农民心理健康与人格类型、经济收入、文化程度的相关研究

为了了解农民心理健康现状及其与人格类型、经济收入、文化程度之间的相互关系。我们采用症状自评量表(SCL-90)和艾森克人格量表(EPQ),随机抽取吉林省各市、州470名农民进行调查,并与国内常模进行比较。结果表明:农民的心理健康水平低于全国正常人的平均水平;大多数农民倾向于内倾性格,情绪稳定;经济收入、文化程度是影响农民心理健康的重要因素。     

大学生心理健康现状及对策分析

近年来,大学生心理健康问题日益突现,引起了人们的广泛关注。本文在简要分析了大学生心理健康现状和心理问题的表现后,根据笔者多年思政教育工作实践,提出高校心理健康教育应分成三个有机组成部分,即早期心理健康教育与心理问题预防、心理问题预警与干预、心理危机应急处理与事后控制,并分别进行了深入研究。     

普通大学生心理健康的评价方法

人的体质健康应是具有良好的生理机能,完善的身体形态,较强的身体活动能力和健康的心理状态.在有关大学生体质健康研究结果与文献的基础上,文章通过对多种心理健康测试方法的分析研究,旨在找到与发现一种适合于我国普通大学生心理健康方面进行综合评价的心理健康测试、评价方法.     

基于风险承受能力的大学生就业选择的实证

文章通过对中南大学在读本科生和硕士研究生进行问卷调查,获取数据,建立计量模型验证了风险承受能力应当作为大学生就业选择时重要考虑因素的假定,同时分析了大学生风险承受能力的影响因素。     

对当代大学生心理健康问题的思考

文章从当代大学生心理健康问题的现状出发,分析目前大学生心理健康问题的主要特点及成因,提出了解决大学生心理健康问题的办法,以期让每一名大学生都能全面发展,健康成长,成为21世纪复合型、开拓创新型、多向思维能力的人才。     

青少年心理健康的影响因素与群体差异——基于CEPS数据的多水平分析

青少年心理健康的影响因素及其作用机制是现有研究尚未充分讨论的问题。使用中国教育追踪调查(CEPS)基线数据进行多水平分析的结果显示,青少年心理健康不仅受到家庭因素、压力因素和人际关系因素的影响,还受到学校群体因素的作用。其中,群体经济地位和群体教育程度不仅对青少年的心理健康产生直接效应,还通过调节作用间接地影响家庭亲子关系和学业压力对青少年心理健康的作用强度,这些结论可为进一步认识学校在青少年身心全面发展中的作用机制提供一定的参考。     

户籍制度背景下农民工与城市工的人格特质比较

我国特有的二元户籍制度导致农民工在城市不能同等地享有劳动收入、社会保障、公共服务等,这些外部生存障碍是否对农民工的人格特质产生影响值得研究.文章基于广东省制造企业-员工匹配的实证调查,采用BIF大五人格量表,分析同在制造业工作的农民工和城市工的人格差异.研究发现:户籍不同的农民工和城市工在16～25岁群组人格特质相差不大,甚至农民工的尽责性要稍高于城市工;从26～35岁群组起两者之间出现人格距离,农民工五个维度的人格特质开始低于城市工,随着年龄的增长两者人格距离越来越大;56岁以上的群组,两者人格距离最为明显.这说明50后农民工在临近退休时,因各方面保障的缺乏人格特质与城市工有了显著差异.建议改革户籍制度,特别是要破除农民工在享有城市资源和公共服务等方面的无形墙.     

大学生心理健康教育与思想政治教育相结合的有效途径

一、充分认识大学生心理健康教育与思想政治教育的相关性高等学校大学生心理健康教育和思想政治教育是学校德育工作的重要组成部分,心理健康教育与思想政治教育既有联系又有区别,思想政治教育工作重点在于解决世界观、价值观和人生观的问题,而心理健康教育工作的重点在于对自我     

2010届高校毕业生意向选择的统计考察——以武汉地区部分高校为例

全球金融危机对我国大学生的就业产生了严重冲击,这在2009届毕业生就业时已经体现得非常明显,使得2010届毕业生在选择考研或者就业时难以取舍。文章首先把考研看作一项人力资本投资,在各种因素得以量化的条件下,通过改进成本收益分析的简化模型,运用净现值法分析考研这项投资的成本收益,计算出全国各个地区大学生投资硕士研究生教育的净收益,结果表明个人投资硕士研究生教育是一项高回报的投资。并进一步运用计量经济模型和平均增长率方法预测我国2010年硕士研究生报名人数,在此基础上分析相关的影响因素。最后提出金融危机背景下进行研究生教育投资的相关建议。     

