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BACKGROUND: Emotional competencies are skills necessary to adequately understand, express, and regulate emotional phenomena. Among the emotional competencies is emotion regulation. Not having adequate development of this emotional competence is related to psychological problems such as depression. One of the characteristics of individuals with developmental disabilities is the presence of difficulties with emotion regulation. These difficulties can affect an individual's autonomy, social competence, and the development of independent life. AIMS: This paper presents a scoping review to identify the technology designed and developed to support the emotion regulation of individuals with developmental disabilities. METHODS AND PROCEDURES: We combined the guidelines for a systematic literature review in computer science and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The process resulted in twelve stages through which we conducted this scoping review. First, a search query was defined and executed in computer science's five most representative search engines. We used different inclusion, exclusion, and quality criteria for selecting the works included in this review. OUTCOMES AND RESULTS: Thirty-nine papers aimed at supporting the emotional competencies of individuals with developmental disabilities were included, of which nine support emotion regulation. As a result, different areas of opportunity in developing technology to support the emotion regulation of individuals with developmental disabilities are discussed. CONCLUSIONS AND IMPLICATIONS: Technology supporting emotion regulation in individuals with developmental disabilities is a growing but little-explored field. For the literature supporting emotion regulation, we detected opportunities for study. Some of them aimed at investigating whether we could use technologies developed for other emotional competencies to support emotion regulation and how the characteristics of this technology can support individuals with developmental disabilities.

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Abstract Introduction Suicide attempts are the most predictive risk factor for suicide deaths. Most people who attempt suicide receive care from out-of-hospital Emergency Services (OES), where these requests are managed and classified. Objective Validate the Emergency Coordination Center (ECC) classification for the detection of suicidal behavior requests. Method A descriptive, cross-sectional study of requests to the ECC of Málaga (Spain) during 2013 and 2014 was conducted. To classify the requests, the authors considered the ECC categorization when answering the call and the clinical assessment of the healthcare professional when attending the person who had made the call at the scene, which was considered the reference standard. To analyze the validity of the ECC classification system, sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated. Results The total number of requests for medical assistance analyzed was 112,599. The validity indicators of the classification system for suicidal behavior were sensitivity = 44.78%, specificity = 99.34%, PPV = 46.91% and NPV = 99.28%. Discussion and conclusion The ECC classification system has a lower capacity to detect the presence of suicidal behavior and a higher capacity to identify its absence in the requests received. OES provide key information on suicidal behavior requests as they can be one of the first places people with this problem go to. It would therefore be extremely useful to improve the classification systems for requests related to suicidal behavior.

Resumen Introducción Los intentos de suicidio constituyen el factor de riesgo más predictivo de todos los casos de suicidio consumado. La mayoría de las personas que intentan suicidarse reciben atención en los Servicios de Urgencias Extrahospitalarios (SUE) donde se gestionan y clasifican estas demandas. Objetivo Validar la clasificación del Centro Coordinador de Urgencias y Emergencias (CCUE) para detectar las demandas relacionadas con la conducta suicida. Método Se llevó a cabo un estudio descriptivo y transversal de las demandas al CCUE de Málaga (España) realizadas durante 2013 y 2014. Para su clasificación se tuvo en cuenta la categorización en el CCUE al responder la llamada y el juicio clínico del profesional sanitario cuando atiende al demandante in situ, considerando éste como patrón de referencia. Para evaluar la validez del sistema de clasificación se calcularon la sensibilidad, la especificidad y los valores predictivos positivo (VPP) y negativo (VPN). Resultados El total de demandas sanitarias analizadas fue de 112,599. Los indicadores de validez del sistema de clasificación para las demandas por conductas de suicidio fueron una sensibilidad = 44.78%, especificidad = 99.34%, VPP = 46.91% y VPN = 99.28%. Discusión y conclusión El sistema de clasificación del CCUE presenta una capacidad más baja para detectar presencia de conducta suicida comparada con una capacidad más alta para identificar su ausencia en las demandas recibidas. Los SUE aportan información relevante sobre las demandas por conducta suicida ya que pueden ser uno de los primeros lugares a los que acuden las personas con este problema. Por ello, sería de gran utilidad mejorar los sistemas de clasificación de las demandas por conducta suicida.

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Handheld computers are increasingly being used by hospital workers. With the integration of wireless networks into hospital information systems, handheld computers can provide the basis for a pervasive computing hospital environment; to develop this designers need empirical information to understand how hospital workers interact with information while moving around. To characterise the medical phenomena we report the results of a workplace study conducted in a hospital. We found that individuals spend about half of their time at their base location, where most of their interactions occur. On average, our informants spent 23% of their time performing information management tasks, followed by coordination (17.08%), clinical case assessment (15.35%) and direct patient care (12.6%). We discuss how our results offer insights for the design of pervasive computing technology, and directions for further research and development in this field such as transferring information between heterogeneous devices and integration of the physical and digital domains.

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