Can Online Consumers Contribute to Drug Knowledge? A Mixed-Methods Comparison of Consumer-Generated and Professionally Controlled Psychotropic Medication Information on the Internet

Background Ongoing initiatives to filter online health searches exclude consumer-generated content from search returns, though its inferiority compared with professionally controlled content is not demonstrated. The antidepressant escitalopram and the antipsychotic quetiapine have ranked over the last 5 years as top-selling agents in their respective drug classes. Both drugs have various off-label mental health and non?mental health uses, ranging from the relief of insomnia and migraines to the treatment of severe developmental disorders. Objective Our objective was to describe the most frequently reported effects of escitalopram and quetiapine in online consumer reviews, to compare them with effects described in professionally controlled commercial health websites, and to gauge the usability of online consumer medication reviews. Methods A stratified simple random sample of 960 consumer reviews was selected from all 6998 consumer reviews of the two drugs in 2 consumer-generated (www.askapatient.com and www.crazymeds.us) and 2 professionally controlled (www.webmd.com and www.revolutionhealth.com) health websites. Professional medication descriptions included all standard information on the medications from the latter 2 websites. All textual data were inductively coded for medication effects, and intercoder agreement was assessed. Chi-square was used to test for associations between consumer-reported effects and website origination. Results Consumers taking either escitalopram (n = 480) or quetiapine (n = 480) most frequently reported symptom improvement (30.4% or 146/480, 24.8% or 119/480) or symptom worsening (15.8% or 76/480, 10.2% or 49/480), changes in sleep (36% or 173/480, 60.6% or 291/480) and changes in weight and appetite (22.5% or 108/480, 30.8% or 148/480). More consumers posting reviews on consumer-generated rather than professionally controlled websites reported symptom worsening on quetiapine (17.3% or 38/220 versus 5% or 11/220, P \u3c .001), while more consumers posting on professionally controlled websites reported symptom improvement (32.7% or 72/220 versus 21.4% or 47/220, P = .008). Professional descriptions more frequently listed physical adverse effects and warnings about suicidal ideation while consumer reviews emphasized effects disrupting daily routines and provided richer descriptions of effects in context. The most recent 20 consumer reviews on each drug from each website (n = 80) were comparable to the full sample of reviews in the frequency of commonly reported effects. Conclusion Consumer reviews and professional medication descriptions generally reported similar effects of two psychotropic medications but differed in their descriptions and in frequency of reporting. Professional medication descriptions offer the advantage of a concise yet comprehensive listing of drug effects, while consumer reviews offer greater context and situational examples of how effects may manifest in various combinations and to varying degrees. The dispersion of consumer reviews across websites limits their integration, but a brief browsing strategy on the two target medications nonetheless retrieved representative consumer content. Current strategies for filtering online health searches to return only trusted or approved websites may inappropriately address the challenge to identify quality health sources on the Internet because such strategies unduly limit access to an entire complementary source for health information

Portals to Wonderland: Health portals lead to confusing information about the effects of health care

BACKGROUND: The Internet offers a seemingly endless amount of health information of varying quality. Health portals, which provide entry points to quality-controlled collections of websites, have been hailed as a solution to this problem. The objective of this study is to assess the extent to which government-run health portals provide access to relevant, valid and understandable information about the effects of health care. METHODS: We selected eight clinically relevant questions for which there was a systematic review, searched four portals for answers, and compared the answers we found to the results of the systematic reviews. RESULTS: Our searches resulted in 3400 hits, 155 of which mentioned both the condition and the intervention in one of the eight questions. Sixty-three of the 155 web pages did not give any information about the effect of the intervention. Seventy-seven qualitatively described the effects of the intervention. Twenty-six of these had information that was too unclear to be categorised; 15 were not consistent with the systematic review; and 36 were consistent with the review, but usually did not mention what happens without the intervention, what outcomes have been measured or when they were measured. Fifteen web pages quantitatively described effects. Four of these were abstracts from the systematic review, nine had information that was incomplete and potentially misleading because of a lack of information about people not receiving the intervention and the length of follow-up; one had information that was consistent with the review, but only referred to three trials whereas the review included six; and one was consistent with the review. CONCLUSION: Information accessible through health portals is unlikely to be based on systematic reviews and is often unclear, incomplete and misleading. Portals are only as good as the websites they lead to. Investments in national health portals are unlikely to benefit consumers without investments in the production and maintenance of relevant, valid and understandable information to which the portals lead

