大学生病理性互联网使用情况的流行病学调查

目的了解高校上网大学生病理性互联网使用(HIU)的患病率及其影响因素，为预防和控制大学生HIU的发生提供理论依据。方法采用分层整群随机抽样的方法，从长沙地区高校中随机抽取20个班级，对所选班级的上网大学生进行现场无记名问卷调查。结果上网大学生HIU患病率为14．2％。多因素分析结果表明，男性、来自城镇、有不良嗜好、与父母沟通程度差、高年级、学习成绩差为患HIU的危险因素，B型性格、外语专业为保护因素。结论长沙地区上网大学生HIU的患病率高，与多种因素有关。应从多方面进行针对性防治。     

长沙地区大学生饮水量及其影响因素的多水平分析

目的了解长沙地区大学生饮水量情况,并探讨大学生饮水量的影响因素。方法 2014年12月—2015年1月,采用问卷调查和实际测量结合的方法,在长沙高校中分层随机抽取4所高校的1000名大学生进行调查和测量,并利用多水平模型分析大学生饮水量的特征及影响因素。结果长沙地区大学生总饮水量中位数为2803 mL/d,直接饮水量为1983 mL/d,间接饮水量为757 mL/d。大学生在春/秋季总饮水量中位数为2656 mL/d,夏季为3480 mL/d,冬季为2236 mL/d。男生总饮水量中位数为3344 mL/d,女生为2512 mL/d。多水平模型分析结果显示,大学生饮水量影响因素分别为性别、体质指数(BMI)、吸烟饮酒情况和季节。结论大学生饮水量受到性别、BMI、吸烟饮酒情况和季节等因素的影响,因此在评价大学生经饮水暴露引起的水环境健康风险时应综合考虑各因素条件下的饮水量。     

大学生网络成瘾现状及相关因素分析

目的了解大学生网络成瘾现状,分析其相关因素,为采取有效干预措施提供依据.方法采用整群和分层随机抽样方法抽取大学生680名进行问卷调查,对其中485名上网者的调查结果采用单因素及多因素Logistic回归分析.结果网络成瘾者共48人,占总上网人数的9.9%.成瘾者和非成瘾者在人际关系、网络技能、对网络的态度、上网时间、上网频率、上网最主要目的、常用的网络服务等方面差异存在显著性.结论网络成瘾者有其自身特点.需采取有针对性的干预措施,维护大学生的身心健康.     

福州市大学生口腔健康状况及健康行为分析

了解福州市大学生口腔健康状况及其对口腔健康的认知、态度、行为,为开展高校大学生口腔保健工作提供科学依据.方法 分别对福州市大学城6所高校按不同年级分层,以班级为单位,整群随机抽取3 150名学生进行问卷调查.结果 福州市大学生牙龈炎患病率为73.3%,口腔溃疡患病率为49.2%,龋齿率为39.1%;每天刷牙≥2次者占80.0%,知晓正确刷牙方法者占43.8%;从未有洁牙史和从未定期做口腔保健检查的分别为76.1%和41.1%%;在患口腔疾病时,43.2%的学生选择忍着而未做任何处理,44.6%的学生从未接受过口腔健康教育.多因素Logistic回归分析显示,专业、年级、每天刷牙次数是大学生牙龈炎的影响因素.专业和年级存在相乘交互作用,调整OR值为1.458(95%CI=1.241~1.712).结论 福州市大学生口腔健康状况不佳,口腔健康知识较为薄弱,口腔保健行为较差.亟需加强非医学低年级大学生的口腔健康教育工作,提高大学生口腔健康水平.     

