Dataset Information

A Bayesian Network-Based Browsing Model for Patients Seeking Radiology-Related Information on Hospital Websites: Development and Usability Study.

ABSTRACT:

Background

An increasing number of people are visiting hospital websites to seek better services and treatments compared to the past. It is therefore important for hospitals to develop websites to meet the needs of their patients. However, few studies have investigated whether and how the current hospital websites meet the patient's needs. Above all, in radiation departments, it may be difficult for patients to obtain the desired information regarding modality and diagnosis because such information is subdivided when described on a website.

Objective

The purpose of this study is to suggest a hospital website search behavior model by analyzing the browsing behavior model using a Bayesian network from the perspective of one-to-one marketing.

Methods

First, we followed the website access log of Hokkaido University Hospital, which was collected from September 1, 2016, to August 31, 2017, and analyzed the access log using Google Analytics. Second, we specified the access records related to radiology from visitor browsing pages and keywords. Third, using these resources, we structured 3 Bayesian network models based on specific patient needs: radiotherapy, nuclear medicine examination, and radiological diagnosis. Analyzing each model, this study considered why some visitors could not reach their desired page and improvements to meet the needs of visitors seeking radiology-related information.

Results

The radiotherapy model showed that 74% (67/90) of the target visitors could reach their requested page, but only 2% (2/90) could reach the Center page where inspection information, one of their requested pages, is posted. By analyzing the behavior of the visitors, we clarified that connecting with the radiotherapy and radiological diagnosis pages is useful for increasing the proportion of patients reaching their requested page.

Conclusions

We proposed solutions for patient web-browsing accessibility based on a Bayesian network. Further analysis is necessary to verify the accuracy of the proposed model in comparison to other models. It is expected that information provided on hospital websites will be improved using this method.

SUBMITTER: Suzuki R

PROVIDER: S-EPMC7854043 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Bayesian Network-Based Browsing Model for Patients Seeking Radiology-Related Information on Hospital Websites: Development and Usability Study.

Suzuki Ryusuke R Suzuki Teppei T Tsuji Shintaro S Fujiwara Kensuke K Yamashina Hiroko H Endoh Akira A Ogasawara Katsuhiko K

Journal of medical Internet research 20210119 1

<h4>Background</h4>An increasing number of people are visiting hospital websites to seek better services and treatments compared to the past. It is therefore important for hospitals to develop websites to meet the needs of their patients. However, few studies have investigated whether and how the current hospital websites meet the patient's needs. Above all, in radiation departments, it may be difficult for patients to obtain the desired information regarding modality and diagnosis because such ...[more]

PMID: 33464211

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Project description:BackgroundAdolescence is a unique developmental period characterized by biological, social, and cognitive changes, as well as an interest in managing one's own health care. Many adolescents use the internet to seek health care information. However, young people face barriers before they can understand and apply the health information that they access on the web. It is essential that usability of adolescent health websites on the internet is improved to help adolescents overcome these barriers and allow them to engage successfully with web-based health care content.ObjectiveThe aim of this review was to synthesize the usability of specific health information websites. These findings were mapped onto the adolescent neurodevelopmental profile, and a design brief based on the findings was developed to tailor future websites for specific adolescent requirements.MethodsA systematic search conducted using PubMed, PsycINFO, and Education Resources Information Center (ERIC) identified 25 studies that assessed the usability of health information websites. Adolescent feedback was collected by a mixture of surveys, focus groups, interviews, and think-aloud procedures.ResultsA majority of the information websites were developed for specific health issues that may be relevant to adolescents. The most preferred website features were interactive content such as games and quizzes, as well as videos, images, audio clips, and animations. Participants also preferred communicating with other adolescents with similar conditions or learning about their experience through real stories and testimonials. Adolescents found it difficult to use health information websites if they contained too much text, were too cluttered, or had features that made it difficult to access. The findings are considered in the context of adolescent social processes, low tolerance of delayed gratification, and attraction to novelty and mapped onto a neurodevelopmental model of adolescence.ConclusionsYoung people's feedback can determine usability and content that make a health information website easy or informative to use. Neurodevelopmental profiles and the users' specific preferences and skills should be addressed in future development of health information websites for adolescents.

