J Public Health 2008 Ibrahim 449 55

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Validation of a health literacy screening tool (REALM) in a UKPopulation with coronary heart disease

S. Y. Ibrahim1

, F. Reid2

, A. Shaw1

, G. Rowlands1

, G. B. Gomez3

, M. Chesnokov4

,M. Ussher21Institute of Primary Care and Public Health, Faculty of Health and Social Care, London South Bank University, 103 Borough Road, London SE1 0AA, UK2Division of Community Health Sciences, St. Georges, University of London, UK3Division of Epidemiology, Public Health and Primary Care, Imperial College, London, UK4Institute of Psychiatry, Kings College London, UK

Address correspondence to Saima Y. Ibrahim, E-mail: [email protected]

A B S T R A C T

Background Health literacy (HL) has been recognized as an important public health issue in other developed countries such as the US. There is

currently no HL screening tool valid for use in the UK. This study aimed to validate a US-developed HL screening tool (the Rapid Estimate for Adult

Literacy in Medicine; REALM) for use in the UK against the UKs general literacy screening tool (the Basic Skills Agency Initial Assessment Test,BSAIT).

Methods A cross-sectional survey involving 300 adult patients admitted to hospital for investigation of coronary heart disease were given the

REALM and BSAIT tools to complete as well as specific questions considered likely to predict HL. These questions relate to the difficulty in

understanding medical information, medical forms or instructions on tablets, frequency of reading books and whether the participants job

involves reading.

Results The REALM was significantly correlated with the BSAIT (r 0.70;P, 0.001), and significantly related to seven of the eight questions

likely to be predictive of HL.

Conclusions This study has shown that the REALM has face, criterion and construct validity for use as an HL screening tool in the UK, in research

and in everyday clinical practice. Further studies are needed to assess the prevalence of low HL in a wider population and to explore the links that

may exist between low HL and poor health in the UK.

Keywords health literacy, literacy, patient needs, poor health, screening tools

Introduction

As the UKs healthcare system develops, there are increased

demands for patients to be able to read and understand

often complex information in leaflets, medication labels,

appointment slips, consent forms and other health-related

materials. Those with low literacy are likely to find difficulty

in understanding this information.13

General literacy has been defined as using printed andwritten information to function in society, to achieve ones

goals and to develop ones knowledge and potential.4

National surveys show that 16% of the population in the

UK have low general literacy skills.5 Health literacy (HL) has

been recognized as a domain of literacy and can be defined

as the degree to which individuals have the capacity to

obtain, process and understand basic health information

and services needed to make appropriate health decisions.6

Therefore, HL is more than just the ability to read and

write, but relates to the successful application of literacy

skills in a health context.

Extensive research in the US has highlighted the impact

of low HL both on the individuals health and on the

healthcare system. HL has been shown to act as an indepen-

dent risk factor for poor health.7 Low HL can act as a

barrier to achieving or maintaining good health through

S. Y. Ibrahim, Research Assistant

F. Re id, Senior Lecturer in Medical Statistics

A. Shaw, Senior Research Fellow

G. Rowlands, Professor and Director of the Institute of Primary Care and Public Health

G. B. Gomez, Research Assistant/PhD Student

M. Chesnokov, Research Programme Manager

M. Ussher, Senior Lecturer in Psychology

# The Author 2008, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. 449

Journal of Public Health | Vol. 30, No. 4, pp. 449 455 | doi:10.1093/pubmed/fdn059 | Advance Access Publication 25 July 2008


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difficulties with reading and understanding medical forms

and leaflets, making and keeping appointments1 and with

following medication instructions.1 3 These difficulties may

be exacerbated by the social stigma patients with low literacy

experience, which can act as a barrier to gaining social

support and advice.89 Patients with low HL are at a higher

risk of poor health and hospitalization resulting in higherhealthcare costs.7,10

The Rapid Estimate of Adult Literacy in Medicine

(REALM) has been developed in the US as a screening tool

for HL.11 It is a word recognition and pronunciation tool

designed for use in healthcare settings and has been shown

to correlate highly with measures of HL such as the Test of

Functional Health Literacy in Adults (TOFHLA).1113

Although the REALM has been used in the UK before, in

three different studies, it has never been validated for use in

a UK population.1416 This raises a concern as both

language and healthcare systems in the US differ signifi-

cantly from those in the UK. Validating an HL screeningtool in the UK would allow researchers to study the impact

of HL and healthcare providers to identify individuals with

limited HL, and hence tailor care to patients needs.

