Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

BACKGROUND

The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience. However, improper integration of these new technologies carries potential risks and could further exacerbate the risks posed by illicit online pharmacies by inadvertently directing users to illegal vendors.

OBJECTIVE

The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations.

METHODS

We conducted a comparative assessment of AI-generated recommendations from Google's Search Generative Experience (SGE) and Microsoft Bing's Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases.

RESULTS

Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat's and 13.23% (18/136) of Google SGE's recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%).

CONCLUSIONS

While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.

What generative AI means for trust in health communications

ABSTRACTLarge language models are fundamental technologies used in interfaces like ChatGPT and are poised to change the way people access and make sense of health information. The speed of uptake and investment suggests that these will be transformative technologies, but it is not yet clear what the implications might be for health communications. In this viewpoint, we draw on research about the adoption of new information technologies to focus on the ways that generative artificial intelligence (AI) tools like large language models might change how health information is produced, what health information people see, how marketing and misinformation might be mixed with evidence, and what people trust. We conclude that transparency and explainability in this space must be carefully considered to avoid unanticipated consequences.

Assessment and Comparison of Database Search Engines for Peptidomic Applications

Protein database search engines are an integral component of mass spectrometry-based peptidomic analyses. Given the unique computational challenges of peptidomics, many factors must be taken into consideration when optimizing search engine selection, as each platform has different algorithms by which tandem mass spectra are scored for subsequent peptide identifications. In this study, four different database search engines, PEAKS, MS-GF+, OMSSA, and X! Tandem, were compared with Aplysia californica and Rattus norvegicus peptidomics data sets, and various metrics were assessed such as the number of unique peptide and neuropeptide identifications, and peptide length distributions. Given the tested conditions, PEAKS was found to have the highest number of peptide and neuropeptide identifications out of the four search engines in both data sets. Furthermore, principal component analysis and multivariate logistic regression were employed to determine whether specific spectral features contribute to false C-terminal amidation assignments by each search engine. From this analysis, it was found that the primary features influencing incorrect peptide assignments were the precursor and fragment ion m/z errors. Finally, an assessment employing a mixed species protein database was performed to evaluate search engine precision and sensitivity when searched against an enlarged search space containing human proteins.

Innovation in Cross-Linking Mass Spectrometry Workflows: Toward a Comprehensive, Flexible, and Customizable Data Analysis Platform

Cross-linking mass spectrometry (XL-MS) is widely used in the analysis of protein structure and protein-protein interactions (PPIs). Throughout the entire workflow, the utilization of cross-linkers and the interpretation of cross-linking data are the core steps. In recent years, the development of cross-linkers and analytical software mostly follow up on the classical models of non-cleavable cross-linkers such as BS3/DSS and MS-cleavable cross-linkers such as DSSO. Although such a paradigm promotes the maturity and robustness of the XL-MS field, it confines the innovation and flexibility of new cross-linkers and analytical software. This critical insight will discuss the classification, advantages, and disadvantages of existing data analysis search engines. Take the new platinum-based metal cross-linker as an example, potential pitfalls in characterization of cross-linked peptides using existing software are discussed. Finally, ideas on developing more flexible, comprehensive, and user-friendly cross-linkers and software tools are proposed.

Image retrieval effectiveness of Bing Images, Google Images and Yahoo Image Search in the scientific field of tourism and COVID-19

The year 2020 brought a big concern for the global community because of COVID-19, which affected every sector of society, and tourism is no exception. Researchers across the globe are publishing their studies related to different dimensions of tourism in the context of COVID-19, and images have formed an essential component of their research. In tourism, images related to COVID-19 can open new dimensions for scholars. The main aim of the research is to measure the retrieval effectiveness of three image search engines (ISEs), that is, Bing Images, Google Images and Yahoo Image Search, concerning images related to COVID-19 and tourism. The study attempts to identify the capability of the ISEs to retrieve the desired and actual images related to COVID-19 and tourism. The PubMed Central (PMC) Database was consulted to retrieve the desired images and develop a testbed. The advanced search feature of PMC Database was explored by typing the search terms ‘COVID-19’ and ‘Tourism’ using ‘AND’ operator to make the search more comprehensive. Both the terms were searched against the ‘Figure/Table’ caption to retrieve papers carrying images related to COVID-19 and tourism. Queries were executed across the select ISEs, that is, Bing Images, Google Images and Yahoo Image Search. Retrieved images were individually analysed against the original image from the articles to determine the Precision, Relative Recall, F-Measure and Fallout Ratio. The format of the images in JPG/JPEG, besides checking the original image rank in the retrieved lot, was also ascertained. Bing Images scores more in terms of Mean Precision, followed by Google Images and Yahoo Image Search. For the Relative Recall measure, Google Images scores high, followed by Bing Images and Yahoo Image Search, respectively. Regarding F-Measure and Fallout Ratio, Bing Images outperforms Google Images and Yahoo Image Search. In retrieving the sought format of JPG/JPEG, Google Images performs best, followed by Yahoo Image Search and Bing Images. Google Images produces the original image at the first rank on more than one occasion. In contrast, Bing Images retrieves the original image at the first rank in two instances. Yahoo Images performs poorly over this metric as it does not retrieve any original image at the first rank on any other instance. The study cannot be generalised as the scope is only limited to the images indexed by PMC. Furthermore, the retrieval effectiveness of only three ISEs is measured. The study is the first to measure the retrieval effectiveness of ISEs in retrieving images related to the COVID-19 pandemic and tourism. The study can be extended across other image-indexing databases pertinent to tourism studies, and the retrieval effectiveness of other ISEs can also be considered.

