Patient Education and Counseling 88 (2012) 44–53

Review

Diabetes self-management in patients with low health literacy: Ordering findingsfrom literature in a health literacy framework

Mirjam P. Fransen a,*, Christian von Wagner b, Marie-Louise Essink-Bot a

a Department of Public Health, Amsterdam Medical Centre, University of Amsterdam, Amsterdam, The Netherlandsb Health Behaviour Research Centre, University College London, London, UK

A R T I C L E I N F O

Article history:

Received 8 July 2011

Received in revised form 2 November 2011

Accepted 30 November 2011

Keywords:

Literature review

Health literacy

Diabetes self-management

Sociocognitive determinants

Theoretical framework

A B S T R A C T

Objective: To review studies on the association between health literacy (HL), diabetes self-management

and possible mediating variables.

Methods: We systematically searched for empirical studies in PubMed. Findings were ordered by a HL

framework that outlines routes between HL, sociocognitive determinants and health actions.

Results: Of the 11 relevant studies, three reported a significant positive association between HL and

specific diabetes self-management domains. Ten studies investigated the association between HL and

knowledge (n = 8), beliefs (n = 2), self-efficacy (n = 3) and/or social support (n = 1). Significant

associations were found between HL and knowledge (n = 6), self-efficacy (n = 1) and social support

(n = 1). Of the three studies evaluating the effect of these sociocognitive variables on diabetes self-

management, only one found proof for a mediating variable (social support) in the pathway between HL

and self-management.

Conclusion: There is only limited evidence for a significant association between HL and diabetes self-

management, and for the mediating role of sociocognitive variables in this pathway.

Practice implications: Longitudinal studies, including HL, diabetes self-management and potential

mediators, are needed to substantiate possible associations between these variables. Such research is

essential to enable evidence-based development of interventions to increase adequate and sustainable

self-management in diabetic patients with low HL.

� 2011 Elsevier Ireland Ltd. All rights reserved.

Contents lists available at SciVerse ScienceDirect

Patient Education and Counseling

jo ur n al h o mep ag e: w ww .e lsev ier . co m / loc ate /p ated u co u

1. Introduction

1.1. Diabetes self-management

Self-management has become increasingly important in thetreatment of diabetes mellitus type 2 (DM2). Patients with DM2have become partners in the treatment of their own disease andself-management is crucial to obtain adequate glycaemic control.There is no universally accepted definition of self-management.Barlow et al. defined general self-management as the patient’sability to manage the symptoms, treatment, physical andpsychosocial consequences and lifestyle changes inherent in livingwith a chronic disease [1]. Diabetes self-management is generallydivided into four domains: nutritional management; exercise andphysical activity; blood glucose monitoring; and medicationutilization [2–4]. The American Association of Diabetes Educators

* Corresponding author at: Department of Public Health K2-204, Academic

Medical Centre, University of Amsterdam, PO-Box 22660, 1100 DD Amsterdam, The

Netherlands. Tel.: +31 20 5667443; fax: +31 20 6972316.

E-mail address: m.p.fransen@amc.uva.nl (M.P. Fransen).

0738-3991/$ – see front matter � 2011 Elsevier Ireland Ltd. All rights reserved.

doi:10.1016/j.pec.2011.11.015

(ADEE) operationalized nutritional management into makinghealthy food choices, understanding portion sizes and learningthe best times to eat. Regular activity is important for overallfitness, weight management and blood glucose control. Togetherwith healthcare professionals, patients should address barriers toregular physical activity and develop an appropriate plan tobalance food and medication with the activity level. The AADE alsonote that daily self-monitoring of blood glucose provides patientswith diabetes the information they need to assess how food,physical activity and medications affect their blood glucose levels.To adequately utilize medications, patients should be knowledge-able about each medication, including its action, side effects,efficacy, toxicity, prescribed dosage, appropriate timing, frequencyof administration, effect of missed/delayed doses and instructionsfor storage, travel and safety [5].

1.2. Health literacy

To implement optimal diabetes self-management, patientsmust apply specific knowledge and decision-making skills acrossthe multiple domains of self-management. This requires adequate

Fig. 1. Framework of health literacy and health actions.