心理资本量表在大学生群体中的修订与信效度检验

修订心理资本量表并检验其在大学生群体中的信度和效度。文章以549名大学生为样本进行项目分析和探索性因子分析;以1082名大学生为样本进行验证性因子分析、信度分析和校标效度分析,并抽取62名被试4周后重测。结果表明:(1)修订后的心理资本量表可以提取自信、希望、坚韧性和乐观四个因子,累积解释方差60.8%,具有较好的结构效度(χ2=615.46,GFI=0.94,AGFI=0.92,CFI=0.92,IFI=0.92,RMSEA=0.07)。(2)修订后的量表信度为0.89,重测信度为0.70;各分量表的信度介于0.73~0.81,重测信度介于0.50~0.62。(3)心理资本量表及其分量表与主观幸福感、积极情绪正相关(r=0.35~0.69,P<0.001),与学业倦怠、学业拖延负相关(r=-0.17~-0.48,P<0.001)。修订后的心理资本量表符合心理测量学要求,可以作为大学生心理资本的测量工具。     

基于结构方程模型的城市流动人口心理健康影响因素分析

利用清华大学"中国城镇化与劳动移民研究成人问卷"的数据信息进行结构方程模型建构,以此研究个体因素和社会因素如何具体影响流动人口心理健康。研究结果显示:女性流动人口心理健康状况相对于男性要差;教育因素对女性流动人口心理健康的影响更为明显,教育水平越高的流动人口心理状态表现更积极;经济因素对流动人口心理健康影响不显著;流动人口的社会交往程度越高,城市居民对流动人口的社会排斥程度越低,他们的心理健康状况就越好。因此,在关注流动人口时不能只关注经济因素,城市应创造一个更友善的社会环境来接纳流动人口,并提供更多的社会交往空间,使其在城市更健康快乐的生活。     

社会经济地位与老年健康——基于(CGSS)2013数据的实证分析

借助中国综合社会调查(CGSS)2013年的截面数据,选取3 108个60岁及以上老年人样本,采用有序Probit模型,从自评健康、心理健康和生理健康三个维度,考察反映老年人社会经济地位的诸多因素对其健康的影响。实证结果表明:较高的社会经济地位对老年人健康有明显的提升作用。城镇老年人的健康状况明显好于农村,但农村老年人更为广泛的社会网络对其精神支持的影响较城镇老年人更大。具有党员身份的老年人与其心理健康呈显著正向关系,老年人的健康状况也会随受教育程度的提高而改善,主观阶层认同较高的老年人的健康水平也相对较高。从人口学特征来看,老年男性的健康状况比女性要好,有配偶的老年人精神状态更加乐观。就政策含义而言,当下应针对老年群体的异质性给予更多关注,积极提升老年人的生命质量和生活质量,共同营造一个"健康老龄化"的社会。     

大学生考研意愿调查报告

通过对在校大学生的抽样调查,分析了当前大学生考研意愿的现状及影响考研意愿的因素,解释了导致当前研招报考人数下降的原因,力图为相关政策制定和高校教学改革提供依据。     

Tell me why I don't like Mondays: investigating day of the week effects on job satisfaction and psychological well-being

Summary.  The paper explores the relationship between the day of the week on which a survey respondent is interviewed and their self-reported job satisfaction and mental health scores by using data from the British Household Panel Survey. Evidence presented here confirms that self-reported levels of job satisfaction and subjective levels of mental distress systematically vary according to the day of the week on which respondents are interviewed even when controlling for other observed and unobserved characteristics. However, we find that the main conclusions from previous studies of the determinants of job satisfaction and mental well-being are robust to the inclusion of day-of-interview controls.     

