Comparison of Modes of Administration and Response Options in the Assessment of Subjective Health Using the First Question of SF-36

To compare two modes of administration (self-administered; by interviewer) and two response options format (using words; images of “facial-expressions”) of the first question of SF-36 (Q1SF-36), and to test its validity. We included 825 participants (20–90 years). Q1SF-36, using words or images, was included in a global questionnaire interview and at the end participants filled the SF-36. The agreement was tested by weighted kappa coefficients (WKappa). Classification Trees were used in the calibration of Q1SF-36 responses, with the physical (PDSF36) and mental dimensions of SF-36. Polyserial correlation coefficients and areas under the ROC curves (AUC) were used for validation. After categorization, using PDSF36 classification trees, the WKappa were 0.770 (self-administered vs. interviewer), 0.569 (self-administered vs. facial-expressions) and 0.566 (interviewer vs. facial-expressions). The WKappa between the PDSF36 and the modes (self-administered, interviewer and facial-expressions) were 0.784, 0.713 and 0.579 and the corresponding polyserial correlation coefficients were 0.784, 0.713 and 0.579. A good discriminatory power was found comparing the modes with the PDSF36 (AUC = 0.907, 0.923 and 0.827), but not with mental dimension (AUC = 0.538, 0.501 and 0.629). The Q1SF-36, by self-administration or interviewer, may be a valid alternative for assessment of subjective physical health, but not mental health.     

On Combining Wavelets Expansion and Sparse Linear Models for Regression on Metabolomic Data and Biomarker Selection

Wavelet thresholding of spectra has to be handled with care when the spectra are the predictors of a regression problem. Indeed, a blind thresholding of the signal followed by a regression method often leads to deteriorated predictions. The scope of this article is to show that sparse regression methods, applied in the wavelet domain, perform an automatic thresholding: the most relevant wavelet coefficients are selected to optimize the prediction of a given target of interest. This approach can be seen as a joint thresholding designed for a predictive purpose. The method is illustrated on a real world problem where metabolomic data are linked to poison ingestion. This example proves the usefulness of wavelet expansion and the good behavior of sparse and regularized methods. A comparison study is performed between the two-steps approach (wavelet thresholding and regression) and the one-step approach (selection of wavelet coefficients with a sparse regression). The comparison includes two types of wavelet bases, various thresholding methods, and various regression methods and is evaluated by calculating prediction performances. Information about the location of the most important features on the spectra was also obtained and used to identify the most relevant metabolites involved in the mice poisoning.     

Beyond Contact? Policy approaches to work with families of looked after children in four European countries

In England, placement within the looked after system is not viewed as a desirable long‐term solution for most children, and policy has prioritised continued contact with parents, and swift return home, wherever possible. This review examines policy approaches to work with families of looked after children in England and in three other European countries: Denmark, France and the Netherlands, aiming to identify areas for shared learning in relation to this challenging area of policy and practice. The research highlights relationships between care populations and policy understandings of the purpose of work with families, including understandings of children's and/or parents’ rights.     

An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents

Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed.     

How Moroccan‐Dutch parents learn in communities of practice: Evaluating a bottom‐up parenting programme

Research shows that top‐down‐designed parenting programmes do not always meet the needs of postmigration parents. Bottom‐up programmes by migrant organizations hold a promise to fill this gap; however, research about these programmes and appropriate evaluation methodologies is scarce. Drawing upon Wenger's ( 2010 ) “communities of practice,” this paper explores an alternative perspective on parenting programme evaluation. Findings are presented from a study looking into social learning processes of postmigration parents who participated in a bottom‐up programme about raising teenagers in urban areas. Using an ethnographically inspired method combined with a preprogramme and postprogramme design, 115 Moroccan‐Dutch mothers and fathers from 15 programme groups participated. Results show that the programme provided a social learning space in which parents used themselves as resources to learn collectively about parenting. Moreover, parents consciously engaged in learning interactions across learning spaces stretched into their social networks. These analyses showed how parents' development of “learning citizenship” (Wenger, 2009 ) provides us with insight in collective learning dimensions present in a bottom‐up parenting programme, which is often not included in evaluation studies. Implications for practitioners as facilitators of parents' collective learning are presented.     

Multivariate log-skewed distributions with normal kernel and their applications

We introduce two classes of multivariate log-skewed distributions with normal kernel: the log canonical fundamental skew-normal (log-CFUSN) and the log unified skew-normal. We also discuss some properties of the log-CFUSN family of distributions. These new classes of log-skewed distributions include the log-normal and multivariate log-skew normal families as particular cases. We discuss some issues related to Bayesian inference in the log-CFUSN family of distributions, mainly we focus on how to model the prior uncertainty about the skewing parameter. Based on the stochastic representation of the log-CFUSN family, we propose a data augmentation strategy for sampling from the posterior distributions. This proposed family is used to analyse the US national monthly precipitation data. We conclude that a high-dimensional skewing function lead to a better model fit.     

Relationships of Online Social Comparison and Parenting Satisfaction among New Mothers: The Mediating Roles of Belonging and Emotion

New mothers frequently seek information and community on social networking sites as they seek to establish their parenting practices. As social networking sites for mothers (SNSM) present an environmental influence on the family system, a mother’s experience with social comparison, belonging, and emotion on SNSM can bear significant influence over her satisfaction with her parenting. The present study utilized survey methods to explore mothers’ (n= 336) reported experiences of these variables. We use structural equation modeling to specify a model with good fit, which indicated that greater downward comparison directly related to greater parenting satisfaction, with belonging and negative emotion as mediating indirect relationships. Implications for family communication and mothers’ SNSM practices are discussed.