M.P. Fransen et al. / Patient Education and Counseling 88 (2012) 44–53 45

health literacy (HL). The Institute of Medicine (IOM) defined HL asthe degree to which individuals have the capacity to obtain,process, and understand basic health information and servicesneeded to make appropriate health decisions [6]. Subjects with lowHL tend to be less likely to successfully manage chronic diseases[7,8]. They generally have less knowledge about their disease,exhibit inadequate self-management and have poor health out-comes [9–14].

1.3. Framework for health literacy and health actions

In 2007 Paasche-Orlow and Wolf developed a framework thatoutlined routes through which HL might affect health actions inthe access and utilization of health care, patient–providerinteractions and self-management [15]. Drawing upon these ideas,von Wagner et al. developed a framework for health literacy andhealth actions that was derived from health psychology (Fig. 1)[16]. This framework was developed to guide research on theprocesses through which HL affects health outcomes. Theframework proposes that health actions (access and use of healthcare, patient–provider interactions, and the management of healthand illness, e.g. diabetes self-management) determine healthoutcomes (e.g. HbA1c level) through sociocognitive motivationaland volitional determinants. Motivational determinants includetraditional social cognition constructs (e.g. beliefs and attitudes)which in turn are associated with access to health information andknowledge. For example, adequate knowledge in diabetes self-management consists of knowing the effect of food on bloodglucose. Volitional determinants on the other hand refer toobjective and subjective (e.g. self-efficacy) action control andinclude task-specific skills, such as information processing andnavigational skills to acquire specific knowledge about adherenceregimens, and cognitive skills (e.g. anticipate on glucose levels).The motivational and volitional determinants are not affected bylevels of HL alone, but form a symbiotic relationship with externalsystem factors. For example accessibility of health care informa-tion, communication skills of the health care provider, and out-of-pocket costs for health care. The motivational determinant

‘patient’s understanding of a healthy diet’ also depends on howwell the healthcare provider is able to explain what the patientshould or should not eat to maintain a healthy diet [16].

1.4. Aim

The aim of this paper is to review the literature on theassociation between HL and diabetes self-management, and thepossible mediating variables in this pathway. A secondary aim is toorder the findings in the framework proposed by von Wagner et al.In the Section 2 we explain why we chose this framework to orderour literature findings and describe the methods for our literaturereview. The findings of our literature review are schematicallyreported in the Section 3. The paper ends with a discussion of thefindings and implications for further research.

2. Methods

2.1. Literature review

In July 2011, we searched for articles on HL, diabetes, diabetesself-management and its four domains (nutritional management;exercise and physical activity; blood glucose monitoring; andmedication utilization). Relevant search terms were derived fromliterature on HL and diabetes self-management [9–14]. We usedthe following keywords and Medical Subject Headings (MeSH) tosearch in PubMed:

[Health literacy or literacy or numeracy] and [diabetes] and[self-management or self-monitor or medication adherence or dietor food or exercise or sports].

Except for ‘numeracy’ and ‘self-monitor’, all terms were MeSHterms. This means that PubMed automatically searched for paperswith equivalents of these terms. Additional articles were identifiedby reviewing the reference lists of the retrieved articles.

Inclusion criteria were:� Empirical studies among patients with DM2.� Reporting on the association between HL and diabetes self-

management tasks.

Fig. 2. Flow diagram literature search.

M.P. Fransen et al. / Patient Education and Counseling 88 (2012) 44–5346

� Published in the English language.

Exclusion criteria were:� Papers reporting on patients with comorbidity.� Reviews and case reports.� Not published as a scientific paper (e.g. abstracts or theses).

The initial search yielded 139 papers, published between 1988and June 2011. A flow diagram of the review process is presented inFig. 2. After one reviewer (MF) screened titles and abstracts on

Fig. 3. Findings of literature review

relevance, this number was reduced to 32 publications. The 32abstracts were then critically reviewed by MLE, resulting in 26 fullpapers. Most excluded papers did not report on the associationbetween HL and performance of diabetes self-management tasks.Consensus was reached between MF and MLE-B by reading anddiscussing the content of 26 full-text papers. All reviews stageswere based on the same in- and exclusion criteria. Papers wererated as sufficient when MF and MLE both decided that allinclusion criteria were clearly met and exclusion criteria were notapplicable. This accounted for 10 papers. Papers were rateddoubtful when there was no consensus on sufficiency for inclusion,e.g. when papers met part of the inclusion criteria. This accountedfor 16 papers, most of these concerned intervention developmentstudies where the association between HL and self-managementwas partly studied. These doubtful papers (n = 16) were exten-sively discussed by MF and MLE, resulting in the exclusion of 15papers, leaving 11 papers for the literature study.

