Measuring Health Literacy in Individuals With Diabetes

Abstract

Objective. To identify instruments used to measure health literacy and numeracy in people with diabetes; evaluate their use, measurement scope, and properties; discuss their strengths and weaknesses; and propose the most useful, reliable, and applicable measure for use in research and practice settings. Methods. A systematic literature review was conducted to identify the instruments. Nutbeam’s domains of health literacy and a diabetes health literacy skill set were used to evaluate the measurement scope of the identified instruments and to evaluate their applicability in people with diabetes. Results. Fifty-six studies were included, from which one diabetes-specific (LAD) and eight generic measures of health literacy (REALM, REALM-R, TOFHLA, s-TOFHLA, NVS, 3-brief SQ, 3-level HL Scale, SILS) and one diabetes-specific (DNT) and two generic measures of numeracy (SNS, WRAT) were identified. These instruments were categorized into direct measures, that is, instruments that assess the performance of individuals on health literacy skills and indirect measures that rely on self-report of these skills. The most commonly used instruments measure selective domains of health literacy, focus mainly on reading and writing skills, and do not address other important skills such as verbal communication, health care system navigation, health-related decision making, and numeracy. The structure, mode, and length of administration and measurement properties were found to affect the applicability of these instruments in clinical and research settings. Indirect self- or clinician-administered measures are the most useful in both clinical and research settings. Conclusion. This review provides an evaluation of available health literacy measures and guidance to practitioners and researchers for selecting the appropriate measures for use in clinical settings and research applications.

Keywords

chronic disease management health communications literacy measurement development patient education

Health literacy is a set of skills that people need to function effectively in the health care environment (Berkman, Terry, & McCormack, 2010). These skills include the ability to read and understand written text, locate and interpret information in documents, and write or complete forms (functional); the ability to speak and listen effectively and communicate about health-related information (interactive); the ability to navigate the health care system and make appropriate health decision (critical); and the ability to use numeric information for tasks, such as interpreting medication dosages, food labels, and blood glucose measurements (numeracy; Berkman et al., 2010; Nutbeam, 2008).

Diabetes is a prototypical multifactorial chronic condition, characterized by a high level of complexity that requires extensive self-care education and management. The demands on individuals with diabetes is complicated by the fact that diabetes self-management often relies on printed educational material and verbal instructions and requires advanced health literacy skills (White, Wolff, Cavanaugh, & Rothman, 2010). With the emerging evidence on the adverse effects of inadequate health literacy on health care and outcomes in people with diabetes (Powell, Hill, & Clancy, 2007; Sarkar, Karter, Liu, Moffet, et al., 2010; Schillinger et al., 2002; Schillinger et al., 2004), the assessment of health literacy skills is becoming crucial in this population. Since individuals often read several grade levels lower than the highest grade achieved in school (Baker et al., 1996), educational attainment cannot be used as a proxy for health literacy, which made the development of health literacy measures a necessity.

As a result of this, several instruments were developed to assess skills or screen for inadequate health literacy (Baker, Williams, Parker, Gazmararian, & Nurss, 1999; Chew, Bradley, & Boyko, 2004; Chew et al., 2008; Davis et al., 1993; Parker, Baker, Williams, & Nurss, 1995). These instruments vary in their development, structure, measurement scope, and subsequently psychometric properties. Although these instruments have been used with several patient populations, their usefulness and applicability for people with diabetes remains challenging. The reason is the complexity of tasks and skills that are required by people who have diabetes and the postulation that the available instruments do not address that complexity and all the important components of health literacy altogether. Additionally, the continuous adjustment of the meaning and components of health literacy makes the available instruments questionable in what they actually measure. We therefore lack an understanding of the characteristics and measurement scope of health literacy measures used in people with diabetes and their applicability in this population. In this review, we identified instruments used to measure health literacy in individuals with diabetes, evaluated their measurement scope and properties, and proposed recommendations for their use and applicability in different settings.

Method

Data Sources, Search Strategy, and Study Selection

We conducted a systematic review of nine databases: Medline, PubMed, CINAHL, SCOPUS, Web of Science, ERIC, Nursing and Allied Health Source, Health Source (Nursing/Academic Edition), and Health and Psychosocial instruments. The searches were not limited to any time period, language, or type of published paper. The following search terms were used to identify eligible studies: literacy, numeracy, health literacy, diabetes, diabetic, type 2 diabetes, type 1 diabetes, instrument, measure, assessment, questionnaire, survey, and screening. Keywords were matched to database-specific indexing terms. The names of the identified instruments were used as keywords in further searches of databases. Electronic searches were supplemented by hand searching “health literacy”–specific issues in journals and cross-referencing with identified articles (detailed information about the search strategy are available on request). The search strategy and retrieval process are displayed in Figure 1.

Figure 1.

Search strategy and retrieval process

Data Extraction and Synthesis

Data on the general characteristics of the studies including design, methods, sample characteristics, and health literacy measures used in each study were extracted (see the appendix). From these studies, we identified the health literacy instruments used for people with diabetes (Table 1). Data on the measurement scope and psychometric properties of the identified instruments were also extracted (Tables 1 and 2).

Table 1.

