Inferring Social Isolation in Older Adults through Ambient Intelligence and Social Networking Sites

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Main Author: Wilfrido Campos
Format: Artículo científico
Language:en
Published: Instituto Politécnico Nacional 2016
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author Wilfrido Campos
author_facet Wilfrido Campos
contents Inferring Social Isolation in Older Adults through Ambient Intelligence and Social Networking Sites Wilfrido Campos Alicia Martinez Wendy Sanchez Hugo Estrada Jesus Favela Joaquin Perez Computación older adults Predictive model social isolation ambient intelligence social networking site Early diagnosis of social isolation in older adults can prevent physical and cognitive impairment or further impoverishment of the ir social network. This diag nosis is usually performed by personal and periodic application of psycho logical assessment instruments. This situation encourages the development of novel approaches able to monitor risk situations in social interactions to obtain early diagnosis and implement appropriate measures. This paper presents the development of a prediction model of social isolation in older adults through Ambient Intelligence (AmI) and Social Networking Sites (SNSs). The p redictive model has been evaluated in terms of it s accuracy, sensitivity, specificity, predictive values. This paper also presents the results of a n experimental test applying the proposed approach with real users, obtaining a prediction accuracy of 87% a nd a type II error rate of 15%. The proposed model will benefit institutions interested in developing technological solutions to detect early stages of social isolation, resulting i n improving the quality of life of older adults. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61544821013 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.20
format Artículo científico
id redalyc_61544821013
institution Redalyc
language en
publishDate 2016
publisher Instituto Politécnico Nacional
spellingShingle Inferring Social Isolation in Older Adults through Ambient Intelligence and Social Networking Sites
Wilfrido Campos
Computación
older adults
Predictive model
social isolation
ambient intelligence
social networking site
Inferring Social Isolation in Older Adults through Ambient Intelligence and Social Networking Sites Wilfrido Campos Alicia Martinez Wendy Sanchez Hugo Estrada Jesus Favela Joaquin Perez Computación older adults Predictive model social isolation ambient intelligence social networking site Early diagnosis of social isolation in older adults can prevent physical and cognitive impairment or further impoverishment of the ir social network. This diag nosis is usually performed by personal and periodic application of psycho logical assessment instruments. This situation encourages the development of novel approaches able to monitor risk situations in social interactions to obtain early diagnosis and implement appropriate measures. This paper presents the development of a prediction model of social isolation in older adults through Ambient Intelligence (AmI) and Social Networking Sites (SNSs). The p redictive model has been evaluated in terms of it s accuracy, sensitivity, specificity, predictive values. This paper also presents the results of a n experimental test applying the proposed approach with real users, obtaining a prediction accuracy of 87% a nd a type II error rate of 15%. The proposed model will benefit institutions interested in developing technological solutions to detect early stages of social isolation, resulting i n improving the quality of life of older adults. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61544821013 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.20
title Inferring Social Isolation in Older Adults through Ambient Intelligence and Social Networking Sites
topic Computación
older adults
Predictive model
social isolation
ambient intelligence
social networking site
url https://www.redalyc.org/articulo.oa?id=61544821013