A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved]
Background Digital health literacy (DHL) is the ability to find, understand, and appraise online health-related information, as well as apply it to health behavior. It has become a core competence for navigating online information and health service environments. DHL involves solving ill-structured...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2024-03-01
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| Series: | Open Research Europe |
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| Online Access: | https://open-research-europe.ec.europa.eu/articles/3-98/v2 |
| _version_ | 1797197305351241728 |
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| author | David Williamson Shaffer Anna Jeney Rik Crutzen Andrew R. Ruis Gjalt-Jorn Peters Szilvia Zörgő |
| author_facet | David Williamson Shaffer Anna Jeney Rik Crutzen Andrew R. Ruis Gjalt-Jorn Peters Szilvia Zörgő |
| author_sort | David Williamson Shaffer |
| collection | DOAJ |
| description | Background Digital health literacy (DHL) is the ability to find, understand, and appraise online health-related information, as well as apply it to health behavior. It has become a core competence for navigating online information and health service environments. DHL involves solving ill-structured problems, where the problem and its solution are not clearcut and may have no single answer, such as in the process of sensemaking. We employ and expand on information foraging theory to address how experts and novices in information retrieval perform a search task. Our overarching aim is to pinpoint best practices and pitfalls in understanding and appraising health-related information online to develop a digital intervention to increase DHL and critical thinking. Methods In this feasibility study, we recruited a total of twenty participants for our expert and novice subsamples. We collected sociodemographic data with a self-developed survey, video data through an observation protocol of a 10-minute search task, as well as audio-video data via a retrospective think-aloud. The three, multimodal data streams were transcribed and aligned. Codes were developed inductively in several iterations, then applied deductively to the entire dataset. Tabularized, coded and segmented qualitative data were used to create various quantitative models, which demonstrate viability for the qualitative and statistical comparison of our two subsamples. Results Data were visualized with Epistemic Network Analysis to analyze code co-occurrences in the three aligned data streams, and with Qualitative/Unified Exploration of State Transitions to examine the order in which participants in our two subsamples encountered online content. Conclusions This paper describes our methods and planned analyses elaborated with mock figures. Quantifying qualitative data, aligning data streams, and representing all information in a tabularized dataset allows us to group data according to various participant attributes and employ data visualization techniques to pinpoint patterns therein. |
| first_indexed | 2024-04-24T06:41:51Z |
| format | Article |
| id | doaj.art-15864d334978492db61eb77dca30cde3 |
| institution | Directory Open Access Journal |
| issn | 2732-5121 |
| language | English |
| last_indexed | 2024-04-24T06:41:51Z |
| publishDate | 2024-03-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | Open Research Europe |
| spelling | doaj.art-15864d334978492db61eb77dca30cde32024-04-23T00:00:01ZengF1000 Research LtdOpen Research Europe2732-51212024-03-01318703A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved]David Williamson Shaffer0Anna Jeney1Rik Crutzen2Andrew R. Ruis3https://orcid.org/0000-0003-1382-4677Gjalt-Jorn Peters4Szilvia Zörgő5https://orcid.org/0000-0002-6916-2097Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USABaltic-Black Sea Regional Studies Programme, Ivan Franko National University of Lviv, Lviv, UkraineCare and Public Health Research Institute, Maastricht University, Maastricht, Limburg, 6200 MD, The NetherlandsDepartment of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USATheory, Methodology & Statistics, Faculty of Psychology, Open University of the Netherlands, Heerlen, PO box 2960, 6401 DL, The NetherlandsCare and Public Health Research Institute, Maastricht University, Maastricht, Limburg, 6200 MD, The NetherlandsBackground Digital health literacy (DHL) is the ability to find, understand, and appraise online health-related information, as well as apply it to health behavior. It has become a core competence for navigating online information and health service environments. DHL involves solving ill-structured problems, where the problem and its solution are not clearcut and may have no single answer, such as in the process of sensemaking. We employ and expand on information foraging theory to address how experts and novices in information retrieval perform a search task. Our overarching aim is to pinpoint best practices and pitfalls in understanding and appraising health-related information online to develop a digital intervention to increase DHL and critical thinking. Methods In this feasibility study, we recruited a total of twenty participants for our expert and novice subsamples. We collected sociodemographic data with a self-developed survey, video data through an observation protocol of a 10-minute search task, as well as audio-video data via a retrospective think-aloud. The three, multimodal data streams were transcribed and aligned. Codes were developed inductively in several iterations, then applied deductively to the entire dataset. Tabularized, coded and segmented qualitative data were used to create various quantitative models, which demonstrate viability for the qualitative and statistical comparison of our two subsamples. Results Data were visualized with Epistemic Network Analysis to analyze code co-occurrences in the three aligned data streams, and with Qualitative/Unified Exploration of State Transitions to examine the order in which participants in our two subsamples encountered online content. Conclusions This paper describes our methods and planned analyses elaborated with mock figures. Quantifying qualitative data, aligning data streams, and representing all information in a tabularized dataset allows us to group data according to various participant attributes and employ data visualization techniques to pinpoint patterns therein.https://open-research-europe.ec.europa.eu/articles/3-98/v2methodology unified methods data visualization open source software multimodal data digital health literacyeng |
| spellingShingle | David Williamson Shaffer Anna Jeney Rik Crutzen Andrew R. Ruis Gjalt-Jorn Peters Szilvia Zörgő A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] Open Research Europe methodology unified methods data visualization open source software multimodal data digital health literacy eng |
| title | A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] |
| title_full | A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] |
| title_fullStr | A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] |
| title_full_unstemmed | A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] |
| title_short | A feasibility study for a unified, multimodal analysis of online information foraging in health-related topics [version 2; peer review: 2 approved] |
| title_sort | feasibility study for a unified multimodal analysis of online information foraging in health related topics version 2 peer review 2 approved |
| topic | methodology unified methods data visualization open source software multimodal data digital health literacy eng |
| url | https://open-research-europe.ec.europa.eu/articles/3-98/v2 |
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