Dataset Information

The Causal Relationship Between Portal Usage and Self-Efficacious Health Information-Seeking Behaviors: Secondary Analysis of the Health Information National Trends Survey Data.

ABSTRACT:

Background

Patient portals have drawn much attention, as they are considered an important tool for health providers in facilitating patient engagement. However, little is known about whether the intensive use of patient portals contributes to improved management of patients' health in terms of their confidence in acquiring health information and exercising self-care. There is a lack of randomized trials with these outcomes measured both pre- and postadoption of patient portals.

Objective

The aim of this study was to examine the causal relationship between the usage of patient portals and patients' self-efficacy toward obtaining health information and performing self-care.

Methods

This study was a secondary data analysis that used data from a US national survey, the National Cancer Institute's Health Information National Trends Survey 5 Cycle 1. Patient portal usage frequency was used to define the treatment. Survey items measuring self-efficacy on a Likert-type scale were selected as the main outcomes, including patients' confidence in obtaining health information and performing self-care. To establish causality using survey data, we adopted the instrumental variables method. To determine the direction of the causal relationship in the presence of high-dimensional confounders, we further proposed a novel testing framework that employs conditional independence tests in a directed acyclic graph. The average causal effect was measured using the two-stage least squares regression method.

Results

We showed that frequently using patient portals improves patients' confidence in obtaining health information. The estimand of the weighted average causal effect was 0.14 (95% CI 0.06-0.23; P<.001). This means that when increasing the portal usage intensity, for instance, from 1-2 times to 3-5 times per year, the expected average increase in confidence level measured on a Likert-type scale would be 0.14. However, we could not conclusively determine the causal effect between patient portal usage and patients' confidence in exercising self-care.

Conclusions

The results support the use of patient portals and encourage better support and education to patients. The proposed statistical method can be used to exploit the potential of national survey data for causal inference studies.

SUBMITTER: Park J

PROVIDER: S-EPMC7875689 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

The Causal Relationship Between Portal Usage and Self-Efficacious Health Information-Seeking Behaviors: Secondary Analysis of the Health Information National Trends Survey Data.

Park Jaeyoung J Liang Muxuan M Alpert Jordan M JM Brown Richard F RF Zhong Xiang X

Journal of medical Internet research 20210127 1

<h4>Background</h4>Patient portals have drawn much attention, as they are considered an important tool for health providers in facilitating patient engagement. However, little is known about whether the intensive use of patient portals contributes to improved management of patients' health in terms of their confidence in acquiring health information and exercising self-care. There is a lack of randomized trials with these outcomes measured both pre- and postadoption of patient portals.<h4>Object ...[more]

PMID: 33502334

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Project description:BackgroundSeeking online health information (OHI) has become a common practice globally. The information seekers could face health risks if they are not proficient in OHI literacy. The OHI-seeking behaviors and skills of Chinese college students, the largest proportion of college students in the world, are understudied. This study was aimed to describe OHI-seeking behaviors and skills of college students in Guangdong, China.MethodsCollege students in the Guangdong province with OHI-seeking experience were invited via WeChat, QQ, and Sina Weibo using QR code posters and flyers for participation in this online anonymized questionnaire-based study. Data on demographics, OHI literacy, information resources, search approaches, and behaviors were collected. The relationship between perceived OHI literacy and high-risk behaviors was investigated by bivariate logistic regression analysis.ResultsRespondents were 1203 college students with a mean age of 20.6 years, females (60.2%), and undergraduates (97.2%). They sought health information via websites (20.3%), WeChat (2.6%), or both (77.1%). Baidu was the main search engine, and baike.baidu.com (80.3%), Zhihu.com (48.4%), and Zhidao.baidu.com (35.8%) were top three among 20 searched websites for information about self-care (80.7%), general health (79.5%), disease prevention (77.7%), self-medication (61.2%), family treatment (40.9%), drugs (37.7%), western medications (26.6%), hospitals (22.7%), physicians (21.4%), and Traditional Chinese Medicine (15.6%). Despite most respondents (78%) lacked confidence in the evidence quality and satisfaction with the results, only 32.4% further consulted doctors. Many (> 50%) would recommend the retrieved information to others. About 20% experienced hacking/Internet fraud. Cronbach's alpha for the internal consistency of OHI literacy was 0.786. Bivariate logistic regression analysis showed that students who believed they can judge the evidence level of OHI were more likely to self-diagnose (OR = 2.2, 95%CI, 1.6-3.1) and look for drug usage (OR = 3.1, 95%CI, 1.9-5.0).ConclusionsThis study reveals Chinese college students' heavy reliance on OHI to manage their own and others' health without sufficient knowledge/skills to identify misinformation and disinformation. The apparent risky information-seeking behaviors of Chinese college students warrant the provision of regulated, accurate, and actionable health information; assurance of cybersecurity; and health information literacy promotion in colleges by concerned authorities.

