AI Empowers Autism Nutritional Care Solutions: A Family-Centred Innovation

Kurniawan Arif Maspul; Muhammad Ardhin

doi:10.47134/phms.v2i3.418

Authors

Kurniawan Arif Maspul University of the People https://orcid.org/0000-0001-6394-3688
Muhammad Ardhin University of the People https://orcid.org/0009-0000-3665-969X

DOI:

https://doi.org/10.47134/phms.v2i3.418

Keywords:

Autism Sensitive AI, Nutritional Care Innovation, Family-Centred Design, Participatory Case Study, Compassionate Technology

Abstract

Autism Spectrum Disorder (ASD), affecting 1 in 36 U.S. children, presents profound feeding challenges—extreme food selectivity, sensory aversions, and mealtime meltdowns—that strain caregivers and jeopardize child health. Over 70% of caregivers report clinically significant stress, exacerbated by healthcare systems offering generic, neurologically disconnected dietary advice. This study introduces Feeding Assistant for Children with ASD, a personalized AI assistant grounded in the SPELL framework (Structure, Positive approaches, Empathy, Low arousal, Links) and health behavior theories (Social Cognitive Theory, Ecological Systems Theory). Built via participatory co-design with families, clinicians, and AI engineers, the tool delivers culturally sensitive, context-aware nutrition planning and feeding strategies. Over six weeks, a case study with a neurodiverse family demonstrated reduced caregiver stress (quantified via validated scales) and fewer mealtime refusals, validated through mixed-method analysis. The AI’s empathetic tone, structured routines, and sensory-sensitive recommendations align with neurobiological insights, such as atypical connectivity in the amygdala and insula. Ethical safeguards—privacy protocols, bias mitigation, and cultural inclusivity—ensure dignity-centered care. Results advocate for systemic integration of AI into national health strategies, emphasizing equitable access, interdisciplinary training, and policy reforms to bridge gaps in ASD care. This AI model redefines technology's function as both a practical ally and an emotional anchor, building resilience in neurodiverse households.

References

Al-Beltagi, M. (2024). Nutritional management and autism spectrum disorder: A systematic review. World Journal of Clinical Pediatrics, 13(4), 99649.

Al-Beltagi, M., Saeed, N. K., Bediwy, A. S., Alhawamdeh, R., & Elbeltagi, R. (2025). Management of critical care emergencies in children with autism spectrum disorder. World Journal of Critical Care Medicine, 14(2).

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596

Apex ABA. (2023, October 11). What are autism meltdowns? Causes, triggers & symptoms. https://www.apexaba.com/blog/what-are-autism-meltdowns

Ardhin, M. (2025, May 1). A GPT creation framework. Medium. https://ardhin23.medium.com/a-gpt-creation-framework-8a9f668bcf60

Ardhin, M. (2025, May 6). Prompt engineering for GPTs: A chatbot development perspective. Medium. https://ardhin23.medium.com/prompt-engineering-for-gpts-a-chatbot-development-perspective-0676d1ee4283

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28), 2.

Beadle-Brown, J., & Mills, R. (2018). Understanding and responding to autism: the SPELL framework. Brighton: Pavilion Publishing.

Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Harvard university press.

Courchesne, E., Pierce, K., Schumann, C. M., Redcay, E., Buckwalter, J. A., Kennedy, D. P., & Morgan, J. (2007). Mapping early brain development in autism. Neuron, 56(2), 399-413.

Esposito, M., Mirizzi, P., Fadda, R., Pirollo, C., Ricciardi, O., Mazza, M., & Valenti, M. (2023). Food Selectivity in Children with Autism: Guidelines for Assessment and Clinical Interventions. International journal of environmental research and public health, 20(6), 5092. https://doi.org/10.3390/ijerph20065092

Fletcher-Watson, S., Adams, J., Brook, K., Charman, T., Crane, L., Cusack, J., ... & Pellicano, E. (2019). Making the future together: Shaping autism research through meaningful participation. Autism, 23(4), 943-953.

Haytham, A. O., Khuan, L., Ying, L. P., & Hassouneh, O. (2022). Coping mechanism among parents of children with autism spectrum disorder: a review. Iranian journal of child neurology, 16(1), 9.

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399.

Maenner, M. J., Warren, Z., Williams, A. R., Amoakohene, E., Bakian, A. V., Bilder, D. A., Durkin, M. S., Fitzgerald, R. T., Furnier, S. M., Hughes, M. M., Ladd-Acosta, C. M., McArthur, D., Pas, E. T., Salinas, A., Vehorn, A., Williams, S., Esler, A., Grzybowski, A., Hall-Lande, J., Nguyen, R. H. N., … Shaw, K. A. (2023). Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020. Morbidity and mortality weekly report. Surveillance summaries (Washington, D.C. : 2002), 72(2), 1–14. https://doi.org/10.15585/mmwr.ss7202a1

Maspul, K. A. (2021). Public health revitalisation towards healthy Indonesia. Academia Letters, 2.

Maspul, K. A. (2025). How Far Will Our Compassion Reach for Down Syndrome?. Journal Health of Indonesian, 3(01), 17-27.

McFadden, K., & Minshew, N. J. (2013). Evidence for dysregulation of axonal growth and guidance in the etiology of ASD. Frontiers in human neuroscience, 7, 671.

National Autistic Society. (n.d.). Meltdowns – a guide for all audiences. https://www.autism.org.uk/advice-and-guidance/topics/behaviour/meltdowns/all-audiences

National Autistic Society. (n.d.). The SPELL framework. https://www.autism.org.uk/what-we-do/autism-know-how/training/the-spell-framework

Pellicano, E., & Stears, M. (2011). Bridging autism, science and society: Moving toward an ethically informed approach to autism research. Autism research, 4(4), 271-282.

Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the health belief model. Health education quarterly, 15(2), 175-183.

Yin, R. K. (2017). Case study research and applications: Design and methods. Sage publications.