Caregiver and Clinician Priorities for User-Centered Metaverse-Based Speech-Language Therapy: An Analytic Hierarchy...

Background/Objectives: Metaverse technologies are increasingly considered for pediatric speech-language therapy, yet adoption has outpaced evidence on what caregivers and speech-language pathologists (SLPs)-the groups whose decisions drive uptake-consider important. This study identified and compared the priorities caregivers and SLPs assign to factors relevant to metaverse-based speech-language therapy for children, and examined whether caregiver priorities differ by developmental stage. Methods: In this cross-sectional formative needs assessment, a three-stage instrument-development sequence using the Analytic Hierarchy Process (AHP) produced a hierarchy of 3 high-level categories (Subject, System, Content), 8 medium-level categories, and 24 sub-factors. Caregivers of children aged 0-12 years with language development deficits, all receiving therapy (48.8% without a formal disability diagnosis, 43.2% with developmental language disorder), and practicing SLPs in Korea were recruited by convenience sampling. After data cleaning, 250 caregivers and 67 SLPs were analyzed, with caregiver data stratified into early-childhood, pre-school, and school-age groups. Results: Both groups ranked the high-level categories identically-Subject (67.8% vs. 67.4%), Content (18.7% vs. 18.1%), System (13.4% vs. 14.5%)-with differences ≤ 1.1 percentage points, and 9 of the 10 highest-ranked sub-factors were shared. Divergence was concentrated in Content: caregivers weighted Quality over Amount (54.7% vs. 45.3%), whereas SLPs reversed this (66.9% vs. 33.1%). Among caregivers, priorities were stable in rank order across ages, with caregiver-related factors declining and SLP-related and content-quality factors rising with age. Conclusions: Caregivers and SLPs converged on a strongly child-centered, developmentally grounded set of priorities while differing in content expectations. This shared structure indicates that developmentally appropriate, safety-first services may be able to address both groups' priorities through age-adaptive content and role-differentiated support. As the sample was non-probabilistic and analyses descriptive, findings are hypothesis-generating.