Project description:BACKGROUND:People engage in health information-seeking online when experiencing unusual or unfamiliar bodily changes. It is not well understood how people consult the internet for health information after the onset of unfamiliar symptoms and before receiving a potential diagnosis and how online information-seeking can help people appraise their symptoms. This lack of evidence may be partly due to methodological limitations in capturing in real time the online information-seeking process. OBJECTIVE:We explored women's symptom attribution and online health information-seeking in response to a hypothetical and unfamiliar breast change suggestive of cancer (nipple rash). We also aimed to establish the feasibility of capturing in real time the online information-seeking process with a tool designed to track participant online searches and visited websites, the Vizzata browser tracker. METHODS:An online survey was completed by 56 cancer-free women (mean age 60.34 [SD 7.73] years) responding to a scenario asking them to imagine noticing a red scaly rash on the nipple. Participants were asked to make symptom attributions when presented with the scenario (T1) and again after seeking information online (T2). The online tracking tool, embedded in the survey, was used to capture in real time participant search terms and accessed websites. RESULTS:The tracking tool captured the search terms and accessed websites of most of the participants (46/56, 82%). For the rest (10/56, 18%), there was evidence of engagement in online information-seeking (eg, medical terminology and cancer attribution at T2) despite their searching activity not being recorded. A total of 25 participants considered cancer as a potential cause for the nipple rash at T1, yet only one of these used cancer as a search term. Most participants (40/46, 87%) used rash-related search terms, particularly nipple rash and rash on nipple. The majority (41/46, 89%) accessed websites containing breast cancer information, with the National Health Service webpage "Paget disease of the nipple" being the most visited one. At T2, after engaging in the internet search task, more participants attributed the nipple rash to breast cancer than at T1 (37/46, 66% vs 25/46, 45%), although a small number of participants (6/46) changed from making a cancer attribution at T1 to a noncancer one at T2. CONCLUSIONS:Making a cancer attribution for an unfamiliar breast change did not necessarily translate into cancer-termed searches. Equally, not all internet searches led to a cancer attribution. The findings suggest that online information-seeking may not necessarily help women who experience unfamiliar breast cancer symptoms understand their condition. Despite some technical issues, this study showed that it is feasible to use an online browser tracking tool to capture in real time information-seeking about unfamiliar symptoms.

Project description:BackgroundDental caries is the most common chronic oral disease, affecting 2.4 billion people worldwide who on average have 2.11 decayed, missing, or filled teeth. It impacts the quality of life of patients, socially and economically. However, the comprehension of dental caries may be difficult for most people, as it involves a multifactorial etiology with the interplay between the tooth surface, the dental biofilm, dietary fermentable carbohydrates, and genetic and behavioral factors. Therefore, the production of effective materials addressed to the education and counseling of patients for the prevention of dental caries requires a high level of specialization. In this regard, the dental caries-related contents produced by laypersons and their availability on the Internet may be low-quality information.ObjectiveThe aim of this study was to assess the readability and the quality of dental caries-related information on Brazilian websites.MethodsA total of 75 websites were selected through Google, Bing, Yahoo!, and Baidu. The websites were organized in rankings according to their order of appearance in each one of the 4 search engines. Furthermore, 2 independent examiners evaluated the quality of websites using the DISCERN questionnaire and the Journal of American Medical Association (JAMA) benchmark criteria. The readability of the websites was assessed by the Flesch Reading Ease adapted to Brazilian Portuguese (FRE-BP). In addition, the information presented on the websites was categorized as etiology, prevention, and treatment of dental caries. The statistical analysis was performed using Spearman rank correlation coefficient, Mann-Whitney U test, hierarchical clustering analysis by Ward minimum variance method, Kruskal-Wallis test, and post hoc Dunn test. P<.05 was considered significant.ResultsThe Web contents were considered to be of poor quality by DISCERN (mean 33.48, standard deviation, SD 9.06) and JAMA (mean 1.12, SD 0.97) scores, presenting easy reading levels (FRE-BP: mean 62.93, SD 10.15). The rankings of the websites presented by Google (ρ=-.22, P=.08), Baidu (ρ=-.19, P=.53), Yahoo! (ρ=.22, P=.39), and Bing (ρ=-.36, P=.23) were not correlated with DISCERN scores. Moreover, the quality of websites with health- and nonhealth-related authors was similar (P=.27 for DISCERN and P=.47 for JAMA); however, the pages with a greater variety of dental caries information showed significantly higher quality scores than those with limited contents (P=.009).ConclusionsOn the basis of this sample, dental caries-related contents available on Brazilian websites were considered simple, accessible, and of poor quality, independent of their authorship. These findings indicate the need for the development of specific policies focused on the stimulus for the production and publication of Web health information, encouraging dentists to guide their patients in searching for recommended oral health websites.

