HEALTH INFORMATION SEARCH PERSONALIZATION WITH SEMANTIC NETWORK USER MODEL

2014 ◽  
Author(s):  
IRA PUSPITASARI ◽  
KEN-ICHI FUKUI ◽  
KOICHI MORIYAMA ◽  
MASAYUKI NUMAO
Keyword(s):  
Health Information ◽  
Information Search ◽  
Semantic Network ◽  
User Model

Health information needs, sources, and barriers of primary care patients to achieve patient-centered care: A literature review

2016 ◽  
Vol 22 (4) ◽  
pp. 992-1016 ◽  
Author(s):  
Martina A Clarke ◽  
Joi L Moore ◽  
Linsey M Steege ◽  
Richelle J Koopman ◽  
Jeffery L Belden ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Information ◽  
Information Search ◽  
Information Needs ◽  
Information Sources ◽  
Medical Condition ◽  
Information Access ◽  
The Internet ◽  
Common Information ◽  
Primary Care Patients

To synthesize findings from previous studies assessing information needs of primary care patients on the Internet and other information sources in a primary care setting. A systematic review of studies was conducted with a comprehensive search in multiple databases including OVID MEDLINE, CINAHL, and Scopus. The most common information needs among patients were information about an illness or medical condition and treatment methods, while the most common information sources were the Internet and patients’ physicians. Overall, patients tend to prefer the Internet for the ease of access to information, while they trust their physicians more for their clinical expertise and experience. Barriers to information access via the Internet include the following: socio-demographic variables such as age, ethnicity, income, education, and occupation; information search skills; and reliability of health information. Conclusion: Further research is warranted to assess how to create accurate and reliable health information sources for both Internet and non-Internet users.

Investigating and Drawing a Pattern of Health Information Search Based on Genetic Changes in the Circadian Clock

2021 ◽  
Vol 6 (3) ◽  
pp. 176-187
Author(s):  
Akram Mehrandasht ◽  
◽  
Najla Hariri ◽  
Daryoosh Matlabi ◽  
◽  
...  
Keyword(s):  
Circadian Clock ◽  
Health Information ◽  
Information Search ◽  
Genetic Changes

Online Health Information Consumers’ Learning across Health-Related Search Tasks from the Perspective of Retrieval Platform Switching (Preprint)

2021 ◽  
Author(s):  
Yijing Chen ◽  
Hanming Lin ◽  
Jin Zhang ◽  
Yiming Zhao
Keyword(s):  
Information Retrieval ◽  
Health Information ◽  
Information Search ◽  
Health Knowledge ◽  
Online Health Information ◽  
Related Information ◽  
Search Tasks ◽  
Health Related ◽  
Platform Switching ◽  
Information Consumers

BACKGROUND Online health information retrieval has been a top choice for acquiring health information and knowledge by millions worldwide. OBJECTIVE This study aims to investigate consumers’ modification of retrieval platform switch paths across health-related search tasks and learning via such a change. METHODS A lab user experiment was designed to obtain data on consumers’ health information search behavior. Participants accomplished health-related information search tasks. Screen movements were recorded by EV screen-recording software. The participants underwent in-depth interviews immediately after finishing the tasks. Screen recordings and interview data were both coded and analyzed. RESULTS Three types of learning, including the similar transfer learning, optimizing learning, and SERP-guided learning were identified based on five change patterns of retrieval platform switch paths adopted by health information consumers from task 1 to task 2. Health information consumers’ retrieval platform switch based on information usefulness evaluation. And they accessed different amounts and types of health knowledge from different retrieval platforms. CONCLUSIONS The results suggest that health information consumers exhibit learning both through retrieval platform switching and the knowledge they consume during the search process. This facilitates the assessment of a certain retrieval platform’s usefulness by measuring the amount and types of health knowledge in each search result. This study also contributes to the enhancement of consumers’ health information retrieval abilities, and to helping optimize health information retrieval platforms by increasing their exposure to consumers and increasing the matching degree between knowledge types and consumer needs.

Measuring health information seeking challenges in chronic disease: A psychometric analysis of a brief scale

2019 ◽  
pp. 174239531983647 ◽  
Author(s):  
Samantha R Paige ◽  
Elizabeth Flood-Grady ◽  
Janice L Krieger ◽  
Michael Stellefson ◽  
M David Miller
Keyword(s):  
Chronic Disease ◽  
Health Information ◽  
Information Search ◽  
Information Seeking ◽  
Measurement Properties ◽  
Primary Data ◽  
Average Score ◽  
Moderate Degree ◽  
Health Information Seeking ◽  
Response Option

Information seeking is a cornerstone of patient activation in chronic disease self-management. To date, there are few brief and literacy-sensitive tools to measure intrinsic barriers of health information seeking. The Health Information National Trends Survey includes four items from the Information Seeking Experiences scale to measure frustration, effort, concern, and comprehension of information sought during a recent medical/health information search. Limited evidence exists for its construct validity and use in primary data collection in chronic disease. This measurement study examines the psychometric properties of the scale. Qualtrics Panelists with at least one chronic disease ( N = 684) participated in an online survey. The average score was M = 12.85 ( SD = 3.97), indicating a moderate degree of health information seeking challenges. Confirmatory factor analysis of data collected using this scale supported unidimensionality (RMSEA = .03; CFI/TLI = .99/.99). There was adequate scale (ω = .83) and item (value = .98) reliabilities. Rasch analyses showed optimal measurement error and response predictability with item-fit (values = .80–1.20). Response option “agree” was less likely to be selected than any other response option, although not posing a threat to scale reliability. Results demonstrate that this brief scale has sufficient measurement properties for its use as a measure of intrinsic health information seeking barriers among patients with chronic disease.

An Empirical Note on Health Information Digital Divide

2017 ◽  
Vol 8 (2) ◽  
pp. 15-34 ◽  
Author(s):  
Ajeya Jha ◽  
Jaya Rani Pandey
Keyword(s):  
Discriminant Analysis ◽  
Digital Divide ◽  
Health Information ◽  
Information Search ◽  
Geographical Location ◽  
Family Type ◽  
Online Health Information ◽  
Chi Square ◽  
And Gender ◽  
E Mail

Availability of healthcare information on internet has made it possible for patients or their relatives to search for such information. This study was undertaken to find answers to such questions. In all 754 respondents participated in the survey. The variables selected from literature survey and exploratory study are Health Information Digital Divide, Income, Having E-mail id, access to internet, geographical location, Education, family-type, age and gender. As the data is categorical the significance of difference has been calculated using Chi-square test. Later discriminant analysis was conducted to predict patients who make online health information search and the ones who do not. The result show that Income, Having E-mail id, access to internet, geographical location, Education and gender are significant factors that determine the propensity of people for online healthcare search. Age and family-type, however, were found to have no impact on such a behavior. Using discriminant analysis 94.5 percent patients who make online health information search could be correctly predicted.

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