Apoyo social e ideación suicida en pacientes con cáncer

El diagnóstico de cáncer ha sido asociado con un alto riesgo de presentar ideación suicida en comparación con la población no oncológica, sin embargo se ha considerado al apoyo social como un factor protector para la ocurrencia de esta conducta. La presente investigación tuvo como objetivo identificar la relación entre el apoyo social percibido y la ideación suicida en 90 pacientes oncológicos adultos en Bogotá, bajo la hipótesis de que a mayor apoyo social percibido, menor presencia de ideación suicida. Se midió la variable de apoyo social a través del cuestionario Duke UNC y la ideación suicida a través de cuatro instrumentos: Escala de Ideación Suicida (SSI), Escala de Desesperanza de Beck (BHS), el ítem 9 del Inventario de Depresión de Beck (BDI-IA) y una entrevista semiestructurada. Los resultados mostraron que no existe relación entre el apoyo social percibido y la ideación suicida. Por otro lado se identificó una prevalencia de suicidio entre 5,6% y 22,77%, confirmando que el paciente con cáncer considera el suicidio y es fundamental evaluar esta variable en esta población. Se considera importante continuar con la realización de investigaciones que permitan generalizar los resultados a la población oncológica colombiana.

Sexting, psychological distress and dating violence among adolescents and young adults

Resumen tomado de la publicaci??n

Social perception gaze patterns, symptom severity and resting brain function measured using Arterial Spin Labelling

Autistic spectrum disorder (ASD) is characterised by qualitative alterations in reciprocal social interactions. Some recent studies show alterations in gaze patterns during social perception and rest-functional abnormalities in the ‘social brain network’. This study investigated: i) social perception gaze patterns in children with ASD and controls, ii) the relationship between autism clinical severity and social perception gaze patterns, iii) the relationship between resting cerebral blood flow (rCBF) and social perception gaze patterns. Methods: Nine children with ASD and 9 children with typical development were studied. Eye-tracking was used to detect gaze patterns during presentation of stimuli depicting social scenes. Autism clinical severity was established using the Autism Diagnostic Interview Revised (ADI-R). Arterial spin labelling MRI was used to quantify rCBF. Results: The ASD group looked less at social regions and more at non-social regions than controls. No significant correlation was found between ASD clinical severity and social perception gaze patterns. In the ASD group, gaze behaviour was related to rCBF in the temporal lobe regions at trend level. Positive correlations were found between temporal rCBF and gaze to the face region, while negative correlations were found between temporal rCBF and gaze to non-social regions. Conclusions: These preliminary results suggest that social perception gaze patterns are altered in children with ASD, and could be related to temporal rCBF.

Positive schizotypy and trait dissociation as vulnerability factors for post-traumatic distress

Objective. This study investigated whether trait positive schizotypy or trait dissociation was associated with increased levels of data-driven processing and symptoms of post-traumatic distress following a road traffic accident. Methods. Forty-five survivors of road traffic accidents were recruited from a London Accident and Emergency service. Each completed measures of trait positive schizotypy, trait dissociation, data-driven processing, and post-traumatic stress. Results. Trait positive schizotypy was associated with increased levels of data-driven processing and post-traumatic symptoms during a road traffic accident, whereas trait dissociation was not. Conclusions. Previous results which report a significant relationship between trait dissociation and post-traumatic symptoms may be an artefact of the relationship between trait positive schizotypy and trait dissociation.

