Messenger use and video calls as correlates of anxiety and depressive symptoms – Results from the CORONA HEALTH APP study of German adults during the COVID-19 pandemic (Preprint)

crossref(2023)

引用 0|浏览2
暂无评分
摘要
BACKGROUND Specialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily in virtual space. To appropriately test these objective data for their added value for epidemiological research during the pandemic, it is necessary to include established predictors. OBJECTIVE Therefore, via a comprehensive model, we investigated the extent to which smartphone-based social interaction data contribute to the prediction of depressive and anxiety symptoms, also taking into account established and pandemic-specific predictors. METHODS We developed the CORONA HEALTH APP and obtained participation by 490 Android users who agreed to allow us to collect smartphone-based social interaction data between July 2020 and February 2021. In a cross-sectional design, we automatically collected data concerning average app usage in terms of the categories (video-)telephony, messenger use, social media use and SMS use as well as pandemic-specific predictors and sociodemographic covariates. We statistically predicted depressive and anxiety symptoms using elastic net regressions. To exclude overfitting, we used tenfold cross-validation. RESULTS Of the smartphone-based social interaction data included, only messenger use proved to be a significant negative predictor of depressive and anxiety symptoms. Video calls were negative predictors only for depressive symptoms and text messages were negative predictors only for anxiety symptoms. CONCLUSIONS The results show the relevance of smartphone-based social interaction data in predicting depressive and anxiety symptoms. However, even taken together in the context of a comprehensive model with well-established predictors, they only add a small amount of value.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要