67
views
0
recommends
+1 Recommend
2 collections
    0
    shares

      Submit your digital health research with an established publisher
      - celebrating 25 years of open access

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Assessing the Viability of Social Media for Disseminating Evidence-Based Nutrition Practice Guideline Through Content Analysis of Twitter Messages and Health Professional Interviews: An Observational Study

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Given the high penetration of social media use, social media has been proposed as a method for the dissemination of information to health professionals and patients. This study explored the potential for social media dissemination of the Academy of Nutrition and Dietetics Evidence-Based Nutrition Practice Guideline (EBNPG) for Heart Failure (HF).

          Objectives

          The objectives were to (1) describe the existing social media content on HF, including message content, source, and target audience, and (2) describe the attitude of physicians and registered dietitian nutritionists (RDNs) who care for outpatient HF patients toward the use of social media as a method to obtain information for themselves and to share this information with patients.

          Methods

          The methods were divided into 2 parts. Part 1 involved conducting a content analysis of tweets related to HF, which were downloaded from Twitonomy and assigned codes for message content (19 codes), source (9 codes), and target audience (9 codes); code frequency was described. A comparison in the popularity of tweets (those marked as favorites or retweeted) based on applied codes was made using t tests. Part 2 involved conducting phone interviews with RDNs and physicians to describe health professionals’ attitude toward the use of social media to communicate general health information and information specifically related to the HF EBNPG. Interviews were transcribed and coded; exemplar quotes representing frequent themes are presented.

          Results

          The sample included 294 original tweets with the hashtag “#heartfailure.” The most frequent message content codes were “HF awareness” (166/294, 56.5%) and “patient support” (97/294, 33.0%). The most frequent source codes were “professional, government, patient advocacy organization, or charity” (112/277, 40.4%) and “patient or family” (105/277, 37.9%). The most frequent target audience codes were “unable to identify” (111/277, 40.1%) and “other” (55/277, 19.9%). Significant differences were found in the popularity of tweets with (mean 1, SD 1.3 favorites) or without (mean 0.7, SD 1.3 favorites), the content code being “HF research” ( P=.049). Tweets with the source code “professional, government, patient advocacy organizations, or charities” were significantly more likely to be marked as a favorite and retweeted than those without this source code (mean 1.2, SD 1.4 vs mean 0.8, SD 1.2, P=.03) and (mean 1.5, SD 1.8 vs mean 0.9, SD 2.0, P=.03). Interview participants believed that social media was a useful way to gather professional information. They did not believe that social media was useful for communicating with patients due to privacy concerns and the fact that the information had to be kept general rather than be tailored for a specific patient and the belief that their patients did not use social media or technology.

          Conclusions

          Existing Twitter content related to HF comes from a combination of patients and evidence-based organizations; however, there is little nutrition content. That gap may present an opportunity for EBNPG dissemination. Health professionals use social media to gather information for themselves but are skeptical of its value when communicating with patients, particularly due to privacy concerns and misconceptions about the characteristics of social media users.

          Related collections

          Most cited references20

          • Record: found
          • Abstract: found
          • Article: not found

          Tailored interventions to overcome identified barriers to change: effects on professional practice and health care outcomes.

          In the previous version of this review, the effectiveness of interventions tailored to barriers to change was found to be uncertain. To assess the effectiveness of interventions tailored to address identified barriers to change on professional practice or patient outcomes. For this update, in addition to the EPOC Register and pending files, we searched the following databases without language restrictions, from inception until August 2007: MEDLINE, EMBASE, CINAHL, BNI and HMIC. We searched the National Research Register to November 2007. We undertook further searches to October 2009 to identify potentially eligible published or ongoing trials. Randomised controlled trials (RCTs) of interventions tailored to address prospectively identified barriers to change that reported objectively measured professional practice or healthcare outcomes in which at least one group received an intervention designed to address prospectively identified barriers to change. Two reviewers independently assessed quality and extracted data. We undertook quantitative and qualitative analyses. The quantitative analyses had two elements.1. We carried out a meta-regression to compare interventions tailored to address identified barriers to change with either no interventions or an intervention(s) not tailored to the barriers.2. We carried out heterogeneity analyses to investigate sources of differences in the effectiveness of interventions. These included the effects of: risk of bias, concealment of allocation, rigour of barrier analysis, use of theory, complexity of interventions, and the reported presence of administrative constraints. We included 26 studies comparing an intervention tailored to address identified barriers to change to no intervention or an intervention(s) not tailored to the barriers. The effect sizes of these studies varied both across and within studies.Twelve studies provided enough data to be included in the quantitative analysis. A meta-regression model was fitted adjusting for baseline odds by fitting it as a covariate, to obtain the pooled odds ratio of 1.54 (95% CI, 1.16 to 2.01) from Bayesian analysis and 1.52 (95% CI, 1.27 to 1.82, P < 0.001) from classical analysis. The heterogeneity analyses found that no study attributes investigated were significantly associated with effectiveness of the interventions. Interventions tailored to prospectively identified barriers are more likely to improve professional practice than no intervention or dissemination of guidelines. However, the methods used to identify barriers and tailor interventions to address them need further development. Research is required to determine the effectiveness of tailored interventions in comparison with other interventions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Understanding the Factors That Influence the Adoption and Meaningful Use of Social Media by Physicians to Share Medical Information

