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Exploring the relationships between health literacy, social support, self-efficacy and self-management in adults with multiple chronic diseases

BMC Health Services Research volume 23, Article number: 923 (2023) Cite this article

Abstract

Background

Self-management in chronic diseases is essential to slowing disease progression and preventing complications. However, empirical research on the associations of critical factors, such as health literacy, social support, and self-efficacy with self-management in the context of multiple chronic diseases is scarce. This study aimed to investigate these associations and provides insights for healthcare providers to develop effective educational strategies for people with multiple chronic diseases.

Methods

Using a cross-sectional survey design, adults (n = 600) diagnosed with at least two chronic diseases were conveniently recruited. To measure health literacy, social support, self-efficacy, and chronic disease self-management behaviours, the Health Literacy Questionnaire (HLQ), Medical Outcome Study - Social Support Survey, Self-efficacy in Managing Chronic Disease, and Self-management in Chronic Diseases instruments were utilized respectively. Comorbidity status was assessed using Age-adjusted Charlson Comorbidity Index (ACCI). A generalised linear regression model was used with a backward technique to identify variables associated with self-management.

Results

Participants’ mean age was 61 years (SD = 15.3), 46% were female, and most had up to 12 years of education (82.3%). Mean scores for HLQ domains 1–5 varied from 2.61 to 3.24 (possible score 1–4); domains 6–9 from 3.29 to 3.65 (possible score 1–5). The mean scores were 52.7 (SD = 10.4, possible score 0–95), 5.46 (SD = 1.9, possible score 0–10) and 82.1 (SD = 12.4, possible score 30–120) for social support, self-efficacy, and self-management, respectively. Mean ACCI was 6.7 (SD = 2.1). Eight factors (age > 65 years, being female, 4 health literacy domains, greater social support, and higher self-efficacy levels) were significantly associated with greater self-management behaviours while comorbidity status was not. The factors that showed the strongest associations with self-management were critical health literacy domains: appraisal of health information, social support for health, and healthcare provider support.

Conclusions

Developing critical health literacy abilities is a more effective way to enhance self-management behaviours than relying solely on self-confidence or social support, especially for people with multiple chronic diseases. By facilitating communication and patient education, healthcare providers can help patients improve their critical health literacy, which in turn can enhance their self-management behaviours.

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Background

As the global population continues to age, there has been a significant rise in the prevalence of multiple chronic diseases among older individuals, which is becoming a growing burden on healthcare systems worldwide [1]. People with multiple chronic diseases are likely to experience extra physical and psychological symptoms, requiring a greater frequency of visits to a range of healthcare professionals, higher medication burden, and more hospital admissions [2, 3]. Developing self-management behaviours is crucial for them to prevent long-term health complications [4], reduce or slow chronic disease progression [5], and improve health-related quality of life [6]. Except for unique requirements in treatment, adequate self-management in any chronic disease would involve six core skills - problem-solving, decision-making, resource utilisation, establishing and maintaining a patient-provider relationship, action planning, and self-tailoring to manage the diseases [7]. Self-management can be more challenging for individuals with low health literacy capabilities and is often reflected in lower adherence to treatment regimens [8], increasing difficulty with accessing suitable health services, and higher rates of emergency department presentations [9].

Health literacy comprises the ability to obtain, communicate, process and understand health information and services, and to make decisions about one’s health [10]. Health literacy is more than simply the ability to read health information as functional literacy is not sufficient for people to manage health conditions or complex healthcare systems. Nutbeam proposed the notion that health literacy is inclusive of three ascending hierarchical skill domains: (i) functional – reading and writing skills, (ii) communicative – cognitive and literacy skills needed to apply information and (iii) critical – to analyse information and to use that information to make health decisions [11]. Studies of health literacy across demographic groups have demonstrated that many people have difficulties in at least one of those health literacy domains [12], especially those with multiple chronic diseases [13]. Research has shown that different domains of health literacy have varying impacts on self-management behaviours in chronic diseases. While it is important for individuals to be able to understand basic health information, functional health literacy has been found to be less crucial than communicative and critical health literacy domains [14] in fostering self-management behaviours in chronic diseases [15,16,17,18,19].

While strong health literacy abilities empower individuals to make their own health decisions, for various reasons, such as being older or having multiple diseases, can mean that many people are likely to need some sort of support from a network of social relationships (e.g. family members, friends, neighbours, relatives and others) to do so [20]. These social relationships can provide various types of support around everyday activities, and this support is more important when someone needs help with healthcare. Access to social support networks can improve mental health [21] and greater adherence to a treatment plan [22], both of which are core to successful self-management behaviours. Social support can come in variety of forms, inclusive of emotional, informational and tangible support [23]. For example, Wang et al. tested a model finding that informational support, over other social supports, was the most important in type 2 diabetes self-management [24]. Social support also has a strong association with chronic kidney disease (CKD) self-management than functional health literacy does [14].

Another contributing factor to self-management is self-efficacy, which is the self-belief of an individual about their capacity to successfully perform an activity [25]. Self-efficacy is a mechanism to achieve effective self-management, as it is a core belief that underlies each of the basic processes of behavioural changes: it’s the motivation to change, the ability to overcome obstacles, and the extent one can maintain new behaviour [26]. Studies consistently report a positive correlation between self-efficacy and chronic disease self-management [27, 28]. Self-efficacy strategies when integrated into interventions as a mechanism to improving chronic disease self-management behaviours, have demonstrated effectiveness [29, 30].

