Toward Comprehensive Health Literacy Assessment for Online Health Information: Assessing Falls Prevention Websites Designed for Older Adults and Their Caregivers

2015 ◽  
Vol 3 (2) ◽  
pp. 20-27
Author(s):  
Nichole Egbert ◽  
Phillip R. Reed
Keyword(s):  
Older Adults ◽  
Health Literacy ◽  
Health Information ◽  
Falls Prevention ◽  
Online Health Information ◽  
Literacy Assessment ◽  
Comprehensive Health

scholarly journals Relationship Between Levels of Digital Health Literacy Based on the Taiwan Digital Health Literacy Assessment and Accurate Assessment of Online Health Information: Cross-Sectional Questionnaire Study (Preprint)

2020 ◽  
Author(s):  
Peggy Liu ◽  
Ling-Ling Yeh ◽  
Jiun-Yi Wang ◽  
Shao-Ti Lee
Keyword(s):  
Health Literacy ◽  
High Risk ◽  
Health Information ◽  
Digital Health ◽  
Characteristic Curve ◽  
Risk Groups ◽  
The Internet ◽  
Online Health Information ◽  
Literacy Assessment ◽  
Information Bank

BACKGROUND The increasing amount of health information available on the internet makes it more important than ever to ensure that people can judge the accuracy of this information to prevent them from harm. It may be possible for platforms to set up protective mechanisms depending on the level of digital health literacy and thereby to decrease the possibility of harm by the misuse of health information. OBJECTIVE This study aimed to create an instrument for digital health literacy assessment (DHLA) based on the eHealth Literacy Scale (eHEALS) to categorize participants by level of risk of misinterpreting health information into high-, medium-, and low-risk groups. METHODS This study developed a DHLA and constructed an online health information bank with correct and incorrect answers. Receiver operating characteristic curve analysis was used to detect the cutoff value of DHLA, using 5 items randomly selected from the online health information bank, to classify users as being at low, medium, or high risk of misjudging health information. This provided information about the relationship between risk group for digital health literacy and accurate judgement of online health information. The study participants were Taiwanese residents aged 20 years and older. Snowball sampling was used, and internet questionnaires were anonymously completed by the participants. The reliability and validity of DHLA were examined. Logistic regression was used to analyze factors associated with risk groups from the DHLA. RESULTS This study collected 1588 valid questionnaires. The online health information bank included 310 items of health information, which were classified as easy (147 items), moderate (122 items), or difficult (41 items) based on the difficulty of judging their accuracy. The internal consistency of DHLA was satisfactory (α=.87), and factor analysis of construct validity found three factors, accounting for 76.6% of the variance. The receiver operating characteristic curve analysis found 106 people at high risk, 1368 at medium risk, and 114 at low risk of misinterpreting health information. Of the original grouped cases, 89.6% were correctly classified after discriminate analysis. Logistic regression analysis showed that participants with a high risk of misjudging health information had a lower education level, lower income, and poorer health. They also rarely or never browsed the internet. These differences were statistically significant. CONCLUSIONS The DHLA score could distinguish those at low, medium, and high risk of misjudging health information on the internet. Health information platforms on the internet could consider incorporating DHLA to set up a mechanism to protect users from misusing health information and avoid harming their health.

Age and Neurocognition Are Associated With Credibility Evaluations of Health Websites

2021 ◽  
Author(s):  
Michelle A. Babicz ◽  
Samina Rahman ◽  
Victoria Kordovski ◽  
Savanna Tierney ◽  
Steven Paul Woods
Keyword(s):  
Older Adults ◽  
Health Literacy ◽  
Health Information ◽  
Age Groups ◽  
The Internet ◽  
Online Health Information ◽  
Younger Adults ◽  
Neurocognitive Functions ◽  
Credibility Rating ◽  
Future Work

