Parsa Sharmila, Vappu Schroderus, Eemil Lagerspetz, Ella Peltonen
{"title":"Towards understanding smartphone usage and sleep with a crowdsensing approach","authors":"Parsa Sharmila, Vappu Schroderus, Eemil Lagerspetz, Ella Peltonen","doi":"10.1145/3410530.3414442","DOIUrl":null,"url":null,"abstract":"Smartphone usage and sleep quality have established connections in psychological research, but in the HCI context, the topic is still understudied. In this paper, we present preliminary insights into behavioral patterns between smartphone usage and sleep quality by using crowdsensed data. We utilize a large-scale mobile usage dataset and a PHQ-8 depression questionnaire answered by 743 participants from varying age groups and socioeconomic backgrounds. Based on our preliminary results, we provide a methodological pipeline for future work towards understanding the relationship between daily smartphone usage patterns and sleep quality in the wild.","PeriodicalId":7183,"journal":{"name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410530.3414442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Smartphone usage and sleep quality have established connections in psychological research, but in the HCI context, the topic is still understudied. In this paper, we present preliminary insights into behavioral patterns between smartphone usage and sleep quality by using crowdsensed data. We utilize a large-scale mobile usage dataset and a PHQ-8 depression questionnaire answered by 743 participants from varying age groups and socioeconomic backgrounds. Based on our preliminary results, we provide a methodological pipeline for future work towards understanding the relationship between daily smartphone usage patterns and sleep quality in the wild.
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