Project description:Baby boomers and older adults, a subset of the population at high risk for chronic disease, social isolation, and poor health outcomes, are increasingly utilizing the Internet and social media (Web 2.0) to locate and evaluate health information. However, among these older populations, little is known about what factors influence their eHealth literacy and use of Web 2.0 for health information.The intent of the study was to explore the extent to which sociodemographic, social determinants, and electronic device use influences eHealth literacy and use of Web 2.0 for health information among baby boomers and older adults.A random sample of baby boomers and older adults (n=283, mean 67.46 years, SD 9.98) participated in a cross-sectional, telephone survey that included the eHealth literacy scale (eHEALS) and items from the Health Information National Trends Survey (HINTS) assessing electronic device use and use of Web 2.0 for health information. An independent samples t test compared eHealth literacy among users and non-users of Web 2.0 for health information. Multiple linear and logistic regression analyses were conducted to determine associations between sociodemographic, social determinants, and electronic device use on self-reported eHealth literacy and use of Web 2.0 for seeking and sharing health information.Almost 90% of older Web 2.0 users (90/101, 89.1%) reported using popular Web 2.0 websites, such as Facebook and Twitter, to find and share health information. Respondents reporting use of Web 2.0 reported greater eHealth literacy (mean 30.38, SD 5.45, n=101) than those who did not use Web 2.0 (mean 28.31, SD 5.79, n=182), t217.60=-2.98, P=.003. Younger age (b=-0.10), more education (b=0.48), and use of more electronic devices (b=1.26) were significantly associated with greater eHealth literacy (R(2) =.17, R(2)adj =.14, F9,229=5.277, P<.001). Women were nearly three times more likely than men to use Web 2.0 for health information (OR 2.63, Wald= 8.09, df=1, P=.004). Finally, more education predicted greater use of Web 2.0 for health information, with college graduates (OR 2.57, Wald= 3.86, df =1, P=.049) and post graduates (OR 7.105, Wald= 4.278, df=1, P=.04) nearly 2 to 7 times more likely than non-high school graduates to use Web 2.0 for health information.Being younger and possessing more education was associated with greater eHealth literacy among baby boomers and older adults. Females and those highly educated, particularly at the post graduate level, reported greater use of Web 2.0 for health information. More in-depth surveys and interviews among more diverse groups of baby boomers and older adult populations will likely yield a better understanding regarding how current Web-based health information seeking and sharing behaviors influence health-related decision making.

Project description:BackgroundThe Internet provides a platform to access health information and support self-management by consumers with chronic health conditions. Despite recognized barriers to accessing Web-based health information, there is a lack of research quantitatively exploring whether consumers report difficulty finding desired health information on the Internet and whether these consumers would like assistance (ie, navigational needs). Understanding navigational needs can provide a basis for interventions guiding consumers to quality Web-based health resources.ObjectiveWe aimed to (1) estimate the proportion of consumers with navigational needs among seekers of Web-based health information with chronic health conditions, (2) describe Web-based health information-seeking behaviors, level of patient activation, and level of eHealth literacy among consumers with navigational needs, and (3) explore variables predicting navigational needs.MethodsA questionnaire was developed based on findings from a qualitative study on Web-based health information-seeking behaviors and navigational needs. This questionnaire also incorporated the eHealth Literacy Scale (eHEALS; a measure of self-perceived eHealth literacy) and PAM-13 (a measure of patient activation). The target population was consumers of Web-based health information with chronic health conditions. We surveyed a sample of 400 Australian adults, with recruitment coordinated by Qualtrics. This sample size was required to estimate the proportion of consumers identified with navigational needs with a precision of 4.9% either side of the true population value, with 95% confidence. A subsample was invited to retake the survey after 2 weeks to assess the test-retest reliability of the eHEALS and PAM-13.ResultsOf 514 individuals who met our eligibility criteria, 400 (77.8%) completed the questionnaire and 43 participants completed the retest. Approximately half (51.3%; 95% CI 46.4-56.2) of the population was identified with navigational needs. Participants with navigational needs appeared to look for more types of health information on the Internet and from a greater variety of information sources compared to participants without navigational needs. However, participants with navigational needs were significantly less likely to have high levels of eHealth literacy (adjusted odds ratio=0.83, 95% CI 0.78-0.89, P<.001). Age was also a significant predictor (P=.02).ConclusionsApproximately half of the population of consumers of Web-based health information with chronic health conditions would benefit from support in finding health information on the Internet. Despite the popularity of the Internet as a source of health information, further work is recommended to maximize its potential as a tool to assist self-management in consumers with chronic health conditions.

