Digital Intervention in Children With Developmental Language Disorder: Systematic Review
Bibliographic record
Abstract
Background: Developmental language disorder (DLD) is one of the most common neurodevelopmental disorders. Effective intervention is primarily important for improving the language and communication skills of children with DLD, and strengthening these skills ensures quality of life and prevents negative effects in adulthood. Digital interventions have the potential to complement conventional language intervention, reducing the workload for therapists and increasing accessibility to language training in homes or schools. Objective: This systematic review aimed to explore the language domain that is most frequently targeted by digital intervention in children with DLD. Methods: The study protocol was registered in the International Prospective Register for Systematic Reviews (PROSPERO) and was ascribed the CRD42023477946 registration code. The initial search was conducted on May 2023 from 4 databases: "PubMed," "Scopus," "PsycInfo," and "IEEE Xplore," following a method adapted from PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Inclusion criteria include studies recruiting patients diagnosed with DLD; studies that reported digital interventions based on apps, video games, augmented reality, or any other type of software based on language outcomes; and English language studies. Reviews, letters, conference proceedings, abstracts, editorials, and studies not published in English were removed. The titles and abstracts of the identified records were initially screened and selected by 2 independent and blinded reviewers. Data extraction and quality assessment were performed by 3 independent reviewers. Results: Overall, 13 studies were included; 961 children with DLD underwent a digital intervention. The mean age ranged from 3.47 (SD 0.17) to 11.19 (SD 1.12) years. A total of 8 were randomized controlled trials, and 5 were quasi-experimental studies. Targeting domains of digital intervention were phonological skills (n=5), general language function (n=3), grammar (n=3), and vocabulary (n=2). Conclusions: This systematic review indicates that phonological skills are the most frequently targeted language domain by digital interventions in children with DLD. Given the limited number and the heterogeneity of the studies included, it is still unclear whether digital intervention was effective in improving different language skills in children with DLD. There was less evidence supporting its effectiveness in expressive language skills, which indicates a need to update expressive language digital training programs in the future. Further higher-level evidence, such as randomized controlled trial studies in this area, is needed to direct the development of digital programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".