Patient activation, knowledge, and health literacy association with self-management behaviors in persons with heart failure

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Heart & Lung j o u r n a l h o m e p a g e : w w w. h e a r t a n d l u n g . c o m

Patient activation, knowledge, and health literacy association with self-management behaviors in persons with heart failure Ann F. Jacobson, PhD, RN a,*, Veronica Sumodi, MSN, RN a, Nancy M. Albert, PhD, CCNS, CHFN, CCRN, NE-BC, FAHA, FCCM, FAAN b, Robert S. Butler, MS c, Lori DeJohn, MSN, RN a, Donna Walker, MSN, CNP, CHFN d, Kelly Dion, MSN, CNP e, Hua-Li Lin Tai, MSN, RN, CHFN e, Donna M. Ross, MSN, ACNS-BC, CHFN f a Cleveland

Clinic Hillcrest Chronic Care, 6801 Mayfield Rd., Mayfield Heights, OH 44124 Clinic, 9500 Euclid Avenue, Mail code J3-4, Cleveland OH 44195 c Cleveland Clinic Quantitative Health Sciences, 9500 Euclid Avenue/JJN3-01, Cleveland, OH 44195 d Cleveland Clinic Euclid Hospital Chronic Care, 18901 Lakeshore Blvd, Euclid, OH 44119 e Cleveland Clinic South Pointe Hospital Chronic Care, 20000 Harvard Ave, Warrensville Heights, OH 44122 f Cleveland Clinic Lakewood Chronic Care, 14519 Detroit Ave., Lakewood, OH 44107 b Cleveland

A R T I C L E

I N F O

Article history: Received 1 March 2018 Accepted 26 May 2018 Available online Keywords: heart failure self-management health literacy patient activation heart failure knowledge

A B S T R A C T

Background: More evidence is needed about factors that influence self-management behaviors in persons with heart failure. Objective: To test a correlational mediation model of the independent variables of health literacy, patient activation, and heart failure knowledge with heart failure self-management behaviors. Methods: The study used a prospective, cross-sectional, correlational design. Correlation and multiple regression were used to analyze associations among variables. Results: Of 151 participants, 57% were male, and mean age was 68 years. Heart failure self-management behaviors was positively correlated with patient activation level (p = .0008), but not with health literacy or heart failure knowledge. Conclusions: Persons with heart failure may better manage their condition if sufficiently activated, regardless of their level of health literacy or knowledge of heart failure disease and management processes. © 2018 Elsevier Inc. All rights reserved.

Introduction Heart failure (HF) is a chronic, progressive condition, affecting individuals’ and families’ quality of life and increasing health care utilization and expenditures. An estimated 6.5 million Americans 20 years of age or older have HF, with prevalence projected to increase 46 percent by 2030. Total cost for HF was estimated at $30.7 billion in 2012.1 Health care reform initiatives, such as pay for performance and accountable-care organizations, have created the need to develop solutions for effective long-term management of chronic HF to reduce costs and improve quality. In addition, the Institute of Medicine’s call for patient-centered care2 placed heightened em-

Abbreviations: HF, Heart Failure; TOFHLA, Test of Functional Health Literacy in Adults; S-TOFHLA, Short Test of Functional Health Literacy in Adults; EHFScBS, European Heart Failure Self-Care Behavior Scale; REALM, Rapid Estimate of Adult Literacy in Medicine; PAM, Patient Activation Measure; DHFKS, Dutch Heart Failure Knowledge Scale. Funding: This research was internally funded. * Corresponding author. E-mail address: [email protected] (A.F. Jacobson). 0147-9563/$ – see front matter © 2018 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.hrtlng.2018.05.021

phasis on self-management behaviors to improve health and quality of life outcomes and reduce mortality, morbidity and health care costs. Goals of HF care include slowing its progression and managing symptoms. Although provider-directed care, such as prescribing medications, is an important component of disease management, ongoing self-management by patients is necessary to improve quality of life and slow disease progression and functional loss.3,4 The 2017 Scientific Statement of the American Heart Association cited the importance of self-care to building healthier lives and achieving treatment outcomes.5 The 2015 position paper of the American Association of Heart Failure Nurses cited the essential need to engage patients in self-care through education and promotion of skill mastery.6 By testing a multivariate model of the association of health literacy, patient activation level, and heart failure knowledge with HF self-management, this study addresses recommendations to apply modeling techniques to connect complex elements of self-management.7 Self-management includes engaging in proactive processes to deal with health conditions.4 In the HF population, this includes multiple behaviors: sign/symptom identification and management;

