Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov 4;23(11):e25745.
doi: 10.2196/25745.

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Vera C Kaelin  1   2 , Mina Valizadeh  3   4 , Zurisadai Salgado  2   5 , Natalie Parde #  3   4 , Mary A Khetani #  1   2   5   6
Affiliations

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Vera C Kaelin et al. J Med Internet Res. .

Abstract

Background: In the last decade, there has been a rapid increase in research on the use of artificial intelligence (AI) to improve child and youth participation in daily life activities, which is a key rehabilitation outcome. However, existing reviews place variable focus on participation, are narrow in scope, and are restricted to select diagnoses, hindering interpretability regarding the existing scope of AI applications that target the participation of children and youth in a pediatric rehabilitation setting.

Objective: The aim of this scoping review is to examine how AI is integrated into pediatric rehabilitation interventions targeting the participation of children and youth with disabilities or other diagnosed health conditions in valued activities.

Methods: We conducted a comprehensive literature search using established Applied Health Sciences and Computer Science databases. Two independent researchers screened and selected the studies based on a systematic procedure. Inclusion criteria were as follows: participation was an explicit study aim or outcome or the targeted focus of the AI application; AI was applied as part of the provided and tested intervention; children or youth with a disability or other diagnosed health conditions were the focus of either the study or AI application or both; and the study was published in English. Data were mapped according to the types of AI, the mode of delivery, the type of personalization, and whether the intervention addressed individual goal-setting.

Results: The literature search identified 3029 documents, of which 94 met the inclusion criteria. Most of the included studies used multiple applications of AI with the highest prevalence of robotics (72/94, 77%) and human-machine interaction (51/94, 54%). Regarding mode of delivery, most of the included studies described an intervention delivered in-person (84/94, 89%), and only 11% (10/94) were delivered remotely. Most interventions were tailored to groups of individuals (93/94, 99%). Only 1% (1/94) of interventions was tailored to patients' individually reported participation needs, and only one intervention (1/94, 1%) described individual goal-setting as part of their therapy process or intervention planning.

Conclusions: There is an increasing amount of research on interventions using AI to target the participation of children and youth with disabilities or other diagnosed health conditions, supporting the potential of using AI in pediatric rehabilitation. On the basis of our results, 3 major gaps for further research and development were identified: a lack of remotely delivered participation-focused interventions using AI; a lack of individual goal-setting integrated in interventions; and a lack of interventions tailored to individually reported participation needs of children, youth, or families.

Keywords: customization; goal-setting; health care; human-machine interaction; machine learning; natural language processing; pediatric rehabilitation; personalization; robotics; technology; young persons.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Study selection process.
See this image and copyright information in PMC

References

    1. Wang S, Blazer D, Hoenig H. Can ehealth technology enhance the patient-provider relationship in rehabilitation? Arch Phys Med Rehabil. 2016 Sep;97(9):1403–6. doi: 10.1016/j.apmr.2016.04.002.S0003-9993(16)30065-X - DOI - PubMed
    1. Lowes LP, Noritz GH, Newmeyer A, Embi PJ, Yin H, Smoyer WE, ‘Learn from Every Patient’ Study Group 'Learn From Every Patient': implementation and early results of a learning health system. Dev Med Child Neurol. 2017 Feb 22;59(2):183–91. doi: 10.1111/dmcn.13227. doi: 10.1111/dmcn.13227. - DOI - DOI - PubMed
    1. Stevenson RD. Integration of research and clinical practice: the future is now. Dev Med Child Neurol. 2017 Feb 16;59(2):119–20. doi: 10.1111/dmcn.13281. doi: 10.1111/dmcn.13281. - DOI - DOI - PubMed
    1. Cacioppo M, Bouvier S, Bailly R, Houx L, Lempereur M, Mensah-Gourmel J, Kandalaft C, Varengue R, Chatelin A, Vagnoni J, Vuillerot C, Gautheron V, Dinomais M, Dheilly E, Brochard S, Pons C, ECHO Group Emerging health challenges for children with physical disabilities and their parents during the COVID-19 pandemic: The ECHO French survey. Ann Phys Rehabil Med. 2021 Aug 18;64(3):101429. doi: 10.1016/j.rehab.2020.08.001. http://europepmc.org/abstract/MED/32818674 S1877-0657(20)30157-3 - DOI - PMC - PubMed
    1. Eunice Kennedy Shriver National Institute of Child Health and Human Development and the NIH Medical Rehabilitation Coordinating Committee NIH Rehabilitation Plan 2020. [2021-01-21]. https://nichd.ideascalegov.com/a/campaign-home/51 .

Publication types