Health information can be collected through platforms outside of traditional healthcare settings. Examples of these platforms include personal health records, web portals, and mobile health applications. On the personal level, health literacy is the degree to which individuals can find, understand, and use information and services to inform health-related decisions and actions for themselves and others. Individuals with low health literacy will have difficulty understanding and utilizing these platforms or services to their fullest potential in self-management and improving health outcomes.
The purpose of this literature review is to identify gaps in the current landscape of direct-to-consumer health literacy interventions. The findings will be used to inform future interventions.
- Individuals with lower incomes and educational attainment are the least likely group to seek out assistance with health literacy.
- Consumers with chronic diseases are common users of electronic healthcare services.
- Direct-to-consumer health literacy interventions are shifting toward mobile health applications.
- Direct-to-consumer health literacy interventions are transitioning to a community-based participatory research approach.
- There is a lack of follow-up in direct-to-consumer health literacy interventions to assess retention of electronic health tools or clinically significant change in health outcomes.
Consumers can generate health data and obtain health information across multiple, digital platforms beyond the traditional healthcare settings.1 These platforms fall under the umbrella of eHealth, which can be defined as “cost-effective and secure use of information and communication technologies (ICT) in support of health and health-related fields”.2 Examples of ICT outside of the traditional healthcare setting include untethered personal health records (PHR), web portals, and mobile health (mHealth) tools. In recent times, mobile technology is commonly used in eHealth due to its ease of access for consumers in terms of portability and usability.3 mHealth can now be considered a subset of eHealth, which involves tools such as applications found on smartphones, tablets, and computers.4
Health literacy can be described as “the degree to which individuals have the ability to find, understand, and use information and services to inform health-related decisions and actions for themselves and others”.5 Low levels of health literacy have been linked to poor health outcomes, so it is important that individuals have sufficient health literacy when using eHealth.6
A well-known health literacy intervention is the teach-back method. Healthcare professionals use this method to ensure patients understand their treatment plan and/or diagnosis.7 Other health literacy interventions come in the form of eHealth through direct-to-consumer models.8 However, there is limited knowledge about eHealth and its impact on health literacy levels in various populations.9 Thus, understanding the current landscape of direct-to-consumer health literacy interventions will allow for future development of interventions for users with varying degrees of health literacy.
A literature review was conducted to understand the current landscape of studies on direct-to-consumer health literacy interventions. The literature review will attempt to answer several research questions about health literacy:
- What factors drive consumers to determine they need assistance with their health literacy?
- Where do consumers turn to find help with health literacy?
- What health literacy resources exist outside of the provider settings? If they exist, how do they operate to meet consumers’ needs?
- What gaps in direct-to-consumer health literacy are unanswered?
In this study, a search strategy was created to search for relevant articles. The search period lasted from September 2, 2021, to September 15, 2021. From the research questions, key concepts identified as relevant for the literature review analysis included mobile technology, personal health information, health literacy, self-efficacy, and personal health records. These key terms were used to construct search terms to find relevant publications. The search terms were finalized based on input from a medical librarian at the Texas Medical Center Library. PubMed was chosen as the sole database, as it contains millions of full-text articles from life sciences and biomedical science journals. Duplicate publications were removed using Zotero’s duplication finder. During the full-text review and analysis process, additional relevant articles were identified through forward snowballing.
Only articles within the last 10 years were included in the study’s evaluation process. After the duplicate articles were removed, the titles and abstracts were screened based on an inclusion/exclusion criterion for relevance. Articles were deemed relevant if they tracked health literacy scores or health-related scores/parameters or self-efficacy, the basis of the study revolved around personal health management or self-management or self-efficacy in relation to health promotion and health education concepts or health literacy, and the interaction was performed outside of the traditional healthcare setting such as interactions with one’s healthcare provider. This same screening criteria was utilized during the full-text review. Many articles were excluded because usability principles in mobile application design were the primary objective of the study. Other studies were excluded if they included interaction with doctors as part of the intervention or tethered personal health records and patient portals were used in the study, as these tools are connected to a medical organization’s electronic health record (EHR) system. The only exception to this rule is when a study involves the use of an untethered PHR where an individual has the choice to integrate their personal health record into a medical organization’s EHR system.