Project description:Information-seeking behaviour is necessary to improve knowledge on diabetes therapy and complications. Combined with other self-management skills and autonomous handling of the disease, it is essential for achieving treatment targets. However, a systematic review addressing this topic is lacking. The aims of this systematic review were to identify and analyse existing knowledge of information-seeking behaviour: (1) types information-seeking behaviour, (2) information sources, (3) the content of searched information, and (4) associated variables that may affect information-seeking behaviour.The systematic review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) requirements. MEDLINE, CINAHL, EMBASE, ScienceDirect, PsycInfo, Cochrane Library, Web of Science, CCMed, ERIC, Journals@OVID, Deutsches Ärzteblatt and Karlsruher virtueller Katalog (KvK) databases were searched. Publications dealing with information-seeking behaviour of people with diabetes mellitus published up to June 2015 were included. A forward citation tracking was performed in September 2016 and June 2017. Additionally, an update of the two main databases (MEDLINE, CINAHL) was conducted, considering studies published up to July 2017. Studies published in languages other than English or German were excluded, as well as letters, short reports, editorials, comments and discussion papers. A study selection and the critical appraisal of the selected studies were performed independently by two reviewers. A third reviewer was consulted if any disagreement was found. Data extraction and content analysis were performed using selected dimensions of Wilson's 'model of information behaviour'.Twenty-six studies were included. Five 'types of information-seeking behaviour' were identified, e.g. passive and active search. The 'Internet' and 'healthcare professionals' were the most frequently reported sources. 'Diet', 'complications', 'exercise' and 'medications and pharmacological interactions' were the most frequently identified content of information. Seven main categories including associated variables were identified, e.g. 'socioeconomic', 'duration of DM', and 'lifestyle'.The systematic review provides a valuable overview of available knowledge on the information-seeking behaviour of people with diabetes mellitus, although there are only a few studies. There was a high heterogeneity regarding the research question, design, methods and participants. Although the Internet is often used to seek information, health professionals still play an important role in supporting their patients' information-seeking behaviour. Specific needs of people with diabetes must be taken into consideration.PROSPERO CRD42016037312.

Project description:BackgroundHealth care organizations are tasked with providing web-based health resources and information. Usability refers to the ease of user experience on a website. In this study, we conducted a usability analysis of academic medical centers in the United States, which, to the best of our knowledge, has not been previously carried out.ObjectiveThe primary aims of the study were to the following: (1) adapt a preexisting usability scoring methodology to academic medical centers; (2) apply and test this methodology on a sample set of academic medical center websites; and (3) make recommendations from these results on potential areas of improvements for our sample of academic medical center websites.MethodsAll website usability testing took place from June 1, 2020, to December 15, 2020. We replicated a methodology developed in previous literature and applied it to academic medical centers. Our sample included 73 US academic medical centers. Usability was split into four broad categories: accessibility (the ability of those with low levels of computer literacy to access and navigate the hospital's website); marketing (the ability of websites to be found through search engines and the relevance of descriptions to the links provided); content quality (grammar, frequency of information updates, material relevancy, and readability); and technology (download speed, quality of the programming code, and website infrastructure). Using these tools, we scored each website in each category. The composite of key factors in each category contributed to an overall "general usability" score for each website. An overall score was then calculated by applying a weighted percentage across all factors and was used for the final "overall usability" ranking.ResultsThe category with the highest average score was technology, with a 0.82 (SD 0.068, SE 0.008). The lowest-performing category was content quality, with an average of 0.22 (SD 0.069, SE 0.008). As these numbers reflect weighted percentages as an integer, the higher the score, the greater the overall usability in that category.ConclusionsOur data suggest that technology, on average, was the highest-scored variable among academic medical center websites. Because website functionality is essential to a user's experience, it is justified that academic medical centers invest in optimal website performance. The overall lowest-scored variable was content quality. A potential reason for this may be that academic medical center websites are usually larger in size, making it difficult to monitor the increased quantity of content. An easy way to improve this variable is to conduct more frequent website audits to assess readability, grammar, and relevance. Marketing is another area in which these organizations have potential for improvement. Our recommendation is that organizations utilize search engine optimization techniques to improve their online visibility and discoverability.

