Cognitive inertia and the implicit association test

The authors review the implicit association test (IAT), its use in marketing, and the methodology and validity issues that surround it. They focus on a validity problem that has not been investigated previously, namely, the impact of cognitive inertia on IAT effects. Cognitive inertia refers to the difficulty in switching from one categorization rule to another, which causes IAT effects to depend on the order of administration of the two IAT blocks. In Study 1, the authors observe an IAT effect when the compatible block precedes the incompatible block but not when it follows the incompatible block. In Studies 2 and 3, the IAT effect changes its sign when the order of the blocks reverses. Cognitive inertia distorts individual IAT scores and diminishes the correlations between IAT scores and predictor variables when the block order is counterbalanced between subjects. Study 4 shows that counterbalancing the block order repeatedly within subjects can eliminate cognitive inertia effects on the individual level. The authors conclude that researchers should either interpret IAT scores at the aggregate level or, if individual IAT scores are of interest, counterbalance the block order repeatedly within subjects.

Who stays, who benefits? Predicting dropout and change in cognitive behaviour therapy for psychosis

This study investigates predictors of outcome in a secondary analysis of dropout and completer data from a randomized controlled effectiveness trial comparing CBTp to a wait-list group (Lincoln et al., 2012). Eighty patients with DSM-IV psychotic disorders seeking outpatient treatment were included. Predictors were assessed at baseline. Symptom outcome was assessed at post-treatment and at one-year follow-up. The predictor x group interactions indicate that a longer duration of disorder predicted less improvement in negative symptoms in the CBTp but not in the wait-list group whereas jumping-to-conclusions was associated with poorer outcome only in the wait-list group. There were no CBTp specific predictors of improvement in positive symptoms. However, in the combined sample (immediate CBTp+the delayed CBTp group) baseline variables predicted significant amounts of positive and negative symptom variance at post-therapy and one-year follow-up after controlling for pre-treatment symptoms. Lack of insight and low social functioning were the main predictors of drop-out, contributing to a prediction accuracy of 87%. The findings indicate that higher baseline symptom severity, poorer functioning, neurocognitive deficits, reasoning biases and comorbidity pose no barrier to improvement during CBTp. However, in line with previous predictor-research, the findings imply that patients need to receive treatment earlier.

COGNITIVE IMPACT OF INTERACTIVE MULTIMEDIA

Technology has been gradually introduced in heath education. One of the most attractive features of this technology-based education is the use of multimedia. In this article we explore the research evidence about the role that multimedia is playing in education. From that analysis we describe the most relevant features of this technology to prepare a common ground of discussion about the evaluation of its impact on educational outcomes. As part of this analysis, we organize current research evidence on the use of technology in medical education, distinguishing diverse variables involved in the process, like knowledge (declarative, procedural), learner characteristics, curricular scenario, etc. This article presents an overview of the Distributed Representations theory and its relationship with research on educational outcomes and multimedia. Next we discuss the relationship between media and diverse learning theories, proposing a theory based taxonomy for educational multimedia.

Physical and Emotional States as Memory-Relevant Factors: Cognitive Monitoring by Young Children

The Flavell (l981) model of cognitive monitoring and metamnemonic development was tested by four experiments conducted to determine whether preschool children (1) recognize that mood, fatigue, and fear are variables that influence learning; and (2) self-monitor their internal states and adjust their study behavior when they are sad or tired.

Decomposing speed of information processing in elementary cognitive tasks

Many studies obtained reliable individual differences in speed of information processing (SIP) as measured by elementary cognitive tasks (ECTs). ECTs usually employ response times (RT) as measure of SIP, but different ECTs target different cognitive processes (e.g., simple or choice reaction, inhibition). Here we used modified versions of the Hick and the Eriksen Flanker task to examine whether these tasks assess dissociable or common aspects of SIP. In both tasks, task complexity was systematically varied across three levels. RT data were collected from 135 participants. Applying fixed-links modeling, RT variance increasing with task complexity was separated from RT variance unchanging across conditions. For each task, these aspects of variance were represented by two independent latent variables. The two latent variables representing RT variance not varying with complexity of the two tasks were virtually identical (r = .83). The latent variables representing increasing complexity in the two tasks were also highly correlated (r = .72) but clearly dissociable. Thus, RT measures contain both task-unspecific, person-related aspects of SIP as well as task-specific aspects indicating the cognitive processes manipulated with the respective task. Separating these aspects of SIP facilitates the interpretation of individual differences in RT.