北京某高校大学生干眼患病现状及影响因素

调查北京某高校大学生干眼患病现况及其影响因素,为大学生的干眼防治提供科学依据.方法 利用多阶段随机抽样的方法,于2019年1-4月对北京邮电大学4个年级509名学生进行干眼病横断面调查,使用自制问卷收集大学生用眼习惯,利用裂隙灯及泪液检测试纸进行眼表体征检查,采用SPSS 22.0统计软件对结果进行单因素x2检验及多因素Logistic回归分析.结果 大学生干眼的患病率为31.04%(158/509),不同年级、专业、眼镜佩戴、眼部化妆行为大学生干眼患病率差异有统计学意义(x2值分别为17.12,12.50,10.28,4.56,P值均<0.01).多因素Logistic回归分析发现,年级(OR=1.43)、专业类别(OR=0.67)、眼镜佩戴(OR=0.63)均是大学生干眼病的影响因素(P值均<0.01).结论 大学生干眼的患病率较高,应加大对干眼病相关知识及预防措施宣教,预防干眼病的发生.     

网络行为对大学生学习成绩和心理健康状况的影响

目的探讨上网行为对大学生学习成绩、心理健康状况的影响,为高校教育工作者引导大学生科学地应用网络提供理论依据.方法分层整群抽取长沙市中南大学、湖南师范大学、长沙大学的本、专科学生945人,对学习成绩、心理健康状况进行多因素Logistic回归分析.结果专业兴趣、抑郁、玩网络游戏与学习成绩有关(P＜0.05),学习任务、专业兴趣、平均每天上网时间、网龄与心理健康有关(P＜0.05).结论学习成绩和心理健康与网络行为密切相关.     

大学生足部卫生状况及其影响因素分析

目的了解大学生卫生习惯、足部卫生现状及相关知识知晓率,为大学生足部皮肤病防治提供依据。方法采用分层整群抽样法,随机抽取新乡3所高校的40个班级,对所抽到班级的所有学生进行问卷调查,共调查学生1020名。结果大学生足部皮肤病患病率为57.3%,其中足癣、甲真菌病、趾疣、嵌甲的患病率分别为35.7%,15.6%,8.6%,23.1%,男、女生患病率差异均有统计学意义(P值均0.01);鸡眼、湿疹患病率分别为12.1%,8.3%,男、女生患病率差异无统计学意义。不同学校学生足癣患病率差异有统计学意义(χ2=12.002,P=0.002),大部分大学生的足部皮肤病防治知识比较匮乏。结论大学生足部皮肤病特别是足癣患病率较高,足部健康知识贫乏。学校应加强健康教育,提高学生防范意识,改进其足部卫生习惯。     

潮汕地区大学生网络行为心理调查与对策研究

目的 了解大学生使用网络情况,进一步了解网络对大学生的影响.方法 采用问卷调查法,对广东潮汕4所大专院校600名大学生进行了网络使用情况的抽样调查.结果 潮汕地区大学生100 %有上网经历,13.31 %有网络成瘾的倾向.上网聊天频率最高,为63.72 %,其次为查资料,为54.13 %.结论 过度上网给学生心理方面造成很大影响.高校应指导大学生正确、适度上网.阅读疗法是集预防、治疗、发展健康心理于一体的心理治疗方法.是一种引导大学生正确上网的有效措施.     

某高校学生病理性网络使用心理社会因素分析

目的 探讨影响大学生病理性网络使用（PIU）的社会心理危险因素,为大学生病理性网络使用的防治和干预提供依据.方法 采用病理性网络使用问卷对1 058名大学生进行调查,同时运用SCL-90、艾森克个性问卷（EPQ）、青少年生活事件量表（ASLEC）、抑郁自评量表（SDS）、社会支持评定量表（SSRS）等问卷,对病理性网络使用者的社会心理危险因素进行调查,并进行非条件Logistic多因素逐步回归分析.结果 病理性网络使用者占被调查人数的6.99%;多因素回归分析显示：病理性网络使用组与对照组在情绪稳定性、负性生活事件、社会支持、社会支持利用度方面,差别有统计学意义.结论 大学生病理性网络使用与社会心理因素关系密切.     

