Bing Search Engine Research Articles

Quality Assessment and Review of Online Information relating to Third Molar Pain and Removal

##Statement of the problem: Dental professionals have embraced the internet as a means to enhance patient care and optimise access to dental services. However, dental information present on the internet is unregulated and varies in quality, accuracy and readability. ##Purpose of the study: This paper aims to assess the quality of the information online relating to third molars. Materials and methods: Two key terms (wisdom tooth pain and wisdom tooth extraction) were entered into Google, Yahoo and Bing search engines. Websites were assessed using the DISCERN and the HoNCode instruments. ##Results: A total of 60 websites were assessed. 2 websites were excluded in accordance with the exclusion criteria and 15 duplicate websites were excluded, leaving 43 unique sites. In the websites addressing “wisdom tooth pain” the average HoNCode score awarded was 40% (range 13-72%) while the average DISCERN score awarded was 43(range 24-70). In the websites addressing “wisdom tooth extraction” the average HoNCode score awarded was 35%(range 15-75%) while the average DISCERN score awarded was 35(range 25-69). ##Conclusions: The overall quality of the websites assessed is fair. This result shows that the reasonable patient may be misinformed by Internet sources on material risks. Clinicians should be aware of tools such as DISCERN and HoNCode and utilise them in the development of online content for their own practice.

Scoping review: Alternatives to self-harm recommended on mental health self-help websites.

Less than half of all young people with mental health difficulties will seek professional treatment. Due to the private nature of self-harm it is estimated that only 1:28 young males and 1:18 young females who self-harm ever present to hospital. Self-help supports improved coping strategies and life changes without reliance on a clinical intervention which could be used to reduce self-harming behaviours. The study objective is to review self-help alternatives to self-harm on mental health websites that can be accessed by young people. Google, Bing, and Yahoo search engines were used to search for appropriate websites. Eighty-two unique websites on mental health were identified, of which 55 met the inclusion criteria. A total of 1177 self-help suggestions were found for those struggling with self-harm urges. The average number of suggestions per site was 42 (Range 3-252). The main techniques suggested were: seeking social contact/help, physical activity, displacement/mimicking techniques, relaxing/comforting techniques, sensory techniques, fun/diverting techniques, aggressive techniques, creative/reflective techniques. This review found not all strategies were suitable for young people and that the large number of possible strategies could be challenging for a young person to navigate. However, mental health self-help websites were generally of high quality and gave a range of potentially helpful strategies. The categories created from this review could be used as a guide to consider with the young person when making an individualized self-help plan to manage self-harm urges. Further research is required to assess if and how these techniques could be used individually or in combination to reduce self-harm.

Quality of online information for the general public on familial hypercholesterolaemia

Objective: This study aimed to assess the quality and readability of web-based information on familial hypercholesterolaemia. Design, setting and methods: Internet searches using the terms ‘familial hypercholesterolemia’, ‘hypercholesterolemia’, ‘inherited high cholesterol’, ‘hereditary high cholesterol’ and ‘inherited high LDL’ were conducted with the Google, Yahoo! and Bing search engines using default settings during August 2021. The first 50 web links that appeared using each search engine were evaluated using the Flesch Reading Ease Score (FRES) and DISCERN instrument for readability and the quality of the website. The LIDA tool was used to assess reliability and usability. Results: In all, 750 websites were accessed and 38 websites were included in the analysis. The majority of the websites (29, 76.3%) were owned by non-governmental institutions. Twelve (30.8%) websites were certified by the Health On the Net Foundation (HON) code of conduct. Only 17 websites (44.7%) had a stated author. Twenty-nine (76.3%) websites had a stated date of publication. Only 16 (42.1%) provided references for the statements made. Infographics were used in 17 (44.7%) websites. The median FRES was 47.15 (range: 22.3–91.8), which is equivalent to college-level readability. The median LIDA usability and reliability score was 38.00 (range: 25–46) and 15.00 (range: 7–24), respectively. The median DISCERN score was 45.00 (range: 17–76). The DISCERN score was significantly associated with the FRES (0.047) and whether the website was governmental or not (0.028). Conclusion: According to this study, the readability, reliability, usability and quality of the majority of websites were inadequate. Due to the rapid growth in the use of the Internet, steps need to be taken to standardise and regulate patient education websites for this and perhaps other health conditions.

