Abstract
Background:
Technology access and use are increasing worldwide. Adults can potentially use technology to assist with health promotion and medical care.
Introduction:
The purpose of this study was to compare the prevalence of participation in online health-related activities between different genders of U.S. adults aged 18–90 years.
Methods:
Primary data collected through a survey panel were used to examine associations between gender and technology ownership, Internet health-seeking behaviors and online behaviors related to health, having an app, and preferences for health information. Data were collected through an online survey panel of U.S. adults (n = 400) in March 2017.
Results and Materials:
Almost 75% had ever looked for health information and 56.8% had searched for information in the past month. About one-third of both genders (34.1%) reported tracking any health indicator regularly, and 24% had a health app. Compared with males, females were more likely to have ever sought health information online and to have a mobile app for health. No significant differences were observed between gender and individual or total e-health literacy scores. The top three preferences for health sources were Web sites (81.3%), in person (72.0%), and then print materials (72.0%).
Conclusions:
This study illustrates that U.S. adults are using the Internet for health activities; however, females are more likely to engage in different e-health behaviors than males. Additional research could determine the causal factors behind these group differences in the use of online healthcare and health implications in public health practice for each group.
Introduction
Technology access and use are increasing worldwide. Adults can potentially use technology to assist with health promotion and medical care. E-health is defined as “health services and information delivered or enhanced through the Internet and related technologies.” 1 These services operate to empower consumers to increase their knowledge base and access to personal health records, encourage and enable multimodal patient and health professional communication, and offer education to consumers. 1 New technologies can also facilitate access to health information seeking, managing of personal health through different platforms (e.g., health system portals and electronic personal health records), and peer-to-peer healthcare. 2 –5
A majority (83%) of Internet users have used the Internet to search for health information, 6 and 62% of those who own a smartphone have used it to get information about a health condition. 7 Although associations between general health information seeking and gender have been reported in the literature, 3,6 –9 there still remains the need to study disparities in e-health use across different social groups to inform education and medical care. 10 –12 In addition, less is known about other e-health behaviors beyond health-seeking behaviors between genders. Differences in use of those behaviors can lead to disparities in prevention, accessing healthcare, and incidence of health conditions.
The purpose of this study was to explore gender differences in technology ownership, health information seeking, and other online behaviors related to health, monitoring of health indicators, use of a health app, and Internet health literacy in U.S. adults. It also assessed trust in information sources and preferences for health information. Finally, predictors of recent Internet health seeking and use of a health app were examined. These results could inform future public health and health systems' need to incorporate technology for health promotion and medical care.
Methods
The design of this study was a cross-sectional, Internet survey of U.S. adults. We recruited adults in the United States who (1) had Internet access and (2) spoke English. Participants were drawn from Lightspeed, an international, online consumer panel that recruits respondents by opt-in e-mails through multiple methods. Potential panelists must register with a unique e-mail address and password and complete an in-depth demographic registration. They were invited by e-mail to take the survey based on the aforementioned inclusion criteria. Participants were invited by e-mail to participate and complete the survey on a Health Insurance Portability and Accountability Act (HIPAA) complaint version of SurveyMonkey. For those interested, they read the informed consent and gave passive consent by clicking to begin the survey. No identifying information was given. Those who completed the survey were given points by Lightspeed. This study was approved by the Emory University Institutional Review Board.
Measures
Technology ownership of different devices (i.e., smartphone, computers, and so on), Internet access, and frequency of Internet use were assessed. 2,13,14 We then asked about monitoring of any health indicator, the method of tracking, and use of mobile apps for health. For health information seeking, participants were asked if they ever looked for health information online and looked for health information in the past month. These items were adopted from the Pew Health and Internet surveys. 2 –4 Participants reported health topics that they searched for in the past month. They also reported on other online activities that they did relate to health (e.g., watch health video, search for others with condition, and so on). Finally, participants indicated how they used the health information (e.g., had conversation with family, changed behavior, and made a decision about a condition).
