Correction: Intensive longitudinal modelling predicts diurnal activity of salivary alpha-amylase.

[This corrects the article DOI: 10.1371/journal.pone.0209475.].

Intensive longitudinal modelling predicts diurnal activity of salivary alpha-amylase.

Salivary alpha-amylase (sAA) activity has been widely used in psychological and medical research as a surrogate marker of sympathetic nervous system activation, though its utility remains controversial. The aim of this work was to compare alternative intensive longitudinal models of sAA data: (a) a traditional model, where sAA is a function of hour (hr) and hr squared (sAAj,t = f(hr, hr2), and (b) an autoregressive model, where values of sAA are a function of previous values (sAAj,t = f(sAA j,t-1, sAA j,t-2, …, sAA j,t-p). Nineteen normal subjects (9 males and 10 females) participated in the experiments and measurements were performed every hr between 9:00 and 21:00 hr. Thus, a total of 13 measurements were obtained per participant. The Napierian logarithm of the enzymatic activity of sAA was analysed. Data showed that a second-order autoregressive (AR(2)) model was more parsimonious and fitted better than the traditional multilevel quadratic model. Therefore, sAA follows a process whereby, to forecast its value at any given time, sAA values one and two hr prior to that time (sAA j,t = f(SAAj,t-1, SAAj,t-2) are most predictive, thus indicating that sAA has its own inertia, with a "memory" of the two previous hr. These novel findings highlight the relevance of intensive longitudinal models in physiological data analysis and have considerable implications for physiological and biobehavioural research involving sAA measurements and other stress-related biomarkers.

Risk Factors and Youth Recidivism Prediction in General and Property Offenders.

The predictive validity of risk factors for recidivism in general offenders is well known, but few studies have considered specific crimes - such as non-violent property offences - in this context. The prediction of risk factors on recidivism among general and property offenders is analysed in an attempt to capture any motivational differences underlying diverse types of crimes. Subsamples of theft and property damage offenders were extracted from a general population of 210 juvenile offenders aged between 14 and 18 years. All participants were assessed using the Spanish version of the Youth Level of Service/Case Management Inventory (YLS/CMI) and their recidivism rates were evaluated in terms of the number of new records in a 24-month follow-up period. Factors pertaining to the Big Four (especially the antisocial peers risk factor) seem to be the most predictive factors for both general offenders and non-violent property offenders; the type of crime does not seem to make a significant difference to youth offenders' needs.

Effects of a psychosocial intervention on the executive functioning in children with ADHD.

The purpose of this study was to analyze the effects of an intensive psychosocial intervention on the executive functioning (EF) in children with ADHD. The treatment was carried out in a coordinated manner over a period of 10 weeks with 27 children with ADHD aged 7 to 10, their parents, and their teachers. A battery of neuropsychological tasks was applied to evaluate attention, interference control, verbal and visuospatial working memory, planning ability, and flexibility. The comparative analysis of the treated group of ADHD children and an untreated ADHD group showed significant differences that were especially important in visuospatial memory and planning in favor of the treated children, even when the scores in the pretreatment phase were included as covariables. Likewise, improvements were observed in the parents' and teachers' behavioral ratings of hyperactivity or impulsivity and inattention. The conclusion was drawn that psychosocial interventions with children with ADHD can have a positive effect on some executive functions.

Mitochondrial DNA haplogroups do not play a role in the variable phenotypic presentation of the A3243G mutation.

Thirty-five mitochondrial (mt) DNAs from Spain that harbor the mutation A3243G in association with either MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis, and strokelike episodes) syndrome or a wide array of disease phenotypes (ranging from diabetes and deafness to a mixture of chronic progressive external ophthalmoplegic symptoms and strokelike episodes) were studied by use of high-resolution restriction fragment length polymorphism analysis and control-region sequencing. A total of 34 different haplotypes were found, indicating that all instances of the A3243G mutation are probably due to independent mutational events. Haplotypes were distributed into 13 haplogroups whose frequencies were close to those of the general Spanish population. Moreover, there was no statistically significant difference in haplogroup distribution between patients with MELAS and those with disease phenotypes other than MELAS. Overall, these data indicate that the A3243G mutation harbors all the evolutionary features expected from a severely deleterious mtDNA mutation under strong negative selection, and they reveal that European mtDNA backgrounds do not play a substantial role in modulating the mutation's phenotypic expression.

Modelos de regresión multinivel: aplicación en psicología escolar / Multilevel regression models: Applications in school psychology

Es frecuente en la investigación comportamental que el proceso de recogida de datos no siga los principios del muestreo aleatorio simple supuesto por la regresión clásica, sino un muestreo por agrupamientos (cluster sampling) en donde junto con los participantes se selecciona también unidades contextuales a las que éstos pertenecen tales como escuelas, municipios o empresas. La consecuencia de utilizar regresión ordinaria es la producción de sesgos en el error típico de medida y un aumento en la probabilidad de cometer errores de inferencia. El análisis multinivel modela explícitamente estas relaciones jerárquicas proporcionando además estimaciones sobre la variabilidad contextual de los coeficientes de regresión. El objetivo del trabajo es simplificar el análisis multinivel como una generalización del análisis de covarianza, a partir de conceptos estadísticos más comunes como los diseños de medidas repetidas, modelos de efectos fijos y aleatorios. Se presentan ejemplos de aplicaciones en el contexto de la psicología escolar (AU)

Data collection procedures in the behavioral sciences do not always follow the rules of simple random sampling, an assumption of ordinary least squares regression. This is the case in cluster sampling designs which contain more than one type of experimental unit, such as subjects that are nested within classes, schools or companies. Failure of taking into consideration the special structure of the data results in estimation bias for the standard error and in an increase in the probability of inference errors. Multilevel analysis models this relationship among the observations while providing unbiased standard error and estimates of the contextual variability of regression coefficients. The purpose of this paper is to simplify multilevel analysis as a generalization of the analysis of covariance on the basis of commonly used statistical concepts such as repeated measures designs, fixed and random effects models. Several application examples in school psychology are reviewed (AU)