Multiple Layers of Complexity in O-Glycosylation Illustrated With the Urinary Glycoproteome

While N-glycopeptides are relatively easy to characterize, O-glycosylation analysis is more complex. In this article, we illustrate the multiple layers of O-glycopeptide characterization that make this task so challenging. We believe our carefully curated dataset represents perhaps the largest intact human glycopeptide mixture derived from individuals, not from cell lines. The samples were collected from healthy individuals, patients with superficial or advanced bladder cancer (three of each group), and a single bladder inflammation patient. The data were scrutinized manually and interpreted using three different search engines: Byonic, Protein Prospector, and O-Pair, and the tool MS-Filter. Despite all the recent advances, reliable automatic O-glycopeptide assignment has not been solved yet. Our data reveal such diversity of site-specific O-glycosylation that has not been presented before. In addition to the potential biological implications, this dataset should be a valuable resource for software developers in the same way as some of our previously released data has been used in the development of O-Pair and O-Glycoproteome Analyzer. Based on the manual evaluation of the performance of the existing tools with our data, we lined up a series of recommendations that if implemented could significantly improve the reliability of glycopeptide assignments.

Using Search Trends to Analyze Web-Based Interest in Lower Urinary Tract Symptoms-Related Inquiries, Diagnoses, and Treatments in Mainland China: Infodemiology Study of Baidu Index Data

Background

Lower urinary tract symptoms (LUTS) are one of the most commonly described urination disorders worldwide. Previous investigations have focused predominantly on the prospective identification of cases that meet the researchers’ criteria; thus, the genuine demands regarding LUTS from patients and related issues may be neglected.

Objective

We aimed to examine web-based search trends and behaviors related to LUTS on a national and regional scale by using the dominant, major search engine in mainland China.

Methods

Baidu Index was queried by using LUTS-related terms for the period of January 2011 to September 2020. The search volume for each term was recorded to analyze search trends and demographic distributions. For user interest, user demand graph data and trend data were collected and analyzed.

Results

Of the 13 LUTS domains, 11 domains are available in the Baidu Index database. The Baidu search index for each LUTS domain varied from 37.78% to 1.47%. The search trends for urinary frequency (2011-2018: annual percent change APC=7.82%; P<.001), incomplete emptying (2011-2014: APC=17.74%; P<.001), nocturia (2011-2018: APC=11.54%; P<.001), dysuria (2017-2020: APC=20.77%; P<.001), and incontinence (2011-2016: APC=13.39%; P<.001) exhibited fluctuations over time. The search index trends for weak stream (2011-2017: APC=−4.68%; P<.001; 2017-2020: APC=9.32%; P=.23), split stream (2011-2013: APC=9.50%; P=.44; 2013-2020: APC=2.05%; P=.71), urgency (2011-2018: APC=−2.63%; P=.03; 2018-2020: APC=8.58%; P=.19), and nocturnal enuresis (2011-2018: APC=−3.20%; P=.001; 2018-2020: APC=−4.21%; P=.04) remained relatively stable and consistent. The age distribution of the population for all LUTS-related inquiries showed that individuals aged 20 to 40 years made 73.86% (49,218,123/66,635,247) of the total search inquiries. Further, individuals aged 40 to 49 years made 12.29% (8,193,922/66,635,247) of the total search inquiries for all LUTS-related terms. People from the east part of China made 67.79% (45,172,031/66,635,247) of the total search queries. Additionally, most of the searches for LUTS-related terms were related to those for urinary diseases to varying degrees.

Conclusions

Web-based interest in LUTS-related terms fluctuated wildly and was reflected timely by Baidu Index in mainland China. The web-based search popularity of each LUTS-related term varied significantly and differed based on personal interests, the population’s concerns, regional variations, and gender. These data can be used by care providers to track the prevalence of LUTS and the population’s interests, guide the establishment of disease-specific health care policies, and optimize physician-patient health care sessions.

Detecting Impending Stroke From Cognitive Traits Evident in Internet Searches: Analysis of Archival Data

Background

Cerebrovascular disease is a leading cause of mortality and disability. Common risk assessment tools for stroke are based on the Framingham equation, which relies on traditional cardiovascular risk factors to predict an acute event in the near decade. However, no tools are currently available to predict a near/impending stroke, which might alert patients at risk to seek immediate preventive action (eg, anticoagulants for atrial fibrillation, control of hypertension).