Using Search Queries to Understand Health Information Needs in Africa

The lack of comprehensive, high-quality health data in developing nations creates a roadblock for combating the impacts of disease. One key challenge is understanding the health information needs of people in these nations. Without understanding people's everyday needs, concerns, and misconceptions, health organizations and policymakers lack the ability to effectively target education and programming efforts. In this paper, we propose a bottom-up approach that uses search data from individuals to uncover and gain insight into health information needs in Africa. We analyze Bing searches related to HIV/AIDS, malaria, and tuberculosis from all 54 African nations. For each disease, we automatically derive a set of common search themes or topics, revealing a wide-spread interest in various types of information, including disease symptoms, drugs, concerns about breastfeeding, as well as stigma, beliefs in natural cures, and other topics that may be hard to uncover through traditional surveys. We expose the different patterns that emerge in health information needs by demographic groups (age and sex) and country. We also uncover discrepancies in the quality of content returned by search engines to users by topic. Combined, our results suggest that search data can help illuminate health information needs in Africa and inform discussions on health policy and targeted education efforts both on- and offline.Comment: Extended version of an ICWSM 2019 pape

Health Misinformation in Search and Social Media

People increasingly rely on the Internet in order to search for and share health-related information. Indeed, searching for and sharing information about medical treatments are among the most frequent uses of online data. While this is a convenient and fast method to collect information, online sources may contain incorrect information that has the potential to cause harm, especially if people believe what they read without further research or professional medical advice. The goal of this thesis is to address the misinformation problem in two of the most commonly used online services: search engines and social media platforms. We examined how people use these platforms to search for and share health information. To achieve this, we designed controlled laboratory user studies and employed large-scale social media data analysis tools. The solutions proposed in this thesis can be used to build systems that better support people's health-related decisions. The techniques described in this thesis addressed online searching and social media sharing in the following manner. First, with respect to search engines, we aimed to determine the extent to which people can be influenced by search engine results when trying to learn about the efficacy of various medical treatments. We conducted a controlled laboratory study wherein we biased the search results towards either correct or incorrect information. We then asked participants to determine the efficacy of different medical treatments. Results showed that people were significantly influenced both positively and negatively by search results bias. More importantly, when the subjects were exposed to incorrect information, they made more incorrect decisions than when they had no interaction with the search results. Following from this work, we extended the study to gain insights into strategies people use during this decision-making process, via the think-aloud method. We found that, even with verbalization, people were strongly influenced by the search results bias. We also noted that people paid attention to what the majority states, authoritativeness, and content quality when evaluating online content. Understanding the effects of cognitive biases that can arise during online search is a complex undertaking because of the presence of unconscious biases (such as the search results ranking) that the think-aloud method fails to show. Moving to social media, we first proposed a solution to detect and track misinformation in social media. Using Zika as a case study, we developed a tool for tracking misinformation on Twitter. We collected 13 million tweets regarding the Zika outbreak and tracked rumors outlined by the World Health Organization and the Snopes fact-checking website. We incorporated health professionals, crowdsourcing, and machine learning to capture health-related rumors as well as clarification communications. In this way, we illustrated insights that the proposed tools provide into potentially harmful information on social media, allowing public health researchers and practitioners to respond with targeted and timely action. From identifying rumor-bearing tweets, we examined individuals on social media who are posting questionable health-related information, in particular those promoting cancer treatments that have been shown to be ineffective. Specifically, we studied 4,212 Twitter users who have posted about one of 139 ineffective ``treatments'' and compared them to a baseline of users generally interested in cancer. Considering features that capture user attributes, writing style, and sentiment, we built a classifier that is able to identify users prone to propagating such misinformation. This classifier achieved an accuracy of over 90%, providing a potential tool for public health officials to identify such individuals for preventive intervention

