This prospective pilot study will evaluate an AI-enabled autism caregiver support tool for caregivers of children with autism in Indiana and Kenya. The tool is designed to provide evidence-based autism information, caregiver emotional support, and local service-navigation guidance, with safety guardrails and escalation pathways for high-risk concerns. Caregivers will receive access to the tool and complete baseline and follow-up assessments. The primary purpose of the study is to assess feasibility, acceptability, safety, engagement, and clinical-trial readiness. Exploratory caregiver outcomes include autism knowledge, caregiver self-efficacy, emotional distress and well-being, resource navigation, unmet needs, service engagement, satisfaction, and preparedness to take next steps after diagnosis. Findings will inform the design of a future fully powered effectiveness-implementation trial.
Families of children with autism often face significant challenges following diagnosis, including difficulty accessing reliable information, navigating complex systems of care, identifying appropriate services, and managing the emotional demands associated with caregiving. These challenges may be particularly pronounced in rural, underserved, and resource-constrained settings where access to specialty autism services and family navigation support is limited. This study will evaluate an AI-enabled autism caregiver support tool designed to provide evidence-based autism information, caregiver emotional support, and service-navigation guidance for caregivers of children with autism in Indiana, United States, and western Kenya. The intervention was developed through a reciprocal innovation approach involving partners in both settings and was informed by caregiver, clinician, educator, and community stakeholder input. The tool is designed to provide plain-language information about autism, answer frequently asked caregiver questions, help caregivers identify relevant services and resources, and provide supportive coping guidance. Safety guardrails are incorporated to address crisis, medical, diagnostic, treatment-related, and other high-risk questions. The tool is not intended to diagnose autism, replace clinical care, or provide emergency services. The study will use a prospective single-arm pre-post pilot design. Approximately 60 caregivers of children with autism will be recruited in Indiana and Kenya and provided access to the AI-enabled caregiver support tool. Participants will complete baseline and follow-up assessments and will have access to the intervention throughout the study period. Usage data, including engagement with the tool, use of resource-navigation features, and safety-related interactions, will also be collected. The primary focus of the study is to evaluate feasibility, acceptability, safety, engagement, and clinical-trial readiness. Specific outcomes will include recruitment, retention, assessment completion, intervention uptake, participant engagement, safety events and escalations, usability, and implementation outcomes such as acceptability, feasibility, and appropriateness. Additional exploratory outcomes will include autism knowledge, caregiver self-efficacy, access to reliable information, emotional well-being, service navigation, unmet caregiver needs, service engagement, preparedness to take next steps following diagnosis, satisfaction with the intervention, and trust in the AI-enabled caregiver support tool. These outcomes will be used to estimate outcome variability and inform selection of measures for a future fully powered effectiveness-implementation study. By evaluating an AI-enabled caregiver support intervention in both Indiana and Kenya, this study will generate important information regarding implementation, safety, usability, engagement, and caregiver support needs across diverse cultural and resource settings. Findings will inform future efforts to develop scalable approaches for improving access to autism information, caregiver support, and service navigation for families of children with autism.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
60
Participants will receive access to an AI-enabled autism caregiver support tool adapted for their local setting. The tool provides plain-language, evidence-based information about autism; answers caregiver questions; supports caregiver coping; helps families identify relevant services and resources; and includes safety guardrails for crisis, medical, diagnostic, behavioral, and treatment-related questions. The tool is not intended to diagnose autism, replace clinical care, or provide emergency services.
Indiana University
Indianapolis, Indiana, United States
Moi Teaching and Referral Hospital
Eldoret, Kenya
Recruitment rate
Recruitment feasibility measured as the proportion of eligible participants who enroll in the study, calculated as the number of enrolled participants divided by the number of eligible participants approached for study participation.
Time frame: Study enrollment period (up to 12 months)
Retention rate
Participant retention measured as the proportion of enrolled participants who complete the final study follow-up assessment.
Time frame: Baseline to 6-month follow-up
Assessment completion rate
Assessment feasibility measured as the proportion of participants who complete all required baseline and follow-up study assessments, including caregiver-reported outcome measures and implementation assessments.