Causal Inference in the Presence of Interference in Sponsored Search Advertising

In classical causal inference, inferring cause-effect relations from data relies on the assumption that units are independent and identically distributed. This assumption is violated in settings where units are related through a network of dependencies. An example of such a setting is ad placement in sponsored search advertising, where the likelihood of a user clicking on a particular ad is potentially influenced by where it is placed and where other ads are placed on the search result page. In such scenarios, confounding arises due to not only the individual ad-level covariates but also the placements and covariates of other ads in the system. In this paper, we leverage the language of causal inference in the presence of interference to model interactions among the ads. Quantification of such interactions allows us to better understand the click behavior of users, which in turn impacts the revenue of the host search engine and enhances user satisfaction. We illustrate the utility of our formalization through experiments carried out on the ad placement system of the Bing search engine.

Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming

Given a network and a subset of interesting vertices whose identities are only partially known, the vertex nomination problem seeks to rank the remaining vertices in such a way that the interesting vertices are ranked at the top of the list. An important variant of this problem is vertex nomination in the multiple graphs setting. Given two graphs G 1, G 2 with common vertices and a vertex of interest , we wish to rank the vertices of G 2 such that the vertices most similar to x are ranked at the top of the list. The current article addresses this problem and proposes a method that first applies adjacency spectral graph embedding to embed the graphs into a common Euclidean space, and then solves a penalized linear assignment problem to obtain the nomination lists. Since the spectral embedding of the graphs are only unique up to orthogonal transformations, we present two approaches to eliminate this potential nonidentifiability. One approach is based on orthogonal Procrustes and is applicable when there are enough vertices with known correspondence between the two graphs. Another approach uses adaptive point set registration and is applicable when there are few or no vertices with known correspondence. We show that our nomination scheme leads to accurate nomination under a generative model for pairs of random graphs that are approximately low-rank and possibly with pairwise edge correlations. We illustrate our algorithm’s performance through simulation studies on synthetic data as well as analysis of a high-school friendship network and analysis of transition rates between web pages on the Bing search engine. Supplementary materials for this article are available and include R code, data, and an appendix with detailed proofs.

Intimate Partner Violence as Reflected in Internet Search Data

Intimate partner violence (IPV) is a major public health concern with serious consequences for victims’ physical and mental health. Despite the high prevalence of IPV, describing it and detecting people suffering from it is difficult due to its sensitive nature and stigma associated with it. Existing tools for screening and tracking IPV victims are laborious, time-consuming, expensive, and require human supervision. Search engine data has previously been shown to provide insights into temporal behavioral information about millions of users who are truthful in their information seeking. Here, we present a large-scale analysis of individuals experiencing IPV providing insights into their characteristics and behavior. We extracted the queries from Bing search engine data of more than 50 thousand US-based individuals suffering from IPV. We provide insights into the differences among subpopulations of people experiencing IPV and the topics they search for. We find that approximately half of the users begin to search for IPV following an acute event (physical violence or abuse) and 20% of users actively hide their interest in IPV. Users typically begin to seek help 3 weeks after beginning to query about IPV. The topics of interest to people experience IPV include the effects of IPV, help seeking, and methods to escape from IPV. Our insights show that early cues of IPV may be difficult to detect within search queries, though even in the late stage that many IPV users are identified, interventions such as ads to guide people to safely exit violent situations could be beneficial.

Online Information on Painful Sexual Dysfunction in Women: Quality Analysis of Websites in SPANISH about Dyspareunia, Vaginismus and Vulvodynia.