Project description:BackgroundOwing to the fact that firefighters have unique health risks, access to firefighter-specific internet-based health information is a potential mechanism for achieving better health and work outcomes.ObjectiveThe objective of our study was to identify the amount and nature of health information resources available on Canadian firefighter-specific websites and the extent to which resources are consistent across websites as a surrogate indicator of diffusion of information.MethodsA search of health resources on firefighter websites (union and employer) for all Canadian provinces, major cities and a subset of smaller cities, and the International Association of Fire Fighters (IAFF) website was conducted on Google (July 2017). Content was identified and classified based on the type of resource, health focus, and location. The quantity and nature of the resources were summarized using descriptive statistics.ResultsAmong all (N=313) websites reviewed, 41 websites had health information with a cumulative total of 128 resources that addressed firefighter mental (59/128, 46.1%), physical (43/128, 33.6%), and work health (26/128, 20.3%). The highest density of information was found on international and national websites (13 resources per website) and the least on local websites (1 resource per 7 websites). Three provinces (Ontario, Québec, and British Columbia) hosted 81% (65/80) of the provincial, territorial and local resources. General mental health (20/59, 34%), posttraumatic stress disorder (14/59, 24%), and suicide (14/59, 24%) were the most prevalent topics within the mental health resources, whereas half (21/43, 49%) of all physical health resources were on cancer. No resources from Northern Canada were found. Musculoskeletal health was not mentioned in any of the resources identified. There was minimal cross-linking of resources across sites (only 4 resources were duplicated across sites), and there was no clear indication of how the content was vetted or evaluated for quality.ConclusionsThere was wide variation in the amount and type of information available on different firefighter websites with limited diffusion of information across jurisdictions. Quality evaluation and coordination of resources should be considered to enhance firefighters' access to quality health information to meet their specific needs. Mental health and cancer information aligned with high rates of these health problems in firefighters, whereas the lack of information on musculoskeletal health was discordant with their high rate of work injury claims for these problems.

Project description:BackgroundThe problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data that can concern billions of variables. These data present new challenges. In particular, it is difficult to discover predictive variables, when each variable has little marginal effect. An example concerns Genome-wide Association Studies (GWAS) datasets, which involve millions of single nucleotide polymorphism (SNPs), where some of the SNPs interact epistatically to affect disease status. Towards determining these interacting SNPs, researchers developed techniques that addressed this specific problem. However, the problem is more general, and so these techniques are applicable to other problems concerning interactions. A difficulty with many of these techniques is that they do not distinguish whether a learned interaction is actually an interaction or whether it involves several variables with strong marginal effects.Methodology/findingsWe address this problem using information gain and Bayesian network scoring. First, we identify candidate interactions by determining whether together variables provide more information than they do separately. Then we use Bayesian network scoring to see if a candidate interaction really is a likely model. Our strategy is called MBS-IGain. Using 100 simulated datasets and a real GWAS Alzheimer's dataset, we investigated the performance of MBS-IGain.Conclusions/significanceWhen analyzing the simulated datasets, MBS-IGain substantially out-performed nine previous methods at locating interacting predictors, and at identifying interactions exactly. When analyzing the real Alzheimer's dataset, we obtained new results and results that substantiated previous findings. We conclude that MBS-IGain is highly effective at finding interactions in high-dimensional datasets. This result is significant because we have increasingly abundant high-dimensional data in many domains, and to learn causes and perform prediction/classification using these data, we often must first identify interactions.

Dataset Information

A Bayesian Network-Based Browsing Model for Patients Seeking Radiology-Related Information on Hospital Websites: Development and Usability Study.

Background

Objective

Methods

Results

Conclusions

Publications

A Bayesian Network-Based Browsing Model for Patients Seeking Radiology-Related Information on Hospital Websites: Development and Usability Study.

Similar Datasets

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