The literature indicates that health literacy, social support, and self-efficacy individually or collectively have positive associations with chronic disease self-management abilities. There have been studies examining the individual relationships between health literacy [31] or social support [32] and self-management, or both health literacy and social support as predictors of self-management [14, 33]. Some of these studies have been flawed with respect to health literacy through only measuring the functional dimensions of health literacy [14]. Most of these studies examined these relationships in one chronic disease [31,32,33]. Due to the increasing prevalence of and burden associated with living with multiple chronic diseases, people will need greater health literacy capabilities, self-efficacy, and/or need additional social support. However, no studies have examined the relative strengths of the relationships between all these concepts on self-management behaviours for multiple chronic diseases. This knowledge would inform healthcare providers to better support patients.

Aims

This study aimed to test the associations between health literacy, social support, and self-efficacy on self-management behaviours of individuals with multiple chronic diseases.

Methods

Design

A cross-sectional design was employed and is reported according to STROBE guidelines [34].

Participants and setting

Participants were recruited from three inpatient medical wards (cardiology, nephrology, and endocrinology) at a large tertiary public hospital in Hanoi, Vietnam between November 2018 to April 2019. The inclusion criteria were: (i) being ≥ 18 years of age, (ii) having a confirmed medical diagnosis of 2 or more of the following chronic diseases: heart failure with a New York Heart Association classification of II-IV [35], hypertension (or systolic BP ≥ 140 mmHg, diastolic BP ≥ 90 mmHg or on prescribed antihypertensive agents) [36], CKD with an estimated glomerular filtration rate (eGFR) < 90mL/min/1.7m2 (or eGFR grades 2–5 according to Kidney Disease Improving Global Outcomes guidelines) [37] or diabetes type 2 [38] for at least 3 months, and (iii) volunteered to participate. A medical doctor in each ward identified patients with two or more of these diseases/conditions and notified the research team. These chronic diseases were identified due to their high prevalence and high frequency of their combinations in clinical settings, and their similar principles of self-management, inclusive of monitoring symptoms, managing medication treatment, and making dietary, exercise and other lifestyle adjustments [39], that enabled the measurement of self-management using the same instrument, purposefully modified for this study. Excluded where those with a critical illness, cognitive impairment, or unable to communicate verbally.

Sample size

Sample size was calculated using a rule-of-thumb ratio of at least 10 participants per variable in a structural equation model with 44 variables [40], and adding a further 20% to account for missing data, resulted in a minimum sample size of 528 needed for this study.

Data collection

Following ethics approval and obtaining site permissions, a medical doctor in each ward/clinic assisted with identifying eligible patients and referred them to the research team. Four research assistants extracted data from patients’ medical records and assisted participants with responding to a printed set of instruments by explaining or reading questions aloud. Research assistants were final year undergraduate nursing students and were trained in participant recruitment, obtaining consent, and collecting data. Data collection occurred at bed sides or in a quiet place in outpatient clinics. It took participants approximately 20–30 min to complete all instruments.

Instruments

Demographic questionnaire

A brief demographic questionnaire gathered data on age, gender, marital status, highest qualification, employment status, average household income and who was main support person. Data was also extracted from participants’ medical records, including all medical diagnoses for the calculation of Charlson Comorbidity index.

Aged-adjusted charlson comorbidity index (ACCI)

The comorbidity status was assessed using the Age-adjusted Charlson Comorbidity Index (ACCI), which was calculated as a sum of a participant’s score for age and for chronic disease/condition [41]. Age is scored 1 point for every decade from the age of 40. Each chronic disease is scored on a scale ranging from 1 to 6 depending on the severity of the condition.

Health literacy questionnaire (HLQ)

Health literacy was measured using the HLQ, a multidimensional instrument comprising 44 items covering 9 conceptually distinct domains of health literacy. Each item is scored by a 4-point Likert scale (domains 1–5; 1 = strongly disagree to 4 = strongly agree) or a 5-point Likert (domains 6–9; 1 = cannot do or always difficult to 5 = always easy). A mean score is calculated for each domain, and no aggregated score is computed for overall scale. A cut off score of ≤ 2.5 (domains 1–5) and ≤ 3.5 (domains 6–9) indicates a low health literacy level, as recommended by the instrument developers. Descriptions of a high and low level of health literacy in each domain have been stated elsewhere [42]. The domains also account for Nutbeam’s three health literacy dimensions of functional (domains 2, 8, 9), communicative (domains 1, 3, 4, 6, 7, 8) and critical (domains 3, 4, 5) abilities. Unlike other functional health literacy instruments, the HLQ also measures the skills needed to access and use health services (i.e. navigating in health setting, engaging with healthcare providers, etc.) and how responsive the health system and professionals are to them [43]. The HLQ demonstrates good composite reliability of each scale [42] and confirmatory factor analysis demonstrates each of the nine HLQ domains as a robust independent measure [44]. The HLQ is available in many languages including Vietnamese, and permission to use it was granted from the instrument developers. In this current study, Cronbach’s alpha coefficients of HLQ domains varied from 0.81 to 0.89.

