App-Based Ecological Momentary Assessment of Problematic Smartphone Use During Examination Weeks in University Students: 6-Week Observational Study.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2025-02-05 DOI:10.2196/69320
Ji Seon Ahn, InJi Jeong, Sehwan Park, Jooho Lee, Minjeong Jeon, Sangil Lee, Gangho Do, Dooyoung Jung, Jin Young Park
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Abstract

Background: The increasing prevalence of problematic smartphone use (PSU) among university students is raising concerns, particularly as excessive smartphone engagement is linked to negative outcomes such as mental health issues, academic underperformance, and sleep disruption. Despite the severity of PSU, its association with behaviors such as physical activity, mobility, and sociability has received limited research attention. Ecological momentary assessment (EMA), including passive data collection through digital phenotyping indicators, offers an objective approach to explore these behavioral patterns.

Objective: This study aimed to examine associations between self-reported psychosocial measures; app-based EMA data, including daily behavioral indicators from GPS location tracking; and PSU in university students during the examination period.

Methods: A 6-week observational study involving 243 university students was conducted using app-based EMA on personal smartphones to collect data on daily behaviors and psychosocial factors related to smartphone overuse. PSU was assessed using the Korean Smartphone Addiction Proneness Scale. Data collected from the Big4+ app, including self-reports on mood, sleep, and appetite, as well as passive sensor data (GPS location, acceleration, and steps) were used to evaluate overall health. Logistic regression analysis was conducted to identify factors that significantly influenced smartphone overuse, providing insights into daily behavior and mental health patterns.

Results: In total, 23% (56/243) of the students exhibited PSU. The regression analysis revealed significant positive associations between PSU and several factors, including depression (Patient Health Questionnaire-9; odds ratio [OR] 8.48, 95% CI 1.95-36.87; P=.004), social interaction anxiety (Social Interaction Anxiety Scale; OR 4.40, 95% CI 1.59-12.15; P=.004), sleep disturbances (General Sleep Disturbance Scale; OR 3.44, 95% CI 1.15-10.30; P=.03), and longer sleep duration (OR 3.11, 95% CI 1.14-8.48; P=.03). Conversely, a significant negative association was found between PSU and time spent at home (OR 0.35, 95% CI 0.13-0.94; P=.04).

Conclusions: This study suggests that negative self-perceptions of mood and sleep, along with patterns of increased mobility identified through GPS data, increase the risk of PSU, particularly during periods of academic stress. Combining psychosocial assessments with EMA data offers valuable insights for managing PSU during high-stress periods, such as examinations, and provides new directions for future research.

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基于应用程序的大学生考试周问题智能手机使用生态瞬间评估:为期 6 周的观察研究
背景:大学生中越来越多的智能手机使用问题(PSU)引起了人们的关注,特别是过度使用智能手机与心理健康问题、学习成绩不佳和睡眠中断等负面结果有关。尽管PSU很严重,但它与身体活动、移动性和社交能力等行为的关系却受到了有限的研究关注。生态瞬时评估(EMA),包括通过数字表型指标被动收集数据,为探索这些行为模式提供了客观的方法。目的:本研究旨在探讨自我报告的社会心理测量之间的关联;基于应用程序的EMA数据,包括来自GPS位置跟踪的每日行为指标;和PSU在大学生考试期间。方法:对243名大学生进行为期6周的观察性研究,在个人智能手机上使用基于app的EMA,收集与智能手机过度使用相关的日常行为和心理社会因素数据。PSU采用韩国智能手机成瘾倾向量表进行评估。从Big4+应用程序收集的数据,包括情绪、睡眠和食欲的自我报告,以及被动传感器数据(GPS位置、加速度和步数)被用来评估整体健康状况。进行了逻辑回归分析,以确定显著影响智能手机过度使用的因素,从而深入了解日常行为和心理健康模式。结果:共有23%(56/243)的学生表现出PSU。回归分析显示PSU与几个因素之间存在显著的正相关,包括抑郁症(患者健康问卷-9;优势比[OR] 8.48, 95% CI 1.95-36.87;P=.004),社交互动焦虑(社交互动焦虑量表;或4.40,95% ci 1.59-12.15;P=.004),睡眠障碍(一般睡眠障碍量表;或3.44,95% ci 1.15-10.30;P=.03)和较长的睡眠时间(OR 3.11, 95% CI 1.14-8.48;P = 03)。相反,PSU与呆在家里的时间呈显著负相关(OR 0.35, 95% CI 0.13-0.94;P = .04点)。结论:这项研究表明,负面的情绪和睡眠自我感知,以及通过GPS数据确定的活动增加的模式,增加了PSU的风险,特别是在学业压力期间。将心理社会评估与EMA数据相结合,为在高压力时期(如考试)管理PSU提供了有价值的见解,并为未来的研究提供了新的方向。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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