Characteristics of Identified Health Literacy and Numeracy Instruments

Measure	Type of Measure	Number of Items/Questions	Administration Mode/Time	Scoring	Measurement Properties^a,b	Languages Available
Direct health literacy measures
REALM (Davis et al., 1991)	Word recognition and pronunciation test	66 words	Clinician/researcher administered; <3 min	Grade is assigned based on total score that ranges from 0 to 66: 0-18 = ≤ 3rd grade; 19-44 = 4th-6th grade; 45-60 = 7th-8th grade; 61-66 = ≥9th grade	Reliability: Cronbach’s α: .99; ICC: .92; Validity: .97 (with PIAT-R), .96 (with WRAT-R), .88 (with SORT-R)	English
REALM-R (Bass, Wilson, & Griffith, 2003)	Word recognition and pronunciation test	8 words	Clinician/researcher administered; <2 min	Grade is assigned based on total score that ranges from 0 to 8. Score ≤6 corresponds to 6th grade and indicates poor HL	Reliability: Cronbach’s α: .91 (Bass et al., 2003); Validity: .72 (with REALM), .64 (with WRAT-R)	English
TOFHLA (Parker et al., 1995)	Reading comprehension and numeracy test	50-item (reading comprehension); 17-item (numerical ability test)	Self-administered; 22 min	Scores range 0-100: <60 = inadequate HL; 60-75 = marginal HL; >75 = adequate HL	Reliability: Cronbach’s α: .98; Validity: .84 (with REALM), .74 (with WRAT-R)	English, Spanish, Chinese
s-TOFHLA (Baker, et al., 1999)	Reading comprehension	36-item reading assessment	Self-administered; 7 min	Scores range 0-36: 0-16 = inadequate HL; 17-22 = marginal HL; 23-36 = adequate HL	Reliability: Cronbach’s α: .98; Validity: .91 (with TOFHLA), .80 (with REALM)	English, Spanish, Chinese
NVS (Weiss et al., 2005)	Reading Comprehension; Numeracy	6 questions on a ice cream nutrition label	Self-administered; 3 min	Each item answered correctly is given a score of 1. Scores range: 1-6 (score <4 = limited HL)	Reliability: Cronbach’s α: .76; Validity: .59 (with TOFHLA); AUROC: .88 (based on TOFHLA); Screening sensitivity: 72% (based on TOFHLA); Screening specificity: 87% (based on TOFHLA)	English, Spanish
LAD (Nath, Sylvester, Yasek, & Gunel, 2001)	Word recognition and pronunciation test	3-graded word lists including 60 words	Clinician/researcher administered; 3 min	Grade is assigned based on total score that ranges from 0 to 60: 0-20 = ≤4th grade; 21-40 = 5th-9th grade; 41-60 = ≥9th grade	Reliability: ICC: .86; Validity: .90 (with REALM), .81 (with WRAT-3)	English
Indirect health literacy measures
3-brief SQ (Chew et al., 2008)	Self-report of confidence in HL skills	3 questions	Self-administered or clinician/researcher administered; Time: 1-2 min	Values of 0, 1, 2, 3, and 4 are assigned to each response option for each question; Score ranges from 0 to 12; High scores = high HL skills; Low scores = low HL skills	AUROC: .66-.87 (based on s-TOFHLA), .72-.84 (based on REALM); Screening sensitivity: 48-60 (based on s-TOFHLA); Screening specificity: 79-83 (based on s-TOFHLA)	English
3-level HL scale (Ishikawa et al., 2008)	Self-report of HL skills	14 items, 3 domains: functional (5 items), communicative (5 items), and critical (4 items)	Self-administered or clinician/researcher administered; 5-6 min	Each item is scored on a 4-point scale ranging from 1 (never) to 4 (often); The scores of the items are summed up and divided by the number of the items in the scale. Higher scores indicate higher health literacy level	Reliability: Cronbach’s α: Overall scale: .78; Functional domain: .84; Communicative domain: .77; Critical domain: .65	Japanese
SILS (Morris, MacLean, Chew, & Littenberg, 2006)	Self-report of HL skills	1 question	Self-administered or clinician/researcher administered; Time: ½ min	Possible scores are: 0 (never), 1 (rarely), 2 (sometimes), 3 (often), 4 (always); Score >2 = difficulty with reading printed health material	AUROC: .64-.87 (based on s-TOFHLA); Screening sensitivity: .47-.73 (based on s-TOFHLA); Screening specificity: 83 (based on s-TOFHLA)	English
Direct numeracy measures
DNT (Huizinga et al., 2008)	Reading recognition, spelling, and arithmetic computation	43 questions in 5 domains and 8 math problem types	Researcher/clinical or self-administered; 30 min	Items are scored as binary outcomes—correct or incorrect—Scores are reported as percent correct (with a possible range of 0% to 100%)	Reliability: Cronbach’s α: .95 (43-item version), .90 (15-item version); Validity: .96 (DNT-15 with DNT-43)	English, Spanish
WRAT (Stone, Jastak, & Wilkinson, 1995)	Reading recognition, spelling, and arithmetic computation	Reading test: 15 letters and 42 individual words; Spelling test: 13 letters and 40 words; Arithmetic test: two parts: Part I: counting, reading number symbols, and solving simple arithmetic problems. Part II: 40 arithmetic problems	Self-administered; 20-30 min	3 scores: spelling, arithmetic, and reading; Scoring: 1 = correct answer, 0 = incorrect answer, scores are standardized, and the average score = 100	—	English
Indirect numeracy measures
SNS (Fagerlin et al., 2007)	Ability to perform mathematical tasks	8 questions	Researcher/clinical or self-administered; 2 min	Responses on 6-point Likert-type scale (from Not at all good to Extremely good); Score range: 1-6	Validity; .63-.68 (with Lipkus and other numeracy scales)	English

