Cognitive conflicts in major depression: between desired change and personal coherence.

Objectives: The notion of intrapsychic conflict has been present in psychopathology for more than a century within different theoretical orientations. However, internal conflicts have not received enough empirical attention, nor has their importance in depression been fully elaborated. This study is based on the notion of cognitive conflict, understood as implicative dilemma (ID), and on a new way of identifying these conflicts by means of the Repertory Grid Technique.

Cognitive reserve as a predictor of two year neuropsychological performance in early onset first-episode schizophrenia.

Introduction: The concept of cognitive reserve (CR) has been defined as individual differences in the efficient utilization of brain networks which allow some people to cope better than others with brain pathology. CR has been developed mainly in the field of aging and dementia after it was observed that there appears to be no direct relationship between the degree of brain pathology and the severity of clinical manifestations of this damage. The present study applies the concept of CR to a sample of children and adolescents with a first episode of schizophrenia, aiming to assess the possible influence of CR on neuropsychological performance after two year follow-up, controlling for the influence of clinical psychopathology.

Psychometric properties of the Spanish Human System Audit Short-Scale of transformational leadership.

The aim of this research is to examine the psychometric properties of a Spanish version of the Human System Audit transformational leadership short-scale (HSA-TFL-ES). It is based on the concept of Bass developed in 1985. The HSA-TFL is a part of the wider Human System Audit frame.

Using artificial neural networks in clinical neuropsychology: high performance in mild cognitive impairment and Alzheimer's disease.

Mild cognitive impairment (MCI) is a transitional state between normal aging and Alzheimer disease (AD). Artificial neural networks (ANNs) are computational tools that can provide valuable support to clinical decision making, classification, and prediction of cognitive functioning. The aims of this study were to develop, train, and explore and develop the ability of ANNs to differentiate MCI and AD, and to study the relevant variables in MCI and AD diagnosis.

Patient and clinician's ratings of improvement in methadone-maintained patients: Differing perspectives?

Background: In the last few years there seems to be an emerging interest for including the patients' perspective in assessing methadone maintenance treatment (MMT), with treatment satisfaction surveys being the most commonly-used method of incorporating this point of view. The present study considers the perspective of patients on MMT when assessing the outcomes of this treatment, acknowledging the validity of this approach as an indicator. The primary aim of this study is to evaluate the concordance between improvement assessment performed by two members of the clinical staff (a psychiatrist and a nurse) and assessment carried out by MMT patients themselves.

Psychometric data for the revised token test in normally developing Mexican children ages 4-12 years.

Language comprehension is vital to social and educational development but few pediatric tests are available for its assessment. To approach this problem, two versions of the Token Test (TT), "TT short form" (DeRenzi & Faglioni, 1978) and "Revised Token Test" (RTT), were first compared. Using a sample of 88 normally developing Spanish-speaking children, the tests were compared on their: (a) established psychometric development and (b) internal consistency.

Using mental tasks transitions detection to improve spontaneous mental activity classification.

This paper presents an algorithm based on canonical variates transformation (CVT) and distance based discriminant analysis (DBDA) combined with a mental tasks transitions detector (MTTD) to classify spontaneous mental activities in order to operate a brain-computer interface working under an asynchronous protocol. The algorithm won the BCI Competition III--Data Set V: Multiclass Problem, Continuous EEG--achieving an averaged classification accuracy over three subjects of 68.65% (79.

Multi-episode survival analysis: an application modelling readmission rates of heroin dependents at an inpatient detoxification unit.

The purpose of this study is to describe the characteristics of a statistical technique appropriate for analysing multi-episode data (multi-episode survival analysis), and to show its application in modelling the flow of readmissions at an inpatient detoxification unit. Data are from 784 opioid-dependent patients admitted at an inpatient detoxification unit, who totalled 1,255 admission episodes. Information stored prospectively at the unit database was reviewed for the following variables at the time of each patient discharge: episode serial number, sex, route of heroin administration, reason for discharge, time of discharge, and transition time (re-entry into the inpatient detoxification unit).