Objective

Here, we propose that an algorithm based on internet search queries can identify people at increased risk for a near stroke event.

Methods

We analyzed queries submitted to the Bing search engine by 285 people who self-identified as having undergone a stroke event and 1195 controls with regard to attributes previously shown to reflect cognitive function. Controls included random people 60 years and above, or those of similar age who queried for one of nine control conditions.

Results

The model performed well against all comparator groups with an area under the receiver operating characteristic curve of 0.985 or higher and a true positive rate (at a 1% false-positive rate) above 80% for separating patients from each of the controls. The predictive power rose as the stroke date approached and if data were acquired beginning 120 days prior to the event. Good prediction accuracy was obtained for a prospective cohort of users collected 1 year later. The most predictive attributes of the model were associated with cognitive function, including the use of common queries, repetition of queries, appearance of spelling mistakes, and number of queries per session.

Conclusions

The proposed algorithm offers a screening test for a near stroke event. After clinical validation, this algorithm may enable the administration of rapid preventive intervention. Moreover, it could be applied inexpensively, continuously, and on a large scale with the aim of reducing stroke events.

Integrity of Databases for Literature Searches in Nursing: Avoiding Predatory Journals

The quality of literature used as the foundation to any research or scholarly project is critical. The purpose of this study was to analyze the extent to which predatory nursing journals were included in credible databases, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Scopus, commonly used by nurse scholars when searching for information. Findings indicated that no predatory nursing journals were currently indexed in MEDLINE or CINAHL, and only one journal was in Scopus. Citations to articles published in predatory nursing journals are not likely found in a search using these curated databases but rather through Google or Google Scholar search engines.

Ethical Challenges and Opportunities Associated With the Ability to Perform Medical Screening From Interactions With Search Engines: Viewpoint

Recent research has shown the efficacy of screening for serious medical conditions from data collected while people interact with online services. In particular, queries to search engines and the interactions with them were shown to be advantageous for screening a range of conditions including diabetes, several forms of cancer, eating disorders, and depression. These screening abilities offer unique advantages in that they can serve a broad strata of the society, including people in underserved populations and in countries with poor access to medical services. However, these advantages need to be balanced against the potential harm to privacy, autonomy, and nonmaleficence, which are recognized as the cornerstones of ethical medical care. Here, we discuss these opportunities and challenges, both when collecting data to develop online screening services and when deploying them. We offer several solutions that balance the advantages of these services with the ethical challenges they pose.

Real-World Evidence on the Effect of Missing an Oral Contraceptive Dose: Analysis of Internet Search Engine Queries

Background

Oral contraceptives (OCs) are a unique chronic medication with which a memory slip may result in a threat that could change a person’s life course. Subjective concerns of missed OC doses among women have been addressed infrequently. Anonymized queries to internet search engines provide unique access to concerns and information gaps faced by a large number of internet users.

Objective

We aimed to quantitate the frequency of queries by women seeking information in an internet search engine, after missing one or more doses of an OC; their further queries on emergency contraception, abortion, and miscarriage; and their rate of reporting a pregnancy timed to the cycle of missing an OC.

Methods

We extracted all English-language queries submitted to Bing in the United States during 2018, which mentioned a missed OC and subsequent queries of the same users on miscarriage, abortion, emergency contraceptives, and week of pregnancy.

Results

We identified 26,395 Bing users in the United States who queried about missing OC pills and the fraction that further queried about miscarriage, abortion, emergency contraceptive, and week of pregnancy. Users under the age of 30 years who asked about forgetting an OC dose were more likely to ask about abortion (1.5 times) and emergency contraception (1.7 times) (P<.001 for both), while users at ages of 30-34 years were more likely to query about pregnancy (2.1 times) and miscarriage (5.4 times) (P<.001 for both).

Conclusions

Our data indicate that many women missing a dose of OC might not have received sufficient information from their health care providers or chose to obtain it online. Queries about abortion and miscarriage peaking in the subsequent days indicate a common worry of possible pregnancy. These results reinforce the importance of providing comprehensive written information on missed pills when prescribing an OC.

Online Information of Vaccines: Information Quality, Not Only Privacy, Is an Ethical Responsibility of Search Engines

The fact that Internet companies may record our personal data and track our online behavior for commercial or political purpose has emphasized aspects related to online privacy. This has also led to the development of search engines that promise no tracking and privacy. Search engines also have a major role in spreading low-quality health information such as that of anti-vaccine websites. This study investigates the relationship between search engines' approach to privacy and the scientific quality of the information they return. We analyzed the first 30 webpages returned searching "vaccines autism" in English, Spanish, Italian, and French. The results show that not only "alternative" search engines (Duckduckgo, Ecosia, Qwant, Swisscows, and Mojeek) but also other commercial engines (Bing, Yahoo) often return more anti-vaccine pages (10-53%) than Google.com (0%). Some localized versions of Google, however, returned more anti-vaccine webpages (up to 10%) than Google.com. Health information returned by search engines has an impact on public health and, specifically, in the acceptance of vaccines. The issue of information quality when seeking information for making health-related decisions also impact the ethical aspect represented by the right to an informed consent. Our study suggests that designing a search engine that is privacy savvy and avoids issues with filter bubbles that can result from user-tracking is necessary but insufficient; instead, mechanisms should be developed to test search engines from the perspective of information quality (particularly for health-related webpages) before they can be deemed trustworthy providers of public health information.

