SALUS: A Model for Educational Assistance in Noncommunicable Chronic Diseases


  • Andrêsa Vargas Larentis University of Vale do Rio dos Sinos, Av. Unisinos 950, Bairro Cristo Rei, São Leopoldo, RS, 93022-750, Brazil
  • Débora Nice Ferrari Barbosa Feevale University, ERS-239, 2755, Novo Hamburgo, RS, 93525-075, Brazil
  • Jorge Luis Victória Barbosa University of Vale do Rio dos Sinos, Av. Unisinos 950, Bairro Cristo Rei, São Leopoldo, RS, 93022-750, Brazil


Diseases, Learning, Ubiquitous Computing, Context


Noncommunicable Chronic Diseases (NCDs) are the leading cause of death worldwide, meaning 41 million people die each year. Actions for the prevention and monitoring of NCDs should be promoted through the use of ubiquitous computing technologies to provide health education to individuals. Through ubiquitous computing it is possible to integrate technologies into their daily life. In turn, ubiquitous learning makes possible the integration of the individual with their context, helping in continuous and contextualized learning. In this sense, this paper presents SALUS, a computational model that uses context histories of individuals as a mechanism to assist in the prevention and monitoring of NCDs. The model explores elements of the context of individuals that are used in the composition of context histories. In addition, the analysis of context histories is used to deliver useful information for the individuals. The evaluation was conducted through prototype to assess the correctness of the content and place recommendations indicated by the model. A public database containing data from, 4239 individuals was used in the evaluation, with results showing an occurrence of 28.8% (content recommendation) and 25.4% (place recommendation) with ranges between high (score >60 and ≤80) and very high (score >80). The results obtained from the analysis of context histories indicated that SALUS can support educational assistance in NCDs


Download data is not yet available.

Author Biographies

Andrêsa Vargas Larentis, University of Vale do Rio dos Sinos, Av. Unisinos 950, Bairro Cristo Rei, São Leopoldo, RS, 93022-750, Brazil

Possui graduação em Informática com ênfase em Análise de Sistemas e mestrado em Computação Aplicada pela Universidade do Vale do Rio dos Sinos (Unisinos-2005, 2008). Graduada em Ciências Contábeis pela Universidade do Sul de Santa Catarina (Unisul-2013). Pós-graduada em Formação de Professores para o Ensino Superior na Universidade Paulista (Unip-2017). Atualmente é estudante de doutorado na Unisinos. Possui mais de 12 anos de experiência em consultoria de projetos de desenvolvimento de software para diferentes indústrias. Atuou durante 9 anos como docente em instituição de ensino superior, nos cursos de Sistemas de Informação e Ciência da Computação.

Débora Nice Ferrari Barbosa, Feevale University, ERS-239, 2755, Novo Hamburgo, RS, 93525-075, Brazil

Doutora e Mestre em Ciência da Computação pela Universidade Federal do Rio Grande do Sul (UFRGS-2007, 2001). Bacharel em Análise de Sistemas pela Universidade Católica de Pelotas (UCPel-1998). Pós-doutora pela University of Califórnia Irvine, EUA. Bolsista de Produtividade em Desenvolvimento Tecnológico e Extensão Inovadora - DT - nível 1D do CNPq. É professora titular na Universidade Feevale, atuando como professora permanente do Programa de Pós-graduação em Diversidade Cultural e Inclusão Social (PPGDiver). Também atua nos cursos de bacharelado em Sistemas de Informação e Ciência da Computação. É líder do Grupo de Pesquisa Interdisciplinar em Tecnologia Digital, Neurociência e Educação (CNPq-Feevale). É membro dos grupos de Pesquisa em Informática na Educação (Feevale) e Desenvolvimento em Computação Móvel e Ubíqua (Unisinos).

