Demographic differences in response rates for PHQ9 in a university student population

Objective: To examine differences in complete response rates for depression screening questions based on demographic characteristics. Methods: Cross-sectional study examining associations between demographic characteristics and completely responding depression-screening questions. Participants: “Healthy Minds Study” data, collected in a public University in February 2016, where 7,326 students participated. Results: women (AOR: 0.69; 95% CI =0.57–0.83) and gay/lesbian students (AOR: 0.24; 95% CI =0.10–0.60) had better complete response rates. Non-US (AOR: 1.46; 95% CI =1.03–2.07), black (AOR: 3.32; 95% CI =1.92–5.77), and Middle-Eastern students (AOR: 3.73; 95% CI =1.73–8.02) had lower complete response rates. Conclusions: Our study shows sex, gender, citizenship, and race categories have significant differences in complete response rates for the outcome. Our findings have several implications; including recognizing interventions for depression based on responders may not target those that tend to be “partial-responders”. Efforts in survey design, recruiting and completion of surveys should be maximized.     

Assessing emotional and social health using photographs: An innovative research method for rural studies and its applicability in a care-farming program for youth

A framework for assessing photographs for the emotional and social health of young people (SHAPE) is described and tested, within the context of a rural program. Two independent raters assessed the photographs of participants. To assess inter-rater reliability, Cohen’ K and Kendall’s W were calculated. The two reviewers’ assessments of photographs were in agreement. The assessment of emotional/behavioural display showed 82% agreement. Agreement between reviewers’ judgements of proxemics (W = .866), interaction (W = .722), engagement (W = .932) and overall impression (W = .804) were all significant (p < .005). The method yielded results indicating that participants found gardening immediately engaging but their approach to equines exhibited a change from fascination to confidence during the program. The visual-diary method is a useful and sensitive method for research: where resources are limited; to complement traditional measures; for use with people who lack appropriate verbal communication or literacy skills to complete questionnaires; young children; other underrepresented groups.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

全球影响力分析框架下中沙能源合作的影响因素

石油本身没有政治属性，但由石油衍生的占有权、控制权以及资源开发与利用、价格制定等因素则与国际政治经济关系密切。近年来，对外能源高依存度一直威胁着中国的能源安全并对我国经济社会发展产生着潜在的影响。沙特作为世界上石油储藏量与出口量大国之一，对满足中国能源需求意义重大。中沙具有良好的合作基础以及互补的能源战略，在能源合作方面具有广阔的前景。受国际政治经济因素的影响，中沙能源合作的主要影响因素来自美国、俄罗斯、印度和伊朗。为了保障中国的能源安全，需要进一步强化中沙能源合作力度，当前可以采取的措施主要包括：强化中沙能源领域的金融合作，建立双边制度性合作框架，协助沙特保障国家安全，与沙特和伊朗等国保持紧密的双边关系，等等。     

基于元网络分析的重大基础设施建设项目风险评估框架与实证

重大基础设施项目具有战略性、集成性、复杂性等特征，项目容易受到多种风险因素的综合影响，导致项目目标的偏离。现有风险评估与风险决策的方法缺乏对于风险因素、风险事件之间关联的分析。为了实现重大基础设施建设项目综合系统的风险评估，本文采用元网络分析方法，构建项目目标、风险事件和风险因素的交互模型，揭示重大基础设施风险事件发生机制的黑箱过程。风险评估过程中，通过多个网络叠加运算分析每个风险因素对于各种风险事件以及项目各目标的影响情况，改进了以往仅对风险因素单一影响程度的风险评估方法。同时，本研究选择我国某河流水电站过坝运输项目方案比选的风险评估过程验证方法的适用性。     

基于SWOT模型的农村地区学前教育发展问题研究

SWOT分析法又称作态势分析法，能够将内部的优势劣势、外部的机会威胁逐条列举出来，并据此建立可视化矩阵图，系统全面地提出针对性策略。学前教育作为基础教育的短板，而农村地区学前教育又是学前教育中的短板。借助SWOT模型系统，全面地分析了农村地区学前教育发展的内部与外部的优势（S）、劣势（W）、机会（O）和威胁（T），进而提出相应的增长型战略、扭转型战略、多元化战略和防御型战略，以促进农村地区学前教育平稳、健康发展。     

The practice of deliberative policy analysis in the context of political and cultural challenges: lessons from Thailand

ABSTRACT

This article draws upon insight from a study of those involved in introducing deliberative policy analysis in Thailand at the city scale and presents lessons for both policy practitioners and scholars. The design of each deliberative forum differed, depending on lessons learned from previous forums and the consensus that emerged as a result of deliberation amongst forum facilitators. The underlying principle of this kind of deliberative design is to make deliberative processes authentic, by avoiding coercion, inclusive, by engaging stakeholders who bring forth different ideas, and impactful. To make these forums more exciting, deliberative practices are often linked to other attractive discourses, such as those surrounding smart cities, creative spaces and inclusive development. The case of Thailand sheds light on emerging challenges involved in the practice of deliberative policy analysis in the context of both national political regimes that are not democracies and those in the East.     

Uniform consistency rate of kNN regression estimation for functional time series data

In this paper, we investigate the k-nearest neighbours (kNN) estimation of nonparametric regression model for strong mixing functional time series data. More precisely, we establish the uniform almost complete convergence rate of the kNN estimator under some mild conditions. Furthermore, a simulation study and an empirical application to the real data analysis of sea surface temperature (SST) are carried out to illustrate the finite sample performances and the usefulness of the kNN approach.