Translating Clinical Questions by Physicians Into Searchable Queries: Analytical Survey Study

BACKGROUND

Staying up to date and answering clinical questions with current best evidence from health research is challenging. Evidence-based clinical texts, databases, and tools can help, but clinicians first need to translate their clinical questions into searchable queries. MacPLUS FS (McMaster Premium LiteratUre Service Federated Search) is an online search engine that allows clinicians to explore multiple resources simultaneously and retrieves one single output that includes the following: (1) evidence from summaries (eg, UpToDate and DynaMed), (2) preappraised research (eg, EvidenceAlerts), and (3) non-preappraised research (eg, PubMed), with and without validated bibliographic search filters. MacPLUS FS can also be used as a laboratory to explore clinical questions and evidence retrieval.

OBJECTIVE

Our primary objective was to examine how clinicians formulate their queries on a federated search engine, according to the population, intervention, comparison, and outcome (PICO) framework. Our secondary objective was to assess which resources were accessed by clinicians to answer their questions.

METHODS

We performed an analytical survey among 908 clinicians who used MacPLUS FS in the context of a randomized controlled trial on search retrieval. Recording account log-ins and usage, we extracted all 1085 queries performed during a 6-month period and classified each search term according to the PICO framework. We further categorized queries into background (eg, "What is porphyria?") and foreground questions (eg, "Does treatment A work better than B?"). We then analyzed the type of resources that clinicians accessed.

RESULTS

There were 695 structured queries, after exclusion of meaningless queries and iterations of similar searches. We classified 56.5% (393/695) of these queries as background questions and 43.5% (302/695) as foreground questions, the majority of which were related to questions about therapy (213/695, 30.6%), followed by diagnosis (48/695, 6.9%), etiology (24/695, 3.5%), and prognosis (17/695, 2.5%). This distribution did not significantly differ between postgraduate residents and medical faculty physicians (P=.51). Queries included a median of 3 search terms (IQR 2-4), most often related to the population and intervention or test, rarely related to the outcome, and never related to the comparator. About half of the resources accessed (314/610, 51.5%) were summaries, 24.4% (149/610) were preappraised research, and 24.1% were (147/610) non-preappraised research.

CONCLUSIONS

Our results, from a large sample of real-life queries, could guide the development of educational interventions to improve clinicians' retrieval skills, as well as inform the design of more useful evidence-based resources for clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02038439; https://www.clinicaltrials.gov/ct2/show/NCT02038439.

Dr. Google Will See You Now: Google's Health Information Previews and Implications for Consumer Health

The aim of this exploratory study was to identify the sources of information provided in Google preview features, specifically the knowledge panels and featured snippets, when searching for health information online, with the goal of informing the development of consumer health programs and materials. In a search of the top ten health-related Google searches of 2018, the quality of information sources in the preview content varied both within and between sources. Librarians' knowledge of how a Google search responds to health inquiries of local interest can help them fill in gaps and curate or create more informative health materials for consumers.

Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data

Background

Surveys suggest that a large proportion of people use the internet to search for information on medical symptoms they experience and that around one-third of the people in the United States self-diagnose using online information. However, surveys are known to be biased, and the true rates at which people search for information on their medical symptoms before receiving a formal medical diagnosis are unknown.

Objective

This study aimed to estimate the rate at which people search for information on their medical symptoms before receiving a formal medical diagnosis by a health professional.

Methods

We collected queries made on a general-purpose internet search engine by people in the United States who self-identified their diagnosis from 1 of 20 medical conditions. We focused on conditions that have evident symptoms and are neither screened systematically nor a part of usual medical care. Thus, they are generally diagnosed after the investigation of specific symptoms. We evaluated how many of these people queried for symptoms associated with their medical condition before their formal diagnosis. In addition, we used a survey questionnaire to assess the familiarity of laypeople with the symptoms associated with these conditions.

Results

On average, 15.49% (1792/12,367, SD 8.4%) of people queried about symptoms associated with their medical condition before receiving a medical diagnosis. A longer duration between the first query for a symptom and the corresponding diagnosis was correlated with an increased likelihood of people querying about those symptoms (rho=0.6; P=.005); similarly, unfamiliarity with the association between a condition and its symptom was correlated with an increased likelihood of people querying about those symptoms (rho=−0.47; P=.08). In addition, worrying symptoms were 14% more likely to be queried about.

Conclusions

Our results indicate that there is large variability in the percentage of people who query the internet for their symptoms before a formal medical diagnosis is made. This finding has important implications for systems that attempt to screen for medical conditions.

Impact of Illness on Electronic Health Use (The Seventh Tromsø Study - Part 2): Population-Based Questionnaire Study

Background

Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases.

