scholarly journals Health Information Needs and Health Seeking Behavior during the 2014-2016 Ebola Outbreak: A Twitter Content Analysis

2017 ◽  
Author(s):  
Michelle L. Odlum ◽  
Sunmoo Yoon
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Health Information ◽  
Language Processing ◽  
Information Seeking ◽  
Information Needs ◽  
Disease Outbreaks ◽  
Time Data ◽  
Health Seeking ◽  
Over Time

AbstractIntroductionFor effective public communication during major disease outbreaks like the 2014-2016 Ebola epidemic, health information needs of the population must be adequately assessed. Through content analysis of social media data, like tweets, public health information needs can be effectively assessed and in turn provide appropriate health information to effectively address such needs. The aim of the current study was to assess health information needs about Ebola, at distinct epidemic time points, through longitudinal tracking.MethodsNatural language processing was applied to explore public response to Ebola over time from the beginning of the outbreak (July 2014) to six month post outbreak (March 2015). A total 155,647 tweets (unique 68,736, retweet 86,911) mentioning Ebola were analyzed and visualized with infographics.ResultsPublic fear, frustration, and health information seeking regarding Ebola-related global priorities were observed across time. Our longitudinal content analysis revealed that due to ongoing health information deficiencies, resulting in fear and frustration, social media was at times an impediment and not a vehicle to support health information needs.DiscussionContent analysis of tweets effectively assessed Ebola information needs. Our study also demonstrates the use of Twitter as a method for capturing real-time data to assess ongoing information needs, fear, and frustration over time.All authors have seen and approved the manuscript.

scholarly journals Using Social Media Data to Understand Consumers' Information Needs and Emotions Regarding Cancer: Ontology-Based Data Analysis Study

10.2196/18767 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e18767
Author(s):  
Jooyun Lee ◽  
Hyeoun-Ae Park ◽  
Seul Ki Park ◽  
Tae-Min Song
Keyword(s):  
Social Media ◽  
Health Information ◽  
Language Processing ◽  
Information Needs ◽  
Semantic Analysis ◽  
Care Process ◽  
Cancer Type ◽  
Social Media Data ◽  
Related Information ◽  
Media Data

Background Analysis of posts on social media is effective in investigating health information needs for disease management and identifying people’s emotional status related to disease. An ontology is needed for semantic analysis of social media data. Objective This study was performed to develop a cancer ontology with terminology containing consumer terms and to analyze social media data to identify health information needs and emotions related to cancer. Methods A cancer ontology was developed using social media data, collected with a crawler, from online communities and blogs between January 1, 2014 and June 30, 2017 in South Korea. The relative frequencies of posts containing ontology concepts were counted and compared by cancer type. Results The ontology had 9 superclasses, 213 class concepts, and 4061 synonyms. Ontology-driven natural language processing was performed on the text from 754,744 cancer-related posts. Colon, breast, stomach, cervical, lung, liver, pancreatic, and prostate cancer; brain tumors; and leukemia appeared most in these posts. At the superclass level, risk factor was the most frequent, followed by emotions, symptoms, treatments, and dealing with cancer. Conclusions Information needs and emotions differed according to cancer type. The observations of this study could be used to provide tailored information to consumers according to cancer type and care process. Attention should be paid to provision of cancer-related information to not only patients but also their families and the general public seeking information on cancer.

Sexual health information-seeking behavior on a social media site: predictors of best answer selection

2018 ◽  
Vol 42 (6) ◽  
pp. 880-897 ◽  
Author(s):  
Yong Jeong Yi
Keyword(s):  
Social Media ◽  
Sexual Health ◽  
Health Information ◽  
Information Seeking ◽  
Information Needs ◽  
Content Type ◽  
Sexual Health Information ◽  
Affective Factors ◽  
Health Information Seeking Behavior ◽  
Questions And Answers

PurposeThe purpose of this paper is to identify sexual health information needs and the cognitive and affective factors correlated with the best answer chosen by social Q&A users.Design/methodology/approachThe study collected questions and answers regarding sexual health information on a social Q&A site, and analyzed the questions and a paired sample composed of best and non-best answers (n=480).FindingsThe main information needs of consumers are human development, sexual behavior, and sexual health. Best answers are more likely to include both cognitive (higher level of readability, risky information, social norms) and affective factors (empathy, positive/negative feelings, and optimistic information) than non-best answers.Research limitations/implicationsThe study illuminates the roles of social Q&A as a unique platform to discuss sensitive health topics due to the fact that consumers use such social media sites as critical complementary health information sources.Practical implicationsIf health information providers develop information with the factors that the study suggests, not only will it be more adopted by consumers, but it will also ameliorate the quality concerns about online health information.Originality/valuePrevious studies only investigated the most prevalent factors, rather than the most effective ones, which have a greater influence on best answer selection. This study compares the best answers and the non-best answers to overcome the limitations of the previous studies. Above all, the study applied the persuasion concepts to address the cognitive and affective perspectives to the answer evaluations of social Q&A.

