Parental education and children's online health information seeking: Beyond the digital divide debate

Research has shown that increasing numbers of teenagers are going online to find health information, but it is unclear whether there are disparities in the prevalence of online health seeking among young Internet users associated with social and economic conditions. Existing literature on Internet uses by adults indicates that low income, less educated, and minority individuals are less likely to be online health seekers. Based on the analysis of data from the Pew Internet and American Life Project for the US, this study finds that teens of low education parents are either as likely as or even more likely than teens of high education parents to seek online health information. Multiple regression analysis shows that the higher engagement in health seeking by teens of low education parents is related to a lower prevalence of parental Internet use, suggesting that some of these teens may be seeking online health information on behalf of their low education parents. Implications of these findings are discussed in relation to the issues of the digital divide and digital empowerment.     

Bayesian estimation of a random effects heteroscedastic probit model

Summary Bayesian analysis is given of a random effects binary probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an efficient Markov chain Monte Carlo sampling scheme that generates the parameters in blocks. We use the Bayes factor, cross‐validation of the predictive density, the deviance information criterion and Receiver Operating Characteristic (ROC) curves for model comparison.     

Fisher information matrix for nonlinear mixed effects multiple response models: Evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model

We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic–pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation–maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first‐order linearization estimation methods implemented in the NONMEM software (first‐order (FO), first‐order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite. Copyright © 2009 John Wiley & Sons, Ltd.     

Working‐correlation‐structure identification in generalized estimating equations

Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well‐known criterion of QIC for selecting a working correlation structure, and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads us to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study. Copyright © 2008 John Wiley & Sons, Ltd.     

随机系统的最小熵控制

本文放弃传统的MSE准则,从信息论观点出发,发展了随机系统的一种最小熵(ME)控制方法,并从ME控制的等价性、控制限度、存在性、唯一性及必要条件等方面,研究了ME控制的合理性和实用性。ME方法是一种全局分析法,它不仅包含了MSE和MAP准则,且由于全文在整个推导中并未假定高斯性、线性和非时变等,因而原则上适用于诸如非高斯、非线性、时变等传统方法难以处理的复杂系统;不仅适用于工程系统,将其推广到决策、社会、经济等领域会更为自然和切合实际。     

Internet tools in the medical classroom

Summary: The Internet contains a vast amount of medically relevant information. In order to access this information, however, many networks require one to master applications written in UNIX, an operating system considered by many not to be user friendly. Although these tools may be available on the campus, it is difficult to teach their use unless there is some immediate benefit to the already busy user. From that standpoint, it is important for instructors to realize that common UNIX applications can be utilized as classroom tools to significantly enhance the learning experience by facilitating teacher/student communication. Also, whilst the student enjoys greater communication with the instructor (and with other students) he/she is also becoming adept at using information management tools.     

Cognitive processes involved in the appraisal of stress

Four experiments were organized around a central question: What is the form of relationship between estimated stress level on the one hand and situation strain, personal resources and social support, on the other? The first experiment examined the form of the relationship between estimated level of stress, situation strain and personal resources. The participants were students. They integrated situation strain and personal resources information in a non‐additive way. In particular, the effect of personal resources on the estimated level of stress varied as a function of the level of situation strain considered. When the situation strain was low, the stress level related with this circumstance largely depended on the personal resources of the individual. When the situation strain was high, the stress level related with this circumstance was much less dependent on the personal resources of the individual. The second experiment replicated these results among first‐aid workers, fire‐fighters and persons that had recently been injured. The third and fourth experiments replicated these results in various conditions differing as regards the level of social support. Copyright © 2002 John Wiley & Sons, Ltd.     

从信息经济学的角度看病案信息经济价值

本文从信息经济学的角度出发，分析了病案信息的经济价值、市场需求及其开发利用，揭示了病案信息利用对相关市场参与者的利润、效用、福利增进的机制及在疾病控制中的重大作用，指明了加强病案信息开发的重要性和紧迫性，并提出建议。