The objective of this study was to evaluate the content, quality, and readability of websites containing information on dyspareunia, vaginismus, and vulvodynia in Spanish. Web pages were retrieved entering the terms “dyspareunia”, “vaginismus”, and “vulvodynia” in Google, Yahoo!, and Bing search engines. Two researchers employed the DISCERN and Bermúdez-Tamayo questionnaires to analyze the content and quality of the websites, and the INFLESZ scale to evaluate their readability. IBM SPSS® version 25 statistical software was employed for data analysis. The internet search yielded 262 websites, 91 of which were included after applying the selection criteria. Websites with information on dyspareunia obtained median scores of 24 (30–21) in the DISCERN, 38 (41.0–35.5) in the Bermúdez-Tamayo, and 55.3 (57.2–50.9) in the INFLESZ tools. The results for websites on vaginismus revealed median scores of 23.5 (30–20) in the DISCERN, 37 (42–35) in the Bermúdez-Tamayo, and 52.9 (55.6–46.4) in the INFLESZ. Finally, the median scores for vulvodynia sites was 25.5 (30–20) in the DISCERN, 38 (43–33.7) in the Bermúdez-Tamayo, and 54.2 (57.3–47.2) in the INFLESZ. These outcomes indicate that the quality of information in these websites is very low, while the overall quality of the web pages is moderate. Sites on vaginismus and vulvodynia were “somewhat difficult” to read, while readability was “normal” for websites on dyspareunia. Healthcare professionals should be aware of the shortcomings of these websites and address them through therapeutic education with resources containing updated, quality information. This raises the need for health professionals to generate these resources themselves or for experts and/or scientific societies in the field to check the quality and timeliness of the contents, regardless of whether or not the websites are endorsed with quality seals.

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

BackgroundCerebrovascular 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).ObjectiveHere, we propose that an algorithm based on internet search queries can identify people at increased risk for a near stroke event.MethodsWe 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.ResultsThe 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.ConclusionsThe 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.

The First Predictor of Impending Stroke: An Internet Search-Based Algorithm Blind to Established Cardiometabolic Risk, Outperforms Classical Risk Factor-Based Calculators

Cerebrovascular disease is a leading cause of mortality and disability and an immense global burden. It is partly related to aging in a metabolic syndrome-promoting environment. Prevention strategies are insufficient: they rely on intermittent screening in predominantly high-risk individuals, while most cases occur in the intermediate risk population. Screening algorithms like the Framingham Risk Score predict events in the next decade using traditional risk factors (age, diabetes, hypertension, obesity, hyperlipidemia, atrial fibrillation and smoking). No current tool can predict a near/impending stroke in the next few weeks/months. This could provide a time window for urgent preventive measures (anticoagulation, hypertension control or lipid lowering). Algorithms analyzing daily computer usage, examining motor, language and executive functions, correlate with standard cognitive tests. Covert cerebrovascular disease is linked to subtle cognitive and motor deficits and increased risk for stroke. We examined whether this could be harnessed to predict an imminent stroke. We developed an algorithm based on internet search queries to identify people at increased risk for a near stroke event. The algorithm was entirely blind to traditional cardiovascular risk factors or risks for cognitive decline. We analyzed queries submitted to the Bing search engine by 285 people for which a stroke event was identified and 1195 controls, with regards to attributes previously shown to reflect cognitive function. Controls included random people 60 years and above or similar aged individuals who queried for one of eight control conditions: myocardial infarction, atrial fibrillation, hypertension, migraine, B12 deficiency, depression, hypothyroidism and surgery. We used a random forest model with 1000 trees to distinguish the patient cohort from each of the control cohorts. Ten-fold cross-validation at the user level was used to reduce the likelihood of overfitting. All processing was conducted using Matlab 2019. Results: Our model performed well against all controls with area under the curve of the receiver operating curve (AUC) of 0.985 or higher and a true positive rate (at 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 was acquired beginning 120 days prior to the event. Good prediction accuracy was also obtained for a prospective cohort of users collected one year later. We propose that impending stroke can be identified through alterations in internet usage patterns that reflect cognitive function, with high predictive power (AUC exceeding 0.985 for a near event in comparison to an AUC of ~0.71 in the Framingham Stroke Risk Score for a 10 year event). This could potentially be applied inexpensively, continuously and on a large scale to willing individuals with the aim of reducing stroke events.

