Background: Prolonged sedentary behaviour (SB) is associated with risk of chronic diseases. Digital interventions in SB require mixed method evaluations to understand potential for impact in real-world settings. In this study, the RE-AIM QuEST evaluation framework will be used to understand the potential of a digital health promotion application which targets reducing and breaking up SB across multiple workplace settings.
Methods: Four companies and 80 employees were recruited to use a digital application. Questionnaires were used to measure SB, and additional health and work-related outcomes at baseline, one month, three month and six month follow-up. Qualitative data was collected through focus groups with employees and interviews with stakeholders. Questionnaire data was analysed using Wilcoxon Sign Rank tests and qualitative data was thematically analysed.
Results: The digital application significantly increased standing time at one month for the total group and transitions per hour in one of the companies. Facilitators and barriers were identified across RE-AIM.
Conclusions: Addressing the barriers which have been identified, while maintaining the positive attributes will be critical to producing an effective digital application which also has the potential for impact in the real world.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344978 | PMC |
http://dx.doi.org/10.3390/ijerph17124538 | DOI Listing |
Sci Rep
December 2024
Advanced Research Institute for Digital-Twin Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures.
View Article and Find Full Text PDFBMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Computer Science, Wuhan University, Luojiashan Road, Wuchang District., Wuhan, 430072, Hubei Province, China; Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics, No. 8, Yangqiaohu Avenue, Zanglong Island Development Zone, Jiangxia District, Wuhan, 2007, Hubei Province, China. Electronic address:
The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have been made to enrich molecular representations by integrating data from diverse aspects. Nevertheless, current methodologies frequently compartmentalize geometric and semantic components, resulting in a fragmented approach that impairs the holistic integration of molecular attributes.
View Article and Find Full Text PDFANZ J Surg
December 2024
Royal Prince Alfred Institute of Academic Surgery, Sydney Local Health District, Sydney, New South Wales, Australia.
Background: Facial prosthetics are an important means to rehabilitate patients with congenital or acquired facial defects. However, with a time-consuming manual workflow and workforce shortage, access to facial prosthetics is limited in Australia and worldwide, especially for rural and remote patients. Optical 3D scanning has been increasingly integrated in digitizing data.
View Article and Find Full Text PDFAdv Sci (Weinh)
December 2024
Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Digital PCR (dPCR) has transformed nucleic acid diagnostics by enabling the absolute quantification of rare mutations and target sequences. However, traditional dPCR detection methods, such as those involving flow cytometry and fluorescence imaging, may face challenges due to high costs, complexity, limited accuracy, and slow processing speeds. In this study, SAM-dPCR is introduced, a training-free open-source bioanalysis paradigm that offers swift and precise absolute quantification of biological samples.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!