Medical outcomes study – social support survey (MOS-SS)

The extent of social support a person receives from their social network was measured using the MOS-SS [23]. This instrument consists of one item asking about the number of supporters that a person has when needed, and 19 other items are rated on a Likert scale from 1 (none of the time) to 5 (all of the time) which measures social support experience in 4 dimensions: emotional/information support, tangible support, affectionate support, and positive social interaction. A total score is calculated by a sum of all individual items; a higher score indicates a greater level of perceived social support. This instrument was originally developed for people with chronic diseases, and it had been translated into the Vietnamese language and used in several studies in Vietnam demonstrating good construct validity and reliability [45, 46] including this current study (Cronbach’s alpha was 0.95).

Self-efficacy for managing chronic disease (SEM-CD)

The SEM-CD is used to assess how much confident an individual feels in undertaking self-management tasks in chronic diseases [47]. It has 6 items related to confidence in managing (1) fatigue, (2) physical discomfort/pain, (3) emotional distress, (4) other symptoms/health problems, (5) tasks/activities needed to manage health conditions, and (6) things other than just taking medication. Each item is rated from 1 (not confident at all) to 10 (totally confident); scale scores are standardised into a mean between 1 and 10 with higher scores representing greater confidence in chronic disease self-management. The SEM-CD has been translated into Vietnamese using forward and backward process, and demonstrated a good Cronbach’s alpha of 0.98 in this current study.

Chronic disease self-management instrument (CD-SM)

The search of literature revealed none of the existing self-management instruments were suitable for multiple chronic diseases. Despite the uniqueness in causes and treatment, self-management in diabetes, cardiovascular diseases, and CKD do share the six core self-management skills [7], therefore, an existing Vietnamese language instrument measuring CKD self-management behaviours was modified for this project [48]. This instrument consists of 30 items rated by a 4-point Likert scoring scale from 1 = never to 4 = always; a possible score is between 30 and 120. The instrument measures the frequency of behaviours performed in 4 subscales ‘Understanding my chronic disease’, ‘Taking action to manage my chronic disease’, ‘Seeking social support’ and ‘Diet adherence’. Phrases were amended to suit multiple conditions rather than only CKD without alterations in self-management behaviours, for example the word “kidney disease” was replaced by “my diseases”. Confirmatory factor analyses (CFA) using this current study data demonstrated that each subscale of the CD-SM was reliable (Cronbach’s alpha coefficients: 0.79–0.86) and valid (Understanding my chronic disease: X2/df = 4.60, CFI = 0.94, RMSEA = 0.78 [90% CI 0.07, 0.08]; Taking action to manage my chronic disease: X2/df = 5.46, CFI = 0.96, RMSEA = 0.08 [90% CI 0.07, 0.10]; Seeking social support: X2/df = 1.76, CFI = 0.99, RMSEA = 0.04 [90% CI 0.00, 0.07]; Adhering to a healthy diet: X2/df = 10.1, CFI = 0.99, RMSEA = 0.12, [90% CI 0.06, 0.19]). For reference, a good-fit CFA model, which reflects instrument structural validity, is when CFI ≥ 0.95 and RMSEA falls into [0.4–0.6] [49].

Ethical considerations

This study was approved by a human ethics committee (Queensland University of Technology, approval number 1800001035). Participants received both verbal and written explanation of the study prior to providing voluntary consent to participate, and they had the right to skip any item they did not want to answer, and or to withdraw their participation from the study at 2 weeks after returning their completed questionnaires to the research team.

Statistical analysis

Data were inputted into IBM SPSS™ statistics version 23.0 (IBM Corp., 2015) and assessed for missing data, distributions, and outliers. There was no missing data in the HLQ, MOS-SS, SEM-CD and CD-SM. Scores of HLQ domains, MOS-SS, SEM-CD and CD-SM and ACCI were calculated according to instrument instructions. The cut-off points determining a low health literacy were inconsistent between studies, so we used cut-off scores of ≤ 2.5 (domains 1–5) and ≤ 3.5 (domains 6–9) as suggested by the instrument’s developers. The proportion of people with low health literacy was calculated for each HLQ domain. ACCI scores were divided into 2 groups of < 6 and ≥ 6 (due to an ACCI mean = 6.68). Descriptive statistics were calculated for measured variables (means, standard deviations for the continuous and numbers, percentages for the categorical). Independent t-tests were used to examine the differences between demographic groups in health literacy, self-management, social support, and self-efficacy. Pearson’s correlation coefficients were used to test the linear relationships between these outcome variables. Internal consistency reliability was tested for each measurement scale using a Cronbach’s alpha coefficient.