scholarly journals Using Social Media Data to Understand Consumers' Information Needs and Emotions Regarding Cancer: Ontology-Based Data Analysis Study (Preprint)

2020 ◽  
Author(s):  
Jooyun Lee ◽  
Hyeoun-Ae Park ◽  
Seul Ki Park ◽  
Tae-Min Song
Keyword(s):  
Social Media ◽  
Health Information ◽  
Language Processing ◽  
Information Needs ◽  
Semantic Analysis ◽  
Care Process ◽  
Cancer Type ◽  
Social Media Data ◽  
Related Information ◽  
Media Data

BACKGROUND Analysis of posts on social media is effective in investigating health information needs for disease management and identifying people’s emotional status related to disease. An ontology is needed for semantic analysis of social media data. OBJECTIVE This study was performed to develop a cancer ontology with terminology containing consumer terms and to analyze social media data to identify health information needs and emotions related to cancer. METHODS A cancer ontology was developed using social media data, collected with a crawler, from online communities and blogs between January 1, 2014 and June 30, 2017 in South Korea. The relative frequencies of posts containing ontology concepts were counted and compared by cancer type. RESULTS The ontology had 9 superclasses, 213 class concepts, and 4061 synonyms. Ontology-driven natural language processing was performed on the text from 754,744 cancer-related posts. Colon, breast, stomach, cervical, lung, liver, pancreatic, and prostate cancer; brain tumors; and leukemia appeared most in these posts. At the superclass level, risk factor was the most frequent, followed by emotions, symptoms, treatments, and dealing with cancer. CONCLUSIONS Information needs and emotions differed according to cancer type. The observations of this study could be used to provide tailored information to consumers according to cancer type and care process. Attention should be paid to provision of cancer-related information to not only patients but also their families and the general public seeking information on cancer.

scholarly journals Examining the Correlates of Online Health Information–Seeking Behavior Among Men Compared With Women

2016 ◽  
Vol 12 (5) ◽  
pp. 1358-1367 ◽  
Author(s):  
Irene A. Nikoloudakis ◽  
Corneel Vandelanotte ◽  
Amanda L. Rebar ◽  
Stephanie Schoeppe ◽  
Stephanie Alley ◽  
...  
Keyword(s):  
Social Media ◽  
Health Status ◽  
Health Information ◽  
Information Seeking ◽  
Media Use ◽  
Online Health Information ◽  
Health Information Seeking ◽  
Health Seeking ◽  
Men And Women ◽  
Online Health Information Seeking

This study aimed to identify and compare the demographic, health behavior, health status, and social media use correlates of online health-seeking behaviors among men and women. Cross-sectional self-report data were collected from 1,289 Australian adults participating in the Queensland Social Survey. Logistic regression analyses were used to identify the correlates of online health information seeking for men and women. Differences in the strength of the relation of these correlates were tested using equality of regression coefficient tests. For both genders, the two strongest correlates were social media use (men: odds ratio [ OR] = 2.57, 95% confidence interval [CI: 1.78, 3.71]; women: OR = 2.93, 95% CI [1.92, 4.45]) and having a university education (men: OR = 3.63, 95% CI [2.37, 5.56]; women: OR = 2.74, 95% CI [1.66, 4.51]). Not being a smoker and being of younger age were also associated with online health information seeking for both men and women. Reporting poor health and the presence of two chronic diseases were positively associated with online health seeking for women only. Correlates of help seeking online among men and women were generally similar, with exception of health status. Results suggest that similar groups of men and women are likely to access health information online for primary prevention purposes, and additionally that women experiencing poor health are more likely to seek health information online than women who are relatively well. These findings are useful for analyzing the potential reach of online health initiatives targeting both men and women.

Social Media and the Transformation of Healthcare: A Viewpoint (Preprint)

2020 ◽  
Author(s):  
Ella Forgie ◽  
Hollis Lai ◽  
Bo Cao ◽  
Eleni Stroulia ◽  
Andrew James Greenshaw ◽  
...  
Keyword(s):  
Social Media ◽  
Health Information ◽  
Information Seeking ◽  
Virtual Communities ◽  
Community Support ◽  
Security And Privacy ◽  
Support Network ◽  
Full Potential ◽  
Physician Patient Relationship ◽  
Mediation Effects