Content-Based Model of Web Search Behavior: An Application to TV Show Search

We develop a flexible content-based search model that links the content preferences of search engine users to query search volume and click-through rates, while allowing content preferences to vary systematically based on the context of a search. Content preferences are defined over latent topics that describe the content of search queries and search result descriptions. Compared with existing applications of topic modeling in marketing and recommendation systems, our proposed approach can simultaneously capture multiple types of information and investigate multiple aspects of behavioral dynamics in a single framework that enables interpretable results for business decision making. To facilitate efficient and scalable inference, we develop a full Bayesian variational inference algorithm. We evaluate our modeling framework using real-world search data for TV shows from the Bing search engine. We illustrate how our model can quantify the content preferences associated with each query and how these preferences vary systematically based on whether the query is observed before, during, or after a TV show is aired. We also show that our model can help the search engine improve its ranking of search results as well as address the cold-start problem for new page links. This paper was accepted by Hamid Nazerzadeh, big data analytics.

Quality and readability of web-based Arabic health information on periodontal disease

BackgroundCurrently, the Internet seems to be a helpful tool for obtaining information about everything that we think about, including diseases, their prevention and treatment approaches. However, doubts exist regarding the quality and readability of such information. This study sought to assess the quality and readability of web-based Arabic information on periodontal disease.MethodsIn this infodemiological study, the Google, Yahoo!, and Bing search engines were searched using specific Arabic terms on periodontal disease. The first 100 consecutive websites from each engine were obtained. The eligible websites were categorized as commercial, health/professional, journalism, and other. The following tools were applied to assess the quality of the information on the included websites: the Health on the Net Foundation Code of Conduct (HONcode), the Journal of the American Medical Association (JAMA) benchmarks, and the DISCERN tool. The readability was assessed using an online readability tool.ResultsOf the 300 websites, 89 were eligible for quality and readability analyses. Only two websites (2.3%) were HONcode certified. Based on the DISCERN tool, 43 (48.3%) websites had low scores. The mean score of the JAMA benchmarks was 1.6 ± 1.0, but only 3 (3.4%) websites achieved “yes” responses for all four JAMA criteria. Based on the DISCERN tool, health/professional websites revealed the highest quality of information compared to other website categories. Most of the health/professional websites revealed moderate-quality information, while 55% of the commercial websites, 66% of journalism websites, and 43% of other websites showed poor quality information. Regarding readability, most of the analyzed websites presented simple and readable written content.ConclusionsAside from readable content, Arabic health information on the analyzed websites on periodontal disease is below the required level of quality.

What on-line searches tell us about public interest and potential impact on behaviour in response to minimum unit pricing of alcohol in Scotland.

To investigate whether the introduction of minimum unit pricing (MUP) in Scotland on 1 May 2018 was reflected in changes in the likelihood of alcohol-related queries submitted to an internet search engine, and in particular whether there was any evidence of increased interest in purchasing of alcohol from outside Scotland. Observational study in which individual queries to the internet Bing search engine for 2018 in Scotland and England were captured and analysed. Fluctuations over time in the likelihood of specific topic searches were examined. The patterns seen in Scotland were contrasted with those in England. Scotland and England. People who used the Bing search engine during 2018. Numbers of daily queries submitted to Bing in 2018 on eight alcohol-related topics expressed as a proportion of queries on that day on any topic. These daily likelihoods were smoothed using a 14-day moving average for Scotland and England separately. There were substantial peaks in queries about MUP itself, cheap sources of alcohol and online alcohol outlets at the time of introduction of MUP in May 2018 in Scotland, but not England. These were relatively short-lived. Queries related to intoxication and alcohol problems did not show a MUP peak, but were appreciably higher in Scotland than in England throughout 2018. Analysis of internet search engine queries appears to show that a fraction of people in Scotland may have considered circumventing minimum unit pricing in 2018 by looking for on-line alcohol retailers. The overall higher levels of queries related to alcohol problems in Scotland compared with England mirrors the corresponding differences in alcohol consumption and harms between the countries.

