Influence of a Community Health Worker Intervention on Mental Health Outcomes among Low-Income Latino and African American Adults with Type 2 Diabetes

This study investigated the influence of a community health worker (CHW) diabetes lifestyle intervention on mental health outcomes. Our study was guided by the principles of community-based participatory research. Data were collected from 164 African American (N = 94) and Hispanic adults (N = 70) participating in a randomized, 6-month delayed intervention group design for improving glycemic control. The intervention time periods were baseline to 6 months for the treatment group and 6–12 months for the delayed group. Linear mixed models were used to conduct longitudinal analyses of the Problem Areas in Diabetes (PAID) and Patient Health Questionnaire (PHQ) scales. In the model adjusted for demographics, the PAID dropped significantly from pre-intervention to post-intervention within both the treatment and delayed groups (p < 0.05) with an average intervention effect of ?6.4 (p < 0.01). The PAID dropped even further within the immediate group from 6 to 12 months. Although the PHQ did not change significantly, the PHQ-2 had an average intervention effect of ?0.3 (p < 0.05) in the model adjusted for demographics. This study contributes to an understanding of how a CHW-led diabetes intervention can result in positive mental health outcomes for Latinos and African Americans with Type 2 diabetes. It also highlights the importance of further exploring what factors may contribute to racial/ethnic variation in mental health outcomes for African Americans and Latinos with diabetes and the role CHWs can play.     

Maximum likelihood estimator in a multi-phase random regression model

We consider a random regression model with several-fold change-points. The results for one change-point are generalized. The maximum likelihood estimator of the parameters is shown to be consistent, and the asymptotic distribution for the estimators of the coefficients is shown to be Gaussian. The estimators of the change-points converge, with n ^?1 rate, to the vector whose components are the left end points of the maximizing interval with respect to each change-point. The likelihood process is asymptotically equivalent to the sum of independent compound Poisson processes.     

Lessons learned from Toulouse and Buncefield disasters: from risk analysis failures to the identification of atypical scenarios through a better knowledge management

The recent occurrence of severe major accidents has brought to light flaws and limitations of hazard identification (HAZID) processes performed for safety reports, as in the accidents at Toulouse (France) and Buncefield (UK), where the accident scenarios that occurred were not captured by HAZID techniques. This study focuses on this type of atypical accident scenario deviating from normal expectations. The main purpose is to analyze the examples of atypical accidents mentioned and to attempt to identify them through the application of a well-known methodology such as the bow-tie analysis. To these aims, the concept of atypical event is accurately defined. Early warnings, causes, consequences, and occurrence mechanisms of the specific events are widely studied and general failures of risk assessment, management, and governance isolated. These activities contribute to outline a set of targeted recommendations, addressing transversal common deficiencies and also demonstrating how a better management of knowledge from the study of past events can support future risk assessment processes in the identification of atypical accident scenarios. Thus, a new methodology is not suggested; rather, a specific approach coordinating a more effective use of experience and available information is described, to suggest that lessons to be learned from past accidents can be effectively translated into actions of prevention.     

EWMA Control Charts for Monitoring High Yield Processes

The main objective of this article is to scrutinize the efficiency and verify the performance superiority of the one-sided EWMA control chart on high-yield processes. The proposed control chart is designed to detect both upward and downward shifts of the fraction of non conforming products and is developed based on non transformed geometric counts. Its algorithmic function is theoretically established and numerous performance measures are extracted using analytical methods based on the Markov modeling of the chart. Comparisons with traditional high yield control charts are conducted. Optimality tables and nomograms are included to help graphical determination of the optimal chart parameters.     

Spatial Regression Models Using Inter-Region Distances in a Non-Random Context

This article considers spatial data z( s ₁), z( s ₂),…, z( s _n ) collected at n locations, with the objective of predicting z( s ₀) at another location. The usual method of analysis for this problem is kriging, but here we introduce a new signal-plus-noise model whose essential feature is the identification of hot spots. The signal decays in relation to distance from hot spots. We show that hot spots can be located with high accuracy and that the decay parameter can be estimated accurately. This new model compares well to kriging in simulations.     

A characterization of majority voting rules with quorums

We give a characterization of majority voting rules with quorums in the framework of May (Econometrica 20:680–684, 1952)’s seminal article. According to these voting rules, an alternative is socially chosen if and only if it obtains the relative majority of votes and the total number of voters not abstaining reaches the quorum.     

Missing values: sparse inverse covariance estimation and?an?extension to sparse regression

We propose an ℓ ₁-regularized likelihood method for estimating the inverse covariance matrix in the high-dimensional multivariate normal model in presence of missing data. Our method is based on the assumption that the data are missing at random (MAR) which entails also the completely missing at random case. The implementation of the method is non-trivial as the observed negative log-likelihood generally is a complicated and non-convex function. We propose an efficient EM algorithm for optimization with provable numerical convergence properties. Furthermore, we extend the methodology to handle missing values in a sparse regression context. We demonstrate both methods on simulated and real data.     

The concept of contradiction in ergonomics practice

The present communication deals with the methodology of the ergonomics field intervention process. It proposes an operationalized version of work analysis in terms of contradictions. The aim is to demonstrate that such a dialectic tool and method of representation may assist the ergonomist to frame the essence of a work activity in practical terms, swiftly and in a manner that preserves its multifaceted unity. The proposed method is inspired by two theoretical constructs (i) contradiction as used in Cultural Historical Activity Theory and (ii) regulation, as developed and used by the francophone tradition of ergonomics of activity. Two brief examples of its use are presented and a discussion is made on further developments and possible pitfalls.