E-health literacy was assessed using the e-health literacy scale (eHEALS). It is an eight-item self-reported measure of perceived e-health literacy. The tool assesses an individual's combined knowledge, comfort, and perceived skills at locating, evaluating, and applying electronic health information to health problems. Participants indicated their level of agreement with statements on a five-point Likert-type scale (1 = strongly disagree, 5 = strongly agree, and range: 8–40) with higher scores reflecting greater perceived levels of e-health literacy. Reported Cronbach's α coefficient of the tool is 0.88. 15 Participants also rated how useful the Internet is to making decisions about their health and the importance of accessing resources on the Internet. 15
For health resources, participants rated the extent to which they trust different sources of health information (i.e., Internet, television, and government agency) on a scale of 1 = not at all to 4 = a lot. Participants also indicated their preferences for receipt of health information from different sources (i.e., person, print, Web site, and so on). These items were adopted from the Health Information National Trends Survey (HINTS). 16
Demographic characteristics were assessed, including gender, race, Hispanic origin, income and educational level, employment status, income, having a chronic illness, and difficulty with reading. We also asked about their location in the United States and rurality of their residence.
Data Analyses
The collected data were downloaded from SurveyMonkey into an SPSS format for data analysis. All analyses were conducted in SPSS version 23.0. 17 Descriptive statistics were run and used to report the demographics of the participants, technology ownership, health information seeking, and e-health behaviors, as well as preferences for health resources. Differences among these variables and gender were run through chi square tests and independent sample t-tests. The range, mean score, and standard deviation were calculated for the perceived e-health literacy level. We computed a total score for the eHEALS scale and calculated a Cronbach's α to measure reliability of the total scale for the total sample and by gender. The difference between perceived levels of e-health literacy was examined through independent sample t-tests. To assess predictors of searching for health information in the past month and having a health app, odds ratios (ORs) with 95% Wald confidence intervals (CIs) were estimated using multivariate logistic regression models to assess these e-health behaviors app and respondent characteristics. Covariates in the models included gender, age, race/ethnicity, educational level, income group, marital status, presence of a chronic disease, and e-health literacy score. The level of significance for all tests was set at p < 0.05.
Results and Materials
Sample Characteristic
The panel participants were 50% of both genders with a range of ages between 18 and 90 (M = 50.7 ± 17.1). Race reflected the racial diversity of the United States, with 67.3% white, 19.0% black, and 13.8% other races (Table 1). About 19% were of Hispanic origin. They were mostly from the south, northwest, and west. The participants reported having some college or a college degree and 36.6% had incomes over $75,000. Many participants were married (50.5%) and lived in urban (34.3%) or suburban settings (50.1%). Thirty-seven percent reported having a chronic illness with the highest reported conditions being hypertension, high cholesterol, diabetes, arthritis, and asthma. There were only significant differences between the genders for employment (X 2(3) = 10.1, p < 0.05) and marital status (X 2(2) = 9.0, p < 0.05). A majority (82%) reported rarely or never having difficulty reading written materials.
Respondent Characteristics (n = 400)
p < 0.05.
M, mean; SD, standard deviation.
Technology Ownership and Access
Most owned laptops (72.0%) and smartphones (71.5%), followed by desktop computers, tablets, and DVD players (Table 1). Men reported owning desktop computers and game consoles significantly more than did women (X 2(1) = 14.1, p, 0.001) and X 2(1) = 8.56, p = 003, respectively). Most (92.8%) had access to a computer if they needed one. Over 93% reported going online most often at home. Almost all had access to the Internet (99.0%) and used the Internet several times a day (50.8%) or almost constantly (37.3%).
Health Information Seeking and Technology Use for Health
About one-third of both genders (34.1%) reported tracking any health indicator regularly (Table 2). Female participants were significantly more likely to ever have searched for health information on the Internet and to have searched in the past month than did males (80.5% vs. 69.0%, X 2(1) = 7.01, p = 0.008 and 56.8% vs. 43.2%, X 2(1) = 9.79, p = 0.002, respectively). The top five topics searched were for diet or nutrition, exercise, medicines, quick remedies, and health diseases. Females significantly reported higher use of health applications than did males (29.0% vs. 19.0%). They also were more likely to have apps related to exercise and diet than their male counterparts. About 65% looked for information for themselves the last time they searched the Internet, with males reporting doing so more often than females (72.3% vs. 59.0%). Participants reported looking for health information about 3 times in the past month. Other reported health activities on the Internet reported among a quarter or more of the participants included reading someone else's experience with a health issue (35.8%), watching an online video about health (30.7%), finding others who have a similar health condition (25.3%), and signing up to receive e-mail updates (23.4%).