Objective

The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources.

Methods

Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 7854 (7854/21,083; 37.25%) participants reported to have used some kind of eHealth resource in the last year and suffered (or had suffered) from some kind of specified disease. Logistic regression was used to determine which diseases significantly predicted the use of each eHealth resource.

Results

The use of apps was increased among those individuals that (had) suffered from psychological problems (odds ratio [OR] 1.39, 95% CI 1.23-1.56) and cardiovascular diseases (OR 1.12, 95% CI 1.01-1.24) and those part-time workers that (had) suffered from any of the diseases classified as others (OR 2.08, 95% CI 1.35-3.32). The use of search engines for accessing health information increased among individuals who suffered from psychological problems (OR 1.39, 95% CI 1.25-1.55), cancer (OR 1.26, 95% CI 1.11-1.44), or any of the diseases classified as other diseases (OR 1.27, 95% CI 1.13-1.42). Regarding video services, their use for accessing health information was more likely when the participant was a man (OR 1.31, 95% CI 1.13-1.53), (had) suffered from psychological problems (OR 1.70, 95% CI 1.43-2.01), or (had) suffered from other diseases (OR 1.43, 95% CI 1.20-1.71). The factors associated with an increase in the use of social media for accessing health information were as follows: (had) suffered from psychological problems (OR 1.65, 95% CI 1.42-1.91), working part time (OR 1.35, 95% CI 0.62-2.63), receiving disability benefits (OR 1.42, 95% CI 1.14-1.76), having received an upper secondary school education (OR 1.20, 95% CI 1.03-1.38), being a man with a high household income (OR 1.67, 95% CI 1.07-2.60), suffering from cardiovascular diseases and having a high household income (OR 3.39, 95% CI 1.62-8.16), and suffering from respiratory diseases while being retired (OR 1.95, 95% CI 1.28-2.97).

Conclusions

Our findings show that different diseases are currently associated with the use of different eHealth resources. This knowledge is useful for those who plan eHealth interventions as they can take into account which type of eHealth resource may be used for gaining the attention of the different user groups.

Evaluating the Understandability and Actionability of Web-Based Education Materials for Patients Taking Non-vitamin K Oral Anticoagulants

BACKGROUND

More patients are now taking high-risk medicines such as non-vitamin K oral anticoagulants (NOACs). Hence, patient education materials need to be in an understandable format so that they can be empowered to act on their knowledge. Factors such as health literacy and the design of the medicine information material may influence the patient's ability to understand and act on key information.

METHOD

The PRISMA checklist was used to inform the study design. A structured search was conducted to obtain all freely accessible online educational resources designed for patients about the non-vitamin K antagonists (NOACs) during August 2018. Three search engines were used: Google, Yahoo! and Bing, using the search terms "NOAC" and "anticoagulant" combined with "patient/consumer information and patient/consumer resources."We applied the Patient Education Materials Assessment Tool (PEMAT) to evaluate web-based patient education materials in terms of understandability and actionability for patients taking NOACs.

RESULTS

Of the 35 materials included, the majority of the materials (n = 32, 91%) were rated as highly understandable (PEMAT score ≥70%), and more than three-quarters of all the materials (n = 29, 83%) were rated as poorly actionable (PEMAT score <70%). For understandability, the majority of materials neither provided a summary of the key points nor used visual aids for several items such as simple tables, illustrations, and photographs. For actionability, few materials provided a tangible tool, such as a checklist, to prompt the user into action (n = 4). Few used visual aids such as nonverbal cues to the written instructions (n = 4).

CONCLUSION

To improve the understandability and actionability of most of the NOAC patient education materials, there is a need to include more summaries of information, visual aids, and tangible tools such as checklists. Further research is warranted where patients are involved in providing feedback on the design of medicine information materials for NOACs.

Do Search Engine Helpline Notices Aid in Preventing Suicide? Analysis of Archival Data

Background

Search engines display helpline notices when people query for suicide-related information.

Objective

In this study, we aimed to examine if these notices and other information displayed in response to suicide-related queries are correlated with subsequent searches for suicide prevention rather than harmful information.

Methods

Anonymous suicide-related searches made on Bing and Google in the United States, the United Kingdom, Hong Kong, and Taiwan in a span of 10 months were extracted. Descriptive analyses and regression models were fit to the data to assess the correlation with observed behaviors.

Results

Display of helpline notices was not associated with an observed change in the likelihood of or future suicide searches (P=.42). No statistically significant differences were observed in the likelihood of people making future suicide queries (both generally and specific types of suicide queries) when comparing search engines in locations that display helpline notices versus ones that do not. Pages with higher rank, being neutral to suicide, and those shown among more antisuicide pages were more likely to be clicked on. Having more antisuicide Web pages displayed was the only factor associated with further searches for suicide prevention information (hazard=1.18, P=.002).

Conclusions

Helpline notices are not associated with harm. If they cause positive change in search behavior, it is small. This is possibly because of the variability in intent of users seeking suicide-related information. Nonetheless, helpline notice should be displayed, but more efforts should be made to improve the visibility and ranking of suicide prevention Web pages.