遵义市高校大学生耳鸣现状及危险因素分析

调查高校大学生耳鸣患病现状及危险因素,为预防高校学生的耳鸣发病提供有针对性的防控建议.方法 采用多阶段分层整群抽样的方法,抽取遵义市2 438名高校大学生进行现场流行病学调查,收集一般情况、生活方式、噪声接触等资料,采用t检验、x2检验以及多因素非条件Logistic回归分析高校学生耳鸣的危险因素.结果 大学生耳鸣患病率达16.00%,其中女生为17.00%,男生为13.93%,女生耳鸣检出率高于男生(x2=3.77,P<0.05).多因素非条件Logistic回归分析结果表明,影响大学生耳鸣的因素有饮酒(OR=1.54)、体育锻炼频率较少(OR=1.15)、失眠次数较多(OR=1.48)、去酒吧(OR=1.50)以及去KTV的频率较高(OR=1.32)(P值均<0.05).结论 高校学生耳鸣的危险因素众多.应根据影响因素加大对耳鸣的防控力度,降低耳鸣的患病率.     

大学生病理性互联网使用影响因素的Logistic回归分析

目的探讨大学生病理性互联网使用的影响因素,以寻求有效的预防和干预措施。方法整群抽取湖南省部分高校17～25岁大学生共1212名为研究对象。采用现场问卷调查法,了解大学生病理性互联网使用情况及其影响因素。结果大学生网络使用率为94.47%,病理性互联网使用的发生率为11.09%。Logistic回归分析表明,某些负性心理特征、网络吸引因素及感到大学生活紧张等是促使大学生病理性互联网使用的主要因素,性别为女生、自信、专业的满意度较高、家庭和睦温暖则是保护因素。结论影响大学生病理性互联网使用的因素较多。应从生活、思想、学习等各方面给病理性互联网使用者提供关怀与心理支持。     

山东省医学生网络成瘾现状及影响因素研究

目的 了解山东省医学生网络成瘾现状及其影响因素,为医学生网络成瘾的预防和干预提供对策建议.方法 采用分层随机整群抽样方法,抽取山东省4所本科院校1 009名医学生为研究对象,运用自编网络使用情况调查表和Young氏网络成瘾诊断量表对其进行匿名测评.结果 山东省医学生网络成瘾率为4.76%.网络成瘾组和非网络成瘾组在性别、学习成绩、月均网费、上网途径、是否玩网游、对网络色情的态度、浏览网站类型、上网目的几个方面差异有统计学意义(均P<0.05).Logistic回归分析显示,玩网游(OR=6.451)、上网目的为购物(OR=4.275)、学习成绩差(OR=2.138)、男性(OR=1.927)为网络成瘾的危险因素,上网目的为娱乐(OR=0.466)、上网目的为浏览信息(OR=0.448)、用手机上网(OR=0.416)、主要浏览休闲娱乐网(OR=0.415)是网络成瘾的保护因素.结论 医学生网络成瘾状况需要引起重视,要根据其网络成瘾的影响因素,有重点、全方位、多层次地采取相应的防控措施.     

How The Internet Skills Of European 11- To 16-Year-Olds Mediate Between Online Risk And Harm

Not all children who use the internet will experience harm from the online risks they encounter. One of the factors that might moderate the relationship between risk and harm is children's internet skills. As there has been little research on this topic, this article examines the influence of internet skills on the prevalence of online risks and the degree to which 11- to 16-year-olds experience being harmed by these risks, using data from the EU Kids Online project. The findings suggest that, whilst older children (aged 13–16) are exposed to more online risks, younger children (11–12) report more often being harmed by these risks. After controlling for differences between children due to demographics and internet experience, as well as country differences (using multilevel analysis), the findings reveal that children with more self-reported internet skills experience more risks online. Such skills do not seem to contribute much to differences in being harmed by online risks.     

