{"title":"谁会 \"幽会\"?对phubbing预测因素的系统荟萃分析回顾","authors":"Anisha Arenz, Anna Schnauber-Stockmann","doi":"10.1177/20501579231215678","DOIUrl":null,"url":null,"abstract":"Phubbing (i.e., snubbing someone in face-to-face interactions by focusing on one's phone instead of those present) has increased enormously in recent years and has become a widespread usage phenomenon that is associated with negative consequences, for instance for relationships and friendships. To better understand the predictors of phubbing behavior, the present paper provides a systematic overview of the growing research field. Based on a meta-analytic review of 79 studies and 526 effect sizes, we identified 10 higher-level predictor categories of phubbing behavior: sociodemographics, personality, technology-related norms & experiences, technical equipment, (smart)phone & Internet use, problematic use, well-being, psychopathology, and resilience as well as risk factors. The results of the three-level meta-analysis models indicated that the strongest predictors were problematic use patterns.","PeriodicalId":350930,"journal":{"name":"Mobile Media & Communication","volume":"76 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Who “phubs”? A systematic meta-analytic review of phubbing predictors\",\"authors\":\"Anisha Arenz, Anna Schnauber-Stockmann\",\"doi\":\"10.1177/20501579231215678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phubbing (i.e., snubbing someone in face-to-face interactions by focusing on one's phone instead of those present) has increased enormously in recent years and has become a widespread usage phenomenon that is associated with negative consequences, for instance for relationships and friendships. To better understand the predictors of phubbing behavior, the present paper provides a systematic overview of the growing research field. Based on a meta-analytic review of 79 studies and 526 effect sizes, we identified 10 higher-level predictor categories of phubbing behavior: sociodemographics, personality, technology-related norms & experiences, technical equipment, (smart)phone & Internet use, problematic use, well-being, psychopathology, and resilience as well as risk factors. The results of the three-level meta-analysis models indicated that the strongest predictors were problematic use patterns.\",\"PeriodicalId\":350930,\"journal\":{\"name\":\"Mobile Media & Communication\",\"volume\":\"76 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mobile Media & Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/20501579231215678\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mobile Media & Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/20501579231215678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Who “phubs”? A systematic meta-analytic review of phubbing predictors
Phubbing (i.e., snubbing someone in face-to-face interactions by focusing on one's phone instead of those present) has increased enormously in recent years and has become a widespread usage phenomenon that is associated with negative consequences, for instance for relationships and friendships. To better understand the predictors of phubbing behavior, the present paper provides a systematic overview of the growing research field. Based on a meta-analytic review of 79 studies and 526 effect sizes, we identified 10 higher-level predictor categories of phubbing behavior: sociodemographics, personality, technology-related norms & experiences, technical equipment, (smart)phone & Internet use, problematic use, well-being, psychopathology, and resilience as well as risk factors. The results of the three-level meta-analysis models indicated that the strongest predictors were problematic use patterns.