SearchGUI: A Highly Adaptable Common Interface for Proteomics Search and de Novo Engines

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

The variation in quality and content of patient-focused health information on the Internet for otitis media

BACKGROUND

When symptoms of otitis media appear, parents and patients often access the Internet for health information. We study the content and quality of health information in parent-patient-focused websites for otitis media.

METHODS

We searched the 3 search engines (Google, Yahoo, and Bing) using "otitis media" and "middle ear infection" then reviewed the top 30 hits for each search. We included sites that were focused on providing patient-patient information about otitis media. A variety of instruments were used to assess website content and quality.

RESULTS

In 35 included websites, there was considerable variation in content, with the average site having 11 out of 15 informational items potentially useful to parents and patients on otitis media (range 4-15). Across included websites, the mean DISCERN score was 47 out of 80 (low to medium quality), 16 (46%) were HONcode certified, and 8 (23%) fulfilled all the JAMA benchmark criteria. The average website was written at a 9th/10th-grade reading level.

CONCLUSION

The content and quality of health information for otitis media in parent-and-patient-focused websites is highly variable. Although easy-to-read, high-quality websites with complete content are available, the average website sites is difficult to read without a high school education and is difficult to use. Consideration should be given to adopting a standard approach for presenting disease-specific information to parents and patients.

Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries

Background

Cannabis is one of the most widely used psychoactive substances worldwide, but adverse drug reactions (ADRs) associated with its use are difficult to study because of its prohibited status in many countries.

Objective

Internet search engine queries have been used to investigate ADRs in pharmaceutical drugs. In this proof-of-concept study, we tested whether these queries can be used to detect the adverse reactions of cannabis use.

Methods

We analyzed anonymized queries from US-based users of Bing, a widely used search engine, made over a period of 6 months and compared the results with the prevalence of cannabis use as reported in the US National Survey on Drug Use in the Household (NSDUH) and with ADRs reported in the Food and Drug Administration’s Adverse Drug Reporting System. Predicted prevalence of cannabis use was estimated from the fraction of people making queries about cannabis, marijuana, and 121 additional synonyms. Predicted ADRs were estimated from queries containing layperson descriptions to 195 ICD-10 symptoms list.

Results

Our results indicated that the predicted prevalence of cannabis use at the US census regional level reaches an R² of .71 NSDUH data. Queries for ADRs made by people who also searched for cannabis reveal many of the known adverse effects of cannabis (eg, cough and psychotic symptoms), as well as plausible unknown reactions (eg, pyrexia).

Conclusions

These results indicate that search engine queries can serve as an important tool for the study of adverse reactions of illicit drugs, which are difficult to study in other settings.

ClinicalKey 2.0: Upgrades in a Point-of-Care Search Engine

ClinicalKey 2.0, launched September 23, 2014, offers a mobile-friendly design with a search history feature for targeting point-of-care resources for health care professionals. Browsing is improved with searchable, filterable listings of sources highlighting new resources. ClinicalKey 2.0 improvements include more than 1,400 new Topic Pages for quick access to point-of-care content. A sample search details some of the upgrades and content options.

What Searches Do Users Run on PEDro? An Analysis of 893,971 Search Commands Over a 6-Month Period

BACKGROUND

Clinicians must be able to search effectively for relevant research if they are to provide evidence-based healthcare. It is therefore relevant to consider how users search databases of evidence in healthcare, including what information users look for and what search strategies they employ. To date such analyses have been restricted to the PubMed database. Although the Physiotherapy Evidence Database (PEDro) is searched millions of times each year, no studies have investigated how users search PEDro.

OBJECTIVES

To assess the content and quality of searches conducted on PEDro.

METHODS

Searches conducted on the PEDro website over 6 months were downloaded and the 'get' commands and page-views extracted. The following data were tabulated: the 25 most common searches; the number of search terms used; the frequency of use of simple and advanced searches, including the use of each advanced search field; and the frequency of use of various search strategies.

RESULTS

Between August 2014 and January 2015, 893,971 search commands were entered on PEDro. Fewer than 18 % of these searches used the advanced search features of PEDro. 'Musculoskeletal' was the most common subdiscipline searched, while 'low back pain' was the most common individual search. Around 20 % of all searches contained errors.

CONCLUSIONS

PEDro is a commonly used evidence resource, but searching appears to be sub-optimal in many cases. The effectiveness of searches conducted by users needs to improve, which could be facilitated by methods such as targeted training and amending the search interface.

Pediatric Care Online: A Pediatric Point-of-Care Tool

Pediatric Care Online is the American Academy of Pediatrics' point-of-care tool designed for health care providers. Pediatric Care Online builds on content from Red Book Online and Pediatric Patient Education and features Quick Reference topic pages for more than 250 pediatric health care topics. The multitude of resources available within Pediatric Care Online will be reviewed in this column, and a sample search will be used to illustrate the type of information available within this point-of-care pediatric resource.

