abuse-deterrent extended release tablet technology

Selective Uptake of Oral Extended-Release Hydromorphone After Formulary Listing in Cancer Care.

Kajiura Shinya S, Chikaoka Shingo S, Hayashi Ryuji R

From Task-Technology Fit to Self-Perceived Performance Impact Among Nurses: Exploring the Statistical Mediation of Self-Reported Utilization of the Clinical Nursing Information System: A Cross-Sectional Study.

Su Han H, Zou Yujiao Y, Hu Yan Y, Yuan Zheng Z et al.

To examine task-technology fit within a clinical nursing information system and investigate the associations among task characteristics, technology characteristics, task-technology fit, self-reported system utilization, and nurses' self-perceived performance impact. A cross-sectional study. This study surveyed 1370 nurses. The survey assessed task characteristics, technology characteristics, task-technology fit, self-reported system utilization, and nurses' self-perceived performance impact. Task characteristics and technology characteristics were significantly associated with task-technology fit. Task-technology fit and self-reported system utilization were both significantly associated with nurses' self-perceived performance impact. Statistical mediation analysis indicated that self-reported system utilization statistically accounted for part of the association between task-technology fit and self-perceived performance impact. Nurses who received training reported significantly higher scores across all core constructs. Self-reported system utilization statistically and partially accounted for the association between task-technology fit and nurses' self-perceived performance impact. Improving task-technology fit in clinical nursing information systems may require optimizing the alignment between task demands and technological features, alongside strengthening systematic training. Healthcare organizations should prioritize both system design optimisation and comprehensive training programmes to enhance task-technology fit and promote effective system utilization, which may support nursing practice efficiency and care quality. This study addressed the challenge of suboptimal alignment between clinical nursing information systems and nursing practice needs. The main finding revealed that self-reported system utilization plays a key statistical role in linking task-technology fit to nurses' self-perceived performance impact. This research may inform nursing administrators, informaticists, and system developers by providing evidence to guide technology optimisation and training program development. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. No patient or public contribution. This study focused on registered nurses' professional practice and perceptions regarding the clinical nursing information system.

Could the evolution of stapling technology have influenced the observed reduction in postoperative air leakage?

Wu Jiafu J, Chen Yang Y

Digital intelligence in dental technology education: curriculum and practical teaching reform.

Wang Zhi-Fa ZF, Xu Yao-Xiang YX, Zhao Hao-Ran HR, Xiao Wen-Lin WL

Oral healthcare is rapidly progressing from basic digitalization toward increasingly AI-enabled and data-driven practice, reshaping the competencies required of dental technology professionals and challenging traditionally technician-oriented educational models. This narrative review examines how digital intelligence can support curriculum development and practical teaching reform in dental technology education, with particular attention to application-oriented undergraduate universities. Drawing on representative literature related to digital workflows, virtual simulation, haptic systems, three-dimensional printing, large language models, generative artificial intelligence (AI), blended learning, and interprofessional and industry-education collaboration, this review critically synthesizes current evidence and proposes a literature-informed integrative conceptual framework for competency-based curriculum planning. Available evidence suggests that digital intelligence may broaden educational objectives beyond manual technical skills to include digital design, data interpretation, intelligent decision support, ethical awareness, and interdisciplinary communication. These technologies may also support a transition from conventional repetitive training toward more progressive combinations of virtual simulation, physical operation, chairside observation, project-based learning, and workplace-oriented internship. However, important controversies and challenges remain. Artificial intelligence and virtual simulation should remain supervised complements rather than replacements for teachers, conventional laboratory training, or clinical experience. AI-generated outputs may be affected by hallucination, algorithmic bias, limited explainability and reproducibility, and student overdependence, thereby requiring faculty validation, human oversight, and clear governance under evolving regulatory conditions. Current research gaps include limited dental technology-specific evidence, insufficient long-term evaluation of competency development and workplace transferability, and persistent barriers related to equipment investment, software access, faculty training, and curriculum alignment. Future reform should therefore move from tool-centered adoption toward competency-centered curriculum reconstruction, emphasizing progressive virtual-physical-clinical integration, personalized assessment, faculty development, medicine-engineering collaboration, and sustainable industry-education synergy. Overall, digital intelligence-driven reform may help align dental technology education with changing practice needs; however, its sustained educational benefits remain uncertain because current evidence is derived mainly from pilot studies, cross-sectional surveys, short-term simulations, and review-based synthesis.