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Figure 1. Proposed model of predictors of self-management in persons with Heart Failure.

seeking health advice; dietary sodium modification; fluid management; taking prescribed medications; physical exercise; and preventative behaviors (e.g., influenza vaccine).4,8,9 Early studies of self-management in HF focused primarily on clinician-delivered programs aimed at improving patients’ self-management behaviors.10 Although clinician support of self-management is important, more information is needed to understand intrinsic patient characteristics that influence self-management behaviors.8,11 Effective selfmanagement in persons with HF requires both knowledge about the condition, and strategies to manage it.12 In ambulatory patients with HF, health literacy, HF knowledge and patient activation may be important characteristics that promote self-management . In one report, health literacy was associated with HF self-care scores13; however, in multiple reports, health literacy was associated with knowledge,14–17 but not with self-care.14,16 In 2 reports, patient’s HF self-care confidence was a mediator between health literacy and self-care13,16; however, HF knowledge was not directly assessed for its relationship with self-care in one report13 and in the other, HF knowledge was not directly associated with HF self-care scores.16 Patient activation refers to the ability and willingness to assume the role of managing one’s health condition.18 Few reports on patient activation were available. Of reports, 1 was an intervention study and 2 others involved patients with acutely decompensated HF. In hospitalized adults, patient activation level was positively associated with health literacy and education level,19 and self-care management.20 Many researchers have used interventions to increase patients’ knowledge of HF; and in 1 report, patient activation increased in persons with HF who received a sixmonth activation intervention.21 Overall, reports in the literature showed inconsistent relationships among health literacy, HF knowledge and patient activation on self-management and no report studied all 3 factors together for their association with selfmanagement. Specifically, no research was found to learn if higher levels of patient activation and health literacy, mediated by HF knowledge, would increase HF self-management.

Methods Design, sample and setting A prospective, cross-sectional, correlational design was used to study a convenience sample of adults with HF (N = 151) who were recruited from 4 outpatient centers of a large health system in Northeast Ohio. The 4 outpatient centers were located in mid-size suburban communities and were a part of hospitals with 500 beds or fewer. Eligibility criteria were age 18 years or older, established outpatient center patient (1 month or longer) with diagnosis of any type of HF, and ability to read and respond in writing to English-language study questionnaires. Patients with cognitive impairment or who did not meet the eligibility criteria were excluded. A sample size of 150 was determined a priori. The power analysis was based on a power of .80, alpha of 0.05, a moderate mediation effect size of .20 and a standard deviation of 2.3 for HF knowledge from Dennison et al.’s report of 95 subjects.14 This sample size allowed for control of possible confounding effects of demographic variables (age, educational level, sex and race) on independent variables. Procedure The study was approved by the Institutional Review Board (IRB) of the health system where the study was conducted. The IRB waived the requirement for signed consent forms, since study questionnaires were anonymous and non-invasive. A member of the study team approached eligible patients during their regular clinic visit and invited participation. Those interested were provided a study packet that included a research study information form explaining the study and participation requirements, and study questionnaires. Participants completed the questionnaires during their visit and returned them in sealed envelopes to a drop box in the outpatient center.

Purpose

Variables and measures

The purpose of this study was to test a model of the direct and mediating effects of health literacy, patient activation and HF knowledge on self-management in persons with HF (Figure 1). Knowledge gained from this study contributes to the body of knowledge, and informs health care providers in delivering interventions aimed at maximizing outcomes while accounting for antecedents. Hypotheses were:

The outcome variable, HF self-management, was measured with the European Heart Failure Self-Care Behaviour Scale (EHFScBS) that was designed to measure adherence to HF self-care behaviors such as medications, diet, exercise, and weight and symptom monitoring.22 The EHFScBS contains 12 items with 5-point Likert-style responses to indicate agreement with each item. Responses are computed to yield a final score ranging from 0 – 100, with higher scores reflecting better self-care.23 The instrument, which initially had 12 items, was developed and psychometrically tested in 200324 and 2017.25 When test-retest reliability was assessed in 3 reports, on an individual item level, reliability was low to good.25 Health literacy refers to the capacity to obtain and understand health information and make appropriate health decisions.14 Health literacy was measured using the Test of Functional Health Literacy in Adults (TOFHLA). First published in 1995, the TOFHLA measures

Hypothesis 1 HF knowledge and patient activation are positively associated with HF self-management. Hypothesis 2 The association of health literacy with HF selfmanagement is mediated through HF knowledge. Hypothesis 3 The association of patient activation with HF selfmanagement is partially mediated through HF knowledge.

