Behavioral and Cognitive Interventions With Digital Devices in Subjects With Intellectual Disability: A Systematic Review
Bibliographic record
Abstract
In recent years, digital devices have been progressively introduced in rehabilitation programs and have affected skills training methods used with children and adolescents with intellectual disabilities (ID). The objective of this review is to assess the effects of the use of digital devices on the cognitive functions and behavioral skills in this population, and to acknowledge their potential as a therapeutic tool. Electronic databases were analyzed until February 2020 using search formulas with free terms related to ID and the use of digital systems with children or adolescents. The risk of bias in randomized controlled trials was assessed by means of the modified Cochrane Collaboration tool and the quality level of the non-randomized studies was assessed using the Newcastle-Ottawa Scale. Forty-four studies were analyzed, most of which were categorized as low quality. Of the executive function studies analyzed, 60% reported significant improvements, most commonly related to working memory. Within the cognitive skills, 47% of the studies analyzed reported significant improvements, 30% of them in language. Significant improvements in the social (50%) and behavioral domains (30%) were also reported. These results suggest that digital interventions are effective in improving working memory and academic skills, and positively affect both the social and behavioral domains. Little information has been published regarding the duration of the effects, which could be limited in time. Further research is necessary to assess long-term effectiveness, the influence of comorbidities, and the effects on subjects with severe ID. The inclusion of smartphones and special education centers is also necessary.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".