Readability and Variability Among Online Sources for Patella Dislocation: What Patients are Reading

Patients frequently use the internet to obtain medical information, and the information may be misleading. Patella dislocation is a common orthopaedic injury for which patients may use the internet as a resource to better understand treatment options and recovery. The purpose of this study was to evaluate online information about patella instability in order to assess what patients are reading. A search was performed using Google, Yahoo, and Bing search engines and four similar terms related to patella dislocation (patella instability, kneecap dislocation, dislocated kneecap, and patella dislocation). A list of 37 websites were compiled. The readability of websites was analyzed using Flesch-Reading tools and content was assessed using a content scoring guide that evaluates whether the websites mentioned certain topics relevant to patella dislocation. The website content score was calculated and averaged from the evaluation of two scorers. 17 of 37 (46%) websites disclosed the author credentials, and 13 of 37 (35%) websites were authored by physicians with a M.D. degree. The mean Flesh-Kincaid Grade for all websites was 10.8 ± 3.5 and the mean Flesch Reading Ease Score was 47.6 ± 18, indicating that on average, the websites were moderately difficult to read. Websites that were written by non-physicians had the highest website content score (65.0 out of 100 points), indicating that these websites discussed most topics related to patellar dislocation. Only 8 of 37 (22%) websites had a 3rd party HON seal, which validates the quality and reliability of information on the website. The information presented online about patellar dislocation is unreliable and written at a reading level that is difficult for the average patient to understand. Patients should be aware of the potential inaccuracy of information presented online and orthopaedic surgeons should consider recommending reliable websites to patients.

The Readability of Online Health Information on Middle East Respiratory Syndrome Coronavirus Disease

Objectives: The study aims at exploring the readability of health websites on Middle East respiratory syndrome coronavirus (MERS‐CoV). Methods: The term was searched in Google, Yahoo, and Bing search engines. The readability of the first 30 results for each search engine was evaluated by using the five readability scales, including Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease (FRE), Simple Measure of Gobbledygook (SMOG), Coleman-Liau Index (CLI) and Gunning Fog. Moreover, the official HONcode toolbar was used to identify websites that had been officially certified by the HON foundation. Results: Almost half of the retrieved websites were governmental (44.2%). All the surveyed websites were written above the recommended level and so, their readability is suitable for those with a high school or a college degree. The mean grade level for the MERS related websites was in a similar range across the five readability scales. Furthermore, there was no association between the search rank, credibility, and readability Discussion: The readability level of MERS information available through search engines results, exceeds the recommended 6th-grade level, and they do not currently adhere to the recommended readability guidelines. Even credible websites have provided the contents that are not readable enough for the public. Conclusion: Considering the lack of a specific policy about the providing of readable health information on the web, it is recommended for healthcare providers to advise their patients to use the online information after consulting with the physicians.

Impact of online mental health screening tools on help-seeking, care receipt, and suicidal ideation and suicidal intent: Evidence from internet search behavior in a large U.S. cohort

