic effects of digital therapeutic that used video games to treat or prevent targeted mental health problems are required. Thus, this review aims to explore whether game-based digital therapeutics (DTx) for children and adolescents showed therapeutic effects on targeted mental health problems. As game-based DTx are suggested to show sustained therapeutic effects and the transfer of cognitive functions, it also reviews the maintenance of the therapeutic effects of DTx and the extent of the transfer of cognitive functions. Game-based DTx that are developed to treat or prevent mental health problems (e.g., attention deficit, depression) in children and adolescents are found to show therapeutic effects on targeted mental health problems despite the limitations (e.g., small sample size, limited investigation of the sustainability). This review would contribute to the understanding of whether there is objective evidence of the therapeutic effects of digital therapeutics using video games that deliver treatment or prevention interventions for mental health problems in children and adolescents.

Updates in technology-based interventions for attention deficit hyperactivity disorder

PURPOSE OF REVIEW

Technological advancement has led to the development of novel treatment approaches for attention deficit hyperactivity disorder (ADHD). This review aims to review recent studies which employ the use of technology to treat ADHD, with particular focus on studies published during a 1-year period from February 2019 to February 2020.

RECENT FINDINGS

Most recent studies involved children aged 12 years and below. Interventions included cognitive training through games, neurofeedback and a combination of several approaches. More novel approaches included trigeminal nerve stimulation and brain-computer interface, and studies had utilized technology such as X-box Kinect and eye tracker. There was a shift towards delivering intervention at home and in school, enabled by technology. The study outcomes were variable and mainly included executive functioning measures and clinical ratings. These interventions were generally safe with few reported adverse events.

SUMMARY

Technology has enabled interventions to be delivered outside of the clinic setting and presented an opportunity for increased access to care and early intervention. Better quality studies are needed to inform on the efficacy of these interventions.

A randomized controlled trial of a brain-computer interface based attention training program for ADHD

Objective

The use of brain-computer interface in neurofeedback therapy for attention deficit hyperactivity disorder (ADHD) is a relatively new approach. We conducted a randomized controlled trial (RCT) to determine whether an 8-week brain computer interface (BCI)-based attention training program improved inattentive symptoms in children with ADHD compared to a waitlist-control group, and the effects of a subsequent 12-week lower-intensity training.

Study design

We randomized 172 children aged 6–12 attending an outpatient child psychiatry clinic diagnosed with inattentive or combined subtypes of ADHD and not receiving concurrent pharmacotherapy or behavioral intervention to either the intervention or waitlist-control group. Intervention involved 3 sessions of BCI-based training for 8 weeks, followed by 3 training sessions per month over the subsequent 12 weeks. The waitlist-control group received similar 20-week intervention after a wait-time of 8 weeks.

Results

The participants’ mean age was 8.6 years (SD = 1.51), with 147 males (85.5%) and 25 females (14.5%). Modified intention to treat analyzes conducted on 163 participants with at least one follow-up rating showed that at 8 weeks, clinician-rated inattentive symptoms on the ADHD-Rating Scale (ADHD-RS) was reduced by 3.5 (SD 3.97) in the intervention group compared to 1.9 (SD 4.42) in the waitlist-control group (between-group difference of 1.6; 95% CI 0.3 to 2.9 p = 0.0177). At the end of the full 20-week treatment, the mean reduction (pre-post BCI) of the pooled group was 3.2 (95% CI 2.4 to 4.1).

Conclusion

The results suggest that the BCI-based attention training program can improve ADHD symptoms after a minimum of 24 sessions and maintenance training may sustain this improvement. This intervention may be an option for treating milder cases or as an adjunctive treatment.

Personalized features for attention detection in children with Attention Deficit Hyperactivity Disorder

Measuring attention from electroencephalogram (EEG) has found applications in the treatment of Attention Deficit Hyperactivity Disorder (ADHD). It is of great interest to understand what features in EEG are most representative of attention. Intensive research has been done in the past and it has been proven that frequency band powers and their ratios are effective features in detecting attention. However, there are still unanswered questions, like, what features in EEG are most discriminative between attentive and non-attentive states? Are these features common among all subjects or are they subject-specific and must be optimized for each subject? Using Mutual Information (MI) to perform subject-specific feature selection on a large data set including 120 ADHD children, we found that besides theta beta ratio (TBR) which is commonly used in attention detection and neurofeedback, the relative beta power and theta/(alpha+beta) (TBAR) are also equally significant and informative for attention detection. Interestingly, we found that the relative theta power (which is also commonly used) may not have sufficient discriminative information itself (it is informative only for 3.26% of ADHD children). We have also demonstrated that although these features (relative beta power, TBR and TBAR) are the most important measures to detect attention on average, different subjects have different set of most discriminative features.