Note. PIAT-R = Peabody Individual Achievement Test–Revised; WRAT-R = Wide Range Achievement Test–Revised; SORT-R = Slosson Oral Reading Test–Revised; ICC = intraclass correlation coefficient; AUROC = area under the receiver operating characteristic (ROC) curve; REALM = Rapid Estimate of Adult Literacy in Medicine; REALM-R = Rapid Estimate of Adult Literacy in Medicine–Revised; TOFHLA = Test of Functional Health Literacy in Adults; s-TOFHLA = Test of Functional Health Literacy in Adults–Short Form; 3-brief SQ = 3 brief screening questions; SILS = Single Item Literacy Screener; LAD = Literacy Assessment in Diabetes; NVS = Newest Vital Sign; DNT = Diabetes Numeracy Test; WRAT = Wide Range Achievement Test; SNS = Subjective Numeracy Scale.

All the reported estimates are statistically significant at p value <.05.

The reported validity parameters are either Pearson or Spearman correlations.

Table 2.

Measurement Scope of the Identified Health Literacy and Numeracy Instruments^a

	Diabetes Health Literacy Skill Set							Health literacy Domains
Instrument	Reading and Understanding Health Information	Applying Health Information	Understanding and Applying Health Care Providers’ Instructions	Completing Medical and Health Care Forms	Communicating With Health Care Providers	Navigating the Health Care System	Making Appropriate Health-Related Decisions	Functional HL	Interactive HL	Critical HL	Numeracy
REALM	1	0	0	0	0	0	0	1	0	0	0
REALM-R	1	0	0	0	0	0	0	1	0	0	0
TOFHLA	2	2	0	0	1	0	0	2	0	0	2
s-TOFHLA	0	2	0	0	1	0	0	2	0	0	0
NVS	2	2	0	0	0	0	0	2	0	1	2
LAD	1	0	0	0	0	0	0	1	0	0	0
3-brief SQ	2	0	0	2	0	0	0	2	0	1	0
SILS	2	0	0	2	0	0	0	2	0	0	0
3-level HL Scale	2	2	2	2	2	2	2	2	2	2	0
DNT	2	0	0	0	0	0	0	2	0	0	2
WRAT	2	0	0	0	0	0	0	2	0	0	2
SNS	0	0	0	0	0	0	0	1	0	0	2

Note. HL = health literacy; REALM = Rapid Estimate of Adult Literacy in Medicine; REALM-R = Rapid Estimate of Adult Literacy in Medicine–Revised; TOFHLA = Test of Functional Health Literacy in Adults; s-TOFHLA = Test of Functional Health Literacy in Adults–Short Form; 3-brief SQ = 3 brief screening questions; SILS = Single Item Literacy Screener; LAD = Literacy Assessment in Diabetes; NVS = Newest Vital Sign; DNT = Diabetes Numeracy Test; WRAT = Wide Range Achievement Test; SNS = Subjective Numeracy Scale.

Ratings: 0 = Not addressed, 1 = partially addressed, 2 = fully addressed.

Evaluation of the measurement scope and applicability of the identified instruments was based on Nutbeam’s (2008) three components of health literacy (functional, interactive, critical) and a diabetes health literacy skill set. Functional health literacy focuses on reading and writing skills that enable an individual to function effectively in everyday situations; interactive (or communicative) health literacy includes advanced skills that allow a person to extract information, derive meaning from different forms of communication, and apply new information to changing circumstances; and critical health literacy encompasses more advanced skills for critically analyzing information and using information to exert greater control over life events and situations (Nutbeam, 2008). The health literacy skill set was developed based on a brief review of the literature on diabetes self-care and management, and it includes the following: (a) reading and understanding medication labels, information on medication bottles, blood glucose levels, insulin bottles and pens, and applying this information in taking medication and/or insulin; (b) reading and understanding diabetes education materials and apply the information and instructions in daily life activities; (c) understanding health care providers’ instructions and applying it to daily living, such as diet management, physical activity, smoking cessation, monitoring of blood glucose, and self-assessment; (d) completing medical forms, glucose monitoring logs, and dietary logs; (e) communicating with health care providers, explaining health concerns, asking questions, and obtaining needed information; (f) navigating the health care system; and (g) making appropriate health-related decisions. A score was assigned to each section based on the extent to which each domain and skill were addressed by the instrument (Table 2). Ratings were as follows: 0 = not addressed, 1 = partially addressed, 2 = fully addressed. Two reviewers independently rated the instruments. Cohen’s kappa was used to assess interrater reliability in the ratings between the two reviewers. Scores were used to help in the qualitative comparison of the instruments and not to rank the instruments with respect to ratings.

