Cerit Merve, Lee Angela Y, Hancock Jeffrey, Miner Adam, Cho Mu-Jung, Muise Daniel, Garròn Torres Anna-Angelina, Haber Nick, Ram Nilam, Robinson Thomas N, Reeves Byron
Graduate School of Education, Stanford University, Stanford, CA, United States.
Department of Communication, Stanford University, Stanford, CA, United States.
JMIR Form Res. 2025 Feb 26;9:e59875. doi: 10.2196/59875.
Contrary to popular concerns about the harmful effects of media use on mental health, research on this relationship is ambiguous, stalling advances in theory, interventions, and policy. Scientific explorations of the relationship between media and mental health have mostly been found null or have small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health.
This exploratory empirical demonstration aims to answer whether mental health effects are associated with media use experiences by (1) redirecting research investments to granular and intensive longitudinal recordings of digital experiences to build models of media use and mental health for single individuals over the course of 1 year, (2) using new metrics of fragmented media use to propose explanations of mental health effects that will advance person-specific theorizing in media psychology, and (3) identifying combinations of media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders.
The activity on individuals' smartphone screens was recorded every 5 seconds when devices were in use over 1 year, resulting in a dataset of 6,744,013 screenshots and 123 fortnightly surveys from 5 adult participants. Each participant contributed between 0.8 and 2.7 million screens. Six media use metrics were derived from smartphone metadata. Fortnightly surveys captured symptoms of depression, attention-deficit/hyperactivity disorder, state anxiety, and positive affect. Idiographic filter models (p-technique canonical correlation analyses) were applied to explore person-specific associations.
Canonical correlations revealed substantial person-specific associations between media use and mental health, ranging from r=0.82 (P=.008) to r=0.92 (P=.03). The specific combinations of media use metrics and mental health dimensions were different for each person, reflecting significant individual variability. For instance, the media use canonical variate for 1 participant was characterized by higher loadings for app-switching, which, in combination with other behaviors, correlated strongly with a mental health variate emphasizing anxiety symptoms. For another, prolonged screen time, alongside other media use behaviors, contributed to a mental health variate weighted more heavily toward depression symptoms. These within-person correlations are among the strongest reported in this literature.
Results suggest that the relationships between media use and mental health are highly individualized, with implications for the development of personalized models and precision smartphone-informed interventions in mental health. We discuss how our approach can be extended generally, while still emphasizing the importance of idiographic approaches. This study highlights the potential for granular, longitudinal data to reveal person-specific patterns that can inform theory development, personalized screening, diagnosis, and interventions in mental health.
与大众对媒体使用对心理健康的有害影响的担忧相反，关于这种关系的研究并不明确，阻碍了理论、干预措施和政策的进展。对媒体与心理健康之间关系的科学探索大多发现两者之间没有关联或关联较小，其结果往往归咎于采用横断面研究设计，或对媒体使用和心理健康的测量不够精确。
本探索性实证研究旨在回答心理健康影响是否与媒体使用体验相关，具体通过以下方式：（1）将研究投入重新导向对数字体验进行细致且密集的纵向记录，以构建个体在1年时间内的媒体使用和心理健康模型；（2）使用碎片化媒体使用的新指标，对心理健康影响提出解释，从而推进媒体心理学中针对个体的理论构建；（3）识别媒体行为和心理健康症状的组合，这些组合可能比单一的使用剂量和情感测量或与特定障碍相关的临床症状评估，在研究媒体影响方面更有用。
在1年多的时间里，当个体使用手机时，每隔5秒记录一次手机屏幕上的活动，从而得到一个包含6,744,013张截图的数据集以及来自5名成年参与者的123份每两周一次的调查问卷。每位参与者贡献了80万至270万个屏幕记录。从智能手机元数据中得出六个媒体使用指标。每两周一次的调查问卷记录了抑郁、注意力缺陷多动障碍、状态焦虑和积极情感的症状。应用特质过滤模型（p技术典型相关分析）来探索个体特异性关联。
典型相关分析揭示了媒体使用与心理健康之间存在显著的个体特异性关联，范围从r = 0.82（P = 0.008）到r = 0.92（P = 0.03）。媒体使用指标和心理健康维度的具体组合因人而异，反映出显著的个体差异。例如，一名参与者的媒体使用典型变量的特征是应用切换的负荷较高，这与其他行为相结合，与一个强调焦虑症状的心理健康变量密切相关。对于另一名参与者，长时间的屏幕使用时间与其他媒体使用行为一起，促成了一个对抑郁症状加权更重的心理健康变量。这些个体内部的相关性是该文献中报道的最强相关性之一。
结果表明，媒体使用与心理健康之间的关系高度个体化，这对个性化模型的开发以及基于智能手机的精准心理健康干预具有启示意义。我们讨论了如何普遍扩展我们的方法，同时仍然强调特质方法的重要性。这项研究突出了细致的纵向数据揭示个体特异性模式的潜力，这些模式可为心理健康的理论发展、个性化筛查、诊断和干预提供信息。