Clinical effectiveness of cognitive behavioral therapy for depression in routine care: A propensity score based comparison between randomized controlled trials and clinical practice

Background: The efficacy of cognitive behavioral therapy (CBT) for the treatment of depressive disorders has been demonstrated in many randomized controlled trials (RCTs). This study investigated whether for CBT similar effects can be expected under routine care conditions when the patients are comparable to those examined in RCTs. Method: N=574 CBT patients from an outpatient clinic were stepwise matched to the patients undergoing CBT in the National Institute of Mental Health Treatment of Depression Collaborative Research Program (TDCRP). First, the exclusion criteria of the RCT were applied to the naturalistic sample of the outpatient clinic. Second, propensity score matching (PSM) was used to adjust the remaining naturalistic sample on the basis of baseline covariate distributions. Matched samples were then compared regarding treatment effects using effect sizes, average treatment effect on the treated (ATT) and recovery rates. Results: CBT in the adjusted naturalistic subsample was as effective as in the RCT. However, treatments lasted significantly longer under routine care conditions. Limitations: The samples included only a limited amount of common predictor variables and stemmed from different countries. There might be additional covariates, which could potentially further improve the matching between the samples. Conclusions: CBT for depression in clinical practice might be equally effective as manual-based treatments in RCTs when they are applied to comparable patients. The fact that similar effects under routine conditions were reached with more sessions, however, points to the potential to optimize treatments in clinical practice with respect to their efficiency.

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients

Objective The main purpose of this research is the novel use of artificial metaplasticity on multilayer perceptron (AMMLP) as a data mining tool for prediction the outcome of patients with acquired brain injury (ABI) after cognitive rehabilitation. The final goal aims at increasing knowledge in the field of rehabilitation theory based on cognitive affectation. Methods and materials The data set used in this study contains records belonging to 123 ABI patients with moderate to severe cognitive affectation (according to Glasgow Coma Scale) that underwent rehabilitation at Institut Guttmann Neurorehabilitation Hospital (IG) using the tele-rehabilitation platform PREVIRNEC©. The variables included in the analysis comprise the neuropsychological initial evaluation of the patient (cognitive affectation profile), the results of the rehabilitation tasks performed by the patient in PREVIRNEC© and the outcome of the patient after a 3–5 months treatment. To achieve the treatment outcome prediction, we apply and compare three different data mining techniques: the AMMLP model, a backpropagation neural network (BPNN) and a C4.5 decision tree. Results The prediction performance of the models was measured by ten-fold cross validation and several architectures were tested. The results obtained by the AMMLP model are clearly superior, with an average predictive performance of 91.56%. BPNN and C4.5 models have a prediction average accuracy of 80.18% and 89.91% respectively. The best single AMMLP model provided a specificity of 92.38%, a sensitivity of 91.76% and a prediction accuracy of 92.07%. Conclusions The proposed prediction model presented in this study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients. The ability to predict treatment outcomes may provide new insights toward improving effectiveness and creating personalized therapeutic interventions based on clinical evidence.