Results

Literature Search and Identification of Instruments

Across all databases, the search yielded 1,120 publications. After removal of duplicates, 412 remained. Titles and abstracts were screened for relevance, and based on that, 161 publications were included for full-text review. The full texts of the 161 publications were screened for eligibility, and 53 publications that involved the use of a health literacy measure in individuals with diabetes were included. Only articles written in English were included in this review. The hand search of reference lists of included studies resulted in the inclusion of three additional publications. Thus, the total number of eligible studies was 56.

We identified one diabetes-specific and eight generic measures of health literacy (Table 1): Literacy Assessment in Diabetes (LAD), Rapid Estimate of Adult Literacy in Medicine (the original REALM and the revised form REALM-R), Test of Functional Health Literacy in Adults (TOFHLA and the shorter form s-TOFHLA), Newest Vital Sign (NVS), 3-brief Screening Questions (3-brief SQ), the 3-level health literacy scale (3-level HL Scale), and Single Item Literacy Screener (SILS). In addition, we identified one diabetes-specific and two generic measures of numeracy: Diabetes Numeracy Test (DNT; 15-item and 43-item versions), Wide Range Achievement Test (WRAT; the 3-item version WRAT-3 and the revised version WRAT-R), and the Subjective Numeracy Scale (SNS). In assessments of health literacy in individuals with diabetes, the s-TOFHLA was the most commonly used (26 studies), followed by the REALM (15 studies), 3-brief SQ (7 studies), TOFHLA (4 studies), 3-level HL Scale (3 studies), SILS (2 studies), LAD (2 studies), REALM-R (2 studies), NVS (1 study), WRAT (4 studies), DNT (3 studies), and SNS (1 study).

Several other instruments have been developed to measure general health literacy, such as the Medical Term Recognition Test (METER; Rawson et al., 2009), the News Skills Based Instrument (McCormack et al., 2010), the Mandarin Health Literacy Scale (MHLS; Tsai, Lee, Tsai, & Kuo, 2011), but their use in people with diabetes was not reported and thus not included in our review. Diabetes Specific Health Literacy Measure (DSHLM; Yamashita & Kart, 2011) was presented as a health literacy measure, but in fact resembles a diabetes knowledge test and thus was not considered a health literacy measure in this review.

Description of the Identified Instruments

The identified instruments were categorized into those instruments that directly measure health literacy skills (i.e., assessment of the performance of these skills—REALM, REALM-R, TOFHLA, s-TOFHLA, NVS, and LAD) and instruments that indirectly assess health literacy skills (i.e., instruments that rely on self-report of these skills—3-brief SQ, 3-level HL Scale, and SILS). Additionally, numeracy instruments were also categorized into direct measures (DNT and WRAT) and indirect measures (including the SNS; Table 1). There are considerable differences among the identified instruments used to measure health literacy and numeracy. These instruments vary in their structure, number of items/questions/domains, administration time and mode, scoring system, available languages, and their measurement scope and properties, which entail a number of implications for their use in research and clinical settings. Since the WRAT was not developed to be a measure of the numeracy component of health literacy, it was not evaluated based on the identified criteria or compared with other instruments.

Measurement Properties of the Identified Instruments

The REALM, TOFHLA, and s-TOFHLA have been validated in several populations (including people with diabetes) and have been used in most of the validation studies of newer health literacy instruments such as the 3-brief SQ, NVS, and the SILS (Table 1). Among the identified instruments, the TOFHLA, s-TOFHLA, and the REALM have established their reliability and validity through several applications in different patient groups including the diabetes population. However, these instruments differ in their measurement scope and underlying constructs from newer instruments, and thus, their typical use as a gold standard in validation studies might be reconsidered. For example, the 16-brief Screening Questions (16-brief SQs; Chew et al., 2004), which is the long version of the 3-brief SQ (Chew et al., 2008), were comprehensively developed to address all domains of health literacy and were validated against the s-TOFHLA, which only measures functional health literacy. For instance, the 3-brief SQs performed the best based on the s-TOFHLA in screening for inadequate “functional” health literacy (Chew et al., 2004; Chew et al., 2008). This does not imply that the other questions of the 16-brief SQs that address interactive and critical health literacy have poor measurement properties; however, it does suggest that the validity of these questions should be evaluated against an instrument that measures the same underlying concepts. Further validation of the 16-brief SQ is therefore recommended. Similarly, the 3-level HL Scale, which addresses all aspects of health literacy, except numeracy, was also compared with the REALM and TOFHLA as “gold standards,” where its functional domain performed the best when compared with these instruments (Ishikawa et al., 2009; Ishikawa, Takeuchi, & Yano, 2008). This applies to numeracy measurement instruments as well. Careful attention should be given to revising and developing health literacy and numeracy instruments, particularly with respect to what these instruments are constructed to measure, and accordingly demonstrating their performance using appropriate “gold standards” or comparisons.

