社区老年人的生活质量与心理健康:SEM研究

在Lawton理论框架以及先前研究基础上,进一步对上海社区老年人生活质量与心理健康进行研究。采用结构方程建模的方法对老年人健康生活质量(QHL)、客观生活环境质量(QOE)与心理健康(PWB)的理论构念及其相互关系的理论模型予以实证研究。结果表明,该模型与社区老人测评数据(N=262)的拟合度良好,证明QHL对PWB具有显著正面影响,QOE与QHL显著相关且直接或间接地正面影响PWB。研究表明良好身体健康状况、行为调适能力以及家庭一社区养老环境对促进老人心理健康具有重要意义。     

Long-term efficacy of exercise across diagnostically heterogenous mental disorders and the mediating role of affect regulation skills

BackgroundExercise interventions are efficacious in reducing disorder-specific symptoms in various mental disorders. However, little is known about long-term transdiagnostic efficacy of exercise across heterogenous mental disorders and the potential mechanisms underlying treatment effects.MethodsPhysically inactive outpatients, with depressive disorders, anxiety disorders, insomnia or attention deficit hyperactivity disorder were randomized to a standardized 12-week exercise intervention, combining moderate exercise with behavior change techniques (BCTs) (n = 38), or a passive control group (n = 36). Primary outcome was global symptom severity (Symptom Checklist-90, SCL-90-R) and secondary outcomes were self-reported exercise (Physical Activity, Exercise, and Sport Questionnaire), exercise-specific affect regulation (Physical Activity-related Health Competence Questionnaire) and depression (SCL-90-R) assessed at baseline (T1), post-treatment (T2) and one year after post-treatment (T3). Intention-to-treat analyses were conducted using linear mixed models and structural equations modeling.ResultsFrom T1 to T3, the intervention group significantly improved on global symptom severity (d = −0.43, p = .031), depression among a depressed subsample (d = −0.62, p = .014), exercise (d = 0.45, p = .011) and exercise-specific affect regulation (d = 0.44, p = .028) relative to the control group. The intervention group was more likely to reveal clinically significant changes from T1 to T3 (p = .033). Increases in exercise-specific affect regulation mediated intervention effects on global symptom severity (ß = −0.28, p = .037) and clinically significant changes (ß = −0.24, p = .042).ConclusionsThe exercise intervention showed long-term efficacy among a diagnostically heterogeneous outpatient sample and led to long-lasting exercise behavior change. Long-term increases in exercise-specific affect regulation within exercise interventions seem to be essential for long-lasting symptom reduction.     

Explaining the Relationship between Religiosity and Political Participation: The Mediating Roles of Transcendent Accountability and Religiopolitical Awareness

Prior research tends to find a positive relationship between religiosity and political participation. Explanations of this relationship have focused mostly on religiosity-generated organizational resources (e.g., civic skills), while paying less attention to psychological resources. We simultaneously examined different aspects of religiosity (belief, behavior, and belonging) and political participation (electoral and nonelectoral) in a structural equation model with two psychological resources as mediators: (1) “transcendent accountability”—seeing oneself as responsible to God or a higher power for one's impact on other people and the environment, and (2) “religiopolitical awareness”—perceiving the influence of one's religion and/or spirituality on one's political views and activities. Results from analyzing survey data from a US representative sample showed that transcendent accountability and religiopolitical awareness, whether together or awareness only, mediated positive relationships between religiosity (belief, private and public behaviors, and membership) and political participation (voting and other political activity), highlighting key psychological motivators of political participation.     

有调节的多层中介效应分析

多层中介和多层调节效应分析在社科领域已常有应用,但如果将多层中介和调节整合在一起,可以产生2（多层中介类型）×2（调节变量的层次）×3（调节的中介路径）共12种有调节的多层中介模型。面对有调节的多层中介效应分析,研究者往往束手无策。详述了基于多层线性模型的12种有调节的多层中介的分析方法和基于多层结构方程模型的4类有调节的多层中介分析方法,包括正交分割法,随机系数预测法,潜调节结构方程法和贝叶斯合理值法。这四类方法的核心议题在于如何处理潜调节项。当样本量足够大时,建议选择潜调节结构方程法;当样本量不足时,建议选择贝叶斯合理值法。随后用一个实际例子演示如何进行有调节的多层中介效应分析并有相应的Mplus程序。最后展望了有调节的多层中介效应分析研究的拓展方向。     