The internet has become a common means by which many older adults seek out health information. The prevalence of misinformation on the internet makes the search for accurate online health information a more complex and evaluative process. This study examined the role of age and neurocognition in credibility evaluations of credible and non-credible health websites. Forty-one older adults and fifty younger adults completed a structured credibility rating task in which they evaluated a series of webpages displaying health information about migraine treatments. Participants also completed measures of neurocognition, internet use, and health literacy. Results suggested that older adults rated non-credible health websites as more credible than younger adults, but the age groups did not differ in their ratings of credible sites. Within the full sample, neurocognition was positively associated with credibility ratings for non-credible health websites, whereas health literacy was related to the ratings of credible sites. Findings indicate that older adults may be more likely to trust non-credible health websites than younger adults, which may relate to differences in higher-order neurocognitive functions. Future work might examine whether cognitive-based supports for credibility training in older adults can be used to improve the accuracy with which they evaluate online health information.

scholarly journals Relationship Between Levels of Digital Health Literacy Based on the Taiwan Digital Health Literacy Assessment and Accurate Assessment of Online Health Information: Cross-Sectional Questionnaire Study

10.2196/19767 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e19767
Author(s):  
Peggy Liu ◽  
Ling-Ling Yeh ◽  
Jiun-Yi Wang ◽  
Shao-Ti Lee
Keyword(s):  
Health Literacy ◽  
High Risk ◽  
Health Information ◽  
Digital Health ◽  
Characteristic Curve ◽  
Risk Groups ◽  
The Internet ◽  
Online Health Information ◽  
Literacy Assessment ◽  
Information Bank

Background The increasing amount of health information available on the internet makes it more important than ever to ensure that people can judge the accuracy of this information to prevent them from harm. It may be possible for platforms to set up protective mechanisms depending on the level of digital health literacy and thereby to decrease the possibility of harm by the misuse of health information. Objective This study aimed to create an instrument for digital health literacy assessment (DHLA) based on the eHealth Literacy Scale (eHEALS) to categorize participants by level of risk of misinterpreting health information into high-, medium-, and low-risk groups. Methods This study developed a DHLA and constructed an online health information bank with correct and incorrect answers. Receiver operating characteristic curve analysis was used to detect the cutoff value of DHLA, using 5 items randomly selected from the online health information bank, to classify users as being at low, medium, or high risk of misjudging health information. This provided information about the relationship between risk group for digital health literacy and accurate judgement of online health information. The study participants were Taiwanese residents aged 20 years and older. Snowball sampling was used, and internet questionnaires were anonymously completed by the participants. The reliability and validity of DHLA were examined. Logistic regression was used to analyze factors associated with risk groups from the DHLA. Results This study collected 1588 valid questionnaires. The online health information bank included 310 items of health information, which were classified as easy (147 items), moderate (122 items), or difficult (41 items) based on the difficulty of judging their accuracy. The internal consistency of DHLA was satisfactory (α=.87), and factor analysis of construct validity found three factors, accounting for 76.6% of the variance. The receiver operating characteristic curve analysis found 106 people at high risk, 1368 at medium risk, and 114 at low risk of misinterpreting health information. Of the original grouped cases, 89.6% were correctly classified after discriminate analysis. Logistic regression analysis showed that participants with a high risk of misjudging health information had a lower education level, lower income, and poorer health. They also rarely or never browsed the internet. These differences were statistically significant. Conclusions The DHLA score could distinguish those at low, medium, and high risk of misjudging health information on the internet. Health information platforms on the internet could consider incorporating DHLA to set up a mechanism to protect users from misusing health information and avoid harming their health.

scholarly journals Lifestyle Segmentation to Explain the Online Health Information–Seeking Behavior of Older Adults: Representative Telephone Survey

10.2196/15099 ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. e15099 ◽  
Author(s):  
Winja Weber ◽  
Anne Reinhardt ◽  
Constanze Rossmann
Keyword(s):  
Older Adults ◽  
Health Information ◽  
Information Seeking ◽  
Internet Use ◽  
Information Seeking Behavior ◽  
The Internet ◽  
Online Health Information ◽  
Sociodemographic Variables ◽  
Seeking Behavior ◽  
Health Related