IntroductionMost people with psychiatric illnesses do not receive treatment for almost a decade after disorder onset. Online mental health screens reflect one mechanism designed to shorten this lag in help-seeking, yet there has been limited research on the effectiveness of screening tools in naturalistic settings. Material and methodsWe examined a cohort of persons directed to a mental health screening tool via the Bing search engine (n = 126,060). We evaluated the impact of tool content on later searches for mental health self-references, self-diagnosis, care seeking, psychoactive medications, suicidal ideation, and suicidal intent. Website characteristics were evaluated by pairs of independent raters to ascertain screen type and content. These included the presence/absence of a suggestive diagnosis, a message on interpretability, as well as referrals to digital treatments, in-person treatments, and crisis services. ResultsUsing machine learning models, the results suggested that screen content predicted later searches with mental health self-references (AUC = 0·73), mental health self-diagnosis (AUC = 0·69), mental health care seeking (AUC = 0·61), psychoactive medications (AUC = 0·55), suicidal ideation (AUC = 0·58), and suicidal intent (AUC = 0·60). Cox-proportional hazards models suggested individuals utilizing tools with in-person care referral were significantly more likely to subsequently search for methods to actively end their life (HR = 1·727, p = 0·007). DiscussionOnline screens may influence help-seeking behavior, suicidal ideation, and suicidal intent. Websites with referrals to in-person treatments could put persons at greater risk of active suicidal intent. Further evaluation using large-scale randomized controlled trials is needed.

Comparative Performance Evaluation of Keyword and Semantic Search Engines using Different Query Set Categories

Background: Keyword search engines are unable to understand the intention of user as a result they produce enormous results for user to distinguish between relevant and non relevant answers of user queries. This has led to rise in requirement to study search capabilities of different search engines. In this research work, experimental evaluation is done based on different metrics to distinguish different search engines on the basis of type of query that can be handled by them. Methods: To check the semantics handling performance, four types of query sets consisting of 20 queries of agriculture domain are chosen. Different query set are single term queries, two term queries, three term queries and NLP queries. Queries from different query set were submitted to Google, DuckDuckGo and Bing search engines. Effectiveness of different search engines for different nature of queries is experimented and evaluated in this research using Grade relevance measures like Cumulative Gain, Discounted Cumulative Gain, Ideal Discounted Cumulative Gain, and Normalized Discounted Cumulative Gain in addition to the precision metric. Results: Our experimental results demonstrate that for single term query, Google retrieves more relevant documents and performs better and DuckDuckGo retrieves more relevant documents for NLP queries. Conclusion: Analysis done in this research shows that DuckDuckGo understand human intention and retrieve more relevant result, through NLP queries as compared to other search engines.

Quality, understandability and actionability of online patient education material about hypertension

PurposeThe purpose of this paper is to assess the value of websites accessible to patients looking for Web-based information regarding hypertension management.Design/methodology/approachA cross-sectional research was carried out by finding out Malay and English language websites about hypertension. For this purpose, the keywords “hypertension and treatment” were entered on the Yahoo, Google, Ask.com, Bing and DuckDuckGo search engines, and the first five pages of the results obtained were inspected. The DISCERN tool was deployed for evaluating the quality of information. The actionability and understandability were assessed through the Patient Education Materials Assessment Tool (PEMAT). Eight assessors were asked to assess and grade the involved websites.FindingsOf the 216 websites, eight (4.0%) conformed to the inclusion norms. All websites were classified into private, 4 (50%); government, 2 (25%) and personal, 2 (25%). The general rating of the eight websites was good (mean 51.6 ± 8.2 on a 75-point scale); however, half of the websites were rated as fair (mean 45.3 ± 3.1 on a 75-point scale). All websites conformed to the standard score of ≥70% for understandability (mean 76.1 ± 11.4), but none for actionability (mean 52.8 ± 13.9). Analysis of variance indicated there was no statistical difference with regards to quality (p = 0.525), understandability (p = 0.484) and actionability (p = 0.188) among the three website sets.Originality/valueConsidering the surplus of websites dedicated to information on hypertension, an independent assessment of the quality of these websites will be advantageous. Patients should be rendered high understandability, quality and actionability to evade deceptive online information.