For each paper we reported how HL and self-management wasdefined and measured, which determinants in the pathway betweenHL and self-management were studied, and the most relevantresults. The methodological quality of the papers was based onguidelines for cohort studies as defined by the Cochrane Collabora-tion [17]. We assessed whether the characteristics of the studypopulation and the outcome measures were well defined, the appliedmeasurement tools were valid, confounders were corrected for in theanalysis and whether the results were valid and applicable. Theresults of the review were discussed in light of the HL framework.

2.2. Order findings in framework

The literature findings were ordered in von Wagner’s frame-work for HL and health actions. This framework enables theordering of variables in the pathway between HL and diabetes self-management and places HL in the context of sociocognitive

in health literacy framework.

Table 1Papers reporting on empirical studies on health literacy and diabetes self-management (n = 11).

Author, year Aim Design Population Relevant measurements Analyses Results

Bains and Egede,

2011 [18]

Assess associations

among HL, diabetes

knowledge,

self-management

and glycemic control.

Cross-

sectional

survey

Patients with DM2 in

primary care clinic

in the US (n = 125)

HL: REALM-R Spearman’s correlation

and multiple regression

analysis

HL was significantly associated with knowledge

(b= 0.55; CI 0.29, 0.82).

65+ years: 49%

Mediating variables:

Knowledge was significantly associated with

glycemic control (b = 0.12; CI 0.01–0.23).Female: 72.5%

- Knowledge (DKQ)

HL was not significantly associated with SM or HbA1c.

SM: SDSCA

Other: HbA1cl;

medication adherence

Cavanaugh

et al., 2008 [19]

Examine association

between numeracy

and diabetes control.

Cross-

sectional

survey

Patients with DM1 or

DM2 in primary care

and diabetes clinics

in the US (n = 398)

HL: DNT Cuzick nonparametric

test for trend

Lower DNT scores were associated with:

Median age: 55

Mediating variables:

- Lower median DKT (52% vs 86%, p<0.001)

Female: 51%

- Knowledge (DKT)

- Lower self-efficacy of SM (9% vs 12%, p = 0.003)

Type 2 diabetes: 86%

- Self-efficacy (self-report)

- Adjustment of insulin dose

(38% vs 75%, p<0.001)

Duration diabetes:

9 years

SM: SDSCA

- Adjustment of carbohydrate

intake (12% vs 72%, p<0.001).

Other: Diabetes

control (HbA1C)

Participation in dietary, physical

activity or medication behaviours were not

significantly associated with DNT scores.

DTN was modestly associated with HbA1c

level. A 10-percentage point decrease of

correct DNT responses predicted an increase

of HbA1c of 0.09% (95% CI 0.01–0.16, p = 0.03).

Hawthorne and

Tomlinson,

1999 [20]

Study factors affecting

diabetes control and SM.

Cross-

sectional

survey

British Pakistani patients

with DM2 (n = 201)

HL: Subjective literacy,

no measure reported

x2 test Illiterate patients had less knowledge on:

Mean age: 54 Mediating variables: - Handling raised glucose levels (9% vs 30%, p<0.01)

Female: n = 107 - Knowledge food values - Chiropodist (4% vs 17%, p = 0.01)

- Knowledge SM - Diabetes complications (19% vs

47%; 19% vs 39%, p<0.01; 13% vs 16%, p>0.05).

- Knowledge complications HL was not significantly associated with knowledge

of food values, glucose self-monitoring and HbA1c.SM: Glucose self-

monitoring

(self-reported)

Other: Diabetes

control (HbA1C)

Karter,

et al.,

2010 [21]

Investigate barriers to

insulin initiation following

a new prescription.