To determine which factors had a significant association with self-management behaviours, a generalised linear regression model was used. All assumptions for this model were met, including independent and random data, normal distribution of self-management variables through standard residual plots and linear relationships between variables. Five demographic variables were significantly associated with self-management (p < 0.05) and were used in the model - gender (Male/Female), age (< 65, ≥ 65), education (VET/University/Higher degree; Up to year 12), residential area (City/urban; Rural/remote/mountainous), and main support person (Spouse/Children; Others). The severity of comorbidity, assessed by ACCI, was not significantly associated with self-management, so was not included in the multivariate analysis. The HLQ domain 3 (Actively managing my health) has statements partly overlapping with the concept of self-management, so no correlation was sought between it and the self-management variable, this domain was excluded from multivariate analysis. Five demographic, 8 HLQ domains (except domain 3), self-efficacy and social support variables were entered in the model. Education, residential area, main support person and HLQ domains 6, 7, 8, 9 variables were not significant in the model and were excluded. Standardised coefficients of each variable, 95% confidence intervals (CI), and p values of the final model were reported. The magnitude of standardised coefficients of each factor was compared to determine which factors had higher association with self-management.

Results

Participants’ characteristics

A total of 600 participants with a mean age of 61.54 (SD = 15.3 years) ranging from 20 to 89 years were recruited. Most were male (54%), married (84%), had 12 years of school education or lower (82.4%), and about half lived in a rural area (56.4%). Almost two-thirds (62.5%) reported a monthly family income of 5 million VND or lower (~ US$ 215). All participants had several chronic diseases; the most common chronic diseases were hypertension (89%), diabetes (62%), CKD (61%), and heart failure (28%). The mean ACCI was 6.7 (SD = 2.1), and 71.3% had an ACCI score ≥ 6 (see Table 1).

Table 1 Participant characteristics (n = 600)
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Self-management, social support, self-efficacy and health literacy profiles

The mean scores were 82.1 (CD-SM, SD = 12.4, possible score 30–120), 52.7 (MOS-SS, SD = 10.4, possible score 0–95), and 5.46 (SEM-CD, SD = 1.9, possible score 1–10) indicating that participants had a moderate level of self-management while perceiving a low to moderate level of social support and self-efficacy (see Table 2).

Table 2 Descriptions of self-management, self-efficacy, social support and HLQ scores (n = 600)
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The lowest mean scores of health literacy were in domains 1, 2, 5 (2.61, 2.71, 2.62 respectively) and in domains 8 and 9 (both 3.29), indicating that participants had some difficulties with functional, communicative, and critical health literacy skills. Higher proportions of low health literacy were found in domains 1, 8 and 9 (52%, 56%, 56%, respectively; Table 2). Further details of health literacy profiles, including scores and demographic characteristics with higher health literacy have been published elsewhere [13].

Associations between social support, self-efficacy, and health literacy domains and self-management

All 9 health literacy domains, social support, and self-efficacy were significantly associated with self-management at the bivariate level, and with each other (p < 0.05). The correlation coefficients with self-management were 0.31 (SEM-CD), 0.42 (MOS-SS), between 0.2 and 0.4 (HLQ domains 6,7,8, 9) and 0.4–0.6 (HLQ domains 1, 2, 4, 5; Table 3).

Table 3 Pearson’s correlations between variables (n = 600)
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Models explaining self-management behaviours

The model explaining self-management comprised 8 variables (gender, age, health literacy domains 1, 2, 4, 5, self-efficacy, and social support). Overall, the model demonstrated higher self-management scores amongst females (3.99 score higher, 95% CI [2.58, 5.39], p < 0.001), and by those aged 65 and over (2.27 score higher, 95% CI [0.87, 3.68], p = 0.002). The health literacy domain “Social support for health” had a stronger association with self-management (coefficient = 5.96; 95% CI [3.92, 8.01]) than the general social support variable (coefficient = 0.18, 95% CI [0.11, 0.26], respectively). Health literacy (domains 1, 2, 4 & 5) had stronger explanatory power in self-management behaviours (coefficient = 2.34–8.41) than the level of self-efficacy (coefficient = 0.58, 95% CI [0.18, 3.68]) or general social support (coefficient = 0.18, 95% [0.11, 0.26]; see Table 4).

Table 4 Generalised linear model explaining self-management behaviours (n = 600)
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Discussion

This study evaluated the degree to which individuals with multiple chronic diseases have engaged in self-management behaviours, and examined several factors that may impact these behaviours, including health literacy, social support, and self-efficacy. Results confirmed that individuals’ self-management behaviours were significantly correlated to the support they perceived from their social network, how confident they were in self-management tasks, and their abilities to seek, obtain and use health information. Overall, four health literacy domains (healthcare providers support, social support for health, having information, and abilities to appraise health information) had the strongest association with self-management behaviours beyond those of general social support or self-efficacy.

Almost one in every two participants in this study experienced difficulties in feeling understood and supported by healthcare providers (domain 1), finding health information (domain 8) and understanding health information (domain 9), and that one in three had difficulties in engaging with healthcare providers (domain 6) and navigating the health system (domain 7). Compared to other studies involving people with chronic diseases [50, 51], greater proportions of low health literacy were found in this study. The health literacy difficulties perceived by participants could be explained by individual, socioeconomic, and system contexts. Most participants lived in rural locations, had limited education and low incomes. In Vietnam, the healthcare system has many challenges such as the shortage of community-based (primary care) medical doctors, the overload of patients, the tendence for people to value tertiary hospitals in large cities, and the financial cost of healthcare for most of the population [52]. These factors lead to a reduced frequency of healthcare seeking and insufficient health information provided by hospital staff. Improving therapeutic communication is a crucial opportunity to help healthcare providers identify and mitigate the limited understanding about chronic diseases by patients. To date, addressing health literacy has not been considered at ministerial or organisational levels in Vietnam, although it is a priority and responsibility for clinicians as well as policy-makers in many developed countries [53].