Low HL is likely to become a particular problem if

people become ill or are at an increased risk of illness. For

example, those with coronary heart disease (CHD) are

expected to read, understand and act on complex health

information and medication regimes, as well as consent to

invasive investigations.17 HL has been demonstrated to be

an important issue in cardiovascular disease (CVD),18 but

we were unable to find supporting research carried out in

the UK focusing on HL and CHD, and this study focuses

on this issue. The importance of CHD in public health in

the UK19 makes this disease a suitable choice for investi-

gating HL. This study aimed to validate the REALM for

use in the UK in a group of patients with CHD, as a first

step to building the evidence base on the impact of low HL

on public health in the UK.

Methods

The study entailed a cross-sectional design involving a

questionnaire-based survey.

Participants

Consecutive adult patients with CHD admitted to five cardi-

ology wards at a teaching hospital in south London were

considered for recruitment to the study. Patients considered

to be too ill or distressed to participate by senior ward staff

were not approached, and patients who were approached but

did not meet the inclusion criteria due to sight impairment,

hearing impairment, cognitive difficulties, inability to consult

in English or physical inability to write, were excluded by

the research nurse. Those ,18 years of age were also

excluded. Recruitment took place until 300 completed

interviews were obtained from November 2005 to January

2007.

Measures

The REALM involves subjects reading out loud a list of 66

medical words arranged in an increasing order of difficulty.11

The REALM score is calculated by awarding one for each

correctly pronounced word and nil for each mispronounced

or skipped word. It takes 2 3 min to complete. A score

of 59 or less is defined as indicating low HL by the creators

of the REALM,11 while a score of 60 or more indicates

adequate HL.

The Basic Skills Assessment Initial Test (BSAIT) (literacyversion 1), developed and validated in the UK, provides a

measure of general literacy.20 It takes 20 min for sub-

jects to self-complete a nine-page workbook of 72 questions.

The BSAIT tests reading comprehension using a range of

everyday scenarios such as understanding a cafe menu.

Patient demographics (age, gender, marital status, employ-

ment, ethnicity and age of leaving full-time education) were

recorded. Ethnicity was coded according to the 2001

Census groups of White, Mixed, Asian, Black and Chinese.

Age at leaving full-time education was recoded into those

who left school at or below the school leaving age and

those who left later, using data on school leaving ages fromthe Department for Education and Skills (England).

Six additional questions provided variables with which a

measure of HL would be expected to correlate. Five of

these additional questions were derived from the English

arm of the International Literacy Survey conducted in

1996.21 These questions relate to the difficulty in under-

standing medical forms or instructions on tablets, frequency

of reading books and whether the patients job involves

reading. The question on needing help to read information

or fill in forms from doctors, nurses or hospitals, was

designed by the research team but was not validated.

Procedure

Ward staff indicated which patients could be approached by

the research nurse, who briefed each patient about the study

and gave them the patient information sheet. Written

consent was obtained from all patients who agreed to par-

ticipate. The interview process lasted approximately one

hour and took place by the patients bedside. Demographic

450 JO U R NAL O F PU B LI C HEALT H


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and other questions were read out loud to the patients and

the research nurse recorded the participants responses. The

REALM was presented on a single sheet and given to

participants to read the words out to the research nurse.

The research nurse went through the practice questions of

the BSAIT workbook with each patient, after which the

patients completed the rest of the workbook independentlyas required by the BSAIT procedure.

Analysis

Data were analysed using the Statistical Package for the

Social Sciences (SPSS) software, version 14.0.

Both the criterion and construct validity were assessed.

The criterion validity (measurement against a gold standard)

was assessed in two ways. First, the REALM was correlated

against the BSAIT. As both the REALM and BSAIT scores

were negatively skewed, Spearmans rho was used. Secondly,

the REALM was compared with four alternative measuresof HL relating to patients perception of their ability to

read and understand health-related information, and to

complete medical forms. The percentage of subjects with

low HL (REALM 59) was compared across the ordered

categories of these four measures using the chi-squared test

for trend.

The construct validity (the extent to which the test pre-

dicted other variables in ways which fit with the underlying

construct) was evaluated by assessing the ability of the

REALM to predict HL from patients reported levels of

education, employment status, frequency of reading a book

and whether their job involved reading. The percentage ofsubjects with low HL was compared across categorical vari-

ables using the chi-squared test (or Fishers exact test if

numbers were small), and across ordered categories using

the chi-squared test for trend.