“新农保”影响了老人的健康绩效吗?——来自中国老年健康影响因素跟踪调查的证据

基于"中国老年健康影响因素跟踪调查"2008-2011/2012年两期面板数据,使用PSMDD方法和中介效应模型系统评估"新农保"对老人健康的影响。结果表明,新农保政策的实施对老人的健康既发挥了积极作用,又带来了消极影响。"新农保"能够显著改善老人的自理能力和减少患慢性病数,提高了老人的生理健康,但是却降低了老人的幸福感,使老人患抑郁症的可能性显著提升,导致老人的心理健康状况恶化。提高老人健康绩效的重点应在于对老人心理健康的照料和饮食条件的改善。同时,政府应注意到新农保制度实施过程中的消极影响,提早预防和改进。     

Bayesian structural equation modeling for the health index

There are many factors which could influence the level of health of an individual. These factors are interactive and their overall effects on health are usually measured by an index which is called as health index. The health index could also be used as an indicator to describe the health level of a community. Since the health index is important, many research have been done to study its determinant. The main purpose of this study is to model the health index of an individual based on classical structural equation modeling (SEM) and Bayesian SEM. For estimation of the parameters in the measurement and structural equation models, the classical SEM applies the robust-weighted least-square approach, while the Bayesian SEM implements the Gibbs sampler algorithm. The Bayesian SEM approach allows the user to use the prior information for updating the current information on the parameter. Both methods are applied to the data gathered from a survey conducted in Hulu Langat, a district in Malaysia. Based on the classical and the Bayesian SEM, it is found that demographic status and lifestyle are significantly related to the health index. However, mental health has no significant relation to the health index.     

A time-varying measurement error model for age of onset of a psychiatric diagnosis: applied to first depressive episode diagnosed by the Composite International Diagnostic Interview (CIDI)

A substantial degree of uncertainty exists surrounding the reconstruction of events based on memory recall. This form of measurement error affects the performance of structured interviews such as the Composite International Diagnostic Interview (CIDI), an important tool to assess mental health in the community. Measurement error probably explains the discrepancy in estimates between longitudinal studies with repeated assessments (the gold-standard), yielding approximately constant rates of depression, versus cross-sectional studies which often find increasing rates closer in time to the interview. Repeated assessments of current status (or recent history) are more reliable than reconstruction of a person's psychiatric history based on a single interview. In this paper, we demonstrate a method of estimating a time-varying measurement error distribution in the age of onset of an initial depressive episode, as diagnosed by the CIDI, based on an assumption regarding age-specific incidence rates. High-dimensional non-parametric estimation is achieved by the EM-algorithm with smoothing. The method is applied to data from a Norwegian mental health survey in 2000. The measurement error distribution changes dramatically from 1980 to 2000, with increasing variance and greater bias further away in time from the interview. Some influence of the measurement error on already published results is found.     

A Joint Modeling Approach for Longitudinal Outcomes and Non-ignorable Dropout under Population Heterogeneity in Mental Health Studies

The paper proposes a joint mixture model to model non-ignorable drop-out in longitudinal cohort studies of mental health outcomes. The model combines a (non)-linear growth curve model for the time-dependent outcomes and a discrete-time survival model for the drop-out with random effects shared by the two sub-models. The mixture part of the model takes into account population heterogeneity by accounting for latent subgroups of the shared effects that may lead to different patterns for the growth and the drop-out tendency. A simulation study shows that the joint mixture model provides greater precision in estimating the average slope and covariance matrix of random effects. We illustrate its benefits with data from a longitudinal cohort study that characterizes depression symptoms over time yet is hindered by non-trivial participant drop-out.KEYWORDS: Latent growth curve, MNAR drop-out, survival analysis, finite mixture model, mental health     

Bivariate frailty model for the analysis of multivariate survival time

Because of limitations of the univariate frailty model in analysis of multivariate survival data, a bivariate frailty model is introduced for the analysis of bivariate survival data. This provides tremendous flexibility especially in allowing negative associations between subjects within the same cluster. The approach involves incorporating into the model two possibly correlated frailties for each cluster. The bivariate lognormal distribution is used as the frailty distribution. The model is then generalized to multivariate survival data with two distinguished groups and also to alternating process data. A modified EM algorithm is developed with no requirement of specification of the baseline hazards. The estimators are generalized maximum likelihood estimators with subject-specific interpretation. The model is applied to a mental health study on evaluation of health policy effects for inpatient psychiatric care.     

The mystery of the lost star: A statistical detective story

In July 2005 the Healthcare Commission released its annual "star ratings" for English National Health Service (NHS) trusts¹, in which acute or specialist hospitals, mental health services, ambulance services and primary care trusts were each given 0, 1, 2 or 3 stars. There was some surprise that the Cambridge University Hospitals NHS Foundation Trust (better known as Addenbrooke's Hospital) dropped from the 3 stars obtained in 2004 to 2 stars. David Spiegelhalter investigated .