Experimentation and Stages of Acquisition for Tobacco Consumption in Spanish Adolescents

One area which has been largely neglected when studying the acquisition of addiction to smoking with thetranstheoretical model is whether the individual had previously experimented with smoking. The importance of includingthe experimentation variable was supported by this research

Análisis del patrón de consumo de cánnabis en estudiantes universitarios

Se analiza el patrón de consumo de cannabis en una muestrade 580 jóvenes universitarios (88.4% mujeres, edad media21.4 años). Si bien se observa que proporcionalmente máshombres que mujeres consumen habitualmente cannabis, lamagnitud de consumo de los que se reconocen usuarios essimilar en ambos sexos. Se detecta que la dependencia percibidaal cannabis se incrementa en función de la magnitud de consumo.Existe una relación positiva entre consumo de tabaco yde cannabis: el 90% de los jóvenes que no ha probado nuncael tabaco tampoco ha probado nunca el cannabis, mientrasque menos del 15% de los fumadores habituales de tabaco sehallan en esa situación. Estos resultados sugieren la necesidadde abordajes conjuntos para la prevención del consumo de drogas,principalmente en lo que se refiere al tabaco y el cannabis

Efecto de las pérdidas y ganancias recientes en el riesgo asumido por los automovilistas

Se analiza el efecto de las pérdidas y ganancias recientes sobre la conducta arriesgada y el riesgo percibido en la ejecución del simulador de conducción TIC/PC. Los modelos teóricos analizados coinciden en predecir aumento de la conducta arriesgada tras la pérdida y no modificación tras la ganancia. Los resultados obtenidos no confirman estas predicciones en cuanto al efecto de las pérdidas recientes. Tras las ganancias los sujetos no se diferencian de los controles. En cuanto al riesgo percibido, sólo la Teoría de Riesgo-Cero predice modificaciones tras la pérdida. Si bien nuestros sujetos experimentales perciben menos riesgo tras la pérdida, ello no se traduce en un aumento de la conducta arriesgada. Parece ser que percepción y conducta se rigen por mecanismos diferentes

Creencias sesgadas respecto al grado de "dureza" de algunas drogas en estudiantes universitarios

El objetivo de esta investigación es evaluar las creencias de los estudiantes universitarios respecto a la dureza de diez drogas: anfetaminas, café, heroína, barbitúricos, marihuana, ansiolíticos, tabaco, alcohol, cocaína y té. Ciento cincuenta y cinco estudiantes de Psicología debían indicar si creían que estas sustancias eran o no drogas duras. Los resultados indican que aunque existe consenso a la hora de clasificar como drogas duras a la heroína y la cocaína y como drogas blandas al tabaco, el café y el té, no existe acuerdo respecto a la clasificación de las otras sustancias. Asimismo se observa que aunque la OMS clasifica el alcohol como una droga altamente peligrosa, menos de la mitad de sujetos lo consideran una droga dura. En general los sujetos tienden a considerar las drogas legales como menos duras independientemente de si los efectos nocivos para la salud. Estos resultados adquieren relevancia cuando lo que se pone en juego es la fiabilidad y validez de los datos obtenidos en diferentes investigaciones que utilizan habitualmente esos conceptos

Uso del preservativo en estudiantes de secundaria de Mozambique. Diferencias en razón del género y del tipo de pareja = Condom use amongst high school students in Mozambique differences by gender and kind of partners

La mayor parte de las nuevas infecciones con el VIH en el mundo se producen por transmisión sexual entre adultos jóvenes y se aprecia una mayor vulnerabilidad en las mujeres (Gregson et al., 2002). Los principales objetivos de este trabajo son: estudiar la prevalencia del uso auto informado del preservativo durante la última relación sexual en los estudiantes de secundaria de Mozambique y la intención de emplearlo en las futuras relaciones, sea con la pareja actual o con una ocasional. Los resultados muestran que: 1) el 47% de los va rones y el 62% de las mujeres no utilizaron el preservativo, 2) tanto ellos como ellas están más seguros de que lo utilizarán con una pareja ocasional que con la actual y 3) los que emplearon el preservativo en su última relación sexual tienen más intención de volver a usarlo que aquellos que no lo emplearon

Orientación educativa e intervención psicopedagógica

Enfrentarse al análisis de la orientación educativa y la intervención psicopedagógica y elaborar propuestas que orienten el trabajo de los profesionales en este ámbito, implica, en estos momentos, un desafío difícil de asumir. Licenciados en pedagogía, psicología y psicopedagogía (de estos últimos, menos por la juventud de la licenciatura), con un perfil de formación inicial diferente, asumen responsabilidades profesionales similares e indiferenciadas; la reforma del sistema educativo impulsada por la LOGSE está en fase de implantación, lo que implica una reformulación de los servicios educativos que desde las administraciones educativas se ofrecen a los centros; y el ámbito de la intervención psicopedagógica en esta situación se confunde en ocasiones, o queda indiferenciado, del de otros profesionales del ámbito educativo

What is Abstinence? Definitions and Examples of Abstinence, to Prevent the Sexual Transmission of the HIV Virus, According to Spanish University Students

Research carried out in several Anglo-Saxon countries shows that many undergraduatesidentify oral sex and anal sex as examples of abstinent behaviour, while manyothers consider kissing and masturbation as examples of having sex. The objective ofthis research was to investigate whether a sample of Spanish students gave similarreplies. Seven hundred and fifty undergraduates (92% aged under 26, 67.6%women) produced examples or definitions of the term ‘abstinence’. Spanish studentsmade similar errors to those observed in the Anglo-Saxon samples, in thatbehaviours that were abstinent from a preventive point of view (masturbating andsex without penetration) were not considered as such, while a number of studentsreported oral sex as abstinent behaviour. The results suggest that the information onrisky and preventive sexual behaviour should cease to use ambiguous or euphemisticexpressions and use vocabulary that is clear and comprehensible to everyone

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task