Measurement Scope of the Identified Instruments

Cohen’s kappa between the two reviewers for the rating of measurement scope was .78. Based on the evaluation of the measurement scope of the identified instruments, we found that the most commonly used instruments (s-TOFHLA, REALM) are not sufficiently comprehensive, that is, they measure selective domains of health literacy, namely, reading comprehension and writing ability, thereby tackling only functional aspects of health literacy (Table 2). Other instruments (3-brief SQ, 3-level HL Scale, NVS) address functional health literacy as well as critical health literacy such as decision making, navigating the health care system, and following instructions and applying health information to daily life situations (Table 2). The 3-level HL Scale was the only instrument that was found to address interactive health literacy in addition to functional and critical health literacy (Table 2). The TOFHLA and NVS measure computational skills and thus address the numeracy component of health literacy. DNT focuses on diabetes numeracy in addition to assessing functional aspects of health literacy, where SNS only focuses on general numeracy.

The 3-level HL scale appears to have the broadest measurement scope and the one that addresses all the identified skills and the functional, interactive, and critical aspects of health literacy but not numeracy. However, this instrument was developed in Japanese and was not validated in the English language, and it does not have a brief version that would be more applicable than the long version in clinical settings. Overall, the identified instruments varied widely in their measurement scope and the component of health literacy they measure.

Discussion

Although their measurement scope is limited to aspects of functional health literacy, the REALM and the s-TOFHLA were found to be the most commonly used instruments to measure health literacy among individuals with diabetes; however, due to their limited measurement scope and properties, their typical use as a gold standard in validation studies of other instruments might be reconsidered. In a study that compared the estimates of poor health literacy using the s-TOFHLA and the REALM, Griffin et al. (2010) reported that estimates of poor health literacy varied by the assessment tool used, especially after adjusting for nonresponse bias. The reason for this discrepancy in the estimates could be due to the fact that these instruments measure different aspects of health literacy and thus reflect different entities. This should always be considered while selecting an instrument for the assessment of health literacy and in validation studies of other health literacy instruments.

The identified instruments have inherent strengths and weaknesses as a result of their structure, measurement scope, and properties. First, the REALM (all versions), TOFHLA/s-TOFHLA, NVS, and the LAD were designed to directly measure specific skills. The fact that these measures directly assess the skill level of individuals imposes many limitations on the applicability of these measures especially in the clinical setting, where this approach might impose discomfort and embarrassment particularly for those who have inadequate health literacy skills (Baker, 2006; Berkman et al., 2010; Wolf et al., 2007). This also applies to DNT, which is a direct measure of numeracy compared with the SNS as an indirect less burdensome measure of numeracy.

Second, direct measures require good visual acuity (particularly word recognition tests), good writing ability (such as the TOFHLA, NVS, DNT), and enough concentration to be able to complete the test. These limitations make direct measures less convenient for most clinical settings and for survey-based research. On the other hand, indirect or self-reported health literacy measures (3-brief SQ, 3-level HL scale, SILS, SNS) provide information about confidence with certain skills without directly assessing these skills, and therefore they are less burdensome and do not impose discomfort and embarrassment, which makes them more suitable for most clinical settings and research applications.

Third, the mode of administration of identified instruments plays an important role in their applicability and use. The REALM (all versions), the LAD, and part of the DNT are word-recognition tests and are only administered by a clinician or researcher. This limits their use for research purposes particularly in survey-based studies and makes them less practical for most clinical settings as they would require time from the care provider and could impose discomfort and embarrassment. On the other hand, instruments that are only self-administered (TOFHLA/s-TOFHLA, 3-level HL Scale, SNS) do not impose a lot of discomfort but may have limited use since they require good visual acuity and writing skills. The 3-brief SQ, 3-level HL Scale, SILS, and SNS could be self-administered or clinician/researcher administered, which provides flexibility in their application for research purposes and in most clinical settings.

Fourth, administration time is also a factor that affects the use and applicability of the identified instruments. The TOFHLA, DNT, and WRAT require a long administration time, which makes them less practical for use in most clinical settings. The administration times of the REALM (all versions), s-TOFHLA, NVS, LAD, 3-brief SQ, the 3-level HL Scale, SILS, and SNS are relatively short, making these instruments useful in research and most clinical settings. It could be useful to use a briefer or shortened version of an instrument due to potential time constraints in a specific application or setting; however, it is important to recognize that there could be a trade-off with measurement scope, where briefer versions usually have a narrower scope than longer ones (16-brief SQ vs. 3-brief SQ, TOFHLA vs. s-TOFHLA).

Finally, it is important to note that direct measures (REALM, s-TOFHLA, NVS, LAD, DNT) use terms from the medical field and texts from real medical forms used in clinical settings, which implies that these instruments measure health literacy based on the health system demands of skill level. However, indirect measures (3-brief SQs, 3-level HL Scale, SILS, SNS) assess health literacy skills by asking about personal abilities that are not related to specific medical forms or context. In other words, the level of health literacy skills required by medical forms and texts that are part of the instrument influence the health literacy score of individuals; individuals would score higher as the level of health literacy skills required by the forms is lower. This has a direct implication on measuring health literacy, where it was reported that measuring health literacy using different instruments yields different estimates (Griffin et al., 2010).