Cross-

sectional

survey

Insulin-naive patients with

poorly controlled type 2

diabetes in the USA (n = 169)

HL: SBSQ Not reported Compared to adherent patients,

non-adherent patients more often

reported low HL (30% vs 51%, p<0.05).

Mediating variables:

Non adherent patients:

- Provider communication

Mean age: 61

- SM training

Female: 35%

SM: Adherence of insulin

treatment (dispense of the

newly prescribed insulin

within 60 days of the

prescribing date)

Adherent patients:

Mean age: 58

Female: 47%

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Table 1 (Continued )

Author, year Aim Design Population Relevant measurements Analyses Results

Kim

et al.,

2004 [22]

Examine the association

between HL and SM and

determine the effect of

diabetes education on

SM in patients with

limited and adequate HL.

Prospective

observational

study

DM1/2 patients enrolled

in diabetes education

classes at the Hospital of

the University of

Pennsylvania, USA (n = 92)

HL: s-TOFHLA Paired t-tests At baseline, patients with adequate HL had better

mean knowledge than patients with limited HL

(17.2 vs 13.9, p = 0.014). Health literacy was not

significantly associated with SM or HbA1c-levels.

Adequate HL patients:

Mediating variable:

After diabetes education, those with adequate

HL had higher knowledge scores (19.9 vs 18.0, p<0.00)

and exercised more (2.8 vs 2.1, p = 0.02). But patients

with lower HL reported better adherence to diet

(6.0 vs 5.2, p<0.00), self-glucose monitoring (6.6

vs 5.4, p = 0.002), and foot care (5.1 vs 5.0, p = 0.001).

Mean age: 58

- Diabetes knowledge (DKQ)

Female: 59%

SM: SDSCA

Duration diabetes: 7.8

Other: HbA1c

Limited HL patients:

Mean age: 67

Female: 81%

Duration diabetes: 9.3

Mancuso,

2010 [23]

Examine the impact

of HL on glycemic control.

Cross-

sectional

survey

Patients with DM1/2 in two

primary care clinics in the

USA (n = 102)

HL: TOFHLA Multiple regression

analysis and correlation

coefficients

A significant positive correlation was found between

HL and diabetes knowledge (rho 0.296, p<0.01).

Mean age: 52

Mediating variable:

HL was not significantly correlated with SM or HbA1C.

Female: 61%

- Knowledge of

diabetes (DKT)

Duration diabetes: 5.8 SM: SDSCA

Other: Glycemic control

(HbA1C); patient trust

(HCR Trust Scale);

Depression (CES-D)

Mbaezue

et al.,

2010 [24]

Examine the relationship

between HL and

self-monitoring

of blood glucose.

Cross-

sectional

survey

Diabetic patients

receiving care in a large

urban public health care

setting in the USA (n = 189)

HL: TOFHLA x2 tests and

multivariate logistic

regression analysis

There was no difference in SBMG among patients by

HL level. However, those with adequate HL more

often kept a record of their glucose levels than patients

with inadequate HL (64.6% vs 35.4%, p = 0.049). In

multivariate logistic modelling, no significant

association was found between HL and SBMG.

Mean age: 51

SM: SBMG

Female: 59%

Duration diabetes: 8.5

Osborn

et al.,

2010 [25]

Examine the relationship

between HL, determinants

of SM and glycemic control.

Cross-

sectional

study

Patients with DM2

at a university

hospital (n = 130)

HL: REALM-R Structural equation

modelling

HL did not have a direct effect on diabetes

knowledge, fatalism, SM or glycemic control.

Mean age: 62.7

Mediating variables:

More knowledge (r = 0.22, p<0.05), less fatalism

(r =�0.22, p<0.05, and more social support (r =�0.27),

p<0.01) were independent, direct predictors of

self-management and through self-management

related to glycemic control (r =�0.20, p<0.05).

Female: 72.5%

- Diabetes knowledge

(DKQ)

HL had a direct effect on social support (r = 0.02, p<0.01)

and through social support an indirect effect on SM

(r =�0.07) and an indirect effect on glycemic control

(r =�0.01).

- Diabetes fatalism

- Social support (MOS

Social Support Survey)SM: SDSCA

Other: Glycemic control

(HbA1C)

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8

Powell

et al.,

2007 [26]

Sarkar

et al.,

2006 [27]

Explore the relationship

among HL, readiness to

take health actions

and diabetes knowledge.

