The Rapid Estimate of Adult Literacy in Medicine (REALM) is vital in assessing adults’ health literacy. The domains evaluated by the instruments include prose and pronunciation in health promotion. The valid sample population and size while using REALM is 207 adults aged between 18 and 64 (REALM, 2021). The tool is administered using the traditional face-to-face method for the validation study. The language used in the validated REALM version in English will require no translation for English speakers. REALM entails 125 psychometric items that are administered for two and a half minutes (REALM, 2021). Such short administration time makes it convenient and applicable for primary-care patients, though the several particulars listed could make it tiring (Pelikan & Nowak, 2019). The 125 items generated in the instruments follow the Wide Range Assessment Test (WRAT), promoting its content validity (REALM, 2021). However, REALM is limited in assessing the adult’s comprehension aspects since they can know the pronunciation. The tool does not show if an individual knows the meaning. REALM has a strong correlation with the WRAT outcomes in the adult population in the United States and a lower correlation level among adolescents, thus, is best designed for adults.
Furthermore, REALM is a quick screening tool that assists physicians involved in primary care to identify patients with limitations in reading and approximate their reading levels. Through such an objective measure, the health professional can determine the patient’s reading skills on a scale ranging from 0 to 66 scores. The scores obtained can be categorized into 3rd grade, 4th to 6th grade, 7th or 8th grade, or 9th grade and above (REALM, 2021). In such regard, the tool provides the most comprehensive definitions of the health literacy scoring categories. REALM does not provide a gold standard for evaluation, which allows for the use of the WRAT test for empirical evidence or standardization on the construct validity (Pelikan & Nowak, 2019). A mismatch in the REALM measurement and definition has been realized, where reading levels are measured while the pronunciation test is defined.
At a population level, a physician’s inability to precisely discriminate against people with different reading abilities can interfere with the target clinical intervention for at-risk groups. The health literacy tool’s validity was determined in the United States, with a sample having 54% Blacks and 46% Whites (REALM, 2021). During validation, words used in the content were selected as psychometric units. Face validity was also determined based on the physician’s receptivity, staff, and patients towards the test and its applicability in medical environments. REALM has also demonstrated a higher interrater (0.98 and 0.99) and test-retest (0.99) reliabilities (REALM, 2021). Such considerations indicate its preference in clinical and general population settings. Therefore, REALM is highly applicable and generalizable since it can be used in primary care extensively for reliable health literacy outcomes.
I can critically appraise the features and psychometric properties of the health indices of REALM based on my assessment. In the self-assessment, I directly tested my abilities, self-reported them, and identified the proxy measures (Ji & Laviosa, 2020). The REALM content focused on reading and comprehension even though I felt that the scores category was not well-defined and could not always embrace mutual exclusivity (Pelikan & Nowak, 2019). Moreover, given that there is always room for improvement, my scores were not responsive to change over time within the primary care setting despite the higher interrater reliability of REALM.
I also assumed that the variability of the measuring approach in the tool reflected the complexity and multidimensional aspects of health literacy assessment that are subject to change. For example, health literacy has been developed through the convergence of two major study areas (Okan & Bauer, 2019). First, health education and promotion have become critical concerns and an asset in modern care settings. Second, clinical care has been considered a health risk that requires change management to realize positive health outcomes.
I can account for the differences in the self-assessment strategies, such as identifying individual reading abilities or at-risk persons. However, the lack of adequate and explicit definitions of concepts to be measured in REALM development limits its capabilities to be fully informed of my abilities and face and content validities (Pelikan & Nowak, 2019). Tailoring health literacy information towards the primary care patient’s needs requires REALM to describe their abilities and gaps to be filled based on the outcomes. For instance, more than 7th grade shows high health literacy, while 3rd to 6th grade is considered low (Chiu et al., 2018). Physicians have used different score levels to describe the patient’s best instruction, such as dosing or self-care. For such an evidence-based approach, a patient categorized under 7th grade and above is considered health literate and can follow the medical prescriptions accurately.
With no clear understanding of the different grade categories used in REALM, it is essentially difficult for a person to interpret and apply the 0-66 scores in a clinical or public health setting. From a patient’s perspective, the range of individual abilities and settings helped understand and interpret REALM test scores. Such consideration reflects on the broader construct that has not been incorporated into the instrument. Changes in health literacy should also be assessed using REALM to show the patient’s responsiveness to the tool. Therefore, REALM provides valuable information on patients’ reading skills and levels to guide physicians’ instruction in primary care settings.
Chiu, C., Shih, J., Yeh, J., & Wei, C. (2018). Development of assessment tool and education materials of CKD-specific health literacy. European Journal of Public Health, 28(4). Web.
Ji, M., & Laviosa, S. (2020). The Oxford handbook of translation and social practices. Oxford University Press.
Okan, O., & Bauer, U. (2019). International handbook of health literacy: Research, practice and policy across the life-span. Policy Press.
Pelikan, J., & Nowak, P. (2019). Validating a model & self-assessment tool to measure organizational health literacy in hospitals. European Journal of Public Health, 29(4). Web.
REALM (2021). Rapid estimate of adult literacy in medicine- REALM. Health Literacy. Web.