Occupational disorders considerably impact workers’ quality of life and organizational productivity, and even affect mortality worldwide. Such health issues are related to mental health and ergonomics risk factors. In particular, mental health may be affected by cognitive strain caused by unexpected interruptions and other attention compromising factors. Risk factors assessment associated with cognitive strain in office environments, namely related to attention states, still suffers from the lack of scientifically validated tools. In this work, we aim to develop a series of classification models that can classify attention during pre-defined cognitive tasks based on the acquisition of biosignals to create a ground truth of attention. Biosignals, such as electrocardiography, electroencephalography, and functional near-infrared spectroscopy, were acquired from eight subjects during standard cognitive tasks inducing attention. Individually tuned machine learning models trained with those biosignals allowed us to successfully detect attention on the individual level, with results in the range of 70–80%. The electroencephalogram and electrocardiogram were revealed to be the most appropriate sensors in this context, and the combination of multiple sensors demonstrated the importance of using multiple sources. These models prove to be relevant for the development of attention identification tools by providing ground truth to determine which human–computer interaction variables have strong associations with attention.

Electrodermal activity (EDA) reflects the variation in the electrical conductance of the skin in response to sweat secretion, constituting a non-invasive measure of the sympathetic nervous system. This system intervenes in reactions to stress and is strongly activated in emotional states. In most cases, EDA signals are collected from the hand (fingers or palms), which is not an ideal location for a sensor when the participant has to use their hands during tasks or activities. This study aims to explore alternative locations for retrieving EDA signals (e.g., the chest, back, and forehead). EDA signals from 25 healthy participants were collected using a protocol involving different physical stimuli that have been reported to induce an electrodermal response. The features extracted included the Skin Conductance Response (SCR) height, SCR amplitude, and peak prominence. An analysis of these features and the analysis of the correlation between the standard position with the different locations suggested that the chest, while a possible alternative for EDA signal collection, presents some weak results, and further evaluation of this site is needed. Additionally, the forehead should be excluded as an alternative site, at least in short-term measurements.

One argument for the inclusion of children with special education needs (SEN) is that they will benefit from the interactions and relationships with their typically developing peers. However, students with SEN tend to be more rejected than their non-SEN peers. Considering the negative consequences of peer rejection on socioemotional development and school adjustment, the current study aims to understand the behavioural correlates and specific characteristics of the students with SEN associated with peer rejection. Participants were 227 students (107 with SEN); 53.7% male; mean age 10.79 (SD = 2.16); attending the 3rd (33.9%), 5th (35.3%) and 7th grades (30.8%). Students filled in a Sociometric task and 47 regular school teachers and 31 special education teachers provided information regarding sociodemographic and educational data, behavioural characteristics and student-teacher relationship. SEN status was the most important predictor of rejection followed by social skills. In the case of students with SEN, less familiarity with peers and a less close student-teacher relationship were also associated with rejection. Thus, the findings emphasise the need of professional development programs to assist teachers in the promotion of positive relationships with their students and a positive peer culture within the class.

Los estudios sobre las relaciones entre iguales han reportado los beneficios positivos para eldesarrollo social y emocional y además para el ajuste escolar. Sin embargo, ciertas características llevan a qué algunos alumnos sean menos aceptados por sus iguales. Algunos estudios sugieren que hay diferencias entre géneros: las chicas establecen más frecuentemente relaciones de amistad cercana entre díadas y triadas mientras que las de los chicos se producen más probablemente en una red social más amplia. Además, las relaciones entre agresión y estatus social parecen diferir entre género: las chicas utilizan más la agresión relacional o social, manifestada por comportamientos de exclusión, gossip negativo y amenazas verbales y estos comportamientos son considerados menos adecuados llevando a más rechazo para las chicas que así se comportan. Así, comprender los motivos por los cuales las chicas y chicos rechazan a sus iguales es muy importante pues permite señalar los aspectos más valorados en la interacción y relación con los otros a más de mejorar las intervenciones que tienen como objetivo la integración en el grupo de iguales.En este trabajo buscamos identificar los motivos señalados por las chicas para no escoger a un compañero para jugar o estar en el recreo. Respondieron al cuestionario sociométrico 841 alumnos (418 chicas) de tres cursos escolares: 126 chicas en 4º curso, 83 chicas en 6º curso y 209 chicas en 8º curso. La análisis de contenido de 1272 motivos, con base en una categorización preestablecida ha revelado que, en general, los motivos más referidos por chicas y chicos están relacionados con el comportamiento del alumno objeto de elección negativa. Sin embargo, las chicas refieren a más motivos relacionados con Comportamientos Agresivos, en particular los que si relacionan con Intimidación.