Examine the relationship

between diabetes self-

efficacy and SM in a

population with

a high prevalence

of low HL.

Cross-

sectional

study

Cross-

sectional

study

Patients with DM2 receiving

care at a general internal

medicine clinic in the USA (n = 68)

HL: REALM Multiple linear

regression

analysis

Multivariate

regression

analyses

HL was associated with diabetes knowledge and

hbA1C. Those with low HL had lower DKT scores

(estimated coefficients �13.2; �18.5; �12.9 p = 0.004)

and higher hbA1C levels (estimated coefficients

1.36; 1.21; 1.24 p = 0.02).

Median age: 55

Mediating variable:

No significant association was found between DHBM

scale score and HL levels.

Female: 80%

- Diabetes knowledge (DKT)

Duration diabetes: 7

SM: Diabetes Health

Beliefs (DHBM)Other: HbA1C

Patients with DM2 at two

primary care clinics at a

public hospital in the

USA (n = 408)

HL: s-TOFHLA

Self-efficacy was associated with SM across health

literacy levels (OR 1.14; CI 1.04–1.33).Mean age: 58.1

Mediating variable:

No significant interactions were found between

self-efficacy and HL on the SM outcomes.

Duration diabetes: 9.5

- Diabetes self-efficacy

SM: SDSCA

Wallace

et al.,

2009 [28]

Evaluate the impact of a

literacy-appropriate diabetes

education guide on diabetes

SM among patients with

adequate and inadequate HL.

Intervention

study

English and Spanish speaking

DM2 patients in academic

internal medicine practices

in the USA (n = 250)

HL: s-TOFHLA Independent

t-tests

At baseline, patients with marginal or inadequate HL

scored higher on mean diabetes self-management

activities (manage medications, monitor blood

glucose, maintain a diet, exercise and conduct foot

care) than patients with

adequate HL (76.71 vs 73.52).

Mean age:56

Other:

Female: 64.8%

- Patient activation (PAM)

At baseline, patients with marginal or inadequate HL

scored lower on mean self-efficacy than patients with

adequate HL (73.13 vs 74.02).

- Self-efficacy

- Diabetes knowledge

At baseline, patients with marginal or inadequate

HL scored lower on knowledge than patients with

adequate HL (51.77 vs 60.83).

SM: Subjective scale for

diabetes self-management

activities

DM = Diabetes mellitus. HL = health literacy. DNT = diabetes numeracy test. SM = self-management. SCSCA = summary of diabetes self care activities scale. SBSQ = set of brief screening questions. REALM = rapid estimate of adult

literacy in medicine. TOFHLA = test of functional health literacy in adults. DKQ = diabetes knowledge questionnaire. SBMG = self-monitoring of blood glucose. DKT = diabetes knowledge test. HCR Trust Scale = Health Care Relationship

Trust Scale. CES-D = Centre for Epidemiological Studies Depression Scale. MOS = medical outcomes study. DHBM = Diabetes Health Belief Model Scale. PAM = patient activation measure.

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Table 2Quality of the selected papers on health literacy and diabetes self-management (n = 11).

Author, year Study population

description

Outcome

measures

description

Valid

measurements

Description of

analysis

Correction for

confounders

Validity and

applicability of results

Bains and Egede, 2011 + + + + + +

Cavanaugh et al., 2008 + + + + � +

Hawthorne and Tomlinson, 1999 + � � + � +/-

Karter et al., 2010 + + + � � �Kim et al., 2004 + + + + � +

Mbaezue et al., 2010 + + + + + +

Mancuso et al., 2010 + + + + + +

Osborn et al., 2010 + + + + + +

Powell et al., 2007 + + + + + +

Sarkar et al., 2006 + + + + + +

Wallace et al., 2009 + + + + � �

+: sufficient; �: insufficient; �: doubtful.

M.P. Fransen et al. / Patient Education and Counseling 88 (2012) 44–5350

theories of health behaviour. To design specific evidence-basedinterventions to promote adequate self-management amongdiabetic patients with low HL, we need more information onhow sociocognitive and psychological variables influence self-management in patients with low HL. Von Wagner’s frameworkprovides a suitable theoretical basis for further research andintervention development.

