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

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.