Time frame: 6 months
Intervention Uptake
Intervention uptake measured as the proportion of enrolled participants who initiate at least one interaction with the AI-Enabled Autism Caregiver Support Tool following onboarding and activation.
Time frame: 6 months
Intervention Engagement
Participant engagement with the AI-Enabled Autism Caregiver Support Tool measured using platform analytics, including number of sessions, active use days, questions submitted, conversations completed, and use of resource navigation and caregiver-support features.
Time frame: 6 months
Safety Events and Escalations
Safety of the intervention measured by the number and proportion of high-risk prompts, safety escalations, adverse events, and interactions requiring referral to clinical, crisis, or emergency resources.
Time frame: Baseline through 6 months
Acceptability of the Intervention
Acceptability of the AI-Enabled Autism Caregiver Support Tool measured using the Acceptability of Intervention Measure (AIM), with higher scores indicating greater perceived acceptability.
Time frame: 6 months
Feasibility of the Intervention
Feasibility of the AI-Enabled Autism Caregiver Support Tool measured using the Feasibility of Intervention Measure (FIM), with higher scores indicating greater perceived feasibility.
Time frame: 6 months
Appropriateness of the Intervention
Perceived appropriateness of the AI-Enabled Autism Caregiver Support Tool measured using the Intervention Appropriateness Measure (IAM), with higher scores indicating greater perceived fit, relevance, and suitability for caregiver support.
Time frame: 6 months
System Usability Scale (SUS)
Usability of the AI-Enabled Autism Caregiver Support Tool measured using the System Usability Scale (SUS), a validated measure of perceived usability and ease of use.
Time frame: 6 months
Participant Satisfaction With the Intervention
Participant satisfaction with the AI-Enabled Autism Caregiver Support Tool measured using study-specific satisfaction items assessing overall satisfaction, perceived usefulness, and likelihood of future use.
Time frame: 6 months
Autism Knowledge
Change in caregiver autism knowledge measured using the Autism Spectrum Knowledge Questionnaire (ASKQ-2), with higher scores indicating greater autism-related knowledge.
Time frame: Baseline and 6 months
Unmet Caregiver Needs
Change in caregiver-reported unmet information, emotional support, service-navigation, and autism-related care needs using study-specific caregiver needs assessment items.
Time frame: Baseline and 6 months
Trust in the AI-Enabled Autism Caregiver Support Tool
Participant-reported trust in the information, guidance, and recommendations provided by the AI-Enabled Autism Caregiver Support Tool using study-specific trust measures.
Time frame: 6 months
Preparedness to Take Next Steps Following Autism Diagnosis
Change in caregiver-reported preparedness to make decisions regarding autism-related services, supports, educational planning, and care coordination.
Time frame: Baseline and 6 months
Service Engagement
Change in caregiver-reported engagement with autism-related clinical, educational, behavioral, and community-based services, measured using study-specific service utilization questionnaires documenting referral completion, service initiation, attendance, and ongoing participation in recommended services.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Time frame: Baseline and 6 months
Resource Navigation
Change in caregiver ability to identify, access, and utilize autism-related services and supports, measured using service-navigation items adapted from the National Survey of Children's Health (NSCH), referral completion, service access, and follow-up engagement indicators.
Time frame: Baseline and 6 months
Caregiver Well-Being
Change in caregiver well-being measured using the World Health Organization-Five Well-Being Index (WHO-5), with higher scores indicating greater psychological well-being.
Time frame: Baseline and 6 months
Perceived Access to Reliable Information
Change in caregiver-reported access to trustworthy, understandable, and evidence-based autism-related information, measured using study-specific items assessing confidence in locating, understanding, and using autism-related information for decision-making and service navigation.
Time frame: Baseline and 6 months
Caregiver Self-Efficacy
Change in caregiver self-efficacy and empowerment measured using the Family Empowerment Scale, including confidence in managing autism-related needs, navigating services, and advocating for their child.
Time frame: Baseline and 6 months