3. Results

In this section we first summarize the content and methodo-logical quality of the papers that were included in our review(Section 3.1). We then describe findings on the associationbetween HL and diabetes self-management (Section 3.2). Weend with findings on possible mediating variables in theassociation between health literacy and self-management, dividedinto motivational and volitional determinants (Section 3.3). Fig. 3presents a schematic ordering of the findings in von Wagner’sframework.

3.1. Included papers and methodological quality

Table 1 presents the design and main findings of the papers thatwere included in the review. Ten studies were performed in theUSA, and one in the UK [18–28]. Nine studies were cross-sectional[18–21,23–27]. Two were prospective observational studies toevaluate the effect of diabetes education [22,28]. Table 2summarizes the methodological quality of each paper. Thecross-sectional design that most studies applied limits interpreta-tion of the causality between HL, determinants and self-manage-ment [18–21,23–27]. Because the beneficial effect of self-management on sociocognitive determinants (e.g. knowledge

Table 3Reported associations between health literacy and diabetes self-management activities

Author, year HL-Measure Domain of dia

Nutrition

Bains, 2011 REALM-R 0

Cavanaugh, 2008 DNT +

Hawthorne and Tomlinson, 1999 REALM *

Karter et al., 2010 SBSQ *

Kim et al., 2004 s-TOFHLA 0

Mancuso, 2010 TOFHLA 0

Mbaezue et al., 2010 TOFHLA *

Osborn et al., 2010 REALM-R 0

Sarkar et al., 2006 s-TOFHLA 0

Wallace et al., 2009 s-TOFHLA ?

+: significant positive association; 0: no significant association; ?: no statistical signifi

and self-efficacy) over time is feasible, there could be a reciprocalrelationship that can only be evaluated in prospective cohortstudies. Three studies had problems with statistical power[22,23,26]. Most studies applied valid measures to assess HL,self-management and other variables. However, it must be notedthat in all 11 studies self-management assessment was based onself-report alone and that the applied HL measures only evaluatedfunctional HL and not the broader concept of HL as defined by theIOM.

3.2. Health literacy and self-management

Three studies found a significant direct positive associationbetween HL and self-management activities (Table 3) [19,24].Mbaezue et al. reported that patients with adequate HL more oftenkept a record of their glucose levels than patients with inadequateHL (64.6% vs. 35.4%, p = 0.049). However, no significant associationwas found between HL and the frequency of self-monitoring ofblood glucose [24]. Karter et al. found that significantly more non-adherent patients in insulin treatment reported low HL comparedto adherent patients (51% vs. 30%, p < 0.05) [21]. Cavanaugh et al.found that higher diabetes-related numeracy among patientsreporting insulin use was associated with the adjustment of insulindose for blood glucose level (38% among lowest HL vs. 75% amonghighest HL, p < 0.001) and carbohydrate intake (12% among lowestHL vs. 75% among highest HL) [19]. Eight studies found no directsignificant association between HL and diabetes self-management(Table 3) [18,20,22,23,25–28]. Five of them found that HL was notsignificantly associated with self-care activities as measured by theSummary of Diabetes Self-Care Activities scale (SDSCA)[18,22,23,25,27]. This scale measures self-reported frequency ofdiabetes self-management in the past 7 days for five aspects of the

(n = 11).

betes self-management

Physical activity Glucose monitoring Medication

0 0 0

0 0 +

* 0 *

* * +

0 0 0

0 0 0

* + *

0 0 0

0 0 0

? ? ?

cance reported; *: no association measured.

M.P. Fransen et al. / Patient Education and Counseling 88 (2012) 44–53 51

diabetes regimen: diet, foot care, blood-glucose testing, exerciseand cigarette smoking [3].

In addition to the relation between HL and diabetes self-management, seven studies investigated the relationship betweenHL and HbA1c-level [18,19,22,23,25,26]. Two of them reportedsignificant associations [19,26].