Jorge Luis Victória Barbosa, University of Vale do Rio dos Sinos, Av. Unisinos 950, Bairro Cristo Rei, São Leopoldo, RS, 93022-750, Brazil

Possui graduação em Tecnologia em Processamento de Dados e Engenharia Elétrica pela Universidade Católica de Pelotas (UCPel-1990, 1992). Ele obteve especialização em Engenharia de Software (UCPel-1993), mestrado e doutorado em Ciência da Computação na Universidade Federal do Rio Grande do Sul (UFRGS-1996, 2001). Ele realizou pós-doutorados na Sungkyunkwan University (SKKU, Suwon, Coréia do Sul, 2011) e na University of California Irvine (UCI, Irvine, USA, 2020) através de uma bolsa do Programa CAPES/PRINT (professor visitante no Exterior Sênior). Jorge é professor titular II na Universidade do Vale do Rio dos Sinos (Unisinos). Ele atua nos Programas de Pós-graduação em Computação Aplicada (PPGCA) e em Engenharia Elétrica (PPGEL). Ele coordena o Laboratório de Computação Móvel (Mobilab) e é bolsista de Produtividade em Desenvolvimento Tecnológico e Extensão Inovadora (bolsa DT - Nível 1C) do Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).


WHO, “The top 10 causes of death,” Dec 2020. [Online]. Available:

WHO, “World Health Statistics 2021: Monitoring Health for the SDGs, sustainable developments goals,” 2021. [Online]. Available:

WHO, “The Global Health Observatory,” 2022. [Online]. Available:

H. Kim and B. Xie, “Health Literacy in the eHealth era: A Systematic review of the literature,” Patient Education and Counseling, vol. 100, no. 6, pp. 1073-1082, 2017.

M. Weiser, “The Computer for the 21st Century,” Scientific American, vol. 265, no. 3, pp. 94-104, 1991.

G. J. Hwang, C. C. Tsai, and S. J. H. Yang, “Criteria, strategies and research issues of context-aware ubiquitous learning,” Educational Technology & Society, vol. 11, no. 2, pp. 81-91, 2008.

A. K. Dey, “Understanding and Using Context,” Personal and Ubiquitous Computing, vol. 5, no. 1, pp. 4-7, 2001.

R. Mayrhofer, “Context Prediction based on Context Histories: Expected Benefits, Issues and Current State-of-the-Art,” in 2005 1st International Workshop on Exploiting Context Histories in Smart Environments (ECHISE), Munich, Germany, pp. 31-36, 2005.

P. C. Büttenbender, E. G. Azevedo Neto, W. F. Heckler, and J. L. V. Barbosa, “A Computational Model for Identifying Behavioral Patterns in People with Neuropsychiatric Disorders,” IEEE Latin America Transactions, vol. 20, no. 04, pp. 582-583, 2022.

J. Barbosa, “Multi-Temporal Aspects on Contextual Variability Modeling,” in Anais do XI Simpósio Brasileiro de Computação Ubíqua e Pervasiva. Belém, Brasil, 2019.

A. V. Larentis, D. N. F. Barbosa, C. R. da Silva, and J. L. V. Barbosa, “Applied Computing to Education on Noncommunicable Chronic Diseases: A Systematic Mapping Study,” Telemedicine and e-Health, vol. 26, no. 2, pp. 147-163, 2020.

R. Sabo, J. Robins, S. Lutz, P. Kashiri, T. Day, B. Webel, and A. Krist, “Diabetes Engagement and Activation Platform for Implementation and Effectiveness of Automated Virtual Type 2 Diabetes Self-Management Education: Randomized Controlled Trial,” JMIR diabetes, vol. 6, no. 1, e26621, 2021.

M. Hadjiconstantinou, S. Schreder, C. Brough, A. Northern, B. Stribling, K. Khunti, and M. J. Davies, “Using Intervention Mapping to Develop a Digital Self-Management Program for People with Type 2 Diabetes: Tutorial on MyDESMOND,” Journal of Medical Internet Research, vol. 22, no. 5, e17316, 2020.