Probiotics: Achieving a Better Regulatory Fit

In 2007, the National Institutes of Health (NIH) launched the Human Microbiome Project (HMP), a $150 million initiative to characterize the microbial communities found at several different sites on the human body and to analyze the role of these microbes in human health and disease. Many lines of research have demonstrated the significant role of the microbiota in human physiology. The microbiota is involved, for example, in the healthy development of the immune system, prevention of infection from pathogenic or opportunistic microbes, and maintenance of intestinal barrier function. The HMP findings are helping us understand the role and variation of microorganisms within and across individuals, they are also promoting interest in the development of probiotic products. NIH set aside a portion of HMP funds to study the Ethical, Legal, and Social Implications (ELSI) of the HMP’s scientific goals. Among the funded ELSI studies was an effort to look at the current regulatory framework for probiotics and to determine if it is a good fit for the range of probiotics that are on the market, under development, or that may be developed in the future as a result of the HMP. This article reports on the findings of a Working Group consisting of NIH-funded HMP scientists, physicians, legal academics, government regulators, industry and consumer representatives, bioethicists, food and drug lawyers, and health policymakers who were assembled to address the adequacy of the current regulatory framework for probiotics under the HMP ELSI funded project. Specifically, after discussion of the features of probiotics that are relevant to their regulation and an overview of FDA’s current regulation of probiotics, the article addresses the following questions: 1) Do current regulations adequately address the safety of new probiotic products? 2) Should probiotic foods and dietary supplements be classified as drugs and required to go through the drug approval process? 3) What types of product characterization requirements are appropriate for probiotics? 4) Are current claim regulations appropriate for probiotics and, if not, how might they be improved

Emerging Communication Technologies and Public Health Information Dissemination

Health promotion is a critical constituent of the public health system. Its primary objective is the empowerment of individuals and communities in the interest of positively influencing health behaviours and outcomes. One of the main ways in which successful health promotion is achieved is by the dissemination of relevant health information to individuals and communities. As global health costs rise to match the demands of an increasing and ageing population, such delivery of cost-effective public health information is explored. The recent advances in communication technologies have led to the development of social digital platforms (Web 2.0), with unprecedented opportunities for the extensive dissemination of relevant health information. The widespread uptake of social networking sites (SNS) presents a novel platform for public health promotion and management that can verily overcome the issues faced by current public health initiatives while reaching global populations of health consumers. This thesis aims to provide an exploratory analysis of the current landscape of health information communication across SNS, primarily through the platform Twitter. The research will address literature gaps in this cross-disciplinary field of health and communication sciences found for various SNS user-types, analyse and characterise the types of health information being disseminated across such platforms, as well as examine SNS activity during public health events. Public health officials and Web 2.0 platform developers can utilise findings from this thesis to address limitations of online public health-related communication insofar as they can assist with: a) advising plans for better engagement of information disseminated during health events; b) developing future applications and technologies that are appropriate for disadvantaged groups; c) identifying information dissemination strategies for authoritative health bodies and organizations to effectively reach populations

Pharmaceutical Advertising: A Qualitative Comparison of the Internet and National Magazines

The Internet offers tremendous potential benefits to consumers in terms of increased convenience, choices and information. Yet, along with such benefits, comes new risks to consumers, including an increased risk from fraud, deception and misinformation (FDA and the Internet Conference, October, 1996)