Results

A total of 300 patients participated in this study (Fig. 1).

The majority of the participants were white males, over 60

years and were married or living with a partner (Table 1).

The mean (SD) score for the REALM was 62.1 (6.1) andthe lowest score was 19. REALM scores were negatively

skewed, with 84 participants (28%) scoring the maximum of

66. At a cut-off point of 59 or lower on the REALM, 19%

(n 57) of the sample were found to be in the low literacy

range. REALM scores were not significantly associated with

age, gender or marital status (Table 1). However, ethnicity

was found to be significantly related to REALM scores

(P, 0.001).

Face validity

The REALM requires subjects to recognize and correctly

pronounce 66 medical words of increasing complexity, and

hence has intuitive face validity as a measure of HL. There

was a clear inverse relationship between correct pronuncia-

tion and word length, measured by the number of syllables

per word, adding further to the credibility of the REALM

(Table 2). The number of respondents, who gave a correct

response to the worst performing word, decreased as the

number of syllables increased.

Criterion validity

As there is no gold standard measure of HL in the UK,

the REALM was validated against a general literacy test, the

BSAIT. BSAIT scores were negatively skewed. The mean

(SD) score for the BSAIT was 65 (7.7) and the lowest score

was 29. Forty-three participants scored the maximum of 72

on the BSAIT. Ninety-six subjects (32%) scored 64 or less

on the BSAIT, and were therefore classified as having low

general literacy. The correlation between the REALM and

BSAIT was moderately strong at r 0.70 (P, 0.001)

(Fig. 2).Participants were asked four questions which provided

possible alternative measures of HL. Comparison of REALM

scores with patients perception of their ability to read and

understand health-related information, and ability to complete

medical forms showed a statistically significant relationship

for three of these four questions. Table 3 shows a trend for

decreasing levels of HL with perception of increasing

difficulty in reading or completing medical forms and in

Fig. 1 Recruitment summary.

VAL ID AT IO N OF RE A LM 451


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understanding medical leaflets. Although lower levels of HL

were observed for those who sometimes had difficulty under-

standing instructions on tablets from the chemist, this associ-

ation was not significant.

Construct validity

The construct validity was assessed by the association of

education, employment status and reading (frequency of

reading a book and whether participants job involved

reading) with REALM scores (Table 4). Higher rates of

poor HL were observed for subjects who left school at the

minimum leaving age, who are unemployed, whose job does

not involve reading and who never or only sometimes read

a book. These associations were all statistically significant,

and in the expected direction, reflecting the underlying HL

construct.

Discussion

Main finding of this study

This study confirms that the REALM is a valid HL screening

tool for use in a UK setting. The REALM has face validity

as a tool that presents medical words in order of increasing

difficulty. Additionally, the REALM has criterion validity.

Table 1 Demographic characteristics, by health literacy (HL) status

Characteristic Adequate health literacy (n 242), n (%) Low health literacy (n 58), n (%) P-value

Gender

Female 91 (37.6) 19 (32.8) 0.49

Male 151 (62.4) 39 (67.2)Ethnicity

White 220 (90.9) 45 (77.6) 0.002

Asian 14 (5.8) 3 (5.2)

Black 6 (2.5) 7 (12.1)

Other 2 (0.8) 3 (5.2)

Marital status (n 298)

Single 28 (11.7) 4 (6.9) 0.36

Married/living with partner 144 (60.0) 33 (56.9)

Divorced/separated 27 (11.3) 11 (19.0)

Widowed 41 (17.1) 10 (17.2)

Mean (SD), range Correlation with REALM score (Spearmans rho) P-value

Age (n 298) 64.0 (12.7),2191 0.001 0.98

Table 2 Performance of respondents on individual REALM words, by

number of syllables

REALM words grouped by

number of syllables (number of

words per group)

Number of subjects (out of 300) who

gave a correct response to:

Worst performing

word group

Best performing

word group

1 syllable word (n 10) 294 300

2 syllable words (n

15) 266 3003 syllable words (n 24) 231 299

4 syllable words (n 14) 200 298

5 or 6 syllable words (n 3) 222 292

All words (n 66) 200 300

For example, there are 10 words in the REALM which have one syllable. Of

these, the word which respondents seemed to have most difficulty with

was germs, which 294 out of 300 got correct.

Fig. 2 Scatter plot of REALM scores versus BSAIT scores (criterion validity).



