Evidence map›Paper›PMID 42440013›Full record

ArticleJournal of autism and developmental disorders2026

Adaptive Educational Technologies for Students with Autism Spectrum Disorder: A Meta-analysis of Emotional and Social Engagement Outcomes.

Sofia Mastrokoukou, Angelos Chalkiadakis, Xanthippi Dima, Damaris Anyango Muga, Erastus Manoa Karani, Claudio Longobardi

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Article in Journal of autism and developmental disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sofia Mastrokoukou *Department of Human and Social Sciences, Universitas Mercatorum, Rome, Italy.ORCID http://orcid.org/0000-0002-3350-6679
Angelos Chalkiadakis *Department of Humanities, University of Turin, Turin, Italy.ORCID http://orcid.org/0009-0008-6668-9505
Xanthippi DimaDepartment of Humanities and Social Science, University of Nicosia, Nicosia, Cyprus.
Damaris Anyango MugaDepartment of Psychology, Masinde Muliro University of Science and Technology, Kakamega, Kenya.
Erastus Manoa KaraniDepartment of Psychology, Masinde Muliro University of Science and Technology, Kakamega, Kenya.
Claudio LongobardiDepartment of Psychology, University of Turin, Via Giuseppe Verdi, 8, 10124, Turin, TO, Italy. claudio.longobardi@unito.it.ORCID http://orcid.org/0000-0002-8457-6554

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAdaptive educational technologies are increasingly used to support emotional engagement in students with autism spectrum disorder (ASD), yet their overall effectiveness remains uncertain. This meta-analysis aimed to estimate the impact of adaptive technologies on emotional engagement outcomes and to examine methodological and study-level moderators.

methodsFourteen independent samples from 14 studies published between 2011 and 2024 were included, comprising 524 participants aged 4-17 years (M

resultsRandom-effects models with restricted maximum-likelihood (REML) estimation were used to calculate pooled effect sizes. The overall pooled effect size was Hedges' g = 0.47 (95% CI 0.36-0.58), reflecting a moderate positive effect of adaptive technologies on emotional engagement. Significant heterogeneity was observed (I

conclusionsOverall, findings support the potential of adaptive technologies to improve emotional engagement in students with ASD. Methodological consistency and the use of validated outcome measures are recommended to enhance future evidence synthesis.

Indexed as

Adaptive technologyAutism spectrum disorderEmotional engagementMeta-analysisVirtual reality

Identifiers

PMID42440013

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.