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Purpose: Mobile phone addiction among college students is currently a common phenomenon and has many negative impacts on the students, such as decreased vision and low sleep quality. Since the existing research on this phenomenon has analyzed the net effects of causes on the result, this paper introduces the fuzzy set qualitative comparative analysis (fsQCA) method to explore the relationship between five antecedent conditions (self-control, self-esteem, loneliness, significant others, and school management) and college students' mobile phone addiction from the perspective of configuration.
Method: Taking college students as research subjects, and a questionnaire was used for data collection. Then the FSQCA method was used to obtain configuration results and conduct configuration analysis.
Results: The results show that a single condition is not necessary for this phenomenon. On the contrary, three configurations could bring about the addiction. The first configuration includes self-esteem, loneliness, and significant others. The second configuration contains self-control, self-esteem, loneliness, and school management. The third configuration comprises self-esteem and loneliness.
Conclusions: The findings of this article can effectively explain the reasons of mobile phone addiction among college students and provide references for alleviating and eliminating it.
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http://dx.doi.org/10.1080/17483107.2025.2548858 | DOI Listing |
J Med Internet Res
September 2025
Faculty of Medicine, The University of Sydney, Sydney, Australia.
Background: Hypertensive disorders of pregnancy (HDP) affect up to 10% of pregnancies and can have adverse short and long-term implications for women and their babies. eHealth interventions include any health service or treatment delivered using the internet and related technology that aims to facilitate, capture, or exchange knowledge. eHealth interventions are increasingly used across many health care settings with improved outcomes.
View Article and Find Full Text PDFBraz Oral Res
September 2025
Universidade Federal de Santa Maria -UFSM, Department of Stomatology, Santa Maria, RS, Brazil.
Advancements in digital media have driven the study and use of photographic records as a diagnostic method for carious lesions, with smartphone images being widely utilized across various health fields. This study aimed to evaluate the diagnostic accuracy of smartphone photography for detecting active caries in orthodontic patients. The sample comprised 100 individuals of both sexes, aged 11 to 46 years, who were undergoing fixed orthodontic treatment.
View Article and Find Full Text PDFJMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
JMIR Hum Factors
September 2025
KK Women's and Children's Hospital, Singapore, Singapore.
Background: Breast cancer treatment, particularly during the perioperative period, is often accompanied by significant psychological distress, including anxiety and uncertainty. Mobile health (mHealth) interventions have emerged as promising tools to provide timely psychosocial support through convenient, flexible, and personalized platforms. While research has explored the use of mHealth in breast cancer prevention, care management, and survivorship, few studies have examined patients' experiences with mobile interventions during the perioperative phase of breast cancer treatment.
View Article and Find Full Text PDFFront Artif Intell
August 2025
School of Computation and Communication Science and Engineering, The Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania.
Computer vision has been identified as one of the solutions to bridge communication barriers between speech-impaired populations and those without impairment as most people are unaware of the sign language used by speech-impaired individuals. Numerous studies have been conducted to address this challenge. However, recognizing word signs, which are usually dynamic and involve more than one frame per sign, remains a challenge.
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