For people with multiple chronic diseases, understanding each individual disease and the pathological link between diseases, lifestyle changes, and collective treatment regimens to undertake effective self-management is a complex and challenging requirement. We found that four health literacy domains (having sufficient information, a trusting relationship with a regular healthcare provider/s, specific support for healthcare, and being able to resolve conflicting information), support from a social network, and being confident were significantly associated with self-management in multiple chronic diseases. Critical health literacy (domains 4 and 5) in this study, was much more influential on self-management than communicative (domain 1) and functional (domain 2) health literacy dimensions. Overall, we found that health literacy domains have a stronger association with self-management than either social support or self-efficacy. These results were different from the few existing studies which have previously examined the relationship between health literacy and self-management. For instance, Jacobson et al. found no significant relationship between health literacy and self-management in patients with heart failure [54]. On the other hand, Chen et al. [14] reported that social support did exert a stronger influence on self-management than health literacy among those with CKD. However, it is important to approach these conclusions with caution, as these studies only measured functional health literacy and may not have accounted for other dimensions of health literacy that could have a role in self-management. The current study using the contemporary assessment of health literacy, which is multidimensional, showed the importance of having critical thinking abilities to take active healthcare decisions to self-manage health. For example, these abilities enable patients to recognise breathlessness and weight gain, which may indicate increased fluid retention. Subsequently, patients can make informed decisions such as reducing fluid intake, following guidance to take additional diuretics, or seeking medical assistance when necessary.

Mitigating low health literacy necessitates a comprehensive system-wide approach [55], encompassing various organisational and clinical practice changes. Organisational health literacy is where an organisation such as a hospital or community-based facility demonstrates health literacy policies and practices which makes it easier for individuals to navigate the health system and also directs healthcare providers through policies and training to support patients with low health literacy capabilities [56]. Initiatives such as ensuring clarity of information on hospital websites, simplifying health information pamphlets, and providing training to staff on effective health literacy strategies. It is important to recognise that healthcare providers have a crucial bridging role to mitigate for low health literate patients and the complexity of chronic disease treatment regimens by communicating easy-to-understand information. One simple, low-cost health literacy initiative is the teach-back method where information providers ask patients to repeat the information given to them, or to demonstrate back a procedure, and this initiative should be used for all patients regardless of health literacy abilities [57]. In addition, the results in this study suggested that it’s not enough to simply provide patients with health information; they must also be guided on where to locate information specific to their conditions, and which sources are trustworthy amid the abundance of information available online and elsewhere. Many changes can start from changing therapeutic communication, which is fundamentally the responsibility of the healthcare professional, to enable patients to develop abilities to find and analyse health information. With an enhanced level of health literacy, individuals will have the knowledge and skills to determine when and how to act, enabling them to make informed decisions about their health and well-being. Whenever possible, it is crucial to involve family members (or a friend) in conversations to ensure that patients have the necessary support during a decision-making process. By including these supporters, patients could benefit from their perspectives, as well as emotional and tangible support, leading to informed and active participation in decisions regarding their healthcare.

Overall, these results emphasise the importance of health literacy and social support to self-management in multiple chronic diseases, and in particular, the contribution that critical health literacy capabilities make to be able to enact self-management behaviours. Communication, information giving and educational strategies ought to prioritise tailoring of content and delivery methods to match an individual’s health literacy capability. In addition to providing health information, healthcare providers need to guide patients in identifying reliable sources of information related to their specific conditions. Furthermore, involving family members (or friends) in appointments, conversations, and decision-making processes is likely to enhance the patient feeling supported and could also facilitate the development and sustainability of self-management behaviours. Future research has the potential to develop and evaluate policy and/or practice changes aimed at enhancing health literacy at multiple levels, including ministerial (i.e., department of health), organisational (e.g., hospitals, other health services) or community levels (e.g., local councils, lifestyle groups, etc.). This research would facilitate increased awareness among all stakeholders regarding the prevalence of low health literacy capabilities of patients, and empower stakeholders to fulfill their respective roles in mitigating its impacts on disadvantaged individuals and communities.

Limitations

There are limitations due to the cross-sectional design of this study that all relationships found between variables and self-management should be interpreted as associations rather than as causal relationships. Participants were sought from only one site limiting generalizability; however, this hospital receives patients from the entire north of Vietnam. Lastly, due to the nature of self-reported measures, it is possible that participants either overstated or underestimated their abilities.

Conclusion

This study found eight significant variables associated with self-management in people with multiple chronic diseases, of these variables, the critical health literacy domains were the most important. Healthcare providers do have a vital role in establishing a positive supportive relationship with patients through improving all forms of communication with patients and treating every interaction as a valuable teaching opportunity. Future educational strategies need to tailor content, delivery methods and resources to suit each individual’s health literacy capability. This education also needs to instruct patients how to identify reliable sources of information and to also involve family members (or friends), so that patients have the necessary supports to self-manage their diseases. Lastly, for Vietnam, there is a need for policies and action plans around health literacy and chronic disease self-management at each of the health system levels (i.e., ministerial, organisational, community) due to the growing chronic disease burden.