Full-text articles were reviewed in an ascending chronological order with column topics using the Matrix Method, which involved the construction of a matrix with column topics such as: title, purpose, variable(s), methodological design, number of subjects, sampling design, results, and significance of the article in relation to the objective of the literature review.10 Figure 1 depicts the flow of the documents throughout the review in a PRISMA Flow diagram.11
A total of 712 articles were identified from the initial search strategy. Eighteen of these articles were duplicates. Zotero was used to remove the duplicate articles, and 19 additional articles were found through forward snowballing. A total of 713 records were screened using the inclusion/exclusion criteria. After screening the title/abstracts, 104 articles were determined to meet the criteria for full-text assessment. A total of 74 full-text articles were excluded after the full-text assessment, leaving 30 articles included in the final review. Table 1 summarizes the type of research approach and study design for the 30 studies. 12–41
Twenty-two of these studies were quantitative studies, five studies were qualitative studies, and three studies were mixed-methods studies. From the 24 quantitative studies, eight of the studies were cross-sectional studies; 10 studies were randomized controlled trials; two studies were a pre-test, post-test study; one study was a longitudinal study; and one study was a non-randomized controlled trial. From the five qualitative studies, four of the studies were thematic analysis through oral communication (focus groups and interviews), and one study was a content analysis. From the three mixed-methods studies, one study was a prospective study, one study was a feasibility study, and one was an exploratory sequential mixed-methods study design. The 30 studies were analyzed for broad areas or themes. Eight themes were identified, and the themes are presented in the following subsections titled accordingly to the research questions.
What Factors Drive Consumers to Determine They Need Assistance With Their Health Literacy?
Theme 1: Individuals with low incomes and educational attainment are the least likely group to seek out assistance with health literacy.
Two cross-sectional studies examined the association between demographic and/or socioeconomic factors with the usage of eHealth or health-related seeking behavior on the Internet.20,25,30 One study found older males (>65 years old) with a low socioeconomic (defined by education and income) status were the least likely group be associated with eHealth activities such as tracking personal health information online, looking for health information online, or utilizing an online social support group compared to counterpart groups such as women, 18-34 year old adults, and high SES adults.20 Another cross-sectional study reported individuals with low SES were least likely to engage in using the internet to search for health information.25 In the same study, the researchers reported individuals who did use personal health information management tools were more likely to engage in eHealth activities. Lastly, another cross-sectional study found individuals who were young, college-educated, or have high family incomes use personal health management (PHM) tools (text messaging services, scheduling appointments online, and refilling prescriptions online) more than their counterpart groups.34
Other studies targeted specific populations researchers thought to be considered low SES status such as disadvantaged mothers and pregnant women, rural communities, undernourished communities, and underserved communities.17,26,29 For example, researchers created a mHealth intervention targeting Type 2 diabetic individuals in rural communities using a pre-test, post-test study design.26 The two-week mHealth intervention consisted of diabetes self-management videos accompanied with quizzes, reminders, and a diabetes dictionary. Results from this study were improvements in scores for Rapid Estimate of Adult Literacy in Medicine (REALM), which measures health literacy; Diabetes Knowledge Test, which measures diabetes knowledge; and Diabetes Self-Efficacy Scale, which measures diabetes self-efficacy. The researchers noted these changes were clinically significant.
Theme 2: Consumers with chronic diseases are common users of electronic healthcare services.
A key finding was individuals who are frequent users of healthcare or are managing a chronic condition are common users of electronic healthcare services. One cross-sectional study measured hypertension prevalence and its association with personal health information management. The researchers found adults who reported a hypertension diagnosis were more likely to conduct health-related searches than adults who did not have a hypertension diagnosis.25 Another cross-sectional study found the proportion of individuals who reported either a single chronic condition or multiple chronic conditions used PHM tools (text messaging services, scheduling appointments online, and refilling prescriptions online) significantly more than individuals with no chronic conditions.34 Among those with multiple chronic conditions, those who reported “Good/Excellent” health status were more likely to use PHM tools than those who reported “Fair/Poor” health status. This observation was seen in the aforementioned cross-sectional study as well.25
Although some studies did target the general population, many studies looked at populations with chronic diseases. Examples of these chronic diseases are hypertension, diabetes, pediatric cancer, HIV/AIDS, and breast cancer.13,16,19,22,24,26,32,33,37,40 For one of these studies, the researchers conducted a randomized controlled trial mHealth intervention for persons living with HIV (PLWH).37 The intervention group received a customized PHR for PLWH and received educational sessions on HIV literacy and eHealth competency skills. Researchers reported the intervention group showed significantly greater improvements in Patient Activation Measure (PAM), which measures patient activation, and eHEALS, which measures eHealth literacy, than the control group.