3.3. Possible mediating variables in health literacy and

self-management

Eight studies reported on variables that could be ordered in themotivational determinants (knowledge, beliefs and attitudes) invon Wagner’s framework [18–20,22,23,25,26,28]. Von Wagneremphasized that motivation alone is not enough to perform self-management. Concepts such as self-efficacy (volitional determi-nants) and practical barriers (system factors) influence thetranslation of intentions into action. Three studies reported onHL, self-efficacy and diabetes self-management [19,27,28]. Onestudy reported on HL, social support and self-management [25].We found no studies on the influence of system factors in thepathway between HL and diabetes self-management. Below wedescribe the studies that report on motivational and volitionaldeterminants in the pathway between HL and diabetes self-management.

3.3.1. Motivational determinants

3.3.1.1. Knowledge. Eight studies investigated the associationbetween HL and diabetes knowledge [18–20,22,23,25,26,28]. Sixof them reported a significant positive correlation between HL anddiabetes knowledge [18–20,22,23,26]. However, none of theseactually demonstrated that inadequate knowledge in patients withlow HL influenced their diabetes self-management. Osborn et al.found that diabetes knowledge was positively associated with self-management, but did not find a direct relationship between HL anddiabetes knowledge [25].

3.3.1.2. Beliefs and attitudes. In von Wagner’s framework beliefsand attitudes are considered an important mediating factor in thepathway between HL and self-management. Two studies investi-gated the association between HL and patient beliefs in relation todiabetes self-management [25,26]. Powel et al. found that HL wasnot associated with scores on the Diabetes Health Belief Model(after controlling for educational level, age, DKT score, race) [26].Osborn et al. measured the relation between HL, diabetes fatalismand self-management. Diabetes fatalism is defined as a complexpsychological cycle characterized by perceptions of despair,hopelessness, and powerlessness. They reported that diabetesfatalism had a direct effect on diabetes self-management, but thatHL did not have a direct effect on diabetes fatalism [25]. None ofthe studies assessed the relation between knowledge and beliefs,as proposed in von Wagner’s model.

3.3.2. Volitional determinants

3.3.2.1. Self-efficacy. Three studies investigated the associationbetween HL and self-efficacy [19,27,28]. Cavanaugh et al. de-scribed that patients with higher diabetes-related numeracy weremore likely to have a greater perceived self-efficacy compared withlow numeracy patients [19]. Wallace et al. found that patients withmarginal or inadequate HL scored lower on mean self-efficacy thanpatients with adequate HL at baseline (73.13 vs. 74.02), however,they did not report any significance levels of this difference [28].Only one study investigated the role of self-efficacy in thepathway between HL and diabetes self-management [27]. Theyfound an association between increasing self-efficacy score and

self-management with regard to diet, exercise, self-monitoringand foot care across HL levels, but no significant interactionsbetween self-efficacy and HL [27].

3.3.2.2. Social support. Osborn et al. found that low HL had a directnegative effect on social support (r = �0.2, p < 0.05) and, throughsocial support, had an indirect negative effect on diabetes self-management and glycaemic control [25]. Although social supportwas not implemented in von Wagner’s model, it can be consideredas a post-intentional variable. Therefore, we added it to the modelin the volitional phase.

4. Discussion and conclusion

Below we discuss the main findings in this literature review anddescribe various gaps in research on HL and diabetes self-management. The discussion ends with a reflection on strengthsand weaknesses of this study. The discussion is followed by ageneral conclusion and implications for further research.

4.1. Discussion

4.1.1. Discussion of main findings

The results of this literature review show that evidence for theassociation between HL and diabetes self-management is verylimited and may vary within the domains of self-management. Onlythree studies reported a direct association between HL and specificdomains of diabetes self-management (recording glucose levels,treatment adherence, adjustment of insulin dose, and carbohydrateintake). Eight studies found no direct significant associationbetween HL and self-management. In contrast to what is generallyexpected, current research cannot confirm that low HL is associatedwith inadequate diabetes self-management. This is in line with thenon-consistent data on the impact of HL on glycaemic control thathave been reported over the years [9,12,19,23,25,29,30].