Rare disease diagnosis: A review of web search, social media and large-scale data-mining approaches

Physicians and the general public are increasingly using web-based tools to find answers to medical questions. The field of rare diseases is especially challenging and important as shown by the long delay and many mistakes associated with diagnoses. In this paper we review recent initiatives on the use of web search, social media and data mining in data repositories for medical diagnosis. We compare the retrieval accuracy on 56 rare disease cases with known diagnosis for the web search tools google.com, pubmed.gov, omim.org and our own search tool findzebra.com. We give a detailed description of IBM's Watson system and make a rough comparison between findzebra.com and Watson on subsets of the Doctor's dilemma dataset. The recall@10 and recall@20 (fraction of cases where the correct result appears in top 10 and top 20) for the 56 cases are found to be be 29%, 16%, 27% and 59% and 32%, 18%, 34% and 64%, respectively. Thus, FindZebra has a significantly (p < 0.01) higher recall than the other 3 search engines. When tested under the same conditions, Watson and FindZebra showed similar recall@10 accuracy. However, the tests were performed on different subsets of Doctors dilemma questions. Advances in technology and access to high quality data have opened new possibilities for aiding the diagnostic process. Specialized search engines, data mining tools and social media are some of the areas that hold promise.

ClinicalAccess: a clinical decision support tool

ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines.

An Improved Forensic Science Information Search

Although thousands of search engines and databases are available online, finding answers to specific forensic science questions can be a challenge even to experienced Internet users. Because there is no central repository for forensic science information, and because of the sheer number of disciplines under the forensic science umbrella, forensic scientists are often unable to locate material that is relevant to their needs. The author contends that using six publicly accessible search engines and databases can produce high-quality search results. The six resources are Google, PubMed, Google Scholar, Google Books, WorldCat, and the National Criminal Justice Reference Service. Carefully selected keywords and keyword combinations, designating a keyword phrase so that the search engine will search on the phrase and not individual keywords, and prompting search engines to retrieve PDF files are among the techniques discussed.

The effects of preference for information on consumers' online health information search behavior

BACKGROUND

Preference for information is a personality trait that affects people's tendency to seek information in health-related situations. Prior studies have focused primarily on investigating its impact on patient-provider communication and on the implications for designing information interventions that prepare patients for medical procedures. Few studies have examined its impact on general consumers' interactions with Web-based search engines for health information or the implications for designing more effective health information search systems.

OBJECTIVE

This study intends to fill this gap by investigating the impact of preference for information on the search behavior of general consumers seeking health information, their perceptions of search tasks (representing information needs), and user experience with search systems.

METHODS

Forty general consumers who had previously searched for health information online participated in the study in our usability lab. Preference for information was measured using Miller's Monitor-Blunter Style Scale (MBSS) and the Krantz Health Opinion Survey-Information Scale (KHOS-I). Each participant completed four simulated health information search tasks: two look-up (fact-finding) and two exploratory. Their behaviors while interacting with the search systems were automatically logged and ratings of their perceptions of tasks and user experience with the systems were collected using Likert-scale questionnaires.

RESULTS

The MBSS showed low reliability with the participants (Monitoring subscale: Cronbach alpha=.53; Blunting subscale: Cronbach alpha=.35). Thus, no further analyses were performed based on the scale. KHOS-I had sufficient reliability (Cronbach alpha=.77). Participants were classified into low- and high-preference groups based on their KHOS-I scores. The high-preference group submitted significantly shorter queries when completing the look-up tasks (P=.02). The high-preference group made a significantly higher percentage of parallel movements in query reformulation than did the low-preference group (P=.04), whereas the low-preference group made a significantly higher percentage of new concept movements than the high-preference group when completing the exploratory tasks (P=.01). The high-preference group found the exploratory tasks to be significantly more difficult (P=.05) and the systems to be less useful (P=.04) than did the low-preference group.

CONCLUSIONS

Preference for information has an impact on the search behavior of general consumers seeking health information. Those with a high preference were more likely to use more general queries when searching for specific factual information and to develop more complex mental representations of health concerns of an exploratory nature and try different combinations of concepts to explore these concerns. High-preference users were also more demanding on the system. Health information search systems should be tailored to fit individuals' information preferences.

Specialized tools are needed when searching the web for rare disease diagnoses

In our recent paper, we study web search as an aid in the process of diagnosing rare diseases. To answer the question of how well Google Search and PubMed perform, we created an evaluation framework with 56 diagnostic cases and made our own specialized search engine, FindZebra (findzebra.com). FindZebra uses a set of publicly available curated sources on rare diseases and an open-source information retrieval system, Indri. Our evaluation and the feedback received after the publication of our paper both show that FindZebra outperforms Google Search and PubMed. In this paper, we summarize the original findings and the response to FindZebra, discuss why Google Search is not designed for specialized tasks and outline some of the current trends in using web resources and social media for medical diagnosis.