Theme 3: Major barriers to eHealth for current and potential consumers are concerns about privacy.
Nine studies reported consumer’s concern about privacy related to sharing health information data through eHealth.13,21,23,24,28,28–31,36 Consumers were generally fearful about their privacy. Key findings concluded that consumers are concerned their confidentiality could be breached or that sensitive personal health information was not safe from hackers. One study examined potential barriers to implementation of a personal health information management system, and the researchers found individuals who reported discomfort about the use of technology or the security of online health information were less likely to believe PHM systems would help achieve one’s health goals compared to individuals who are comfortable with using technology or the security of online health information.30 Assurances about online data being secure would be beneficial and needed before engaging with an eHealth tool. However, some studies did find individuals were willing to use an eHealth tool despite their concerns about security and privacy.24,28 In one study, Type 2 diabetic individuals were given a PHR for three to six months.24 The researchers interviewed the individuals about their usage at follow-up visits. Very few participants expressed privacy, which was surprising to the researchers in which they argued the participants accepted potential positive gains regarding PHR usage despite security and privacy risks. Another study in postpartum women and their opinion about PHR usage through a mobile device identified a minority (20 percent of the total participants) group of women who were concerned about privacy and security.28 However, 93.8 percent of individuals who reported privacy concerns were still interested in using a PHR. The researchers did not offer an argument for this observation, but they noted the high interest suggests PHRs are an underutilized tool.
Where Do Consumers Turn to Find Help With Health Literacy?
Theme 4: Consumers utilize the internet and provider interactions rather than eHealth tools to search for health-related information.
A few studies looked at consumer engagement with digital health technology in health-related information searches.18,29,31 Key findings were that consumers prefer using the internet (e.g. Google, YouTube, and Facebook) or found helpful information in patient forums or online support groups. In one study with disadvantaged mothers and pregnant women, participants valued face-to-face contact more than the use of patient portals or text messaging systems.29 Another study found college aged individuals using a personally controlled health management system identified the poll and forum as the most engaging and useful feature of the system.18 Old consumers who did engage in health-seeking behavior on the internet reported they had trouble identifying credible and trustworthy sources.31
What Health Literacy Resources Exist Outside of the Provider Settings? If They Exist, How Do They Operate to Meet Consumers’ Needs?
Theme 5: Direct-to-consumer health literacy interventions are shifting toward mHealth applications.
Appendix A summarizes the study and results of the direct-to-consumer health literacy interventions.12,15–19,22,24,26,27,32,33,35,35,37–41 Unless stated otherwise, the subjects were based in the United States. In recent times, the technology medium has shifted from web portals and computer-based resources (eHealth) to smartphones (mHealth). Some of these tools involved instructor-based methodology (e.g., virtual advisor, researcher-led educational sessions, and expert support) while other tools were used as a stand-alone resource, which included educational modules and/or videos accompanying the modules. 12,15–19,22,24,26,27,32,33,35,35,37–41
Theme 6: Direct-to-consumer health literacy interventions are transitioning to a community-based participatory research approach.
Previous research did not mention the involvement of participants during the eHealth development process.12,15–19,22,24,26,27,32,33,35,39,40 Over time, the researchers deliberately involved the target audience in developing the technology through a study methodology known as community-based participatory research (CBPR).17,37,38,41 One direct-to-consumer health literacy intervention targeting insurance health literacy in ethnic minority groups developed a partnership with organizations involved in Affordable Care Act outreach.38 The partnership worked together to develop a website and video series designed to improve health insurance literacy. Contents of the website were developing using findings from focus groups with participants. The researchers reported intervention participants had an improved knowledge of health insurance eligibility, higher self-efficacy, and intention to seek help with insurance navigation compared to the control group. Another health literacy intervention using a CBPR methodology was the previously mentioned HIV+ PHR study in Theme 2.37 Stakeholders and people living with HIV (PLWH) had an active role in the development of the study. The educational sessions about HIV knowledge and eHealth competency were developed using findings from one-on-one interviews with PLWH. The difference in Patient Activation Measure and eHEALS was statistically significant between the intervention and control group.
