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How recommender systems could support and enhance computer-tailored digital health programs: A scoping review

OBJECTIVE: Tailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally. New approaches are needed to optimise the use of these programs. This paper illustrates the potential...

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Autores principales: Cheung, Kei Long, Durusu, Dilara, Sui, Xincheng, de Vries, Hein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379797/
https://www.ncbi.nlm.nih.gov/pubmed/30800414
http://dx.doi.org/10.1177/2055207618824727
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author Cheung, Kei Long
Durusu, Dilara
Sui, Xincheng
de Vries, Hein
author_facet Cheung, Kei Long
Durusu, Dilara
Sui, Xincheng
de Vries, Hein
author_sort Cheung, Kei Long
collection PubMed
description OBJECTIVE: Tailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally. New approaches are needed to optimise the use of these programs. This paper illustrates the potential of recommender systems to support and enhance computer-tailored digital health interventions. The aim is threefold, to explore: (1) how recommender systems provide health recommendations, (2) to what extent recommender systems incorporate theoretical models and (3) how the use of recommender systems may enhance the usage of computer-tailored interventions. METHODS: A scoping review was conducted, using MEDLINE and ScienceDirect, to identify health recommender systems reported in studies between January 2007 and December 2017. Information was subsequently extracted to understand the potential benefits of recommender systems for computer-tailored digital health programs. Titles and abstracts of 1184 studies were screened for the full-text screening, in which two reviewers independently selected articles and systematically extracted data using a predefined extraction form. RESULTS: A total of 26 articles were included for data extraction. General characteristics were reported, with eight studies reporting hybrid filtering. A description of how each recommender system provides a recommendation is described; the majority of recommender systems used messages as recommendation. We identified the potential effects of recommender systems on efficiency, effectiveness, trustworthiness and enjoyment of the digital health program. CONCLUSIONS: Incorporating a collaborative method with demographic filtering as a second step to knowledge-based filtering could potentially add value to traditional tailoring with regard to enhancing the user experience. This study illustrates how recommender systems, especially hybrid programs, may have the potential to bring tailored digital health forward.
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spelling pubmed-63797972019-02-22 How recommender systems could support and enhance computer-tailored digital health programs: A scoping review Cheung, Kei Long Durusu, Dilara Sui, Xincheng de Vries, Hein Digit Health Tailored Health Communication OBJECTIVE: Tailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally. New approaches are needed to optimise the use of these programs. This paper illustrates the potential of recommender systems to support and enhance computer-tailored digital health interventions. The aim is threefold, to explore: (1) how recommender systems provide health recommendations, (2) to what extent recommender systems incorporate theoretical models and (3) how the use of recommender systems may enhance the usage of computer-tailored interventions. METHODS: A scoping review was conducted, using MEDLINE and ScienceDirect, to identify health recommender systems reported in studies between January 2007 and December 2017. Information was subsequently extracted to understand the potential benefits of recommender systems for computer-tailored digital health programs. Titles and abstracts of 1184 studies were screened for the full-text screening, in which two reviewers independently selected articles and systematically extracted data using a predefined extraction form. RESULTS: A total of 26 articles were included for data extraction. General characteristics were reported, with eight studies reporting hybrid filtering. A description of how each recommender system provides a recommendation is described; the majority of recommender systems used messages as recommendation. We identified the potential effects of recommender systems on efficiency, effectiveness, trustworthiness and enjoyment of the digital health program. CONCLUSIONS: Incorporating a collaborative method with demographic filtering as a second step to knowledge-based filtering could potentially add value to traditional tailoring with regard to enhancing the user experience. This study illustrates how recommender systems, especially hybrid programs, may have the potential to bring tailored digital health forward. SAGE Publications 2019-01-24 /pmc/articles/PMC6379797/ /pubmed/30800414 http://dx.doi.org/10.1177/2055207618824727 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Tailored Health Communication
Cheung, Kei Long
Durusu, Dilara
Sui, Xincheng
de Vries, Hein
How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title_full How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title_fullStr How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title_full_unstemmed How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title_short How recommender systems could support and enhance computer-tailored digital health programs: A scoping review
title_sort how recommender systems could support and enhance computer-tailored digital health programs: a scoping review
topic Tailored Health Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379797/
https://www.ncbi.nlm.nih.gov/pubmed/30800414
http://dx.doi.org/10.1177/2055207618824727
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