Digital interventions can be an important instrument in treating substance use disorder. However, most digital mental health interventions suffer from early, frequent user dropout. Early prediction of engagement would allow identification of individuals whose engagement with digital interventions may be too limited to support behaviour change, and subsequently offering them support. To investigate this, we used machine learning models to predict different metrics of real-world engagement with a digital cognitive behavioural therapy intervention widely available in UK addiction services. Our predictor set consisted of baseline data from routinely-collected standardised psychometric measures. Areas under the ROC curve, and correlations between predicted and observed values indicated that baseline data do not contain sufficient information about individual patterns of engagement.
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http://dx.doi.org/10.3233/SHTI230319 | DOI Listing |
JMIR Pediatr Parent
January 2025
Department of Design Innovation, College of Design, University of Minnesota, Twin Cities, Minneapolis, MN, United States.
Background: Congenital heart disease (CHD) is the most common birth defect, affecting 40,000 births annually in the United States. Despite advances in medical care, CHD is often a chronic condition requiring continuous management and education. Effective care management depends on children's understanding of their condition.
View Article and Find Full Text PDFBehav Sci (Basel)
January 2025
Faculty of Education, University of Macau, Macau SAR, China.
Resilience and flow are crucial in language education, yet most research focuses on formal learning environments, with limited studies on their impact in informal settings. This study explores the relationship between basic psychological needs and engagement in the context of informal digital English learning (IDLE). Using a mixed-methods design, data were collected from 512 Chinese EFL learners.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Group of Biomechatronics, Fachgebiet Biomechatronik, Technische Universität Ilmenau, D-98693 Ilmenau, Germany.
Anguilliform locomotion, an efficient aquatic locomotion mode where the whole body is engaged in fluid-body interaction, contains sophisticated physics. We hypothesized that data-driven modeling techniques may extract models or patterns of the swimmers' dynamics without implicitly measuring the hydrodynamic variables. This work proposes empirical kinematic control and data-driven modeling of a soft swimming robot.
View Article and Find Full Text PDFBrain Sci
January 2025
Department of Mental Health, ASL Salerno, 84125 Salerno, Italy.
Background: The integration of digital health technologies has transformed mental healthcare, particularly for young adults with First-Episode Psychosis (FEP). Digital interventions, such as telepsychiatry and mobile applications, address barriers like social stigma, restricted access to services, and the urgency of timely care.
Methods: A systematic literature review was conducted using PubMed and APA PsycINFO.
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