未经证实:COVID-19大流行改变了人们的生活方式,这种改变的生活方式包括成瘾行为增加的可能性。本系统综述和荟萃分析旨在估计不同行为成瘾的患病率(即,网络成瘾,智能手机成瘾,游戏成瘾,社交媒体成瘾,食物成瘾,运动成瘾,赌博成瘾,和购物成瘾)整体和单独。
UNASSIGNED:四个数据库(PubMed,Scopus,ISIWebofKnowledge,和ProQuest)进行了搜索。对2019年12月至2022年7月以英文发表的同行评审论文进行了审查和分析。使用PECO-S标准选择搜索词:人群(参与者特征无限制),暴露(COVID-19大流行),比较(健康人群),结果(行为成瘾的频率或患病率),和研究设计(观察性研究)。共有94项研究,来自40个不同国家的237,657名参与者(平均年龄25.02岁;57.41%为女性)。与成瘾类型无关的行为成瘾的总体患病率(纠正发表偏倚后)为11.1%(95%CI:5.4至16.8%)。每个单独的行为成瘾的患病率(纠正发表偏倚后)为网络成瘾的10.6%,智能手机成瘾占30.7%,5.3%的游戏成瘾,15.1%的社交媒体成瘾,21%的食物成瘾,9.4%为性成瘾,7%为运动成瘾,7.2%为赌博成瘾,和7.2%的购物成瘾。在封锁期间,食物成瘾的患病率,游戏成瘾,与非封锁期相比,社交媒体成瘾更高。智能手机和社交媒体成瘾与研究的方法学质量(即,博阿斯的风险越高,患病率越高)。社交媒体成瘾的其他相关因素是女性参与者的百分比,参与者的平均年龄,在国家/地区使用互联网的个人百分比,和国家的发展状况。人群中使用互联网的个体百分比与总体行为成瘾的所有患病率以及性成瘾和赌博成瘾的患病率相关。游戏成瘾患病率与数据收集方法相关(在线与其他方法),即使用在线方法收集数据,游戏成瘾患病率要低得多。
未经授权:行为成瘾似乎是COVID-19大流行期间的潜在健康问题。医疗保健提供者和政府当局应开展一些运动,帮助人们应对COVID-19大流行期间的压力,以防止他们在COVID-19和随后的大流行期间产生行为成瘾。
UNASSIGNED:在线版本包含补充材料,可在10.1007/s40429-022-00435-6获得。
UNASSIGNED: The COVID-19 pandemic changed people\'s lifestyles and such changed lifestyles included the potential of increasing addictive behaviors. The present systematic
review and meta-analysis aimed to estimate the prevalence of different behavioral addictions (i.e., internet addiction, smartphone addiction, gaming addiction, social media addiction, food addiction, exercise addiction, gambling addiction, and shopping addiction) both overall and separately.
UNASSIGNED: Four databases (PubMed, Scopus, ISI Web of Knowledge, and ProQuest) were searched. Peer-reviewed papers published in English between December 2019 and July 2022 were reviewed and analyzed. Search terms were selected using PECO-S criteria: population (no limitation in participants\' characteristics), exposure (COVID-19 pandemic), comparison (healthy populations), outcome (frequency or prevalence of behavioral addiction), and study design (observational study). A total of 94 studies with 237,657 participants from 40 different countries (mean age 25.02 years; 57.41% females). The overall prevalence of behavioral addiction irrespective of addiction type (after correcting for publication bias) was 11.1% (95% CI: 5.4 to 16.8%). The prevalence rates for each separate behavioral addiction (after correcting for publication bias) were 10.6% for internet addiction, 30.7% for smartphone addiction, 5.3% for gaming addiction, 15.1% for social media addiction, 21% for food addiction, 9.4% for sex addiction, 7% for exercise addiction, 7.2% for gambling addiction, and 7.2% for shopping addiction. In the lockdown periods, prevalence of food addiction, gaming addiction, and social media addiction was higher compared to non-lockdown periods. Smartphone and social media addiction was associated with methodological quality of studies (i.e., the higher the risk of boas, the higher the prevalence rate). Other associated factors of social media addiction were the percentage of female participants, mean age of participants, percentage of individuals using the internet in country, and developing status of country. The percentage of individuals in the population using the internet was associated with all the prevalence of behavioral addiction overall and the prevalence of sex addiction and gambling addiction. Gaming addiction prevalence was associated with data collection method (online vs. other methods) that is gaming addiction prevalence was much lower using online methods to collect the data.
UNASSIGNED: Behavioral addictions appeared to be potential health issues during the COVID-19 pandemic. Healthcare providers and government authorities should foster some campaigns that assist people in coping with stress during COVID-19 pandemics to prevent them from developing behavioral addictions during COVID-19 and subsequent pandemics.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s40429-022-00435-6.