Efficacy and Compliance of a Working Memory Multitasking Task Mobile Intervention for Children With Attention-Deficit/Hyperactivity Disorder: Single-Arm, Pre-Post Pilot Study
Bibliographic record
Abstract
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder affecting 3%-7% of children globally. Alternative treatments are needed to address the limitations of traditional pharmacotherapy and nonpharmacotherapy, such as drug side effects and substantial time and financial costs. In this light, digital therapeutics for childhood ADHD are emerging as an effective alternative, with the benefits of potentially being free from serious side effects associated with software-based treatments and facilitating easy home use without constraints on time or space. OBJECTIVE: This study aims to evaluate whether a 4-week digital treatment program can improve symptoms, problem behaviors, and neurocognitive functions in children with ADHD, independent of medication status, while also gauging participant satisfaction with the program. METHODS: We recruited 22 Korean children aged 6-12 years with a diagnosis of ADHD. During the preintervention visit, we collected data on ADHD symptoms, relevant behavior scales, and neurocognitive assessments. Participants then used the program 5 times per day, 5 days a week for 4 weeks at home. At the postintervention visit, we collected the same data as during the preintervention visit and gathered additional feedback on their experience over the 4 weeks. RESULTS: A total of 19 participants were included in the statistical analysis, showing significant decreases in scores across various categories. These included the Korean ADHD Rating Scale (Total: P=.004; Inattentive: P=.004; and Hyperactive-impulsive: P=.01) and Korean Conners' Parent Rating Scale (Total: P<.001; Impulsive-hyperactive: P=.001; and Conduct Problem I: P=.04). Significant improvements were also noted in the Stroop word (P=.004), color (P<.001), and color-word (P<.001) scores. No significant differences in treatment effects were found between medicated and unmedicated participants. Caregiver and child satisfaction surveys yielded mean ratings of 4.3 and 4.1 out of 5, respectively. CONCLUSIONS: A 4-week gamified intervention improves attention and hyperactivity-impulsivity in children with ADHD, irrespective of medication status, demonstrating its potential effectiveness and acceptability as a treatment option. As this is a small pilot study and underpowered, larger studies with appropriate control groups are needed in future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".