Dynamic searching in the brain

Cognitive functions rely on the extensive use of information stored in the brain, and the searching for the relevant information for solving some problem is a very complex task. Human cognition largely uses biological search engines, and we assume that to study cognitive function we need to understand the way these brain search engines work. The approach we favor is to study multi-modular network models, able to solve particular problems that involve searching for information. The building blocks of these multimodular networks are the context dependent memory models we have been using for almost 20 years. These models work by associating an output to the Kronecker product of an input and a context. Input, context and output are vectors that represent cognitive variables. Our models constitute a natural extension of the traditional linear associator. We show that coding the information in vectors that are processed through association matrices, allows for a direct contact between these memory models and some procedures that are now classical in the Information Retrieval field. One essential feature of context-dependent models is that they are based on the thematic packing of information, whereby each context points to a particular set of related concepts. The thematic packing can be extended to multimodular networks involving input-output contexts, in order to accomplish more complex tasks. Contexts act as passwords that elicit the appropriate memory to deal with a query. We also show toy versions of several 'neuromimetic' devices that solve cognitive tasks as diverse as decision making or word sense disambiguation. The functioning of these multimodular networks can be described as dynamical systems at the level of cognitive variables.

The journal of undergraduate neuroscience education: history, challenges, and future developments

The 'JUNE and You' sessions presented at the July 2008 Undergraduate Neuroscience Education workshop, sponsored jointly by Faculty for Undergraduate Neuroscience (FUN) and Project Kaleidoscope (PKAL), featured background information about the history and mission of the Journal of Undergraduate Neuroscience Education (JUNE), followed by an informative discussion about the challenges facing JUNE, including new ideas for future developments. This article will highlight some of the information and ideas generated and shared at this conference. Critical discussion points included the need to keep members of FUN actively engaged in submitting and reviewing articles for JUNE. Ways in which authors, reviewers, and interested faculty members could best help in promoting the mission and vision of JUNE were discussed. Concerns about recent hackings into the JUNE website were also raised, and possible solutions and measures that can be taken to minimize this in the future were discussed. In addition, ideas for expanding the role of JUNE to provide a forum to evaluate new and emerging website information that is pertinent to undergraduate neuroscience education was discussed. Ideas for future developments of JUNE included revolving postings of articles as they are accepted, providing links to several related websites, and allowing updates for articles that have been previously published in JUNE. Finally, ideas for maintaining and expanding JUNE's stature as the resource for undergraduate neuroscience education included ensuring that JUNE is listed on important search vehicles, such as PubMed.

Investigating the Roles of Knowledge and Cognitive Abilities in Older Adult Information Seeking on the Web

This study investigated the influences of knowledge, particularly Internet, Web browser, and search engine knowledge, as well as cognitive abilities on older adult information seeking on the Internet. The emphasis on aspects of cognition was informed by a modeling framework of search engine information-seeking behavior. Participants from two older age groups were recruited: twenty people in a younger-old group (ages 60-70) and twenty people in an older-old group (ages 71-85). Ten younger adults (ages 18-39) served as a comparison group. All participants had at least some Internet search experience. The experimental task consisted of six realistic search problems, all involving information related to health and well-being and which varied in degree of complexity. The results indicated that though necessary, Internet-related knowledge was not sufficient in explaining information-seeking performance, and suggested that a combination of both knowledge and key cognitive abilities is important for successful information seeking. In addition, the cognitive abilities that were found to be critical for task performance depended on the search problem's complexity. Also, significant differences in task performance between the younger and the two older age groups were found on complex, but not on simple problems. Overall, the results from this study have implications for instructing older adults on Internet information seeking and for the design of Web sites.

Searching the web: toward maximizing relevance

Searching for information on the Web is paradoxically easy but frustrating. There is an increasingly vast amount of high-quality information available on the Internet, but finding it can seem like groping through the world's largest haystack for the proverbial needle. This review discusses some of the most basic and important methods and techniques, (table 1) applicable to almost any search using almost any search engine, whose thoughtful application ensures that the information found is both high-quality and relevant.

Doctors, patients and the Internet: time to grasp the nettle

The Internet, the fastest growing technology in society, has been driven by the public's hunger for fast, cheap communication. The modern patient increasingly presents to their doctor with an Internet diagnosis and treatment plan, obtained from a website with inaccurate or highly biased information. Doctors have limited access to the Internet in the workplace and often find it difficult to answer specific medical questions using routine search engines. The Internet provides an unparalleled opportunity to revolutionise medical education, bedside decision-making, patient records and communication between professionals and patients. Coordination between government, the Royal Colleges and the healthcare industry is required to develop the necessary software and hardware to help doctors and patients use the Internet to their advantage.

Some benchmark searches for testing search capabilities and medical coverage of internet discovery tools

The past few years have seen a proliferation of search engines for the World Wide Web (WWW), as well as a growing number of specialized subject directories geared to the needs of health care professionals. Yet documentation on scope, coverage, and search features is often uneven at best; and even documented search features may not perform as advertised. This paper will present a group of sample searches to assist users in gauging database size, determining default search operators, and testing for the presence of advanced search features such as case sensitivity, stemming, and concept mapping for medical topics on English-language web sites.