Background As a result of demographic changes, the number of people aged 60 years and older has been increasing steadily. Therefore, older adults have become more important as a target group for health communication efforts. Various studies show that online health information sources have gained importance among younger adults, but we know little about the health-related internet use of senior citizens in general and in particular about the variables explaining their online health-related information–seeking behavior. Media use studies indicate that in addition to sociodemographic variables, lifestyle factors might play a role in this context. Objective The aim of this study was to examine older people’s health-related internet use. Our study focused on the explanatory potential of lifestyle types over and above sociodemographic variables to predict older adults’ internet use for health information. Methods A telephone survey was conducted with a random sample of German adults aged 60 years and older (n=701) that was quota-allocated by gender, age, educational status, and degree of urbanity of their place of residence. Results The results revealed that participants used the internet infrequently (mean 1.82 [SD 1.07]), and medical personnel (mean 2.89 [SD 1.11]), family and friends (mean 2.86 [SD 1.21]), and health brochures (mean 2.85 [SD 1.21]) were their main sources of health information. A hierarchical cluster analysis based on values, interests, and leisure time activities revealed three different lifestyle types for adults aged over 60 years: the Sociable Adventurer, the Average Family Person, and the Uninterested Inactive. After adding these types as second-step predictors in a hierarchical regression model with sociodemographic variables (step 1), the explained variance increased significantly (R2=.02, P=.001), indicating that the Average Family Person and the Sociable Adventurer use the internet more often for health information than the Uninterested Inactive, over and above their sociodemographic attributes. Conclusions Our findings indicate that the internet still plays only a minor role in the health information–seeking behavior of older German adults. Nevertheless, there are subgroups including younger, more active, down-to-earth and family-oriented males that may be reached with online health information. Our findings suggest that lifestyle types should be taken into account when predicting health-related internet use behavior.

An examination of the quality of late-life depression websites on the Internet (Preprint)

2022 ◽  
Author(s):  
Teaghan Pryor ◽  
Kristin Reynolds ◽  
Paige Kirby ◽  
Matthew Bernstein
Keyword(s):  
Mental Health ◽  
Older Adults ◽  
Health Literacy ◽  
Health Information ◽  
Mental Health Literacy ◽  
Late Life ◽  
The Internet ◽  
Late Life Depression ◽  
Mental Health Information

BACKGROUND The Internet can increase the accessibility of mental health information and improve the mental health literacy of older adults. The quality of mental health information on the Internet can be inaccurate or biased, leading to misinformation OBJECTIVE This study’s objectives were to evaluate the quality, usability, and readability of websites providing information concerning depression in later life. METHODS Websites were identified through a Google search, and evaluated by assessing quality (DISCERN), usability (Patient Education Materials Assessment Tool; PEMAT) and readability (Simple Measure of Gobbledygook; SMOG). RESULTS The overall quality of late-life depression websites (N = 19) was moderate, usability was low, and readability was poor. No significant relationship was found between quality and readability of websites. CONCLUSIONS Websites can be improved by enhancing information quality, usability, and readability related to late-life depression. The use of high-quality websites may improve mental health literacy and shared treatment decision-making for older adults.

scholarly journals Literacy, Numeracy, and Health Information Seeking Among Middle-Aged and Older Adults in the United States

2018 ◽  
Vol 32 (1-2) ◽  
pp. 33-41 ◽  
Author(s):  
Takashi Yamashita ◽  
Anthony R. Bardo ◽  
Darren Liu ◽  
Phyllis A. Cummins
Keyword(s):  
United States ◽  
Older Adults ◽  
Health Literacy ◽  
Health Information ◽  
Health Care Providers ◽  
Information Seeking ◽  
The United States ◽  
Health Information Seeking ◽  
Care Providers ◽  
Nationally Representative

Objectives: Health literacy is often viewed as an essential skill set for successfully seeking health information to make health-related decisions. However, this general understanding has yet to be established with the use of nationally representative data. The objective of this study was to provide the first nationally representative empirical evidence that links health information seeking behaviors with health literacy among middle-age to older adults in the United States. Methods: Data were obtained from the 2012/2014 Program for the International Assessment of Adult Literacy (PIAAC). Our analytic sample is representative of adults age 45 to 74 years ( N = 2,989). Results: Distinct components of health literacy (i.e., literacy and numeracy) were uniquely associated with the use of different health information sources (e.g., health professionals, the Internet, television). Discussion: Findings should be useful for government agencies and health care providers interested in targeting health communications, as well as researchers who focus on health disparities.

scholarly journals Simple scoring algorithm to identify community-dwelling older adults with limited health literacy: a cross-sectional study in Taiwan

