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Population aging is a defining demographic reality of our era. It is associated with an increase in the societal burden of delivering care to older adults with chronic conditions or frailty. How to integrate global population aging and technology development to help address the growing demands for care facing many aging societies is both a challenge and an opportunity for innovation. We propose a social technology approach that promotes use of technologies to assist individuals, families, and communities to cope more effectively with the disabilities of older adults who can no longer live independently due to dementia, serious mental illness, and multiple chronic health problems. The main contributions of the social technology approach include: (1) fostering multidisciplinary collaboration among social scientists, engineers, and healthcare experts; (2) including ethical and humanistic standards in creating and evaluating innovations; (3) improving social systems through working with those who deliver, manage, and design older adult care services; (4) promoting social justice through social policy research and innovation, particularly for disadvantaged groups; (5) fostering social integration by creating age-friendly and intergenerational programs; and (6) seeking global benefit by identifying and generalizing best practices. As an emergent, experimental approach, social technology requires systematic evaluation in an iterative process to refine its relevance and uses in different local settings. By linking technological interventions to the social and cultural systems of older people, we aim to help technological advances become an organic part of the complex social world that supports and sustains care delivery to older adults in need.
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http://dx.doi.org/10.3389/fpubh.2021.729149 | DOI Listing |
Diabetes Metab Res Rev
September 2025
Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Aim: Our aim was to ascertain whether metformin can reduce insulin requirement without compromising glycaemic control during pregnancy in women with type 1 diabetes.
Methods: A total of 126 pregnant women with type 1 diabetes were recruited for a randomised, double-blind, placebo-controlled multicentre study. The primary outcome was total insulin change, defined as the difference between baseline and third trimester maximum insulin dose (IU).
Int J Nurs Pract
October 2025
First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background: Despite being efficacious for acute ischemic stroke, treatment with thrombolysis is often delayed because of the inaccessibility of informed consent from patient proxies. Decisional conflict could be an important contributor to this delay; however, its influencing factors remain unknown. This study sought to survey the decisional conflict of proxies for sufferers of acute ischaemic stroke and explore the influencing factors.
View Article and Find Full Text PDFAlzheimers Dement
September 2025
School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Camperdown, Sydney, New South Wales, Australia.
Introduction: Risperidone is approved for behaviors and psychological symptoms of dementia (BPSD), despite modest efficacy and known risks. Identifying responsive symptoms, treatment modifiers, and predictors is crucial for personalized treatment.
Method: A one-stage individual participant data meta-analysis of six randomized controlled trials (risperidone: n = 1009; placebo: N = 712) was conducted.
Environ Sci Pollut Res Int
September 2025
Department of Humanities and Social Sciences, Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati City, Andhra Pradesh, India.
Int Dent J
September 2025
Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité-University Medicine Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; Department of Conservati
Introduction And Aims: Artificial intelligence (AI) is transforming dental care by enhancing diagnostic accuracy, efficiency, and patient experience. This study aimed to assess dental patients' acceptance, perceptions, and concerns regarding AI-powered diagnosis using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework through structural equation modelling (SEM).
Methods: A cross-sectional study was conducted among dental patients at King Saud University Dental Hospital, Riyadh.