UNSTRUCTURED As many as 80% of internet users seek health information online. The social determinants of health (SDoH) are intimately related to who has access to the internet and healthcare as a whole. Those who face more barriers to care are more likely to benefit from accessing health information online, granted the information they are retrieving is accurate. Virtual communities on social media platforms are particularly interesting as venues for seeking health information online because peers have been shown to influence health behaviour more than almost anything else. Thus, it is important to recognize the potential of social media to have positive mediation effects on health, so long as any negative mediation effects are reconcilable. As a positive mediator of health, social media can be used as a direct or indirect mode of communication between physicians and patients, a venue for health promotion and health information, and a community support network. False or misleading content, social contagion, confirmation bias, and security and privacy concerns must be mitigated in order to realize full potential of social media as a positive mediator of health. In any case, it is clear that the intersections between the SDoH, social media, and health are intimate, and they must be taken into consideration by physicians. Here, we argue that a paradigm shift in the physician-patient relationship is warranted, one where physicians: a) acknowledge the impacts of the SDoH on information-seeking behaviour, b) recognize the positive and negative roles of social media as a mediator of health through the lens of the SDoH, and c) use social media to catalyze positive changes in the standard of care.

Framing in Health Communication: Identifying the Factors That Influence the Re-posting of Social Media Messages during COVID-19 Outbreaks in China (Preprint)

2021 ◽  
Author(s):  
Jingzhong Xie ◽  
Jun Lai ◽  
Dongying Zhang
Keyword(s):  
Social Media ◽  
Health Communication ◽  
Health Information ◽  
Information Needs ◽  
Information Sources ◽  
Negative Binomial ◽  
Public Awareness ◽  
Public Health Agencies ◽  
Media Messages ◽  
Action Frame

BACKGROUND Social media has become an important tool to implement risk communication in COVID-19 pandemic, and made health information can gain more exposure by re-posting. OBJECTIVE This paper attempts to identify the factors associated with re-posting of social media messages about health information METHODS Content analysis was applied to scrutinize 4396 Weibo posts that were posted by national and provincial public health agencies Weibo accounts and identified features of information sources and information features, and adopted Zero-Inflated Negative Binomial (ZINB) model to analyze the association between these features and the frequency of message being re-posted. RESULTS Results showed that the followers and the governmental level of information sources are correlated with increased message reposting. The information features, such as hashtags#, picture, video, emotional(!), and the usage of severity, reassurance, efficacy and action frame were associated with increased message reposting behaviors, while hyperlink and usage of uncertainty frame correlated with reduced message reposting behaviors. CONCLUSIONS The features of health information sources, structures , style and content should be paid close attention by health organizations and medical professionals to satisfy the public’s information needs and preferences, promote the public's health engagement. Suitable information systems designing, and health communication strategies making during different stages of the pandemic may improve public awareness of the COVID-19, alleviate negative emotions, promote preventive measures to curb the spread of the virus.

scholarly journals Share to Seek: The Effects of Disease Complexity on Health Information Seeking Behavior (Preprint)

2020 ◽  
Author(s):  
Ashwag Alasmari ◽  
Lina Zhou
Keyword(s):  
Health Information ◽  
Information Seeking ◽  
Information Needs ◽  
Qualitative Content Analysis ◽  
Experimental Studies ◽  
Mixed Data ◽  
Disease Development ◽  
Health Information Seeking ◽  
Alternative Source ◽  
Types Of Information

BACKGROUND Online Questioning and Answering (Q&A) sites have emerged as an alternative source for serving individuals’ health information needs. Despite the amount of studies concerning the analysis of user-generated content in online Q&A sites, there is an insufficient understanding of the effect of disease complexity on information seeking needs, and the types of information shared, and little research have been devoted to questions that involve multimorbidity. OBJECTIVE This study aims to investigate online sharing of health information at different levels of disease complexity. In particular, this study gains a deep insight into the effect of disease complexity in terms of information seeking needs, types of information shared, and stages of disease development. METHODS We first selected a random sample of 400 questions from each site. The data cleaning resulted in a final set of 624 questions, 316 questions from Yahoo Answers and 308 from WebMD Answers. We used a mixed data approach, including qualitative content analysis followed by statistical quantitative analysis. RESULTS The analysis of variance One Way ANOVA showed significant differences in the disease complexity (single versus multimorbid disease questions) only on two information seeking needs: diagnosis (F1, 622 =5.08, p=0.00), and treatment (F1, 622 =4.82, p=0.00). There were also statistically significant differences between the two levels of disease complexity when considering the stages of disease development, the general health stage (F1,622 =48.02, p=0.00) and chronic stage (F1,622 =54.01, p=0.00). Moreover, our findings showed significant differences among the two types of disease complexity on all types of shared information, demographic information (F1,622 =32.24, p=0.00), medical all (F1,622 = 16.75, p=0.00), medical diagnosis (F1,622 =11.04, p=0.00), as well as treatment and prevention (F1,622 =14.55, p=0.00). CONCLUSIONS The findings present implications for designing online Q&A sites to better support health information seeking. Future experimental studies should be conducted to verify these findings and provide effective health information from Q&A sites. CLINICALTRIAL

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