Prevalence and Associated Factors of Pathological Internet Use and Online Risky Behaviors Among Japanese Elementary School Children

BackgroundLittle is known about pathological Internet use (PIU) and online risky behaviors among elementary school children. We aimed to investigate the prevalence and factors associated with PIU and online risky behaviors.MethodsA school-based cross-sectional study was conducted in Toyama, Japan in 2018. The study included 13,413 children in the 4th–6th grades (mean, 10.5 years old) from 110 elementary schools (61.1% of elementary schools in Toyama). We assessed PIU using Young’s Diagnostic Questionnaire (YDQ) and risky behaviors. Poisson regression analysis was conducted.ResultsTotally, 13,092 children returned questionnaires (response rate 97.6%). The prevalence of PIU was 4.2% and that of each risky behavior was as follows: 21.6% for spending money online, 6.6% for uploading personal movies, 5.2% for interpersonal issues, and 2.4% for having met strangers. PIU was significantly associated with boys (prevalence ratio [PR] 1.26; 95% confidence interval [CI], 1.04–1.52), skipping breakfast (PR 1.43; 95% CI, 1.14–1.79), Internet time (for 2∼3 h, PR 3.49; 95% CI, 2.63–4.65; for 3∼4 h, PR 4.45; 95% CI, 3.27–6.06; and for ≥4 h, PR 8.25; 95% CI, 6.45–10.55), physical inactivity (PR 2.63; 95% CI, 2.00–3.47), late bedtime (PR 1.86; 95% CI, 1.45–2.39 for ≥11 p.m.), no rules at home (PR 1.22; 95% CI, 1.01–1.46), no child-parent interaction (PR 1.37; 95% CI, 1.06–1.77), and no close friends in real life (PR 1.69; 95% CI, 1.30–2.19).ConclusionsPIU and risky behaviors were not rare among the elementary school children. Besides unhealthy lifestyles, social and family environments were associated with PIU. Having child-parent interaction and helping children develop close friendships in real life are effective deterrents to PIU.Key words: disharmony, family, gaming disorder, Internet addiction, problematic     

Measuring Problematic Internet Use,Internet Gaming Disorder,and Social Media Addiction in Young Adults: Cross-sectional Survey Study

BackgroundDigital technology use is nearly ubiquitous among young adults; this use provides both benefits and risks. The risks of technology use include maladaptive technology use or technology addiction. Several conceptualizations of these addictions have emerged, each with its own assessment tools. These conditions include problematic internet use (PIU), internet gaming disorder (IGD), and social media addiction (SMA). These conditions have been associated with health outcomes such as problematic alcohol use, sleep disorders, and mental illness. These maladaptive technology conditions have been most commonly studied in isolation from each other.ObjectiveThe aim of this study is to examine PIU, IGD, and SMA together to better inform future research approaches and provider screening practices for young adults.MethodsThis cross-sectional survey study was conducted using Qualtrics panel-based recruitment and survey hosting. We recruited US young adults aged 18-25 years. The survey assessed PIU, IGD, and SMA. Survey measures also included assessments of problematic alcohol use, sleep, depression, and anxiety. We evaluated the frequency of and overlap in positive screening scores among PIU, IGD, and SMA and modeled each condition using multivariate logistic regression. Finally, we calculated sensitivity and specificity, as well as the positive predictive value and negative predictive value of the screening tools using the most prevalent maladaptive technology type.ResultsOur 6000 participants had an average age of 21.7 (SD 2.5) years. Of these 6000 participants, 3062 (51.03%) were female, 3431 (57.18%) were Caucasian, 1686 (28.1%) were in a 4-year college program, and 2319 (38.65%) worked full time. The mean PIU score was 3.5 (SD 3.1), and 53.58% (3215/6000) of participants met the criteria for PIU. The mean IGD score was 2.7 (SD 2.6), and 24.33% (1460/6000) of participants met the criteria for IGD. The mean SMA score was 7.5 (SD 5.7), and 3.42% (205/6000) met the criteria for SMA. Across all 3 maladaptive technology use diagnoses, there were varied associations with demographic variables and similar overlap with health outcomes. The sensitivity of PIU screening to detect IGD was 82% and to detect SMA was 93%, whereas the specificity and positive predictive value were much lower (37%-54% specificity; 6%-37% positive predictive value).ConclusionsThis cross-sectional survey screened a large national sample of adolescents and young adults for PIU, IGD, and SMA to determine prevalence and overlap, demographic associations with each, and associations between these technology-related conditions and health outcomes. There was overlap across PIU, IGD, and SMA in some associated demographic variables and health outcomes. However, the patterns in the associated variables demonstrated unique qualities of each of these conditions.     