What Gaps in Direct-to-Consumer Health Literacy Are Unanswered?
Theme 7: No standard measurement for health literacy combining general functional literacy skills and eHealth literacy skills was across all studies.
From the studies included in this review, various instruments were used to measure and test changes in health literacy. Examples of these instruments include the eHealth Literacy Scale (eHEALS), Rapid Estimate of Adult Literacy in Medicine (REALM), and the Newest Vital Sign instruments.13,14,22,26,29 However, no standardized assessment was used across all interventions. Many of the direct-to-consumer health literacy interventions utilized a knowledge or literacy test pertinent to the study’s research topic such as the Literacy Assessment for Diabetes, Diabetic Knowledge Assessment, Diabetes Knowledge Test, an Arabic translation of the Diabetes Knowledge Test, an adapted version of the Health Insurance Literacy Measure, a nutrition literacy test for mothers, or interpreting health data in various presentation formats.19,26,32,38,39,41
Theme 8: There is a lack of follow-up in direct-to-consumer health literacy interventions to assess eHealth tool retention or clinically significant change in health outcomes.
Although a majority of the direct-to-consumer health literacy interventions reported statistically significant differences in levels of health literacy (as measured by a scale or knowledge assessment test) between intervention and control groups, little to no follow-up was done to evaluate whether the intervention led to significant changes in health outcomes. Only one longitudinal study followed the usage of personal health records (PHRs) over five years.33 The researchers found long-term users were diabetics who measured their blood glucose levels. Also, studies have indicated changes in health literacy did not lead to changes in clinical outcomes. For example, the direct-to-consumer health literacy involving HIV+ patients indicated the intervention group showed statistically significant change in e-health literacy and patient activation.37 However, the researchers point out no statistically significant differences in medication adherence or health status levels were found between the control and intervention group. Another study identified levels of internal health orientation and having trust in digital information were more significant predictors in the usage of digital health than health literacy.29 This observation was consistent with another study that found certain coping mechanisms and adjustment toward a disease correlated with an internal motivation to use a PHR.27 The researchers identified approach-oriented coping style individuals were more likely to use the PHR heavily in tracking symptoms versus avoidance-oriented individuals.
An analysis of the studies in the review led to the identification of eight themes that could be utilized in the development of future direct-to-consumer health literacy interventions.
The review identified two major groups where health literacy interventions can have a noticeable impact in health literacy skills and health outcomes: low SES individuals and individuals with chronic diseases. The American Journal of Managed Care (AJMC) reports both of these groups as vulnerable populations in the United States.42 According to AJMC, these populations experience “greater risk factors [and] worse access to care” compared with the general population. The presence of limited health literacy in vulnerable populations could be an explanatory factor in the development of disease, so future health literacy interventions targeting vulnerable individuals may reduce health disparities.43 For chronic diseases, six in 10 adults in the United States have at least one chronic disease.44 Dunn and Conard argue providing only education to individuals with diabetes or cardiovascular disease is not enough in eliciting behavior change because these diseases require a high level of patient involvement.45 The researchers believe effective self-management skills include knowledge about the disease and medication as well as being able to communicate information effectively to a healthcare team. Furthermore, Dunn and Conard propose a solution in which a progressive model, the Dunn-Conard model, for building functional and critical health literacy skills in chronic disease individuals. They envision the ideal active participant would be involved in shared decision making with the healthcare provider. The usage of the Dunn-Conard model in direct-to-consumer health literacy interventions may not be feasible due to limited provider or expert support. To increase this feasibility, a CBPR methodology could be used to involve expert stakeholders in developing educational content delivered in a stand-alone manner.
Nonetheless, privacy and security concerns exist as a barrier for increasing health literacy through eHealth. In fact, users who expressed being uncomfortable with technology or concerns about the privacy of health information online were more likely to report the usage of personal health information management tools would not have a positive effect on their overall health.30 Addressing security and privacy concerns through general education about technology and cybersecurity throughout the intervention could be a way to overcome this barrier.
