Currently submitted to: JMIR Formative Research
Date Submitted: Jun 20, 2026
Open Peer Review Period: Jun 22, 2026 - Aug 17, 2026
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Eliciting Community Voice in Generative AI Conversational Agent Design for Parent-Child Interaction Therapy Among Low-Income, Hispanic Caregivers: Qualitative Study
ABSTRACT
Background:
Child disruptive behavior disorders are highly prevalent and disproportionately affect families with limited access to evidence-based treatment. Parent-Child Interaction Therapy (PCIT) is an empirically supported intervention for reducing disruptive behaviors; however, access barriers including cost, transportation, and language remain significant challenges for predominantly low-income, Hispanic families. Artificial intelligence (AI)-powered parenting support holds promise for extending reach of evidence-based interventions; however, conversational agent interventions designed without community input risk low uptake and poor fit among historically marginalized populations which may further compound disparities.
Objective:
This study aimed to examine predominantly low-income, Hispanic caregivers’ perspectives, preferences, and concerns regarding AI-powered conversational agents (chatbots) to support parenting practice related to caregiver-child relationship quality and disruptive behaviors, grounded in PCIT principles.
Methods:
Three focus groups (two Spanish-speaking, one English-speaking) were conducted with predominantly low-income, Hispanic caregivers (N = 31) of children ages 2–7 years with reported disruptive behaviors. Participants were recruited through a community-based organization serving predominantly low-income, Hispanic families in Miami-Dade County. Focus group data were analyzed using a rapid qualitative analysis framework with a structured matrix approach to identify themes across groups.
Results:
Themes related to AI-powered parenting support included technology acceptance, learning preferences and conversational style, trust and safety, personalization and privacy, usability and engagement, and barriers to use. Overall, caregivers expressed high openness to AI-powered parenting support but articulated specific design requirements centered on trust, cultural responsiveness, bilingual access, in-the-moment behavioral coaching, and human oversight for safety-sensitive situations.
Conclusions:
Findings highlight that low-income, Hispanic caregivers are receptive to AI-powered parenting support but require design features that reflect their lived experiences, values, and structural constraints. Actively incorporating community voice throughout the design, development, and evaluation process may be instrumental for creating culturally and linguistically responsive parenting conversational agents that are trusted, engaging, and responsive to the needs of the families they are intended to serve. Clinical Trial: N/A
Citation
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