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e045411
Author(s):  
Wen-Hsuan Hou ◽  
Ken N Kuo ◽  
Mu-Jean Chen ◽  
Yao-Mao Chang ◽  
Han-Wei Tsai ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Literacy ◽  
High Risk ◽  
Health Information ◽  
Cross Sectional Study ◽  
Community Dwelling ◽  
Sectional Study ◽  
Cross Sectional ◽  
Scoring Algorithm ◽  
Community Dwelling Older Adults

ObjectiveHealth literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a high risk of limited HL.DesignA cross-sectional study.SettingFour communities in northern, central and southern Taiwan.ParticipantsA total of 648 older adults were included. Moreover, 85% of the core data set was used to generate the prediction model for the scoring algorithm, and 15% was used to test the fitness of the model.Primary and secondary outcome measuresPearson’s χ2 test and multiple logistic regression were used to identify the significant factors associated with the HL level. An optimal cut-off point for the scoring algorithm was identified on the basis of the maximum sensitivity and specificity.ResultsA total of 350 (54.6%) patients were classified as having limited HL. We identified 24 variables that could significantly differentiate between sufficient and limited HL. Eight factors that could significantly predict limited HL were identified as follows: a socioenvironmental determinant (ie, dominant spoken dialect), a health service use factor (ie, having family doctors), a health cost factor (ie, self-paid vaccination), a heath behaviour factor (ie, searching online health information), two health outcomes (ie, difficulty in performing activities of daily living and requiring assistance while visiting doctors), a participation factor (ie, attending health classes) and an empowerment factor (ie, self-management during illness). The scoring algorithm yielded an area under the curve of 0.71, and an optimal cut-off value of 5 represented moderate sensitivity (62.0%) and satisfactory specificity (76.2%).ConclusionThis simple scoring algorithm can efficiently and effectively identify community-dwelling older adults with a high risk of limited HL.

scholarly journals Lifestyle Segmentation to Explain the Online Health Information–Seeking Behavior of Older Adults: Representative Telephone Survey (Preprint)

2019 ◽  
Author(s):  
Winja Weber ◽  
Anne Reinhardt ◽  
Constanze Rossmann
Keyword(s):  
Older Adults ◽  
Health Information ◽  
Information Seeking ◽  
Internet Use ◽  
Information Seeking Behavior ◽  
The Internet ◽  
Online Health Information ◽  
Sociodemographic Variables ◽  
Seeking Behavior ◽  
Health Related

BACKGROUND As a result of demographic changes, the number of people aged 60 years and older has been increasing steadily. Therefore, older adults have become more important as a target group for health communication efforts. Various studies show that online health information sources have gained importance among younger adults, but we know little about the health-related internet use of senior citizens in general and in particular about the variables explaining their online health-related information–seeking behavior. Media use studies indicate that in addition to sociodemographic variables, lifestyle factors might play a role in this context. OBJECTIVE The aim of this study was to examine older people’s health-related internet use. Our study focused on the explanatory potential of lifestyle types over and above sociodemographic variables to predict older adults’ internet use for health information. METHODS A telephone survey was conducted with a random sample of German adults aged 60 years and older (n=701) that was quota-allocated by gender, age, educational status, and degree of urbanity of their place of residence. RESULTS The results revealed that participants used the internet infrequently (mean 1.82 [SD 1.07]), and medical personnel (mean 2.89 [SD 1.11]), family and friends (mean 2.86 [SD 1.21]), and health brochures (mean 2.85 [SD 1.21]) were their main sources of health information. A hierarchical cluster analysis based on values, interests, and leisure time activities revealed three different lifestyle types for adults aged over 60 years: the Sociable Adventurer, the Average Family Person, and the Uninterested Inactive. After adding these types as second-step predictors in a hierarchical regression model with sociodemographic variables (step 1), the explained variance increased significantly (<i>R</i><sup>2</sup>=.02, <i>P</i>=.001), indicating that the Average Family Person and the Sociable Adventurer use the internet more often for health information than the Uninterested Inactive, over and above their sociodemographic attributes. CONCLUSIONS Our findings indicate that the internet still plays only a minor role in the health information–seeking behavior of older German adults. Nevertheless, there are subgroups including younger, more active, down-to-earth and family-oriented males that may be reached with online health information. Our findings suggest that lifestyle types should be taken into account when predicting health-related internet use behavior.

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