Research papereHealth literacy in chronic disease patients: An item response theory analysis of the eHealth literacy scale (eHEALS)
Introduction
In the evolving technological era, patients now have online access to personal healthcare information, as well as the ability to communicate with peers and providers through the Internet and mobile devices. Although a rising number of patients living with chronic disease are accessing online health information [1], research suggests many of these patients lack the skills to effectively navigate and identify relevant health information [2]. Individuals who live with chronic disease are considered unique online health information seekers, because they are searching for specialized and sometimes sophisticated health information that will help them to learn as much as possible about their condition [3]. Chronic disease patients tend to be older [4], disproportionately affected by low socioeconomic status [5], experience poor health-related outcomes [6], and report both low computer and health literacy [7]. As such, it is critical to understand the knowledge and self-efficacy that chronic disease patients with diverse backgrounds have in their ability to access online health information.
eHealth literacy is defined as an individual’s capability to locate, comprehend, and evaluate online health information to make informed health decisions [8]. Chronic disease patients who lack adequate eHealth literacy skills often feel overwhelmed, confused, and frightened when searching for health information online [9], which can lead to resisting the use of the Internet as a source of health information. Healthcare providers who are aware of their patients’ eHealth literacy skillsets can better recommend relevant health information resource or train them to use technology-based resource [9]. Improving patients’ skills using Internet-based health resources, such as interactive discussion forums and secure messaging platforms [10], may enhance patients’ health-related knowledge and self-efficacy and self-manage their chronic condition(s).
A central theoretical construct of eHealth literacy is self-efficacy, which is an estimate of an individual’s belief in his or her own ability to succeed in specific situations or to accomplish a specified task [11]. High self-efficacy and eHealth literacy predict engagement in health promoting behaviors, such as chronic disease self-management [8], [12]. Measuring health seekers’ self-efficacy to successfully locate, understand, and act on web-based health information is particularly important for patients living with chronic disease, because these patient populations experience barriers to healthcare access, cognitive declines attributable to advanced age, and physical immobility [13], [14].
Currently, the only instrument specifically designed to measure eHealth literacy is the eHealth Literacy Scale (eHEALS). eHEALS was developed to measure an individual’s confidence in their ability to locate and evaluate health information from static webpages, as well as to inform the development and recommendation of health programs that align with a patient’s perceived eHealth literacy skill level [15]. While eHEALS has been used to assess eHealth literacy among patients living with chronic disease [16], [17]; there is limited evidence about the reliability and validity of eHealth literacy scores within this population.
van der Vaart and colleagues [18] adapted the original English version of eHEALS to the Dutch language and reported adequate validity and reliability evidence of eHEALS scores earned by patients with rheumatic arthritis (N = 189). However, weak correlations between eHEALS scores and Internet use brought into question the validity of eHEALS to measure eHealth literacy among English-speaking patients living with chronic disease [19]. Moreover, the sample was limited to patients living with only one chronic disease and the size of the sample did not meet sampling recommendations for CFA [20]. Given the limitations in previous research administering the eHEALS in chronic disease populations, the purpose of this study was to explore the one-factor structure and reliability of eHEALS scores among a diverse sample of US chronic disease patients who report using the Internet to find health information. This study goes beyond classical measurement approaches [21], [22] by applying a higher-level Item Response Theory (IRT) technique to explore the reliability and internal structure of responses to eHEALS items.
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Sample and procedures
Participants were recruited to complete a web-based survey through an opt-in Qualtrics Panel. Participants who completed the survey received a cash value reward credited to their Qualtrics account. Institutional Review Board approval was obtained to prior to data collection. Participants were included in the main analyses if they reported: (1) using the Internet or e-mail at least once in the past 12 months, and (2) currently living with at least one chronic disease.
eHealth literacy
eHealth literacy was
Sample and eHealth literacy description
Of the 811 participants who completed the survey, 648 (79.9%) met inclusion criteria. Participants reported being diagnosed with cardiovascular disease (n = 311; 47.9%), arthritis (n = 131; 20.2%), mental health disorder (n = 181; 27.9%), chronic lung disease (n = 52; 8.1%), and cancer (n = 31; 4.5%). A large proportion reported being diagnosed with another chronic disease not listed (n = 269; 41.5%).
The final sample consisted of mostly females (n = 493; 72.1%) and almost equal representation from
Discussion and conclusion
Findings of this study support the intended use of eHEALS to measure self-reported eHealth literacy among chronic disease patients. Similar to other studies exploring the validity of eHEALS scores in other populations [15], [18], [33], eHEALS is a 1-factor measure of eHealth literacy. Overall, results from CTT, CFA, and PCM procedures in this study support the internal structure and reliability of eHEALS among adults who use the Internet who live with at least one chronic disease. Chronic
Funding
This work was supported by the STEM Translational Communication Center and the Graduate Division of the University of Florida’s College of Journalism and Communications, Gainesville, FL.
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