Considering the measurement scope of these instruments, their psychometric properties, and their strengths and limitations collectively, the 3-level HL can be considered the most useful and comprehensive instrument to screen for inadequate health literacy. However, this instrument has not been validated in English. For English-based instruments, the 3-brief SQs (and their longer version 16-brief SQs) have the broadest measurement scope, demonstrated good measurement properties, have many advantages over other instruments, and could be considered the best available instrument to measure functional health literacy. The SNS, although minimally used, has good characteristics that make it very applicable; however, it requires further testing and validation with people who have diabetes.

With the escalating evidence on the adverse effects of inadequate health literacy on health outcomes in people with diabetes (Kim, Love, Questberg, & Shea, 2004; Rothman, Malone, et al., 2004; Sarkar, Karter, Liu, Moffet, et al., 2010; Schillinger et al., 2002), measuring health literacy skills is becoming imperative. Health care professionals tend to overestimate patients’ literacy because they are very accustomed to the medical field and its terminology and because some patients who have inadequate health literacy skills often deny or conceal their deficit. Additionally, patients are often ashamed of their low health literacy, and many adults will attempt to conceal their reading impairments from others (Ad Hoc Committee on Health Literacy for the Council on Scientific Affairs, 1999; Baker et al., 1996). For that, understanding the components of health literacy measurement and screening, in general, and in people with diabetes, in particular, is crucial to the planning and delivery of comprehensive individualized diabetes care and interventions.

The findings of this review are applicable to other chronic conditions with similar health literacy demands on individuals. Additionally, this review did not only address the applicability and usefulness of these instruments in individuals with diabetes but also provided an evaluation of these instruments and their strengths and weaknesses, which are transferable to determining their applicability in other health conditions and situations. Researchers and clinicians could use this review as a guide to the selection of the most suitable instrument for a particular research application or in clinical settings.

Conclusion

We based this evaluation on the most collective and comprehensive description of health literacy; however, without a final consensus on what the underlying constructs of health literacy are, we will continue to fail in using and developing adequate measures of health literacy and in conducting valid measurements. These evaluations of health literacy instruments used in people with diabetes showed that the most commonly used instruments measure selective domains of health literacy and are not sufficiently comprehensive. Each of the identified instruments has strengths and limitations in its measurement scope, properties, applicability, and feasibility. It appears that indirect self- or clinician-administered measures are the most useful in both clinical and research settings. We found that the 3-level HL Scale (Ishikawa et al., 2008) and the 3-brief SQs (Chew et al., 2008) as the most comprehensive, applicable, and useful among the available instruments of health literacy measurement in individuals with diabetes.