Quality of the patient-oriented web-based information on esophageal cancer

This study was aimed to analyze the readability and quality of patient education websites on esophageal cancer. Yahoo!, Google, and Bing search engines were searched using keywords esophageal cancer, esophageal tumor, esophageal tumor, esophageal malignancy, esophageal cancer, esophageal tumor, esophageal tumor, and esophageal malignancy. The first 50 websites resulting in each keyword search were evaluated using validated FRES, LIDA, and DISCERN scores to assess readability, usability, and reliability, and quality of information, respectively. Non-parametric tests were used for statistical analysis. A total of 108 eligible websites were included in the analysis. Thirty (27.8%) out of the 108 eligible web sites had obtained Health on the Net (HON) code certification. The median FRES score of the included websites was 48.25 out of 100 (range: 15.6-70.1). The median LIDA usability and reliability scores were 46.5 out of 54 (range: 22-54) and 39.0 out of 51 (range: 10-51), respectively. The median DISCERN score was 50.5 out of 80 (range: 23-79). A low DISCERN score (≤ 50%) was found in 50% (n = 54) of the websites. The DISCERN score was found to be significantly associated with LIDA usability, reliability, LIDA overall scores (p < 0.001), and HON code certification (p = 0.01). The quality of the websites providing patient-centered information on the Internet ranged between moderate and low with regards to readability, usability, and reliability scores. Better informed decisions on treatment may be facilitated with the access to good quality information online. Therefore, strategies need to be implemented to regulate and standardize websites to provide good quality, accurate information.

Quality of online information for the general public on COVID-19

ObjectivesTo analyse the quality of information included in websites aimed at the public on COVID-19. MethodsYahoo!, Google and Bing search engines were browsed using selected keywords on COVID-19. The first 100 websites from each search engine for each keyword were evaluated. Validated tools were used to assess readability [Flesch Reading Ease Score (FRES)], usability and reliability (LIDA tool) and quality (DISCERN instrument). Non-parametric tests were used for statistical analyses. ResultsEighty-four eligible sites were analysed. The median FRES score was 54.2 (range: 23.2−73.5). The median LIDA usability and reliability scores were 46 (range: 18−54) and 37(range:14−51), respectively. A low (<50 %) overall LIDA score was recorded for 30.9 % (n = 26) of the websites. The median DISCERN score was 49.5 (range: 21–77). The DISCERN score of ≤50 % was found in 45 (53.6 %) websites. The DISCERN score was significantly associated with LIDA usability and reliability scores (p < 0.001) and the FRES score (p = 0.024). ConclusionThe majority of websites on COVID-19 for the public had moderate to low scores with regards to readability, usability, reliability and quality. Practice ImplicationsPrompt strategies should be implemented to standardize online health information on COVID-19 during this pandemic to ensure the general public has access to good quality reliable information.

Diabetic Retinopathy Online: A Powerful Opportunity for Revision

Objective: The objective of this study is to investigate the quality, accuracy, content, and readability of online diabetic retinopathy (DR) information.Methods: This study reviewed the most accessible information online for content related to DR. The term, “Diabetic Retinopathy” was entered into Google, Bing, and Yahoo search engines. Assessments were performed using the DISCERN instrument, JAMA benchmark criteria, Suitability Assessment of Materials (SAM), HONcode, and the American Academy of Ophthalmology (AAO) 2017 Preferred Practice Pattern Guidelines between multiple graders.Results: Twenty-two distinct websites were studied after applying exclusion criteria. The mean DISCERN score calculated was defined as poor by the scale. The mean JAMA score was low at 2 out of 7 possible points. The mean SAM score calculated was defined as adequate by the scale. Less than half of the websites were HONcode certified. Content from the Preferred Practice Pattern was inconsistently expressed throughout websites, with risk factors and management being represented more frequently than screening and diagnostics.Conclusion: The quality of online DR information for patients is overall poor, unreliable, incomprehensible, and inaccurate. Improving these parameters may assist in the overall management of DR as well as other medical diseases. Diabetes educators should not underestimate their key role in being a reliable and effective source of information on DR.