Self-tracking feedback with engaging and persuasive visualizations not only helps convey data but can also affect people's attitudes and behaviors. We investigate persuasive self-tracking feedback by augmenting data videos (DVs)-novel, engaging storytelling media. We introduce a new class of DVs, called Persuasive Data Videos (PDVs), by incorporating four persuasive elements-primary task, dialogue, system credibility, and social supports-drawn from the Persuasive System Design Model. We describe the iterative design of PDVs and a within-subjects preliminary validation to check their persuasive potential. We then assess PDVs' feasibility using the Persuasive Potential Questionnaire in a between-subjects study comparing a PDV against a conventional DV on Amazon Mechanical Turk (N = 252). Our results indicate the feasibility of using PDVs in providing individuals' self-tracking feedback to convey persuasive health messages, based on which we discuss opportunities for designing persuasive behavioral feedback in an engaging way.
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JMIR Hum Factors
January 2025
New College of Florida, Sarasota, FL, United States.
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View Article and Find Full Text PDFPLoS One
January 2025
Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
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Adv Skin Wound Care
January 2025
Demet İnangil, PhD, RN, is Associate Professor, Nursing Department, Hamidiye Faculty of Nursing, University of Health Sciences, Istanbul, Turkey. Nilüfer Ertürk, RN, and Elif Lale Pakdil, RN, are nurses in the Ostomy and Wound Care Department, Health Sciences University, Sultan Abdulhamid Han Training and Research Hospital, İstanbul. İlayda Türkoğlu, MSN, RN, is Research Assistant, Hamidiye Faculty of Nursing, University of Health Sciences. Özgül Torun, RN, is a nurse in the Ostomy and Wound Care Department, Health Sciences University, Sultan Abdulhamid Han Training and Research Hospital. Ayşe Kabuk, PhD, RN, is Assistant Professor, Department of Nursing, Faculty of Health Sciences, Zonguldak Bülent Ecevit University, Zonguldak.
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J Occup Health
January 2025
Panasonic Corporation, Department Electric Works Company/Engineering Division, Osaka, Japan.
Background: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fall risk prediction model using machine learning (ML) and video-based first three steps in middle-aged workers.
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Multimed Man Cardiothorac Surg
January 2025
New Cross Hospital, Royal Wolverhampton NHS Trust, Wolverhampton, United Kingdom.
Robotic-assisted thoracic surgery has become increasingly utilized in recent years. Complex lung cancer resection surgery can be performed using a robotic approach. It facilitates 3-dimentional visualization of structures, enhanced manipulation of tissues and precise movements.
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