Data Availability

The dataset generated and analysed during this current study is not publicly available due to sharing data was not part of this study’s ethics approval. The corresponding author should be contacted if there is any request relating to this study data.

Abbreviations

CKD:

Chronic kidney disease

STROBE:

Strengthening the Reporting of observational studies in Epidemiology

ACCI:

Age-adjusted Charlson Comorbidity Index

HLQ:

Health Literacy Questionnaire

MOS-SS:

Medical Outcome Study – Social Support Survey

SEM-CD:

Self-efficacy in managing chronic disease

CD-SM:

Chronic disease self-management scale

X2/df:

Chi-square divided by degree of freedom

CFI:

Comparative Fit index

RMSEA:

Root mean square error of approximation

CI:

Confidence interval

VND:

Vietnam dong

SD:

Standard deviation

References

  1. Pefoyo AJK, Bronskill SE, Gruneir A, Calzavara A, Thavorn K, Petrosyan Y, et al. The increasing burden and complexity of multimorbidity. BMC Public Health. 2015;15:415.

    PubMed  Google Scholar 

  2. McPhail SM. Multimorbidity in chronic disease: impact on health care resources and costs. Risk Manag Healthc Policy. 2016;9:143–56.

    PubMed  PubMed Central  Google Scholar 

  3. Nunes BP, Flores TR, Mielke GI, Thume E, Facchini LA. Multimorbidity and mortality in older adults: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2016;67:130.

    PubMed  Google Scholar 

  4. Jonkman NH, Groenwold RH, Trappenburg JC, Hoes AW, Schuurmans MJ. Complex self-management interventions in chronic disease unravelled: a review of lessons learned from an individual patient data meta-analysis. J Clin Epidemiology. 2017;83:48–56.

    Google Scholar 

  5. Chen SH, Tsai YF, Sun CY, Wu IW, Lee CC, Wu MS. The impact of self-management support on the progression of chronic kidney disease - a prospective randomized controlled trial. Nephrol Dial Transplant. 2011;26(11):3560–6.

    PubMed  Google Scholar 

  6. Cheng L, Sit JWH, Choi K-C, Chair S-Y, Li X, Wu Y, et al. The effects of an empowerment-based self-management intervention on empowerment level, psychological distress, and quality of life in patients with poorly controlled type 2 diabetes: a randomized controlled trial. Int J Nurs Stud. 2021;116:103407.

    PubMed  Google Scholar 

  7. Lorig KR, Holman HR. Self-management education: history, definition, outcomes, and mechanisms. Ann Behav Med. 2003;26(1):1–7.

    PubMed  Google Scholar 

  8. Zhang NJ, Terry A, McHorney CA. Impact of health literacy on medication adherence: a systematic review and meta-analysis. Ann Pharmacother. 2014;48(6):741–51.

    PubMed  Google Scholar 

  9. Shahid R, Shoker M, Chu LM, Frehlick R, Ward H, Pahwa P. Impact of low health literacy on patients’ health outcomes: a multicenter cohort study. BMC Health Serv Res. 2022;22(1):1148.

    PubMed  PubMed Central  Google Scholar 

  10. Sørensen K, Van den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health. 2012;12(1):1–13.

    Google Scholar 

  11. Nutbeam D. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promot Int. 2000;15(3):259–67.

    Google Scholar 

  12. Shah JM, Ramsbotham J, Seib C, Muir R, Bonner A. A scoping review of the role of health literacy in chronic kidney disease self-management. J Ren Care. 2021;47(4):221–33.

    PubMed  Google Scholar 

  13. Dinh HTT, Nguyen NT, Bonner A. Health literacy profiles of adults with multiple chronic diseases: a cross-sectional study using Health Literacy Questionnaire. Nurs Health Sci. 2020;22:1153–60. https://doi.org/10.1111/nhs.12785

  14. Chen Y-C, Chang L-C, Liu C-Y, Ho Y-F, Weng S-C, Tsai T-I. The roles of social support and health literacy in self-management among patients with chronic kidney disease. J Nurs Scholarsh. 2018;50(3):265–75.

    PubMed  Google Scholar 

  15. Elisabeth Stømer U, Klopstad Wahl A, Gunnar Gøransson L, Hjorthaug Urstad K. Health literacy in kidney disease: Associations with quality of life and adherence. J Ren Care. 2020;46(2):85–94.

    PubMed  Google Scholar 

  16. Demian MN, Shapiro RJ, Thornton WL. An observational study of health literacy and medication adherence in adult kidney transplant recipients. NDT Plus. 2016;9(6):858–65.

    Google Scholar 

  17. Indino K, Sharp R, Esterman A. The effect of health literacy on treatment adherence in maintenance haemodialysis patients: a cross-sectional study. Ren Soc Australas J. 2019;15(1):11–8.

    Google Scholar 

  18. Lai AY, Ishikawa H, Kiuchi T, Mooppil N, Griva K. Communicative and critical health literacy, and self-management behaviors in end-stage renal disease patients with diabetes on hemodialysis. Patient Educ Couns. 2013;91(2):221–7.

