@文章{信息:doi/10.2196/23144，作者=“Henson, Philip和Rodriguez-Villa, Elena和Torous, John”，标题=“重度精神疾病个体屏幕时间与症状学之间的关系调查:纵向观察研究”，期刊=“J Med Internet Res”，年=“2021”，月=“3”，日=“10”，卷=“23”，数=“3”，页=“e23144”，关键词=“mHealth”;精神分裂症;应用程序;移动;背景:智能手机等数字设备的屏幕暴露时间增加与成人和儿童的认知、行为和幸福感有各种各样的关联，但对其与严重精神疾病患者的症状学的关联知之甚少。目的:为了确定屏幕时间与精神疾病个体症状之间的关联范围，我们采用了一种称为规格曲线分析的方法。方法:在这项观察性研究中，我们招募了拥有智能手机的精神分裂症成年人(≥18岁)和健康对照。我们安装了两个研究来源的智能手机应用程序，mindLAMP和Beiwe，收集调查结果，认知测试结果和屏幕时间指标，为期3个月。调查计划每周进行两次，但参与者被指示自然地根据自己的意愿进行多少调查。屏幕时间在后台连续收集。 A total of 140 participants was recruited from the outpatient clinic population as well as through general public advertising. Age-matched, smartphone-owning healthy controls were also part of the recruitment pool. A specification curve analysis was a priori designed to explore the relationship between every combination of independent variable and dependent variable in order to demonstrate to what degree screen time relates to symptoms in individuals with serious mental illness. Results: The sample consisted of 88 participants (54 with schizophrenia and 34 healthy controls) who completed both the initial and follow-up visits, completed at least one self-reported survey, and had a minimum passive data cutoff of 5 consecutive days. While we found an association between smartphone screen time metrics and cognition (adjusted R2=0.107, P<.001), specification curve analysis revealed a wide range of heterogenous associations with screen time from very negative to very positive. The effects differed based on diagnostic group, age bracket, type of regression model used, and the specific independent and dependent variables selected for analysis. Conclusions: The associations between screen time and mental health in patients with schizophrenia are heterogenous when examined with methods that reduce analytical bias. The heterogeneity in associations suggests that complex and personalized potential effects must be understood in the greater context of an individual. This analysis of longitudinally collected screen time data shows potential for future research that could benefit from high resolution metrics on smartphone use. ", issn="1438-8871", doi="10.2196/23144", url="//www.mybigtv.com/2021/3/e23144", url="https://doi.org/10.2196/23144", url="http://www.ncbi.nlm.nih.gov/pubmed/33688835" }