Health Monitoring, Information Seeking, and Other e-Health Behaviors by Gender (n = 400)
p < 0.05.
M, mean; SD, standard deviation.
e-Health Literacy
Generally, both genders reported similar perceived skills in using the Internet for health information; there were no significant differences between genders among the eHEALS items or the composite score (Table 3). The total score was 29.91 (±5.98) overall; it was 30.11 (±5.98) for females and 29.69 (±5.98) for males. They reported higher confidence in knowing how to find helpful health resources (M = 3.87 ± 0.87), how to use the Internet to answer health questions (M = 3.86 ± 0.83), how to use health information to help themselves (M = 3.84 ± 0.90), and where to find helpful health resources (M = 3.83 ± 0.88). The lowest confident scores were for telling high-quality from low-quality information (M = 3.56 ± 0.94) and using information from the Internet to make health decisions (M = 3.55 ± 0.94). The scale had high internal consistency with a Cronbach's α of 0.936. The internal consistency was slightly higher for females versus males.
e-Health Literacy and Attitudes About the Internet by Gender (n = 400)
1 = strongly disagree to 5 = strongly agree.
1 = not useful at all to 5 = very useful.
1 = not important at all to 4 = very important.
eHEALS, e-health literacy scale.
Health Information Resources
Participants reported trusting doctors (M = 3.53 ± 0.79), the Internet (M = 2.78 ± 0.78), and government agencies (M = 2.74 ± 0.93) the most (Table 4). Females reported significantly higher trust in the Internet than did males (t(395) = −2.07, p = 0.039). Overall, the preferred sources of health information were similar across both genders. The top three sources selected were Web sites (81.3%), in person (72.0), and then print materials (72.0%). Smaller proportions selected using mobile apps (12.8%) and social media (10.5%).
Trust in Health Sources and Preferences for Information by Gender (n = 400)
p < 0.05.
1 = not at all to 4 = a lot.
Predictors of Having Sought Health Information Online in the Past Month and an M-Health App
Logistic regressions were performed to ascertain the effects of demographic factors, having a chronic illness and e-health literacy score on the likelihood that participants sought health information in the past month and had a health-related app (Table 5). As seen from the results, those who were male and older were less likely to have sought health information online in the past month and have an m-health app. Adults who were married were more likely to have sought health information than those who were in a relationship and those who were single or divorced/widowed. Higher e-health literacy scores were associated with these e-health behaviors. Increasing income was associated with a reduction in chance of having a health app. Specifically, those who had an income of $25,000–$49,999 were 2.7 times more likely (OR: 2.69; CI: 1.07–6.75), those who had $50,000–$74,999 in income were 3.0 times as more likely (OR: 3.03; CI: 1.14–8.10), and those with $75,000 or more in income were 3.5 times more likely (OR: 3.45; CI: 1.36–8.73) to have a health app than those with an income of <$25,000.
Results of Logistic Regression Models Predicting Having Looked Online for Health Information in the Past Month and a Health App
CI, confidence interval; OR, odds ratio.