            Background Within the medical community there is persistent debate as to whether the information available through social media is trustworthy and valid, and whether physicians are ready to adopt these technologies and ultimately embrace them as a format for professional development and lifelong learning. Objective To identify how physicians are using social media to share and exchange medical information with other physicians, and to identify the factors that influence physicians’ use of social media as a component of their lifelong learning and continuing professional development. Methods We developed a survey instrument based on the Technology Acceptance Model, hypothesizing that technology usage is best predicted by a physician’s attitudes toward the technology, perceptions about the technology’s usefulness and ease of use, and individual factors such as personal innovativeness. The survey was distributed via email to a random sample of 1695 practicing oncologists and primary care physicians in the United States in March 2011. Responses from 485 physicians were analyzed (response rate 28.61%). Results Overall, 117 of 485 (24.1%) of respondents used social media daily or many times daily to scan or explore medical information, whereas 69 of 485 (14.2%) contributed new information via social media on a daily basis. On a weekly basis or more, 296 of 485 (61.0%) scanned and 223 of 485 (46.0%) contributed. In terms of attitudes toward the use of social media, 279 of 485 respondents (57.5%) perceived social media to be beneficial, engaging, and a good way to get current, high-quality information. In terms of usefulness, 281 of 485 (57.9%) of respondents stated that social media enabled them to care for patients more effectively, and 291 of 485 (60.0%) stated it improved the quality of patient care they delivered. The main factors influencing a physician’s usage of social media to share medical knowledge with other physicians were perceived ease of use and usefulness. Respondents who had positive attitudes toward the use of social media were more likely to use social media and to share medical information with other physicians through social media. Neither age nor gender had a significant impact on adoption or usage of social media. Conclusions Based on the results of this study, the use of social media applications may be seen as an efficient and effective method for physicians to keep up-to-date and to share newly acquired medical knowledge with other physicians within the medical community and to improve the quality of patient care. Future studies are needed to examine the impact of the meaningful use of social media on physicians’ knowledge, attitudes, skills, and behaviors in practice.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection

              Background Social media have transformed the communications landscape. People increasingly obtain news and health information online and via social media. Social media platforms also serve as novel sources of rich observational data for health research (including infodemiology, infoveillance, and digital disease detection detection). While the number of studies using social data is growing rapidly, very few of these studies transparently outline their methods for collecting, filtering, and reporting those data. Keywords and search filters applied to social data form the lens through which researchers may observe what and how people communicate about a given topic. Without a properly focused lens, research conclusions may be biased or misleading. Standards of reporting data sources and quality are needed so that data scientists and consumers of social media research can evaluate and compare methods and findings across studies. Objective We aimed to develop and apply a framework of social media data collection and quality assessment and to propose a reporting standard, which researchers and reviewers may use to evaluate and compare the quality of social data across studies. Methods We propose a conceptual framework consisting of three major steps in collecting social media data: develop, apply, and validate search filters. This framework is based on two criteria: retrieval precision (how much of retrieved data is relevant) and retrieval recall (how much of the relevant data is retrieved). We then discuss two conditions that estimation of retrieval precision and recall rely on—accurate human coding and full data collection—and how to calculate these statistics in cases that deviate from the two ideal conditions. We then apply the framework on a real-world example using approximately 4 million tobacco-related tweets collected from the Twitter firehose. Results We developed and applied a search filter to retrieve e-cigarette–related tweets from the archive based on three keyword categories: devices, brands, and behavior. The search filter retrieved 82,205 e-cigarette–related tweets from the archive and was validated. Retrieval precision was calculated above 95% in all cases. Retrieval recall was 86% assuming ideal conditions (no human coding errors and full data collection), 75% when unretrieved messages could not be archived, 86% assuming no false negative errors by coders, and 93% allowing both false negative and false positive errors by human coders. Conclusions This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges and moves toward establishing a standard of reporting social data. Researchers should clearly delineate data sources, how data were accessed and collected, and the search filter building process and how retrieval precision and recall were calculated. The proposed framework can be adapted to other public social media platforms.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                November 2016
                15 November 2016
                : 18
                : 11
                : e295
                Affiliations
                [1] 1Academy of Nutrition and Dietetics Chicago, ILUnited States
                [2] 2College of Public Health Kent State University Kent, OHUnited States
                [3] 3Antidote Education Company Dallas, TXUnited States
                Author notes
                Corresponding Author: Rosa K Hand rhand@ 123456eatright.org
                Author information
                http://orcid.org/0000-0003-1314-1964
                http://orcid.org/0000-0003-2852-5776
                http://orcid.org/0000-0003-3604-4278
                http://orcid.org/0000-0002-1110-0272
                http://orcid.org/0000-0002-8151-6871
                Article
                v18i11e295
                10.2196/jmir.5811
                5128725
                27847349
                3c4eb158-16a9-4c22-a6e4-37b13fa27941
                ©Rosa K Hand, Deric Kenne, Taylor M Wolfram, Jenica K Abram, Michael Fleming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.11.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 28 March 2016
                : 5 July 2016
                : 11 August 2016
                : 24 October 2016
                Categories
                Original Paper
                Original Paper

                Medicine
                social media,information dissemination,medical nutrition therapy,evidence-based medicine,heart failure

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content89

                Cited by16

                Most referenced authors254