Furthermore, limited evidence was found for the hypothesisthat HL influences self-management via motivational and voli-tional determinants as described in von Wagner’s framework. As inother studies, significant associations were found between HL andknowledge (n = 6), self-efficacy (n = 1) and social support (n = 1)[14,31–34]. However, only three studies evaluated the effect ofthese sociocognitive variables on diabetes self-management. Twoof them found that sociocognitive determinants (knowledge andself-efficacy) influenced self-management, but found no associa-tion between HL and these determinants. Only one study foundproof for a mediating variable (social support) in the pathwaybetween HL and self-management. The very limited evidence onthe mediating role of sociocognitive variables may be attributed tothe fact that most studies did not test for causal relations betweenall variables in the pathway between HL and self-management, ascan be done by structural equation modelling. Only Osborn et al.applied this latter technique and found that social support had amediating effect in the pathway between HL and diabetes self-management [25].

4.1.2. Gaps in research on health literacy diabetes self-management

This review has identified several gaps in the research on HLand diabetes self-management. While it is generally assumed thatlow HL is associated with inadequate diabetes self-management,few studies actually investigated this association over the yearsand very few found significant associations in highly specific self-management domains. Only one study used diabetes specific HLmeasures, such as the Diabetes Numeracy Test [19]. Furthermore,the role of possible mediating variables in the pathway between HLand self-management has hardly been evaluated. Research so farhas focused on the association between HL and variables that may

M.P. Fransen et al. / Patient Education and Counseling 88 (2012) 44–5352

play a role in diabetes self-management (e.g. knowledge) and noton the possible mediating role of these variables in the relationshipbetween HL and self-management. Although several studies, forexample, demonstrated that inadequate HL is associated withinsufficient diabetes knowledge, the role of insufficient knowledgeon self-management among patients with low HL remains unclearand needs further investigation [14,31–34]. The same applies tovolitional determinants such as self-efficacy and social support.Although it is generally believed that adequate self-efficacyimproves diabetes self-management, the mediating role of self-efficacy in the pathway between HL and self-management hashardly been studied [35].

4.1.3. Strength and limitations

A limitation of the present review is that only PubMed was usedto search for studies on HL and diabetes self-management, andonly reports in English were included. However, a strength is thatwe are the first to perform a systematic literature search on theassociation between HL and diabetes self-management, andpossible mediating variables. Furthermore, we are the first toorder findings of a literature review in von Wagner’s framework forHL and health actions. The framework has been applied before astheoretical basis for research on the association between healthliteracy and self-efficacy for participation in colorectal cancerscreening and for research on the association between numeracyand quality of patient–provider communication [36,37]. It alsoformed part of a wider framework of health inequalities in cancerscreening [38]. Our study has implications for further research onthe pathway between HL and health actions as described in vonWagner’s framework and stimulates research on the impact of HLon diabetes self-management.

4.2. Conclusion

To date few empirical studies have investigated the associationbetween HL and diabetes self-management. There is only limitedevidence that low HL is associated with inadequate diabetes self-management. This evidence accounts for very specific self-management domains. The evidence for the hypothesis that HLinfluences self-management via possible mediating sociocognitivevariables (e.g. motivational and volitional determinants) is alsoweak.

4.3. Implications

More studies are needed to substantiate the associationbetween HL and diabetes self-management and to identify towhat extent mediating variables play a role in the possiblepathway between HL and diabetes self-management. Prospectivelongitudinal studies are needed to investigate possible causalrelationships between HL, mediating variables and health actions,such as self-management. The size of the research population inthese studies should be sufficient to statistically test and estimatecausal relations (e.g. structural equation modelling). This isnecessary to investigate how HL is related to possible mediatingvariables and to what extent these variables are related to diabetesself-management and, in turn, glycaemic control. Furthermore,standardized valid and diabetes specific measures are needed toassess HL and self-management in low health literate populations.The validity of self-reported measures of HL and self-managementneed to be tested among subjects with low HL. Since currentobjective HL measures only evaluate the ability to read, calculateand understand, new HL measures are needed that also measurethe skills to obtain and use information to make appropriate healthdecisions. Such developments in research on HL and diabetes self-management are essential to understand the impact of HL on

health behaviour, and health outcomes and will eventually enableevidence-based development of interventions to increase ade-quate and sustainable self-management in diabetic patients withlow HL.

Conflicts of interest

The authors have no conflicts of interest to declare.

Acknowledgements

The authors thank Petra Jellema for her constructive commentson this review.

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