Project description:Some of the temporal variations and clock-like rhythms that govern several different health-related behaviors can be traced in near real-time with the help of search engine data. This is especially useful when studying phenomena where little or no traditional data exist. One specific area where traditional data are incomplete is the study of diurnal mood variations, or daily changes in individuals' overall mood state in relation to depression-like symptoms.The objective of this exploratory study was to analyze diurnal variations for interest in depression on the Web to discover hourly patterns of depression interest and help seeking.Hourly query volume data for 6 depression-related queries in Finland were downloaded from Google Trends in March 2017. A continuous wavelet transform (CWT) was applied to the hourly data to focus on the diurnal variation. Longer term trends and noise were also eliminated from the data to extract the diurnal variation for each query term. An analysis of variance was conducted to determine the statistical differences between the distributions of each hour. Data were also trichotomized and analyzed in 3 time blocks to make comparisons between different time periods during the day.Search volumes for all depression-related query terms showed a unimodal regular pattern during the 24 hours of the day. All queries feature clear peaks during the nighttime hours around 11 PM to 4 AM and troughs between 5 AM and 10 PM. In the means of the CWT-reconstructed data, the differences in nighttime and daytime interest are evident, with a difference of 37.3 percentage points (pp) for the term "Depression," 33.5 pp for "Masennustesti," 30.6 pp for "Masennus," 12.8 pp for "Depression test," 12.0 pp for "Masennus testi," and 11.8 pp for "Masennus oireet." The trichotomization showed peaks in the first time block (00.00 AM-7.59 AM) for all 6 terms. The search volumes then decreased significantly during the second time block (8.00 AM-3.59 PM) for the terms "Masennus oireet" (P<.001), "Masennus" (P=.001), "Depression" (P=.005), and "Depression test" (P=.004). Higher search volumes for the terms "Masennus" (P=.14), "Masennustesti" (P=.07), and "Depression test" (P=.10) were present between the second and third time blocks.Help seeking for depression has clear diurnal patterns, with significant rise in depression-related query volumes toward the evening and night. Thus, search engine query data support the notion of the evening-worse pattern in diurnal mood variation. Information on the timely nature of depression-related interest on an hourly level could improve the chances for early intervention, which is beneficial for positive health outcomes.

Project description:BackgroundWorldwide, the internet is an increasingly important channel for health information. Many theories have been applied in research on online health information seeking behaviors (HISBs), with each model integrating a different set of predictors; thus, a common understanding of the predictors of (online) HISB is still missing. Another shortcoming of the theories explaining (online) HISB is that most existing models, so far, focus on very specific health contexts such as cancer. Therefore, the assumptions of the Planned Risk Information Seeking Model (PRISM) as the latest integrative model are applied to study online HISB, because this model identifies the general cognitive and sociopsychological factors that explain health information seeking intention. We shift away from single diseases and explore cross-thematic patterns of online HISB intention and compare predictors concerning different health statuses as it can be assumed that groups of people perceiving themselves as ill or healthy will differ concerning their drivers of online HISB. Considering the specifics of online HISB and variation in individual context factors is key for the development of generalizable theories.ObjectiveThe objective of our study was to contribute to the development of the concept of online HISB in 2 areas. First, this study aimed to explore individual-level predictors of individuals' online HISB intention by applying the postulates of PRISM. Second, we compared relevant predictors of online HISB in groups of people with different health statuses to identify cross-thematic central patterns of online HISB.MethodsData from a representative sample of German internet users (n=822) served to explain online HISB intentions and influencing patterns in different groups of people. The applicability of the PRISM to online HISB intention was tested by structural equation modeling and multigroup comparison.ResultsOur results revealed PRISM to be an effective framework for explaining online HISB intention. For online HISB, attitudes toward seeking health information online provided the most important explanatory power followed by risk perceptions and affective risk responses. The multigroup comparison revealed differences both regarding the explanatory power of the model and the relevance of predictors of online HISB. The online HISB intention could be better explained for people facing a health threat, suggesting that the predictors adopted from PRISM were more suitable to explain a problem-driven type of information-seeking behavior.ConclusionsOur findings indicate that attitudes toward seeking health information online and risk perceptions are of central importance for online HISB across different health-conditional contexts. Predictors such as self-efficacy and perceived knowledge insufficiency play a context-dependent role-they are more influential when individuals are facing health threats and the search for health information is of higher personal relevance and urgency. These findings can be understood as the first step to develop a generalized theory of online HISB.

Dataset Information

The Causal Relationship Between Portal Usage and Self-Efficacious Health Information-Seeking Behaviors: Secondary Analysis of the Health Information National Trends Survey Data.

Background

Objective

Methods

Results

Conclusions

Publications

The Causal Relationship Between Portal Usage and Self-Efficacious Health Information-Seeking Behaviors: Secondary Analysis of the Health Information National Trends Survey Data.

Similar Datasets

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