Footnotes

Appendix

Overview of the Included Studies

Author(s), Year, Source	Study Design	Sample Characteristics	HL/Numeracy Measure(s) Used
Aikens and Piette (2009), USA	Observational, cross-sectional	N = 1,376; two groups: group 1 mean age (SD): 55.3 (11.8), group 2 mean age (SD): 57.2 (10.7); T1DM and T2DM	3-brief SQ
Arthur, Geiser, Arriola, and Kripalani (2009), USA	Observational, cross-sectional (mixed methods)	N = 31, Mean age (SD): NR; T2DM	REALM
Bains and Egede (2011), USA	Observational, cross-sectional	N = 125, Age: 50.7% <65 years and 49.3% ≥65 years;T2DM	REALM-R
Carbone, Lennon, Torres, and Rosal (2006), USA	Observational, cross-sectional (mixed methods)	N = 10, Mean age (range): 65 (55-82); diabetes type: T2DM	s-TOFHLA
Castro, Wilson, Wang, and Schillinger (2007), USA	Observational, cross-sectional	N = 74, Two groups: audiotape group mean age (SD): 64 (10) and telephone follow-up group mean age (SD): 63 (9); diabetes type: T2DM	s-TOFHLA
Cavanaugh et al. (2008), USA	Observational, cross-sectional	N = 398, Median age (IQR): 55 (46-64); T1DM and T2DM	REALM, DNT, WRAT-3R
Cavanaugh et al. (2009), USA	Randomized controlled trial	N = 198, Intervention group median age (IQR): 53 (40-59.5), Control group median age (IQR): 52 (45-59); diabetes type: T1DM and T2DM	REALM
DeWalt, Boone, and Pignone (2007), USA	Observational, cross-sectional	N = 268, Two groups: high HL group mean age (SD): 58 (11) and low HL group mean age (SD): 62 (10); diabetes type: T2DM	REALM
Endres, Sharp, Haney, and Dooley (2004), USA	Observational, cross-sectional	N = 74, Mean age (SD): 31 (6); diabetes type: gestational diabetes	TOFHLA
Gazmararian, Williams, Peel, and Baker (2003), USA	Observational, cross-sectional	N = 653 (266 have diabetes); Age: NR; diabetes type: T1DM and T2DM	s-TOFHLA
Gazmararian et al. (2006), USA	Observational, prospective cohort	N = 1,549, (Individuals who have diabetes and/or coronary heart disease and/or hypertension and/or hyperlipidemia), subgroup analysis; diabetes type: NR	s-TOFHLA
Gazmararian, Ziemer, and Barnes (2009), USA	Observational, cross-sectional	N = 35, Group 1 mean age: 48, Group 2 mean age: 58, Group 3 mean age: 54; diabetes type: NR	REALM
Gerber et al. (2005), USA	Randomized controlled trial	N = 244, Intervention-Low HL group mean age (SD): 57.7 (11.7), Intervention-High HL group mean age (SD): 49.4 (12), Control-Low HL group mean age (SD): 60.4 (10.8), Control-Low HL group mean age (SD): 51.8(11.3); diabetes type: T1DM and T2DM	s-TOFHLA
Gerber et al. (2006), USA	Observational, cross-sectional	N = 255, Mean age (SD): 55.2 (12.3); diabetes type: T1DM and T2DM	s-TOFHLA
Ishikawa, Takeuchi, and Yano (2008), Japan	Observational, cross-sectional	N = 138, Mean age (SD): 65 (9.9); diabetes type: T2DM	3-level HL scale
Ishikawa et al. (2009), Japan	Observational, cross-sectional	N = 134, Mean age (SD): 65 (9); diabetes type: T2DM	3-level HL scale
Ishikawa and Yano (2011), Japan	Observational, cross-sectional	N = 143, Mean age (SD): 65 (9.1); diabetes type: T2DM	3-level HL scale
Jeppesen, Coyle, and Miser (2009), USA	Observational, cross-sectional	N = 225, Mean age (SD): 53.76 (12.8); diabetes type: NR	s-TOFHLA, SILS
Kandula et al. (2009), USA	Interventional: two-group pre–post	N = 190, Mean age (SD): 55.9 (9.3); diabetes type: NR	s-TOFHLA
Kim, Love, Questberg, and Shea (2004), USA	Observational, prospective cohort	N = 92, Mean age: 62; diabetes type: T1DM and T2DM	s-TOFHLA
Laramee, Morris, and Littenberg (2007), USA	Observational, cross-sectional	N = 998, Mean age (range): 65 (22-93); diabetes type: T1DM and T2DM	s-TOFHLA
Mancuso (2010), USA	Observational, cross-sectional	N = 102, Mean age (SD): 52 (9.1); diabetes type: T1DM and T2DM	TOFHLA
Mayberry, Kripalani, Rothman, and Osborn (2011), USA	Observational, cross-sectional	N = 61, Mean age (SD): 56.9 (8.8); diabetes type: T2DM	3-brief SQ, SNS
Mbaezue et al. (2010), USA	Observational, cross-sectional	N = 189, Mean age (SD): 51.2 (10); diabetes type: T1DM and T2DM	s-TOFHLA
McCleary-Jones (2011), USA	Observational, cross-sectional	N = 50, Mean age (SD): 58.6 (11.5); diabetes type: T1DM and T2DM	REALM
Morris, MacLean, Chew, and Littenberg (2006), USA	Observational, cross-sectional	N = 999, Age: 22-93; diabetes type: T1DM and T2DM	SILS, s-TOFHLA
Morris, MacLean, and Littenberg (2006), USA	Observational, cross-sectional	N = 1,002, Median age (IQR): 66 (57-74); diabetes type: T1DM and T2DM	s-TOFHLA
Nath, Sylvester, Yasek, and Gunel (2001), USA	Observational, longitudinal	N = 203, Mean age (SD): 43.6 (15.04); diabetes type: NR	LAD, REALM, WRAT-3
Ntiri and Stewart (2009), USA	Interventional: two-group pre–post	N = 20, Mean age (range): 68.1 (57-84); diabetes type: NR	s-TOFHLA, LAD
Nurss et al. (1997), USA	Observational, cross-sectional	N = 131, Mean age (SD): 54.7 (14); diabetes type: NR	TOFHLA
Osborn, Cavanaugh, Wallston, White, and Rothman (2009), USA	Observational, cross-sectional	N = 383, Median age (IQR): 56 (47-64); diabetes type: T2DM	REALM, DNT, WRAT-3