    PubMed  Google Scholar 

  19. Skoumalova I, Kolarcik P, Madarasova Geckova A, Rosenberger J, Majernikova M, Klein D, et al. Is health literacy of dialyzed patients related to their adherence to dietary and fluid intake recommendations? Int J Environ Res Public Health. 2019;16(21):4295.

    PubMed  PubMed Central  Google Scholar 

  20. Garnett A, Ploeg J, Markle-Reid M, Strachan PH. Self-management of multiple chronic conditions by community-dwelling older adults: a concept analysis. Sage Open Nurs. 2018;4:2377960817752471.

    PubMed  PubMed Central  Google Scholar 

  21. Harandi TF, Taghinasab MM, Nayeri TD. The correlation of social support with mental health: a meta-analysis. Electron Physician. 2017;9(9):5212–22.

    PubMed  PubMed Central  Google Scholar 

  22. Sousa H, Ribeiro O, Paúl C, Costa E, Miranda V, Ribeiro F, et al. Social support and treatment adherence in patients with end-stage renal disease: a systematic review. Semin Dial. 2019;32(6):562–74.

    PubMed  Google Scholar 

  23. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32(6):705–14.

    CAS  PubMed  Google Scholar 

  24. Wang X, He L, Zhu K, Zhang S, Xin L, Xu W, et al. An integrated model to evaluate the impact of social support on improving self-management of type 2 diabetes mellitus. BMC Med Inform Decis Mak. 2019;19:1–12.

    PubMed  PubMed Central  Google Scholar 

  25. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191–215.

    CAS  PubMed  Google Scholar 

  26. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31(2):143–64.

    PubMed  Google Scholar 

  27. Yao J, Wang H, Yin X, Yin J, Guo X, Sun Q. The association between self-efficacy and self-management behaviors among chinese patients with type 2 diabetes. PLoS ONE. 2019;14(11):e0224869.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Tan FCJH, Oka P, Dambha-Miller H, Tan NC. The association between self-efficacy and self-care in essential hypertension: a systematic review. BMC Fam Pract. 2021;22(1):44.

    PubMed  PubMed Central  Google Scholar 

  29. Milazi M, Douglas C, Bonner A. A bundled phosphate control intervention (4Ds) for adults with end-stage kidney disease receiving haemodialysis: a cluster randomized controlled trial. J Adv Nurs. 2021;77(3):1345–56.

    PubMed  Google Scholar 

  30. Nguyen NT, Douglas C, Bonner A. Effectiveness of self-management programme in people with chronic kidney disease: a pragmatic randomized controlled trial. J Adv Nurs. 2019;75(3):652–64.

    PubMed  Google Scholar 

  31. Lee E-H, Lee YW, Chae D, Lee K-W, Hong S, Kim SH et al. Pathways linking health literacy to self-management in people with type 2 diabetes. Healthcare. 2021;9(12).

  32. Koetsenruijter J, van Eikelenboom N, van Lieshout J, Vassilev I, Lionis C, Todorova E, et al. Social support and self-management capabilities in diabetes patients: an international observational study. Patient Educ Couns. 2016;99(4):638–43.

    PubMed  Google Scholar 

  33. Jo A, Ji Seo E, Son Y-J. The roles of health literacy and social support in improving adherence to self-care behaviours among older adults with heart failure. Nurs Open. 2020;7(6):2039–46.

    PubMed  PubMed Central  Google Scholar 

  34. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573–7.

    Google Scholar 

  35. McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) with the special contribution of the heart failure Association (HFA) of the ESC. Eur Heart J. 2021;42(36):3599–726.

    CAS  PubMed  Google Scholar 

  36. Unger T, Borghi C, Charchar F, Khan NA, Poulter NR, Prabhakaran D, et al. 2020 International Society of Hypertension global hypertension practice guidelines. Hypertension. 2020;75(6):1334–57.

    CAS  PubMed  Google Scholar 

  37. Levin A, Stevens PE, Bilous RW, Coresh J, De Francisco AL, De Jong PE, et al. Kidney disease: improving global outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3(1):1–150.

    Google Scholar 

  38. World Health Organization. Diagnosis and management of type 2 diabetes (HEARTS-D). World Health Organization: Geneva, Switzerland.; 2020.

  39. Grady PA, Gough LL. Self-management: a comprehensive approach to management of chronic conditions. Am J Public Health. 2014;104(8):e25–e31.

    PubMed  PubMed Central  Google Scholar 

  40. Kline RB. Principles and practice of structural equation modeling. Guilford publications; 2015.

  41. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47(11):1245–51.

    CAS  PubMed  Google Scholar 

  42. Osborne RH, Batterham RW, Elsworth GR, Hawkins M, Buchbinder R. The grounded psychometric development and initial validation of the health literacy questionnaire (HLQ). BMC Public Health. 2013;13(1):658.

    PubMed  PubMed Central  Google Scholar 

  43. World Health Organization. Regional Office for South-East Asia. Health literacy toolkit for low and middle-income countries: a series of information sheets to empower communities and strengthen health systems. WHO Regional Office for South-East Asia; 2015.

  44. Rademakers J, Waverijn G, Rijken M, Osborne R, Heijmans M. Towards a comprehensive, person-centred assessment of health literacy: translation, cultural adaptation and psychometric test of the dutch health literacy questionnaire. BMC Public Health. 2020;20(1):1850.

