Cargando…
Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention
Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving app...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615593/ https://www.ncbi.nlm.nih.gov/pubmed/28895928 http://dx.doi.org/10.3390/ijerph14091056 |
_version_ | 1783266621424402432 |
---|---|
author | Al-Hajj, Samar Fisher, Brian Smith, Jennifer Pike, Ian |
author_facet | Al-Hajj, Samar Fisher, Brian Smith, Jennifer Pike, Ian |
author_sort | Al-Hajj, Samar |
collection | PubMed |
description | Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. |
format | Online Article Text |
id | pubmed-5615593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-56155932017-09-30 Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention Al-Hajj, Samar Fisher, Brian Smith, Jennifer Pike, Ian Int J Environ Res Public Health Article Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. MDPI 2017-09-12 2017-09 /pmc/articles/PMC5615593/ /pubmed/28895928 http://dx.doi.org/10.3390/ijerph14091056 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Al-Hajj, Samar Fisher, Brian Smith, Jennifer Pike, Ian Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title | Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title_full | Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title_fullStr | Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title_full_unstemmed | Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title_short | Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention |
title_sort | collaborative visual analytics: a health analytics approach to injury prevention |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615593/ https://www.ncbi.nlm.nih.gov/pubmed/28895928 http://dx.doi.org/10.3390/ijerph14091056 |
work_keys_str_mv | AT alhajjsamar collaborativevisualanalyticsahealthanalyticsapproachtoinjuryprevention AT fisherbrian collaborativevisualanalyticsahealthanalyticsapproachtoinjuryprevention AT smithjennifer collaborativevisualanalyticsahealthanalyticsapproachtoinjuryprevention AT pikeian collaborativevisualanalyticsahealthanalyticsapproachtoinjuryprevention |