Cognitive risk perception system for obstacle avoidance in outdoor mUAV missions

La robótica ha evolucionado exponencialmente en las últimas décadas, permitiendo a los sistemas actuales realizar tareas sumamente complejas con gran precisión, fiabilidad y velocidad. Sin embargo, este desarrollo ha estado asociado a un mayor grado de especialización y particularización de las tecnologías implicadas, siendo estas muy eficientes en situaciones concretas y controladas, pero incapaces en entornos cambiantes, dinámicos y desestructurados. Por eso, el desarrollo de la robótica debe pasar por dotar a los sistemas de capacidad de adaptación a las circunstancias, de entendedimiento sobre los cambios observados y de flexibilidad a la hora de interactuar con el entorno. Estas son las caracteristicas propias de la interacción del ser humano con su entorno, las que le permiten sobrevivir y las que pueden proporcionar a un sistema inteligencia y capacidad suficientes para desenvolverse en un entorno real de forma autónoma e independiente. Esta adaptabilidad es especialmente importante en el manejo de riesgos e incetidumbres, puesto que es el mecanismo que permite contextualizar y evaluar las amenazas para proporcionar una respuesta adecuada. Así, por ejemplo, cuando una persona se mueve e interactua con su entorno, no evalúa los obstáculos en función de su posición, velocidad o dinámica (como hacen los sistemas robóticos tradicionales), sino mediante la estimación del riesgo potencial que estos elementos suponen para la persona. Esta evaluación se consigue combinando dos procesos psicofísicos del ser humano: por un lado, la percepción humana analiza los elementos relevantes del entorno, tratando de entender su naturaleza a partir de patrones de comportamiento, propiedades asociadas u otros rasgos distintivos. Por otro lado, como segundo nivel de evaluación, el entendimiento de esta naturaleza permite al ser humano conocer/estimar la relación de los elementos con él mismo, así como sus implicaciones en cuanto a nivel de riesgo se refiere. El establecimiento de estas relaciones semánticas -llamado cognición- es la única forma de definir el nivel de riesgo de manera absoluta y de generar una respuesta adecuada al mismo. No necesariamente proporcional, sino coherente con el riesgo al que se enfrenta. La investigación que presenta esta tesis describe el trabajo realizado para trasladar esta metodología de análisis y funcionamiento a la robótica. Este se ha centrado especialmente en la nevegación de los robots aéreos, diseñando e implementado procedimientos de inspiración humana para garantizar la seguridad de la misma. Para ello se han estudiado y evaluado los mecanismos de percepción, cognición y reacción humanas en relación al manejo de riesgos. También se ha analizado como los estímulos son capturados, procesados y transformados por condicionantes psicológicos, sociológicos y antropológicos de los seres humanos. Finalmente, también se ha analizado como estos factores motivan y descandenan las reacciones humanas frente a los peligros. Como resultado de este estudio, todos estos procesos, comportamientos y condicionantes de la conducta humana se han reproducido en un framework que se ha estructurado basadandose en factores análogos. Este emplea el conocimiento obtenido experimentalmente en forma de algoritmos, técnicas y estrategias, emulando el comportamiento humano en las mismas circunstancias. Diseñado, implementeado y validado tanto en simulación como con datos reales, este framework propone una manera innovadora -tanto en metodología como en procedimiento- de entender y reaccionar frente a las amenazas potenciales de una misión robótica. ABSTRACT Robotics has undergone a great revolution in the last decades. Nowadays this technology is able to perform really complex tasks with a high degree of accuracy and speed, however this is only true in precisely defined situations with fully controlled variables. Since the real world is dynamic, changing and unstructured, flexible and non context-dependent systems are required. The ability to understand situations, acknowledge changes and balance reactions is required by robots to successfully interact with their surroundings in a fully autonomous fashion. In fact, it is those very processes that define human interactions with the environment. Social relationships, driving or risk/incertitude management... in all these activities and systems, context understanding and adaptability are what allow human beings to survive: contrarily to the traditional robotics, people do not evaluate obstacles according to their position but according to the potential risk their presence imply. In this sense, human perception looks for information which goes beyond location, speed and dynamics (the usual data used in traditional obstacle avoidance systems). Specific features in the behaviour of a particular element allows the understanding of that element’s nature and therefore the comprehension of the risk posed by it. This process defines the second main difference between traditional obstacle avoidance systems and human behaviour: the ability to understand a situation/scenario allows to get to know the implications of the elements and their relationship with the observer. Establishing these semantic relationships -named cognition- is the only way to estimate the actual danger level of an element. Furthermore, only the application of this knowledge allows the generation of coherent, suitable and adjusted responses to deal with any risk faced. The research presented in this thesis summarizes the work done towards translating these human cognitive/reasoning procedures to the field of robotics. More specifically, the work done has been focused on employing human-based methodologies to enable aerial robots to navigate safely. To this effect, human perception, cognition and reaction processes concerning risk management have been experimentally studied; as well as the acquisition and processing of stimuli. How psychological, sociological and anthropological factors modify, balance and give shape to those stimuli has been researched. And finally, the way in which these factors motivate the human behaviour according to different mindsets and priorities has been established. This associative workflow has been reproduced by establishing an equivalent structure and defining similar factors and sources. Besides, all the knowledge obtained experimentally has been applied in the form of algorithms, techniques and strategies which emulate the analogous human behaviours. As a result, a framework capable of understanding and reacting in response to stimuli has been implemented and validated.