北京市高中生网络成瘾行为现状及其影响因素分析

目的 了解北京市高中生网络成瘾行为现状及其影响因素,为相关防控干预提供理论依据。方法 采取分层整群随机抽样方法 ,在2014年4-5月抽取北京市18个区县35所重点高中、36所普通高中和31所职业技术学校,并对18 154名学生进行了分析。结果 4.7%的学生报告有网络成瘾行为,其中男生网络成瘾报告率为5.5%,明显高于女生的4.0%(P<0.001);年级越高、母亲文化程度越高的学生网络成瘾报告率越低(χ²=41.00、23.49,P均<0.01);学习成绩自我评价低、职业高中、非核心家庭的学生更易发生网络成瘾(χ²=22.54、66.16和χ²=11.52,P均<0.01)。Logistic回归模型显示,男性、学习成绩自我评价低、单亲、重组及隔代家庭、有过受欺侮行为、常感到孤独及有过性行为是网络成瘾的危险因素,体育锻炼是网络成瘾的保护因素(OR=0.49~0.92)。结论 青少年网络成瘾与家庭、学习成绩、受欺侮行为、情绪问题、身体锻炼和性行为密切相关,应联合家庭、学校和社会对学生网络成瘾行为进行干预,并建立预防机制。     

Attitudes toward online HIV/sexually-transmitted infection prevention programs and Internet user profiles among men who have sex with men

Objectives

To describe the attitudes of men who have sex with men (MSM) toward online HIV/sexually-transmitted infection (STI) prevention programs and to identify and characterize user profiles with regard to their attitudes toward online prevention programs.

Method

A survey in gay venues or via the internet was completed by 2,044 participants from Madrid, Barcelona, Bilbao and San Sebastián (Spain). The survey explored socio-demographic variables, sexual behavior and other risk behaviors associated with HIV infection, as well as attitudes toward online prevention programs. The statistical analysis included factor analysis and non-hierarchical cluster analysis.

Results

Most MSM had positive attitudes towards online HIV/STI prevention programs. Factor analysis revealed two factors: online prevention aimed at interaction and online prevention aimed at information. Based on these factors, three user profiles were identified: users oriented toward informative and interactive online prevention (53.5%), users oriented toward interactive online prevention (25.9%) and users were not oriented toward online prevention (20.7%). On characterizing these profiles, we observed a significant presence of men who were not interested in online prevention among those with a lower educational level, bisexual men and HIV-positive men. Conversely, those most receptive to online prevention were men self-identified as gay, those with a bachelors degree, those who had been tested for HIV and those who were HIV-negative.

Conclusion

The internet can facilitate sexual health promotion among MSM. Characterization of user profiles offers the possibility of segmenting prevention programs and of combining online and offline strategies.     

6～9岁儿童单纯性肥胖发生状况分析

目的:探讨儿童单纯性肥胖的发生状况,为预防和减少其发生提供科学依据。方法:应用多级整群抽样方法,随机抽取长沙市开福区10所小学和深圳市南山区5所小学作为调查的研究现场。收集所有6～9岁学龄儿童年龄、性别、身高、体重等基本信息,计算儿童肥胖的检出率,对儿童单纯性肥胖的发生状况进行分析。结果:儿童单纯性肥胖的检出率为3.59%,其中男生的检出率为5.38%,女生的检出率为1.61%,男生高于女生;深圳市儿童肥胖标准化检出率高于长沙;6～9岁儿童肥胖发生率随着年龄的升高而上升。结论:儿童单纯性肥胖的发生状况与性别、年龄及地区经济状况等因素有关。