    PubMed  PubMed Central  Google Scholar 

  45. Dao-Tran T-H. Stressful life events, modifiable lifestyle factors, depressive symptoms, health-related quality of life, and chronic disease among older women in Vietnam and Australia: a cross-cultural comparison. PhD thesis, Queensland University of Technology. 2017.

  46. Khuong LQ, Vu T-VT, Huynh V-AN, Thai TT. Psychometric properties of the medical outcomes study: social support survey among methadone maintenance patients in Ho Chi Minh City, Vietnam: a validation study. Subst Abuse Treat Prev Policy. 2018;13(1):1–8.

    Google Scholar 

  47. Lorig K, Stewart A, Ritter P, Gonzalez V, Lynch J, Laurent D. Outcome measures for health education and other health care interventions: Sage; 1996.

  48. Nguyen NT, Douglas C, Bonner A. Psychometric evaluation of the culturally and linguistically translated vietnamese chronic kidney disease self-management instrument. Int J Nurs Pract. 2019;25(3):e12727.

    PubMed  Google Scholar 

  49. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Pearson new international edition. Multivariate data analysis. Essex: Seventh Edition Pearson Education Limited Harlow; 2014.

    Google Scholar 

  50. Rheault H, Coyer F, Jones L, Bonner A. Health literacy in indigenous people with chronic disease living in remote Australia. BMC Health Serv Res. 2019;19(1):523.

    PubMed  PubMed Central  Google Scholar 

  51. Stømer UE, Gøransson LG, Wahl AK, Urstad KH. A cross-sectional study of health literacy in patients with chronic kidney disease: Associations with demographic and clinical variables. Nurs Open. 2019;6(4):1481–90.

    PubMed  PubMed Central  Google Scholar 

  52. Kim JY, Kim DI, Park HY, Pak Y, Tran PNH, Thai TT, et al. Unmet healthcare needs and associated factors in rural and suburban Vietnam: a cross-sectional study. Int J Environ Res Public Health. 2020;17(17):6320.

    PubMed  PubMed Central  Google Scholar 

  53. Australian Commission on Safety and Quality in Healthcare. Health literacy: taking action to improve safety and quality. Sydney: ACSQHC; 2014.

    Google Scholar 

  54. Jacobson AF, Sumodi V, Albert NM, Butler RS, DeJohn L, Walker D, et al. Patient activation, knowledge, and health literacy association with self-management behaviors in persons with heart failure. Heart Lung. 2018;47(5):447–51.

    PubMed  Google Scholar 

  55. Brach C. The journey to become a health literate organization: a snapshot of health system improvement. Stud Health Technol Inform. 2017;240:203–37.

    PubMed  PubMed Central  Google Scholar 

  56. Parnell TA, Stichler JF, Barton AJ, Loan LA, Boyle DK, Allen PE. A concept analysis of health literacy. Nurs Forum. 2019;54(3):315–27.

    PubMed  Google Scholar 

  57. Dinh TTH, Bonner A, Clark R, Ramsbotham J, Hines S. The effectiveness of the teach-back method on adherence and self-management in health education for people with chronic disease: a systematic review. JBI Database System Rev Implement Rep. 2016;14(1):210–47.

    Google Scholar 

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Acknowledgements

We acknowledge the APEC Women in Research Fellowship to support Dr Ha Dinh to develop the study proposal. We thank Dr Nguyet Nguyen, Vietnam National University for her support in supervising research assistants and entering data. We thank research assistants for collecting data, and all participants for their participation in this survey.

Funding

APEC Women in Research Fellowship.

Author information

Authors and Affiliations

  1. School of Nursing, University of Tasmania, Launceston, TAS, Australia

    Thi Thuy Ha Dinh

  2. School of Nursing and Midwifery, Griffith University, Brisbane, QLD, Australia

    Thi Thuy Ha Dinh & Ann Bonner

  3. Kidney Health Service, Metro North Hospital and Health Service, Brisbane, QLD, Australia

    Ann Bonner

Authors
  1. Thi Thuy Ha Dinh
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  2. Ann Bonner
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Contributions

TTH.D: Principal project leader, conceptualised the study design, coordinated data collection, analyzed the data, drafted the manuscript, coordinated with co‐authors, read and approved the final manuscript. A.B: Conceptualised the study design, oversaw data collection, assisted with data analysis and interpretation, drafted the manuscript, read and approved the final manuscript.

Corresponding author

Correspondence to Thi Thuy Ha Dinh.

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Ethics approval and consent to participate

This research conforms to the provisions of the Declaration of Helsinki (as revised in Brazil 2013). All participants gave informed consent for the research and that their anonymity was preserved. The research was approved by the Human Ethics Committee at Queensland University of Technology (number 1800001035).

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No conflict of interest is anticipated upon submission of this manuscript.

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Dinh, T.T.H., Bonner, A. Exploring the relationships between health literacy, social support, self-efficacy and self-management in adults with multiple chronic diseases. BMC Health Serv Res 23, 923 (2023). https://doi.org/10.1186/s12913-023-09907-5

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BMC Health Services Research

ISSN: 1472-6963

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