Osborn, Cavanaugh, Wallston, and Rothman (2010), USA	Observational, cross-sectional	N = 383, Mean age (SD): 54.4 (13); diabetes type: T1DM and T2DM	REALM, WRAT-3
Osborn, Bains, and Egede (2010), USA	Observational, cross-sectional	N = 130, Mean age (SD): 60.7 (11.8); diabetes type: T2DM	REALM-R
Powell, Hill, and Clancy (2007), USA	Observational, cross-sectional	N = 68, Median age (IQR): 55 (51-60); diabetes type: T2DM	REALM
Rees et al. (2011), USA	Observational, cross-sectional	N = 17,795, Age: NR; diabetes type: T1DM and T2DM	3-brief SQ
Rothman, DeWalt, et al. (2004), USA	Randomized controlled trial	N = 217, Control group Low HL mean age (SD) = 59 (10.4), Control group High HL mean age (SD) = 56 (10.9), Intervention group Low HL mean age (SD) = 57 (10.5), Intervention group High HL mean age (SD) = 51 (13.1); diabetes type: T2DM	REALM
Rothman, Malone, et al. (2004), USA	Randomized controlled trial	N = 159, Control low HL group mean age (SD): 59 (10.4), Control high HL group mean age (SD): 56 (10.9), Intervention low HL group mean age (SD): 57 (10.5), Intervention low HL group mean age (SD): 51 (13.1); diabetes type: T2DM	REALM
Sarkar, Fisher, and Schillinger (2006), USA	Observational, cross-sectional	N = 408, Mean age (SD): 58.1 (11.4); diabetes type: T2DM	s-TOFHLA
Sarkar et al. (2008), USA	Observational, cross-sectional	N = 796, Mean age (SD): 58 (12); diabetes type: T1DM and T2DM	3-brief SQ
Sarkar, Karter, Liu, Adler, et al. (2010), USA	Observational, cross-sectional	N = 14,102, Mean age: 59; diabetes type: T1DM and T2DM	3-brief SQ
Sarkar, Karter, Liu, Moffet, et al. (2010), USA	Observational, cross-sectional	N = 14,357, Mean age (SD): 58 (10); diabetes type: T2DM	3-brief SQ
Sarkar, Schillinger, López, and Sudore (2011), USA	Observational, cross-sectional	N = 296, Mean age (SD): 54.9 (12.1); diabetes type: T2DM	3-brief SQ, s-TOFHLA
Schillinger et al. (2002), USA	Observational, cross-sectional	N = 408, Mean age (SD): 58.1 (11.4); diabetes type: T2DM	s-TOFHLA
Schillinger et al. (2003), USA	Observational, cross-sectional	N = 408, Age: 55.7% ≥65 and 44.3% <65; diabetes type: T2DM	s-TOFHLA
Schillinger et al. (2004), USA	Observational, cross-sectional	N = 408, Mean age: 58.1; diabetes type: T2DM	s-TOFHLA
Schillinger, Barton, Karter, Wang, and Adler (2006), USA	Observational, cross-sectional	N = 395, Mean age (SD): 57.9 (11.4); diabetes type: T2DM	s-TOFHLA
Schillinger, Handley, Wang, and Hammer (2009), USA	Randomized controlled trial	N = 339, Mean age (SD): 56.1 (12); diabetes type: T2DM	s-TOFHLA
Seligman et al. (2005), USA	Observational, cross-sectional	N = 182, Intervention group mean age (SD): 62.3 (11.3), Control group mean age (SD): 63.4 (9.5); diabetes type: T2DM	s-TOFHLA
Shigaki et al. (2010), USA	Observational, cross-sectional	N = 77, Mean age (SD): 63 (13); diabetes type: T2DM	REALM, NVS
Tang, Pang, Chan, Yeung, and Yeung (2008), China	Observational, cross-sectional	N = 149, Mean age (range): 59.8 (27-90); diabetes type: T2DM	s-TOFHLA
Thabit et al. (2009), Ireland	Observational, cross-sectional	N = 100, Mean age (SD): 45.8 (11.8); diabetes type: T2DM	REALM
Wallace et al. (2009), USA	Observational, cross-sectional	N = 208, Mean age (range): 56 (29-93); diabetes type: T2DM	s-TOFHLA
Wallace, Carlson, Malone, Joyner, and DeWalt (2010), USA	Interventional: one-group pre–post	N = 250, Mean age (range): 58 (23-85); diabetes type: T2DM	s-TOFHLA
White, Osborn, Gebretsadik, Kripalani, and Rothman (2011), USA	Observational, cross-sectional	N = 144, Mean age (SD): 47.8 (12.1); diabetes type: T1DM and T2DM	s-TOFHLA, DNT-15, WRAT-4
Whitten, Buis, Love, and Mackert (2008), USA	Interventional: one-group pre–post	N = 50, Mean age (SD): 40.3 (13.1); diabetes type: NR	s-TOFHLA, REALM
Williams, Baker, Parkes, and Nurss (1998), USA	Observational, cross-sectional	N = 114, Low HL group mean age (SD): 57.4 (10.2), marginal HL group mean age (SD): 53.2 (8.8), high HL group mean age (SD): 49.2 (10.3); diabetes type: T1DM and T2DM	TOFHLA

Note. HL = health literacy; NR = not reported; IQR = interquartile range; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus; REALM = Rapid Estimate of Adult Literacy in Medicine; REALM-R = Rapid Estimate of Adult Literacy in Medicine–Revised; TOFHLA = Test of Functional Health Literacy in Adults; s-TOFHLA = Test of Functional Health Literacy in Adults–Short Form; 3-brief SQ = 3 brief screening questions; SILS = Single Item Literacy Screener; LAD = Literacy Assessment in Diabetes; NVS = Newest Vital Sign; DNT = Diabetes Numeracy Test; WRAT = Wide Range Achievement Test; SNS = Subjective Numeracy Scale.

Authors’ Note

Dr. Johnson is a senior scholar with Alberta Innovates – Health Solutions and holds a Canada Research Chair in Diabetes Health Outcomes.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:

This work was supported in part by an Emerging Team Grant to the Alliance for Canadian Health Outcomes Research in Diabetes (ACHORD; Reference No. OTG-88588), sponsored by the Canadian Institute for Health Research, Institute of Nutrition, Metabolism, and Diabetes.

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