M. D. Adu, U. H. Malabu, A. Malau-Aduli, and B. S. Malau-Aduli, “The development of My Care Hub Mobile-Phone App to Support Self-Management in Australians with Type 1 or Type 2 Diabetes,” Scientific reports, vol. 10, no. 1, pp. 7, 2020.

E. Giannoula, I. Iakovou, I. Katsikavelas, P. Antoniou, V. Raftopoulos, V. Chatzipavlidou, N. Papadopoulos, and P. Bamidis, “A Mobile App for Thyroid Cancer Patients Aiming to Enhance Their Quality of Life: Protocol for a Quasiexperimental Interventional Pilot Study,” JMIR Res Protoc, vol. 9, no. 3, e13409, 2020.

F. Huang, X. Wu, Y. Xie, F. Liu, J. Li, X. Li, and Z. Zhou, “An automated structured education intervention based on a smartphone app in Chinese patients with type 1 diabetes: a protocol for a single-blinded randomized controlled trial,” Trials, vol. 21, no. 1, pp. 944, 2020.

R. Alharbey and S. Chatterjee, “An mHealth Assistive System "MyLung" to Empower Patients with Chronic Obstructive Pulmonary Disease: Design Science Research,” JMIR Form Res, vol. 3, no. 1, e12489, 2019.

M. F. Mohamad Marzuki, N. A. Yaacob, N. M. Bin Yaacob, M. R. Abu Hassan, and S. B. Ahmad, “Usable Mobile App for Community Education on Colorectal Cancer: Development Process and Usability Study,” JMIR Hum Factors, vol. 6, no. 2, e12103, 2019.

L. Woods, J. Duff, E. Roehrer, K. Walker, and E. Cummings, “Design of a Consumer Mobile Health App for Heart Failure: Findings from the Nurse-Led Co-Design of Care4myHeart,” JMIR Nursing, vol. 2, no. 1, e14633, 2019.

M. Almotairi, M. A. Alyami, L. Aikins, and Y. Song, “Improving Patient Outcomes through Customized Learning,” in 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Busan, Korea (South), pp. 363-368, 2018.

S. Hussain and G. Athula, “Extending a Conventional Chatbot Knowledge Base to External Knowledge Source and Introducing User Based Sessions for Diabetes Education,” in 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), Krakow, Poland, pp. 698-703, 2018.

M. Jacobs, J. Johnson, and E. D. Mynatt, “MyPath: Investigating Breast Cancer Patients' Use of Personalized Health Information,” ACM on Human-Computer Interaction, vol.2, pp. 1-21, 2018.

D. N. F. Barbosa and J. L. V. Barbosa, “Aprendizagem com Mobilidade e Aprendizagem Ubíqua,” in F. F. Sampaio; M, Pimentel; E. Santos (Org.). Informática na Educação: games, inteligência artificial, realidade virtual/aumentada e computação ubíqua. Porto Alegre, Brasil: SBC, 2019.

J. D. Novak, “Uma teoria de educação,” São Paulo: Pioneira, 1981.

BIOLINCC. Framingham Heart Study-Cohort (FHS-Cohort). 2021. [Online]. Available:

KAGGLE. Logistic Regression - Heart Disease Prediction. 2022. [Online]. Available:

R. B. Sr D’Agostino, R. S. Vasan, M. J. Pencina, P. A. Wolf, M. Cobain, J. M. Massaro, and W. B. Kannel, “General cardiovascular risk profile for use in primary care: the Framingham Heart Study,” Circulation, vol. 117, no. 6, pp. 743-753, 2008.

FHS. Cardiovascular Disease (10-year risk). 2022. [Online]. Available:



How to Cite

Larentis, A. V., Barbosa, D. N. F., & Barbosa, J. L. V. (2023). SALUS: A Model for Educational Assistance in Noncommunicable Chronic Diseases. IEEE Latin America Transactions, 21(3), 360–366. Retrieved from

Most read articles by the same author(s)