The transition from direct-to-consumer health literacy technological mediums to mHealth such as smartphones, laptops, and tablets was not surprising. According to Lin and Lou, the transition from eHealth to mHealth is due to the removal of barriers related to accessibility of technological equipment and integrated communication channels.46 Developing direct-to-consumer health literacy interventions through mobile health technology may be appropriate for low SES populations because the current technology landscape in the United States indicates there is an increase in smartphone ownership among lower-income Americans.47 Current research indicates mHealth are difficult for current consumers to utilize to its fullest potential because consumers have trouble interpreting the health information and applying it toward improving health outcomes.48
Tailored health communication promotes change in health behavior due to an increased level of perceived personal relevance, so specific populations should be identified before developing mHealth.49 Incorporating community-based participatory research (CBPR) methodologies in the development of direct-to-consumer health literacy interventions can lead to the promising development of a robust tool for patient engagement. An advantage of CBPR is that individuals will feel empowered and engaged with the intervention.50 Cultural humility is demonstrated between the researchers and participants, as collaboration provides a way to address cultural differences between individuals. Trust is developed between the members of the partnership, and the project becomes credible as it aligns with the community in shared social and health goals.
Other technical suggestions in the design of mHealth include the presentation of educational material and health-related information being at an eighth-grade level or below since the average resident in United States reads at an eighth grade level.51 In the development of mHealth applications, design and usability considerations must be taken into account because the majority of users may stop using the applications due to loss of interest, burdens in data entry, and hidden costs.52 One way to evaluate the usability of the application is to utilize a usability questionnaire. One questionnaire has been developed for mobile health applications known as the mHealth App Usability Questionnaire (MUAQ). The questionnaire has demonstrated reliability and validity which makes it a valuable scale for mHealth usability inquiry.53
Current research indicates the lack of a standardized instrument in measuring health literacy across all interventions, but reliable and valid scales do exist, which can be used as screening measures for low health literacy levels.54 These screening tools can identify low functional skills relevant to health literacy such as the Short Assessment of Health Literacy and the Rapid Estimate of Adult Literacy in Medicine.55 E-health literacy can be screened using the eHEALS scale, which has been shown to be a reliable and consistent measurement tool.56 The usage of these tools can identify specific skills that are assessed in future direct-to-consumer health literacy interventions. Furthermore, specific knowledge assessments can be used in-conjunction with these screening tools to determine statistically significant changes in health knowledge between the intervention and control groups.
It is important to acknowledge health literacy does not always correlate with self-efficacy and health outcomes.37,57 In other words, a high health literate individual may not have the best health status or believe they can change their health status compared to individuals with lower health literacy. This observation suggests the plausible interaction between social determinants of health, self-efficacy, and health literacy in affecting one’s health outcome.43 Current research has shown critical health literacy, which involves higher level thinking, is an important skill, leading to higher levels in self-reported involvement of medical decision-making.58 Other research has indicated individuals with higher levels of internal health locus of control are willing to utilize health applications to monitor or change their behavior than groups with lower levels of an internal health locus of control.59 Future direct-to-consumer health literacy intervention should address levels of self-efficacy and work toward improving the individual’s self-efficacy and internal health locus of control.
The literature review has limitations. First, the study may not have captured all relevant articles to direct-to-consumer health literacy interventions in the PubMed database. A reasoning for this event may be due to the search terms. Terminology regarding direct-to-consumer health literacy interventions may be difficult to identify in a database context, so a wide range of terms need to be used in the future. Also, other peer-reviewed journals in different databases may have relevant articles not found in the PubMed database. Future research should include more databases and develop a robust search strategy to ensure more studies regarding direct-to-consumer health literacy interventions are identified.
eHealth and mHealth technology are promising mediums for direct-to-consumer health literacy interventions with mHealth becoming more relevant due to the high prevalence of smartphone users in the United States population. The literature review identified several themes that could be utilized in the future development of direct-to-consumer health literacy interventions. Barriers deterring future users of these tools include privacy and security concerns, as well as the design and usability of potential mHealth. Potential target audiences have been identified such as low socioeconomic status groups, but interventions in health literacy may not be enough to induce clinically significant behavior change. Direct-to-consumer health literacy interventions should address an individual’s self-efficacy and internal health locus of control throughout the usage of the tool.
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Michael Truong (email@example.com) is a graduate student in the School of Biomedical Informatics at the University of Texas Health Science at Houston.
Susan H. Fenton (firstname.lastname@example.org) is an associate professor and associate dean of academic and curricular affairs at The University of Texas Health Science Center at Houston School of Biomedical Informatics.
Sponsored by the AHIMA Foundation (email@example.com) with support from Anisa Tootla and Megan McVane, LCSW.