Social analytics for health integration, intelligence, and monitoring

Nowadays, patient-generated social health data are abundant and Healthcare is changing from the authoritative provider-centric model to collaborative and patient-oriented care. The aim of this dissertation is to provide a Social Health Analytics framework to utilize social data to solve the interdisciplinary research challenges of Big Data Science and Health Informatics. Specific research issues and objectives are described below. The first objective is semantic integration of heterogeneous health data sources, which can vary from structured to unstructured and include patient-generated social data as well as authoritative data. An information seeker has to spend time selecting information from many websites and integrating it into a coherent mental model. An integrated health data model is designed to allow accommodating data features from different sources. The model utilizes semantic linked data for lightweight integration and allows a set of analytics and inferences over data sources. A prototype analytical and reasoning tool called “Social InfoButtons” that can be linked from existing EHR systems is developed to allow doctors to understand and take into consideration the behaviors, patterns or trends of patients’ healthcare practices during a patient’s care. The tool can also shed insights for public health officials to make better-informed policy decisions. The second objective is near-real time monitoring of disease outbreaks using social media. The research for epidemics detection based on search query terms entered by millions of users is limited by the fact that query terms are not easily accessible by non-affiliated researchers. Publically available Twitter data is exploited to develop the Epidemics Outbreak and Spread Detection System (EOSDS). EOSDS provides four visual analytics tools for monitoring epidemics, i.e., Instance Map, Distribution Map, Filter Map, and Sentiment Trend to investigate public health threats in space and time. The third objective is to capture, analyze and quantify public health concerns through sentiment classifications on Twitter data. For traditional public health surveillance systems, it is hard to detect and monitor health related concerns and changes in public attitudes to health-related issues, due to their expenses and significant time delays. A two-step sentiment classification model is built to measure the concern. In the first step, Personal tweets are distinguished from Non-Personal tweets. In the second step, Personal Negative tweets are further separated from Personal Non-Negative tweets. In the proposed classification, training data is labeled by an emotion-oriented, clue-based method, and three Machine Learning models are trained and tested. Measure of Concern (MOC) is computed based on the number of Personal Negative sentiment tweets. A timeline trend of the MOC is also generated to monitor public concern levels, which is important for health emergency resource allocations and policy making. The fourth objective is predicting medical condition incidence and progression trajectories by using patients’ self-reported data on PatientsLikeMe. Some medical conditions are correlated with each other to a measureable degree (“comorbidities”). A prediction model is provided to predict the comorbidities and rank future conditions by their likelihood and to predict the possible progression trajectories given an observed medical condition. The novel models for trajectory prediction of medical conditions are validated to cover the comorbidities reported in the medical literature

The Association of Social Anxiety and Parenting Factors with Adolescent Use of Facebook

Computers and the Internet play a substantial role in how adolescents communicate with one another. Social networking websites, in particular, are a popular medium used by adolescents in which users can develop and maintain a large number of relationships from a single profile page. Facebook represents one of the most widely used social networking websites; however, little is known about the types of factors that are associated with the way in which adolescents use it. The present study examined the association of social anxiety and parenting with adolescent Facebook use. One hundred and sixty-two adolescents between the ages of 16 and 18 completed online questionnaires that measured social anxiety, Facebook use, and parenting factors (control, monitoring, and limit setting). In addition, 192 parents completed questionnaires concerning knowledge of their child\u27s Facebook use as well as their own monitoring and limit setting behaviors regarding Facebook. Contrary to what was hypothesized, results indicated that adolescents with moderate to high social anxiety were just as likely as those with little to no social anxiety to have an active Facebook account. In addition, both groups used Facebook to maintain existing relationships (as opposed to developing new ones) and they used it equally as much. A higher proportion of less socially anxious adolescents had more friends on their Facebook profile page, and this lends partial support for the rich get richer hypothesis in which more socially outgoing individuals are using Facebook to expand their existing large offline social network. With respect to parenting, fathers were significantly more controlling of their daughter\u27s behavior compared to their sons. In addition, mothers engaged in significantly more monitoring and limit setting of their child\u27s Facebook use compared to fathers. These results suggest that mothers may be taking a more active role in monitoring and regulating the online behavior of their children