ReviewChildren (Basel, Switzerland)2026
AI-Enabled Physical Activity Intervention Strategies for Children and Adolescents: A Scoping Review.
Review in Children (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
objectivesMost children and adolescents do not meet recommended physical activity (PA) levels. Artificial intelligence (AI) may enable personalized and adaptive interventions, but evidence across delivery formats remains unclear. This scoping review mapped AI-enabled PA interventions for children and adolescents aged 6-18 years.
methodsFollowing PRISMA-ScR and Joanna Briggs Institute guidance, six databases were searched on 24 May 2026 for English-language studies published since 2018. Eligible studies used AI in intervention delivery and empirically evaluated at least one participant-level PA-related outcome following exposure to the intervention. The review protocol was registered during data analysis.
resultsSeven studies published between 2022 and 2026 were included. Primary AI techniques were computer vision (n = 3), generative AI or large language models (n = 2), reinforcement learning (n = 1), and evolutionary computation (n = 1). Interventions included immersive systems (n = 2), conversational agents (n = 2), exergames or serious games (n = 2), and a robot (n = 1). Three studies used controlled designs and four were single-arm pilot or feasibility studies.
conclusionsAI supported movement recognition, content generation, personalization, and adaptive feedback. However, the small, heterogeneous, and predominantly early-stage evidence base precludes conclusions about effectiveness. Rigorous controlled studies and transparent AI-specific reporting are needed.
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