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First, it is highly correlated with a measure of general literacy

developed in the UK. The level of correlation (0.70) found is

what might be expected for two tests measuring similar but

not identical constructs. Secondly, it is statistically related to

patients perceived difficulty in completion of medical forms

and the degree of help required to read or complete medical

forms. Finally, the REALM has construct validity as people

with low REALM scores are more likely to have left school

at the minimum school leaving age, to report reading a

book less often, to be unemployed and to be in a job that

does not involve reading.Ninety-six participants (32%) of our sample population

were detected to have low general literacy as they scored 64

or less on the BSAIT. This contrasts with the most recent

findings from the Skills for Life Survey, when 16% of the

UK population were detected to have low general literacy.5

There may be several reasons for this; first, this may reflect

the fact that the study population, as might be expected for

people with CHD, was older than the general population

and that older people have lower literacy skills.21 Another

possibility is that people with lower literacy skills are more

likely to have chronic disorders than the general population.

This is supported by the findings of the Skills for Life

Survey, where people with lower general literacy skills had

lower ratings of self-reported general health and were more

likely to report chronic illness and disability.5

Our study shows a prevalence of low HL, as indicated by

the REALM scores, of 19%. If, as in the US, low HL is

found to be a predictor of poorer health, low HL is thus

likely to be an important public health issue in the UK.

What is already known on this topic?

It is known that a large proportion of the population in the

UK have low general literacy and numeracy skills.5 Research

in the US has recognized HL as a contributor to poor

health.4 The prevalence of low general literacy and numeracy

skills in the UK raises the possibility that low HL may be a

public health issue in the UK. The importance of CHD as a

Table 3 Associations of REALM scores with alternative measures of HL (criterion validity)

Measures of HL Never Sometimes Often Always P-value

Are medical forms difficult to fill out? 11.6% (25/216) 39.2% (29/74) 50% (4/8) ,0.001

Are medical booklets or leaflets difficult to understand? 15.7% (38/242) 31.1% (14/45) 50% (3/6) 0% (0/1) 0.008

Are instructions on tablets from the chemist hard to understand? 18.4% (51/277) 31.8% (7/22) 0% (0/1) 0.30Do you ever need help to read information or filling in forms

from doctors, nurses or hospitals?

14.2% (36/254) 47.5% (19/40) 75% (3/4) 0% (0/1) ,0.001

Percentage (n/N) of respondents with low HL (REALM 59). For example, 8 respondents often had difficulty filling out medical forms, of whom 4 scored

in the low HL range. Therefore, 50% of those often experiencing difficulty completing medical forms, had literacy difficulties. In contrast, only 11.6% of

those who never had difficulty filling out medical forms, had low HL.

Table 4. Associations of REALM scores with predictors of HL (construct validity)

Predictor of HL Daily Weekly Sometimes Never P-value

How often do you read a book? 9.0% (12/134) 13.8% (4/29) 24.2% (22/91) 44.4% (20/45) ,0.001

Older than school leaving age At or below school leaving age

Age left full-time education 14.0% (24/172) 25.8% (32/124) 0.010

Employed Unemployed

Employment status (excludes retired

subjects)

11.8% (12/102) 28.6% (12/42) 0.014

Yes No

Does your job involve reading?

(employed subjects only)

9.0% (8/89) 30.8% (4/13) 0.045

Percentage (n/N) of respondents with low HL (REALM 59). For example, 45 respondents never read a book, of whom 44.4% ( n 20) scored in the low

HL range. This contrasts with only 9% with low HL among those who read a book daily.



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public health issue19 makes it an important disease area in

which to start investigating the impact of low HL. In the

US, the REALM has been validated as a quick and easy

screening tool and has been tested across different popu-

lations including primary care patients, university clinic

patients and prison inmates.13 The REALM has also been

validated against other US-developed HL measures such asthe TOFHLA.1214

What this study adds

We have validated the REALM for use in a UK setting. This

has implications for both research and practice. Researchers in

the UK can now investigate the links between low HL and a

variety of physical and psychological health problems.

Investigation of the links between low HL and demonstrable

health outcomes, such as the risk of developing CHD and the

risk of having poorer disease outcomes, will enable an accurate

assessment of both the physical costs of low HL to individuals

and families, and the financial costs to the economy throughhigher hospital admissions and treatment costs.