Discussion
We found that, overall, adults are going to the Internet for information seeking. Both males and females have similar trust in health information and health education preferences; however, adult females were more likely to have ever engaged in ever or recent Internet health-seeking behaviors and to possess a health app. Other studies have found that women are more likely than men to search for health information. 2,9,18 Women may be more activated for health and tend to seek confirmation on health issues by using several sources, often using the Internet with the advice of healthcare providers, family, and friends. 19 Another possible explanation is that women are caregivers and, therefore, are more likely to assume responsibility for the health of others. Caregivers are more likely to interact with health online than other Internet users. 3
Almost a quarter of our adults were interested in health behavior topics such as diet and physical activity, while 20% were interested in more information about medications. Over a third of the adults were tracking a health indicator, which is a sign of patient activation toward health and fitness. Only 13% reported tracking a health indicator by an app, while 10% reported tracking by a Web site, and 9% with a wearable device. As wearable devices become more common in society, these proportions will likely increase in the future. Similar to a recent study, we found that 72% of our sample had a smartphone; Anderson reported that 68% had a smartphone in 2015. 13 Again, we found that females were more likely to have a health app than males as reported in other studies. 9,20 Smartphone-based health technologies can support patient education and self-management, healthcare communication, and symptom or behavioral monitoring. 21,22 Their future potential for health education and patient care is still evolving.
Even though the e-health literacy skills were relatively high in our sample, they reported lower confidence in assessing the quality of information on the Internet and also using it to make health decisions. Health educators and healthcare providers could help educate consumers on authoritative Web sites or could suggest recommended sites that have more reliable information. Interestingly, after Web sites, our sample of adults preferred information in person and in print. This suggests that perhaps multimodal forms of information may be preferential for patients and consumers to receive health information. In addition, although we did not find that racial groups differ on the use of e-health behaviors, other demographic factors may also impact e-health adoption and use. Therefore, other options for health sources are still needed. 23
Adults reported engaging in other e-health behaviors, particularly around finding others with the same health condition and reading about their experiences with health issues. There are many virtual communities for health in existence for a range of health topics 24 –26 ; it is not surprising that some adults are participating in these electronic support groups to seek assistance or experiences with health behaviors or conditions. In addition, adult consumers are being activated by health information seeking. Over 25% changed their health behavior and visited a provider. Furthermore, over one-third talked to their doctors after seeking information online demonstrating that they are going online to be actively involved in the decision-making related to their health. Chung found that patients reported a better patient–physician relationship when they had the opportunity to discuss their online health information with their healthcare providers, and the providers were receptive to discussing the online information. 27
The study findings indicate that age and e-health literacy remain relevant barriers to general access to health information on the Internet and having a health app. In addition, socioeconomic status (SES) defined by income level is an additional barrier to having a health app. Wangberg et al. reported that online health consumers tend to be more educated, earn more, and have better access to high-speed Internet; therefore, it is not surprising that having and using health apps is limited by income and ability to purchase a smartphone. 12 This finding is consistent with other studies that have found a digital divide with having a mobile health app and income. 12,28,29 Furthermore, these findings validated findings from Kontos et al. that lower SES, older, and male online U.S. adults are less likely to engage in a number of e-health activities compared with their counterparts. 11 As smartphones become more widespread and if healthcare providers could encourage supports for health behaviors or conditions, including e-health, then more adults will have the potential to be more informed about health and can use technology-mediated supports. This premise is recommended by the Expanded Chronic Care Model that posits that clinical and information systems with self-management (education and skills training) and community resources (referral to community program and services) can affect clinical outcomes. 30 Extending the reach and use of effective e-health intervention can impact health outcomes. 5,31,32
There are several limitations to the study. First, the sample may have selection biases since the panel might not be representative of all U.S. adults. However, we attempted to recruit a cross section of the population across gender, racial, ethnic, and educational groups. Second, the data are all based on self-report. Third, for the logistic regressions, we included only key demographic characteristics and e-health literacy scores as covariates. There may be other variables that could contribute to the variance explained in predicting these technology and health behaviors. The eHEALS is limited to skillsets related to using e-health and may have to be updated with other competencies related to mobile apps and social media. 33 Finally, although we found some of the significant associations between the covariates and Internet health-seeking behaviors and having a health app, these cannot be interpreted as casual relationships.
The study presents current technology ownership, e-health literacy, information seeking, e-health behaviors, and impacts of e-health information seeking among a sample of U.S. adults. The observed higher information seeking and use of health apps among female adults may reflect differences in overall interest in health. Healthcare providers and educators could promote health information seeking and tracking among male patients and consumers. Further studies are warranted to understand specific needs of males related to information seeking and how to engage them in more health-seeking practices.
Footnotes
Disclosure Statement
No competing financial interests exist.