Seungeun Park, Betty Bekemeier, Abraham Flaxman, Melinda Schultz
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These relationships between the interventions and outcomes appear to be explained by mediating factors such as perceived trustworthiness and quality, domain-specific knowledge, basic beliefs shared by social groups, and political beliefs.Visualization appears to bring advantages by increasing the amount of information delivered and decreasing the cognitive and intellectual burden to interpret information for decision-making. However, understanding data visualization interventions specific to public health leaders' decision-making is lacking, and there is little guidance for understanding a participant's characteristics and tasks. The evidence from this review suggests positive effects of data visualization can be identified, depending on the control of confounding factors on attitude, perception, and decision-making.</p>","PeriodicalId":54984,"journal":{"name":"Informatics for Health & Social Care","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2022-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review.\",\"authors\":\"Seungeun Park, Betty Bekemeier, Abraham Flaxman, Melinda Schultz\",\"doi\":\"10.1080/17538157.2021.1982949\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Data visualization tools have the potential to support decision-making for public health professionals. This review summarizes the science and evidence regarding data visualization and its impact on decision-making behavior as informed by cognitive processes such as understanding, attitude, or perception.An electronic literature search was conducted using six databases, including reference list reviews. Search terms were pre-defined based on research questions.Sixteen studies were included in the final analysis. Data visualization interventions in this review were found to impact attitude, perception, and decision-making compared to controls. These relationships between the interventions and outcomes appear to be explained by mediating factors such as perceived trustworthiness and quality, domain-specific knowledge, basic beliefs shared by social groups, and political beliefs.Visualization appears to bring advantages by increasing the amount of information delivered and decreasing the cognitive and intellectual burden to interpret information for decision-making. 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Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review.
Data visualization tools have the potential to support decision-making for public health professionals. This review summarizes the science and evidence regarding data visualization and its impact on decision-making behavior as informed by cognitive processes such as understanding, attitude, or perception.An electronic literature search was conducted using six databases, including reference list reviews. Search terms were pre-defined based on research questions.Sixteen studies were included in the final analysis. Data visualization interventions in this review were found to impact attitude, perception, and decision-making compared to controls. These relationships between the interventions and outcomes appear to be explained by mediating factors such as perceived trustworthiness and quality, domain-specific knowledge, basic beliefs shared by social groups, and political beliefs.Visualization appears to bring advantages by increasing the amount of information delivered and decreasing the cognitive and intellectual burden to interpret information for decision-making. However, understanding data visualization interventions specific to public health leaders' decision-making is lacking, and there is little guidance for understanding a participant's characteristics and tasks. The evidence from this review suggests positive effects of data visualization can be identified, depending on the control of confounding factors on attitude, perception, and decision-making.
期刊介绍:
Informatics for Health & Social Care promotes evidence-based informatics as applied to the domain of health and social care. It showcases informatics research and practice within the many and diverse contexts of care; it takes personal information, both its direct and indirect use, as its central focus.
The scope of the Journal is broad, encompassing both the properties of care information and the life-cycle of associated information systems.
Consideration of the properties of care information will necessarily include the data itself, its representation, structure, and associated processes, as well as the context of its use, highlighting the related communication, computational, cognitive, social and ethical aspects.
Consideration of the life-cycle of care information systems includes full range from requirements, specifications, theoretical models and conceptual design through to sustainable implementations, and the valuation of impacts. Empirical evidence experiences related to implementation are particularly welcome.
Informatics in Health & Social Care seeks to consolidate and add to the core knowledge within the disciplines of Health and Social Care Informatics. The Journal therefore welcomes scientific papers, case studies and literature reviews. Examples of novel approaches are particularly welcome. Articles might, for example, show how care data is collected and transformed into useful and usable information, how informatics research is translated into practice, how specific results can be generalised, or perhaps provide case studies that facilitate learning from experience.