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The primary prevention of stroke high-risk groups is contingent upon health behavior intervention, and the key to such interventions is health behavioral decision-making. The present study aims to explore the potential classification of the health behavior decision-making of high-risk stroke groups using latent profile analysis (LPA) and the key influencing factors of the LPA classes. A cross-sectional study was conducted from January to May 2023 with 264 high-risk individuals of stroke in Henan Province, China. Data were collected using the Behavioral Decision Assessment Scale of Stroke Patients, the Revised Health Promoting Lifestyle Profile-II and the Social Support Rating Scale. LPA showed that a three-profile model of health behavior decision-making best fit this study. Health behavior decision-making of stroke high-risk groups were divided into three latent classes: high-output behavior type (23.1%), influence-impervious type (60.6%), and influence-sensitive type (16.3%). Comparisons between the three LPA classes showed that living situation, per capita monthly household income, hypertension, overweight/obesity, health promoting lifestyle behavior were significantly different between the participants' latent classes of behavior decision-making. Clinical staff can develop targeted interventions according to different problems existing in the decision-making processes, and improve and implement the screening content and process among community high-risk stroke groups, which has practical significance for promoting their healthy behaviors. Patient or Public Contribution: In our study, survey questionnaires were completed by participants at high risk of stroke.
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http://dx.doi.org/10.1002/nur.70001 | DOI Listing |
Turk J Pediatr
September 2025
Division of Pediatric Infectious Diseases, Faculty of Medicine, İstanbul University, İstanbul, Türkiye.
Aim: This study aimed to describe barriers and facilitators of the adherence of children with human immunodeficiency virus (HIV) to antiretroviral therapy (ART) from the perspectives of their caregivers.
Methods: In-depth interviews were held with the caregivers of 15 children. The collected data were analyzed using thematic analysis procedures.
Turk J Pediatr
September 2025
Department of Pediatrics, Faculty of Medicine, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye.
Background: With the development of technology, easier access to the internet and its excessive use have led to problematic internet use (PIU). The prevalence of PIU and its association with lifestyle behaviors in adolescents have become subjects of increasing academic interest. This study aimed to determine the prevalence of PIU among Turkish high school students and to investigate its association with sleep, physical activity and dietary habits.
View Article and Find Full Text PDFTurk J Pediatr
September 2025
Division of Adolescent Health, Department of Pediatrics, University of Ottawa, Children's Hospital of Eastern Ontario (CHEO), Ottawa, Ontario, Canada.
Background: Food addiction has been increasingly recognized as a contributing factor to obesity and eating disorders. Compulsive eating, characterized by an uncontrollable urge to consume food despite adverse consequences, shares behavioral similarities with substance addiction. This study aims to adapt the Brief Measure of Eating Compulsivity (MEC) into Turkish and evaluate its validity and reliability in the adolescent population.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Department of Community Medicine, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway.
Background: The ability to access and evaluate online health information is essential for young adults to manage their physical and mental well-being. With the growing integration of the internet, mobile technology, and social media, young adults (aged 18-30 years) are increasingly turning to digital platforms for health-related content. Despite this trend, there remains a lack of systematic insights into their specific behaviors, preferences, and needs when seeking health information online.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
College of Nursing, Yonsei University, Seoul, Republic of Korea.
Background: Mobile health (mHealth) interventions can be effective for people living with HIV, who are sensitive to privacy breach risks. Understanding the perceived experiences of intervention participants can provide comprehensive insights into potential users and predict intervention effectiveness. Thus, it is necessary to plan engagement measurement and consider ways to enhance engagement during the app development phase.
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