Using AI to Predict Caregiver Ability to Self-Manage Chronic Illness When Caring For Children With Special Health Care Needs

Jordan Rayle, Timothy Hamilton, Priyanka Poosapati,Gulustan Dogan, Michele Mendes

2022 4th International Workshop on Artificial Intelligence and Education (WAIE)(2022)

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摘要
Children with special health care needs, in most cases, can easily be treated with a combination of medication and parental care. However, the requirements involved can be pushed further when the parent caring for the child must also treat an illness while caring for their own illness. In many instances, this leads to an inability of the parent to be able to manage their own illness while also trying to manage their child's care. Through surveys given out, data was collected to analyze the correlation between both the severity of a child's chronic illness, the intrusiveness felt by a caregiver, and the impact those factors both have on the caregiver's management of their own chronic illness. Through various machine learning algorithms, it was found that there was a fair amount of accuracy when attempting to predict the overall intrusiveness of illness care for parents. However, the results show that the algorithms analyzed could accurately predict this parental intrusiveness of care within a small margin of error.
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关键词
Children with Special Health Care Needs (CSHCN),Self-Efficacy for Managing Chronic Disease (SEMCD),Parent Illness Intrusiveness Rating Scale (PIIRS)
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