Uso de alcohol y tabaco y variables cognitivo-motivacionales en el ámbito escolar: efectos sobre el rendimiento académico en adolescentes españoles

El objetivo de este estudio fue analizar: (a) la relación entre el consumo de tabaco y alcohol y el rendimiento académico y (b) la capacidad predictiva de los factores psicoeducativos y el abuso de alcohol y tabaco sobre el rendimiento académico en una muestra de 352 adolescentes españoles de 2º a 4º de Educación Secundaria Obligatoria (ESO). Para analizar las variables cognitivo-motivacionales se utilizaron el Self-Description Questionnaire-II, la Sydney Attribution Scale y el Achievement Goal Tendencies Questionnaire. El consumo abusivo de alcohol y tabaco, el sexo y la repetición de curso fueron también evaluados utilizando medidas autoinformadas. El rendimiento académico fue evaluado a partir de los registros escolares. Se utilizaron análisis de frecuencias y regresión logística para analizar los datos. Los análisis de frecuencias revelaron que los estudiantes que abusan del tabaco y el alcohol presentan un rendimiento académico más pobre. Los análisis de regresión logística destacaron que los comportamientos saludables así como las variables educativas y cognitivo-motivacionales ejercieron un efecto predictivo diferente sobre el rendimiento académico dependiendo del área académica analizada. Estos resultados señalan que para mejorar el rendimiento académico en la adolescencia se han de tener en consideración no sólo variables académicas sino también variables relacionadas con la salud.

Moderating Variables Impacting Adherence to the Reducing Disability in Alzheimer's Disease (RDAD) Intervention

Thesis (Ph.D.)--University of Washington, 2016-06

Cognitive deficits associated with cancer: A model of subjective and objective outcomes

Cancer and its treatment can affect many different aspects of quality of life. As a construct measured subjectively, quality of life shows an inconsistent relationship with objective outcome measures. That is, sometimes subjective and objective outcomes correspond with each other and sometimes they show little or no relationship. In this article, we propose a model for the relationship between subjective and objective outcomes using the example of cognitive function in people with cancer. The model and the research findings on which it is based help demonstrate that, in some circumstances, subjective measures of cognitive function correlate more strongly with psychosocial variables such as appraisal, coping, and emotions than with objective cognitive function. The model may provide a useful framework for research and clinical practice in quality of life for people with cancer.

The complexity of drinking: Interactions between the cognitive and behavioural determinants of alcohol consumption

This study expanded the earlier work conducted by this laboratory ( Hasking, P.A. and Oei, T.P.S. (2002a) . The differential role of alcohol expectancies, drinking refusal self-efficacy and coping resources in predicting alcohol consumption in community and clinical samples. Addiction Research and Theory , 10 , 465-494), by examining the independent and interactive effects of avoidant coping strategies, positive and negative expectancies and self-efficacy, in predicting volume and frequency of alcohol consumption in a sample of community drinkers. Differential relationships were found between the variables when predicting the two consumption measures. Specifically, while self-efficacy, seeking social support for emotional reasons and using drugs or alcohol to cope were independently related to both volume and frequency of drinking, complex interactions with positive and negative alcohol expectancies were also found. These interactions are discussed in terms of the cognitive and behavioural mechanisms thought to underlie drinking behaviour.

Social cognitive predictors of sun protection intention and behavior

The authors investigated sunbathing behavior and intention prospectively using the Theory of Planned Behavior (TPB). Before summer, 85 young adults who intended to sunbathe completed a TPB questionnaire. After summer, 46 of them completed a second questionnaire about their summertime sunbathing behavior The proposed model was successful in predicting both behavior and intention to use sun protection, with 45% of the variance of self-reported sunscreen use and 32% of the variance in intention explained by the TPB. Items designed to measure self-efficacy and perceived control loaded onto different factors and demonstrated discriminant validity. Self-efficacy predicted both intention and behavior (after controlling for all other TPB variables), but perceived behavioral control did not. The authors discuss the implications of the findings for potential interventions to improve sun protection behavior.

Components of group processes: Have they conributed to the outcome of mood and anxiety diorder patients in a group cognitive-behaviour therapy program

The present study assessed the influence of group processes on clinical outcomes of patients with anxiety and depression following group Cognitive Behavior Therapy (CBT). Five group environment variables were measured: cohesion, leader support, expressiveness, independence, and self-discovery. One hundred and sixty two patients attended a group CBT program and were assessed at pre and post-treatment. Results provided evidence for the effectiveness of group therapy as patients reported significantly lower depression and anxiety at the conclusion of treatment. Expressiveness was the only predictor of post-treatment anxiety, whereas leader support, expressiveness, and independence were significant predictors of post-treatment depression. Overall, findings suggest that the patients benefited from high levels of expressiveness and independence within their therapy group. In contrast, they failed to benefit from high levels of leader support, whereas both group cohesion and self-discovery appeared to be unrelated to outcome