The speed and ease of the administration of the REALM

means that it also has potential as a screening tool that can

be used in everyday clinical practice. Screening patients for

low HL has some potential advantages in everyday clinical

practice; identification of patients with low HL enables them

to be given additional time and resources to support them

to develop skills and to understand health information. The

ease of administration of the REALM (23 min) renders it

short enough for this purpose. It may be, however, that the

stigma associated with low HL might negatively impact

patient self-esteem or the patientpractitioner relationship.

Proxy indicator questions, which can be easily applied to

large populations on routine registration forms, are potentially

a less stigmatizing screening option. In this study we found

that employment status, education attainment, reading a book

and whether or not an individuals job involves reading were

statistically significantly associated with REALM scores.

However, the use of these questions could result in people

being labelled as having low HL without being aware of

being evaluated. Further research is required to assess which

measurement options are best for use in everyday practice

and to understand more about patients views on stigma andacceptability.

Limitations of this study

At the time of the study, there were no measures of HL vali-

dated for use in the UK. The REALM was therefore vali-

dated against the best gold standard available, a test of

general literacy (BSAIT). It is likely that although there will

be a large overlap between health and general literacy, they

reflect different skill sets. Indeed it is possible to hypoth-

esize that people with low general literacy skills who develop

health problems may develop high HL skills in their

disease area; this is a possible explanation for the difference

in prevalence of low general literacy (32%) and HL (19%)

found in our study.

The BSAIT tests a range of skills and presents questionsin varying formats and given the age range of this popu-

lation sample (4080 years), they may not have been fam-

iliar with the style of questions presented to them in the

workbook (such as multiple choice questions). The general-

ization of the findings from this study to other populations

is questionable as the focus was on a population with CHD,

who, by definition will differ from the general population as

they are older and have a chronic disease. Assessment of

low HL in the general population, and of the links between

low HL and the prevalence and severity of chronic dis-

orders, would require further research.

We found that REALM scores were highly negativelyskewed; only seven words wrong out of 66 was sufficient

for a classification of low HL. It can, thus, be argued that

many of the 66 words are redundant and add nothing to

the screening tool. Reducing the length of the REALM to

those words with the most power to discriminate between

those with low and adequate HL would make the REALM

quicker to administer and, thus, more practical for use in

everyday clinical practice.

Our study had a high rate of individuals who declined

participation (42%), which could have been because of indi-

viduals not being able to commit themselves to an hour

long interview for reasons such as being discharged, having

visitors or awaiting procedures. There is also a concern that

participants may have declined to take part in the study

because they were unable to read. We therefore feel it is

likely that the prevalence of those undergoing investigations

of CHD with low HL may be higher than 19%.

Although the REALM will identify individuals at risk of

having low literacy, it should be remembered that the

REALM is only a screening tool and, thus, not a definitive

HL measure. The REALM only tests recognition and pro-

nunciation of medical words and, thus, has limitations as a

measure of the full concept of HL.Since this study was undertaken, the US-developed

TOFHLA [13] has been amended for use in the UK and

has been shown to have construct validity in a UK popu-

lation, by being able to predict healthy lifestyle choices

(eating, smoking) and better levels of self-reported health.22

The TOFHLA, however, takes longer to administer than

the REALM (12 versus 3 min), thus potentially reducing its

usefulness in research and in practice.



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Another measure of HL, also designed in the US, is The

Newest Vital Sign (NVS).23 The NVS presents an American

nutrition label which requires individuals to answer specific

questions relating to it. It takes 3 min to administer and

therefore has potential for use in everyday clinical practice.

Unlike the REALM and TOFHLA, it has no ceiling effect,

meaning it can discriminate between different HL levels atthe upper end of the skill range. The NVS, thus, has poten-

tial as both a research and practice tool; however, it does

require validation for use in the UK.

All of the above measures evaluate HL as a basic skill;

none measure emerging concepts in empowerment and

active citizenship as described by international experts such

as Kickbusch24 and Nutbeam.25 Further research is needed

to develop tools to measure HL in this wider context.

Conclusion

The REALM is now validated for use in the UK as ascreening tool to help identify individuals at risk of low HL.

This study has shown that the REALM has face, criterion

and construct validity for use as a screening tool in research

and in everyday clinical practice. Further research in a UK

setting is needed into this important public health issue.

Funding

The study was funded by STaRNet London. STaRNet

London is funded by the Department of Health.

Acknowledgements

We would like to thank all the staff on participating cardiol-

ogy wards for allowing us to conduct our study. The local

research ethics committee gave their approval to conduct

this study.

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