The multidimensional measurement of the positive symptoms of psychosis

The measures most frequently used to assess psychotic symptoms fail to reflect important dimensions. The Psychotic Symptom Rating Scale (PSYRATS) aims to capture the multidimensional nature of auditory hallucinations and delusions. Individuals (N = 276) who had recently relapsed with positive symptoms completed the auditory hallucinations and delusions PSYRATS scales. These scores were compared with the relevant items from the SAPS and PANSS, and with measures of current mood. Total scores and distribution of items of the PSYRATS scales are presented and correlated with other measures. Positive symptom items from the SAPS and PANSS reflected the more objective aspects of PSYRATS ratings of auditory hallucinations and delusions (frequency and conviction) but were relatively poor at measuring distress. A major strength of the PSYRATS scales is the specific measurement of the distress dimension of symptoms, which is a key target of psychological intervention. It is advised that the PSYRATS should not be used as a total score alone, whilst further research is needed to clarify the best use of potential subscales. Copyright (c) 2007 John Wiley & Sons, Ltd.

Unwanted memories of assault: what intrusion characteristics are associated with PTSD?

Intrusive memories are common in the immediate aftermath of traumatic events, but neither their presence or frequency are good predictors of the persistence of posttraumatic stress disorder (PTSD). Two studies of assault survivors, a cross-sectional study (N = 81) and a 6-month prospective longitudinal study (N = 73), explored whether characteristics of the intrusive memories improve the prediction. Intrusion characteristics were assessed with an Intrusion Interview and an Intrusion Provocation Task. The distress caused by the intrusions, their "here and now" quality, and their lack of a context predicted PTSD severity. The presence of intrusive memories only explained 9% of the variance of PTSD severity at 6 months after assault. Among survivors with intrusions, intrusion frequency only explained 8% of the variance of PTSD symptom severity at 6 months. Nowness, distress and lack of context explained an additional 43% of the variance. These intrusion characteristics also predicted PTSD severity at 6 months over and above what could be predicted from PTSD diagnostic status at initial assessment. Further predictors of PTSD severity were rumination about. the intrusive memories, and the ease and persistence with which intrusive memories could be triggered by photographs depicting assaults. The results have implications for the early identification of trauma survivors at risk of chronic PTSD. (c) 2004 Elsevier Ltd. All rights reserved.

Reduced heart rate responding to trauma reliving in trauma survivors with PTSD: correlates and consequences

The authors investigated whether heart rate (HR) responses to voluntary recall of trauma memories (a) are related to posttraumatic stress disorder (PTSD), and (b) predict recovery 6 months later. Sixty-two assault survivors completed a recall task modeled on imaginal reliving in the initial weeks postassault. Possible cognitive modulators of HR responsivity were assessed; dissociation, rumination, trauma memory disorganization. Individuals with PTSD showed a reduced HR response to reliving compared to those without PTSD, but reported greater distress. Notably, higher HR response but not self-reported distress during reliving predicted greater symptom reduction at follow-up in participants with PTSD. Engagement in rumination was the only cognitive factor that predicted lower HR response. The data are in contrast to studies using trauma reminders to trigger memories, which have found greater physiological reactivity in PTSD. The authors' observations are consistent with models of PTSD that highlight differences between cued or stimulus-driven retrieval and intentional trauma recall, and with E B. Foa and M.J. Kozak (1986) hypothesis that full activation of trauma memories facilitates emotional processing.

Neural and wavelet network models for financial distress classification

This work analyzes the use of linear discriminant models, multi-layer perceptron neural networks and wavelet networks for corporate financial distress prediction. Although simple and easy to interpret, linear models require statistical assumptions that may be unrealistic. Neural networks are able to discriminate patterns that are not linearly separable, but the large number of parameters involved in a neural model often causes generalization problems. Wavelet networks are classification models that implement nonlinear discriminant surfaces as the superposition of dilated and translated versions of a single "mother wavelet" function. In this paper, an algorithm is proposed to select dilation and translation parameters that yield a wavelet network classifier with good parsimony characteristics. The models are compared in a case study involving failed and continuing British firms in the period 1997-2000. Problems associated with over-parameterized neural networks are illustrated and the Optimal Brain Damage pruning technique is employed to obtain a parsimonious neural model. The results, supported by a re-sampling study, show that both neural and wavelet networks may be a valid alternative to classical linear discriminant models.

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.