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a person’s ability to read and understand situations they commonly encounter in the health care setting.26 A shortened version (STOFHLA), developed in 1999, consisting of 36 reading comprehension items in 2 passages,27 was used for this study. Functional health literacy scores are computed as the sum of patients’ correct answers to the 36 total items. Scores are interpreted as 3 categories: Inadequate (0 – 16, unable to read and interpret health texts); Marginal (17 – 22, has difficulty reading and interpreting health texts); and Adequate (23 – 36, can read and interpret most health texts). In a group of 211 patients given the S-TOFHLA, scores were correlated (r = 0.81) with scores on another gold standard literacy test, the REALM.27 Traditionally, the S-TOFHLA is a 7-minute timed test; however, in one report, authors learned that timed testing may underestimate literacy levels in older persons with HF and suggest untimed administration.28 In this study, participants were not restricted in the time taken to complete the S-TOFHLA and items left blank were scored as zero, reflecting low reading comprehension.29 The Patient Activation Measure (PAM) was used to measure activation.30 The PAM is a 13-item, unidimensional, Guttman-like scale that categorizes individuals across a continuum of four activation levels, with Level 1 the lowest (“disengaged and overwhelmed”) and Level 4 the highest (“maintaining behaviors and pushing further”).31 Testing of the initial PAM, containing 22 items, on more than 1500 adults in a national sample produced a Cronbach’s alpha of 0.87.18 Subsequently, the 13-item scale was developed and tested with similar psychometric properties.32 In this study, the Cronbach’s alpha of the 13 item scale was 0.89. The Dutch Heart Failure Knowledge Scale (DHFKS) is a selfadministered scale containing 15 multiple-choice items that concern general knowledge about HF, HF treatment, symptoms and symptom recognition. Questions are based on clinical guidelines of the Netherlands Heart Foundation, which mirror those of U.S. guidelines.33 Each item has three answer options. The scale has a minimum score of 0 (no knowledge) and a maximum score of 15 points (optimal knowledge). Initial psychometric testing of the instrument in 902 patients hospitalized for HF yielded a Cronbach’s alpha of 0.62.34 For this study, one item was removed from the scale because it references a “drogie,” which is a salty lozenge available in the Netherlands but not in the U.S. Patient characteristics were collected to describe the sample. Items included age, sex, race, ethnicity, marital status, living arrangements, education level, years since HF diagnosis, and selfrated health. Responses to demographic items were multiple choice or fill-in-the-blank. Self-rated health was measured with a singleitem, widely-used measure of self-rated health, the Stanford SelfRated Health Measure.35,36 The instrument is a Likert-type scale that was originally tested on 1,129 subjects with chronic disease. Testretest reliability was conducted on a sub-sample of 51 subjects, with a reliability index of .92.37 Data analysis Demographic characteristics of the sample were summarized as means and standard deviations for continuous variables and as counts and percentages for discrete variables. Univariate assessment of the association between selected patient characteristics and HF self-management behavior were made using Pearson’s correlation coefficient. Linear regression methods were used to test study hypotheses. A multivariate analysis of correlations between selected independent variables and HF self-management scores was conducted. Due to the exploratory nature of this descriptive study, initially, a backward elimination regression that included all demographic and study variables was conducted. The independent variables were age, sex, race/ethnicity, education level, years since HF diagnosis, self-

