KJCKorea
Journal Central

Objectives: This study aimed to identify the structural causes of chronic dental treatment backlogs at regional dental health centers for persons with disabilities, which stem from the overlap of mild and severe patients due to the absence of a proper dental delivery system. Consequently, it proposes a three-tier healthcare-welfare linked delivery system through the introduction of 'Local Dental Health Centers for Persons with Disabilities' to establish a robust oral health welfare safety net for vulnerable populations. Methods: Quantitative analyses of administrative data on wait times and domestic/international oral health and welfare policies for persons with disabilities were conducted. Furthermore, a comparative policy review of community-based dental services in developed nations and Focus Group Interviews (FGI) with multidisciplinary experts were implemented to design an actionable policy model. Results: The current system suffers from a severe bottleneck, evidenced by an average waiting time of 137 days for dental treatment under general anesthesia. To alleviate this crisis, this study designed a structured three-tier delivery system consisting of primary (dental home and public health centers), secondary (local centers), and tertiary (regional and central centers) institutions. Under this framework, the newly established secondary local centers are required to deploy a dedicated clinical team comprising at least one dentist and two dental hygienists, regardless of whether they operate in the public or private sector. Furthermore, an 'open designation system' is introduced to select institutions that satisfy rigorous criteria-—including the completion of mandatory specialized training and the provision of physical barrier-free accessibility facilities—thereby enabling them to exclusively manage mild to moderate cases. Conclusions: This study identifies structural causes of regional center backlogs and validates a three-tier oral health delivery system, proposing policies such as legislating secondary local centers and reforming financial incentives. The proposed healthcare-welfare linked model aims to establish a dense, community-centered safety net for persons with disabilities, though future research is needed to enhance practical efficacy through operational protocols and user-centered assessments.

Objectives: This study examined the association between subjective xerostomia and health-related quality of life (HRQoL) among vulnerable community-dwelling older adults. Methods: A cross-sectional survey was conducted among 1,443 adults aged ≥65 years receiving customized care services in Cheonan, Korea. Subjective xerostomia was assessed using a four-item scale, and HRQoL was measured using the EQ-5D-3L. Data were analyzed using descriptive statistics, Spearman correlation, and multiple linear regression. Results: The mean xerostomia score was 6.21±2.24, and the mean EQ-5D index was 0.83±0.15. Xerostomia was negatively correlated with the EQ-5D index (ρ=−0.342, p<0.001). Greater xerostomia remained associated with lower HRQoL after accounting for age and subjective health status (B=−0.009, β=−0.142, p<0.001). Conclusions: Subjective xerostomia was in- dependently associated with poorer HRQoL. These findings support the inclusion of xero- stomia screening and coordinated oral and general health management in community-based care for vulnerable older adults.

Objectives: This study aimed to investigate faculty perceptions of the importance of and need for AI-based team collaboration support functions in project-based courses and Capstone Design, compare these perceptions between the humanities and social sciences and science and engineering disciplines, and propose AI-based team collaboration strategies that reflect both common and discipline-specific needs. Methods: A survey was conducted with 65 faculty members from 16 universities who had experience teaching project-based courses or Capstone Design. The questionnaire measured perceptions of AI-based team collaboration support functions and the need for AI-based collaboration design strategies. Data were analyzed using descriptive statistics, Welch's t-tests, and Importance–Need Analysis to examine disciplinary differences. Results: The findings indicate that faculty members perceive generative AI not merely as a content generation tool but as an educational partner that supports collaboration throughout the project process. The Importance–Need Analysis identified information search and report writing, problem definition and idea generation, and performance management and learning analytics as priority development areas, whereas team discussion and conflict management was classified as a potential improvement area. Science and engineering faculty assigned significantly higher importance to AI-assisted code generation and debugging than did humanities and social sciences faculty. Faculty members from both disciplinary groups also expressed strong needs for AI-supported feedback, learning analytics and diagnostic support, and project coaching. Conclusions: This study identifies priorities for AI-based team collaboration support and provides preliminary design directions for integrating generative AI into collaborative instructional design in higher education. The findings suggest that common core AI support functions should be prioritized, with selected functions strengthened according to disciplinary characteristics.