Thurstonian modeling of ranking data via mean and covariance structure analysis

Although Thurstonian models provide an attractive representation of choice behavior, they have not been extensively used in ranking applications since only recently efficient estimation methods for these models have been developed. These, however, require the use of special-purpose estimation programs, which limits their applicability. Here we introduce a formulation of Thurstonian ranking models that turns an idiosyncratic estimation problem into an estimation problem involving mean and covariance structures with dichotomous indicators. Well-known standard solutions for the latter can be readily applied to this specific problem, and as a result any Thurstonian model for ranking data can be fitted using existing general purpose software for mean and covariance structure analysis. Although the most popular programs for covariance structure analysis (e.g., LISREL and EQS) cannot be presently used to estimate Thurstonian ranking models, other programs such as MECOSA already exist that can be straightforwardly used to estimate these models.This paper is based on the author's doctoral dissertation. Ulf Böckenholt was my advisor. The author is indebted to Ulf Böckenholt for his comments on a previous version of this paper and to Gerhard Arminger for his extensive support on the use of MECOSA. The final stages of this research took place while the author was at the Department of Statistics and Econometrics, Universidad Carlos III de Madrid. Conversations with my colleague there, Adolfo Hernández, helped to greatly improve this paper.     

An incomplete data approach to the analysis of covariance structures

In this paper, linear structural equation models with latent variables are considered. It is shown how many common models arise from incomplete observation of a relatively simple system. Subclasses of models with conditional independence interpretations are also discussed. Using an incomplete data point of view, the relationships between the incomplete and complete data likelihoods, assuming normality, are highlighted. For computing maximum likelihood estimates, the EM algorithm and alternatives are surveyed. For the alternative algorithms, simplified expressions for computing function values and derivatives are given. Likelihood ratio tests based on complete and incomplete data are related, and an example on using their relationship to improve the fit of a model is given.This research forms part of the author's doctoral thesis and was supported by a Commonwealth Postgraduate Research Award. The author also wishes to acknowledge the support of CSIRO during the preparation of this paper and the referees' comments which led to substantial improvements.     

Latent curve analysis

As a method for representing development, latent trait theory is presented in terms of a statistical model containing individual parameters and a structure on both the first and second moments of the random variables reflecting growth. Maximum likelihood parameter estimates and associated asymptotic tests follow directly. These procedures may be viewed as an alternative to standard repeated measures ANOVA and to first-order auto-regressive methods. As formulated, the model encompasses cohort sequential designs and allow for period or practice effects. A numerical illustration using data initially collected by Nesselroade and Baltes is presented.The authors wish to thank John Nesselroade for providing us the data for our illustration and Karen Paul and Connie Tilse for assisting in the data analysis. This research was supported by a grant (No. AG03164) from the National Institute on Aging to the senior author.     

Predictors of multiple concurrent and multiple sexual partnerships among male and female youth aged 18–24 in South Africa

This study aimed to determine predictors of multiple concurrent and multiple sexual partnerships among South African male and female youth. Data were from a cross-sectional population-based household survey of 3 123 youths aged 18 to 24 years from four South African provinces (males = 53.6%, blacks = 97.8%). Results from a sub-sample of being sexually active in the past 12 months (n = 1787) indicate that 5.3% (7.1% in males and 3.1% in females) youth participants had multiple concurrent sexual partners, and 38.8% (50.1% in males and 25.8% in females) had had two or more sexual partners in the past 12 months. Among females, multiple concurrent partnerships were only predicted by lower social network resources. Predictors of multiple sexual partnerships (two or more sexual partners in the past 12 months) among males included high HIV risk perception, never been tested for HIV and hazardous or harmful alcohol use. By contrast, among females, high peer pressure, lower education and ever having taken drugs predicted involvement with multiple sexual partners. Multi-level health promotion interventions are indicated for sexual behaviour change among South African youth.     

The EffectLiteR Approach for Analyzing Average and Conditional Effects

We present a framework for estimating average and conditional effects of a discrete treatment variable on a continuous outcome variable, conditioning on categorical and continuous covariates. Using the new approach, termed the EffectLiteR approach, researchers can consider conditional treatment effects given values of all covariates in the analysis and various aggregates of these conditional treatment effects such as average effects, effects on the treated, or aggregated conditional effects given values of a subset of covariates. Building on structural equation modeling, key advantages of the new approach are (1) It allows for latent covariates and outcome variables; (2) it permits (higher order) interactions between the treatment variable and categorical and (latent) continuous covariates; and (3) covariates can be treated as stochastic or fixed. The approach is illustrated by an example, and open source software EffectLiteR is provided, which makes a detailed analysis of effects conveniently accessible for applied researchers.