The use of multisensory environments in children and adults with autism spectrum disorder: A systematic review
Bibliographic record
Abstract
Multisensory environment is a setting designed with activities and tools that offered sensory stimulation. Despite their widespread use, no evidence-based guidelines are currently available. The aim of this systematic review was to assess the impact of multisensory environment interventions in autism and to provide guidelines. We included all studies of multisensory environment interventions for autistic individuals retrieved from PubMed, Web of Science, and Science Direct up to 30 September 2024. Two researchers appraised the included literature and extracted the data. A total of 1247 unique records were screened for eligibility, and 10 studies were included. Data extraction included demographic characteristics, type of intervention, target symptoms, and outcome measures. Quality assessment tools included the Newcastle-Ottawa Scale and the Cochrane Risk of Bias for randomized controlled trials. The studies were synthesized narratively based on target symptoms. Four studies reported reductions in stereotypic behavior frequency in children and adults; while other studies suggest positive effects on sustained attention, and aggressive and sensory behaviors. Overall, there was insufficient evidence due to the paucity of literature, the significant variation between interventions, and the small sample sizes. Future research should aim to develop a structured intervention approach to address the common limitations of the included designs.Lay abstractMultisensory rooms, also known as multisensory environments, are widely used in clinical practice and schools for autistic people. Despite their widespread use, their usefulness or effectiveness in achieving specific improvements is still unclear. We carry out a comprehensive and systematic quality assessment of all available studies to test the effectiveness of multisensory environment interventions in autism spectrum disorder and to explore what type of targeted intervention is needed to improve both core symptoms and associated features. The results show that multisensory environment could be a useful tool to modulate aggressive and stereotyped behaviors in autistic individuals. Although there is insufficient evidence to conclude on the efficacy of multisensory environment for other types of targets, overall, the results may provide valuable insights for the development of future studies concerning the utility of multisensory environment in therapeutic intervention.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".