PreprintArticleVersion 1This version is not peer-reviewed
Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention
Version 1
: Received: 13 October 2024 / Approved: 14 October 2024 / Online: 14 October 2024 (21:11:46 CEST)
How to cite:
Emezie, A.; Kamel, R.; Dunphy, M.; Young, A.; Nuske, H. J. Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention. Preprints2024, 2024101099. https://doi.org/10.20944/preprints202410.1099.v1
Emezie, A.; Kamel, R.; Dunphy, M.; Young, A.; Nuske, H. J. Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention. Preprints 2024, 2024101099. https://doi.org/10.20944/preprints202410.1099.v1
Emezie, A.; Kamel, R.; Dunphy, M.; Young, A.; Nuske, H. J. Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention. Preprints2024, 2024101099. https://doi.org/10.20944/preprints202410.1099.v1
APA Style
Emezie, A., Kamel, R., Dunphy, M., Young, A., & Nuske, H. J. (2024). Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention. Preprints. https://doi.org/10.20944/preprints202410.1099.v1
Chicago/Turabian Style
Emezie, A., Amanda Young and Heather J. Nuske. 2024 "Using Heart Rate and Behaviors to Predict Effective Intervention Strategies for Children on the Autism Spectrum: Validation of a Technology-Based Intervention" Preprints. https://doi.org/10.20944/preprints202410.1099.v1
Abstract
Many children on the autism spectrum engage in challenging behaviors, like aggression, due to difficulties communicating and regulating their stress. Identifying effective intervention strategies is often subjective and time-consuming. Utilizing unobservable internal physiological data to predict strategy effectiveness may help simplify this process for teachers and parents. This study examined whether heart rate data can predict strategy effectiveness. Teachers and coders from the research team recorded behavioral and heart rate data over three months for each participating student on the autism spectrum using the KeepCalm app, a platform that provides in-the-moment strategy suggestions based on heart rate and past behavioral data, across 226 instances of strategy interventions. A binary logistic regression was performed to assess whether heart rate reduction, time to return to heart rate baseline, and documented skills and challenging behaviors predicted strategy effectiveness. Results suggested that heart rate reduction may be a significant predictor, and supported the existing practice of using behavioral patterns as proxies for strategy effectiveness. Additional analyses indicate proactive strategies are more effective and are associated with greater reduction in heart rate, relative to reactive strategies. Further exploration of how internal physiological data can complement observable behaviors in assessing intervention strategy effectiveness is warranted given the novelty of our findings.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