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rated health, patient activation, health literacy, and HF knowledge. Collinearity diagnostic procedures of variance inflation factors (VIF) and condition indices were conducted to test the variables for independence. Any variable with cut point of VIF = 10 or a condition index greater than 10 was considered to be confounded with other model variables. In the collinearity of the matrix of the independent variables, patient sex was too confounded with the other patient demographics and was not used in the multivariate analysis. Analyses were conducted using SAS version 9.4. Alpha was set at .05 for inferential analyses. Results Characteristics of the sample (N = 151) and summaries of study variables are depicted in Table 1. Participants were primarily male (57%), with a mean age of 67.8 years (SD = 13.0). The majority of participants had completed at least a high school education (83.9%), and had a diagnosis of HF for five years or less (54%). The majority of the participants had adequate health literacy (83.45%) and were at the higher stages of activation (Stage 3, 40.29%; Stage 4, 27.34%). The mean HF self-management score was 78%, and the mean HF knowledge score was 10.5 out of a possible 14 (Table 1). Associations of patient characteristics and independent variables with HF self-management are provided in Table 2. Of patient characteristics, only older age was associated with a higher degree of self-management (p = .0007). Among study variables, patient activation was the only variable positively associated with selfmanagement (p = .0008).

Table 1 Sample characteristics (N = 151)a Variable

Valid Na

n (%) or mean ± SD

Age in years, mean (Range 34–92) Self-Rated Health (5-point scale) (range 1–5) Marital Status Single, Separated, Divorced, Widowed Married Employment Status Working Retired Unemployed or Disabled Living Arrangement Lives alone Lives with family member(s)/friend Sex male Race Black, or Other non-White White Education Level Less than high school 12th grade, no college degree Associate’s degree or higher Years with Heart Failure 5 years or less 6 -10 years 11 or more years HF Self-Management, mean (Range 27.3–100) Health Literacy (Group) 1 (Inadequate) 2 (Marginal) 3 (Adequate) Patient Activation Stage: 1 (disengaged & overwhelmed) 2 (becoming aware but still struggling) 3 (taking action) 4 (maintaining behaviors & pushing further) HF Knowledge, mean (Range 3–14)

120 134 132

67.8 ± 13.0 2.5 ± 0.9

a

N varies across variables due to missing data.

79 (56.8) 53 (40.2) 130 24 (18.4) 65 (50.0) 41 (41.6) 129

130 130

35 (27.1) 94 (72.9) 74 (56.9) 66 (50.8) 64 (49.2)

124 20 (16.1) 71 (57.3) 33 (26.6) 129

139 139

70 (54.3) 27 (20.9) 32 (24.8) 78 ± 16 13 (9.4) 10 (7.2) 116 (83.4)

139

139

19 (13.7) 26 (18.7) 56 (40.3) 38 (27.3) 10.5 ± 1.9

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Table 2 Correlations between patient characteristics and heart failure self-management behavior Variable

N

Demographics Sex male Race white Age Self-rated health Years with heart failure Independent variables Health Literacy Heart Failure Knowledge Patient Activation Stage

Pearson’s r

p-value

130 130 120 134 129

.010 .020 .305 .137 .012

.91 .82 .0007 .11 .89

139 139 139

−.059 .088 .281

.49 .30 .0008

Hypothesis testing The first hypothesis was tested using univariate coefficients of HF knowledge and patient activation with HF self-management (Figure 1, Paths 3 and 4). Only patient activation (Figure 1, Path 3) was significant (Table 3). The second hypothesis predicted a mediation effect of HF knowledge on health literacy’s association with HF self-management. Correlations of the two independent variables with HF Self-Management, as well as to one another, were conducted. A significant association between health literacy and HF knowledge (Figure 1, Path 1) was observed (r = .292 p < .0001), however, the relationship between the combination of the two independent variables and HF self-management (Figure 1, Path 1 and Path 4) was not significant (p = .28; Table 3). The third hypothesis proposed a mediation effect of HF knowledge on patient activation. There was no correlation between the two (Figure 1, Path 2; r = .030, p = .24). Including HF knowledge in the model (Figure 1, Path 2 and Path 4) did not appreciably alter the p value for patient activation (p = .0009) when compared to the p value for the univariate model (p = .0008; Table 3). Multivariate model analysis results The conceptual model for the study (Figure 1) depicted associations of the hypothesized independent variables with the dependent variable of HF self-management, after controlling for patient characteristics that were significantly associated with HF self-management. The multivariate model using the remaining 9 independent variables was analyzed using backward elimination regression methods to generate a reduced model, i.e., a regression model containing only significant (p < .05) terms. The resulting reduced model included two variables: age (β, .4712 (.1093); p < 0.0001); and patient activation (β, 518.59 (141.9); p = 0.0004) (Figure 1, Path 3). In the reduced model, each year increase in age increased the estimate of the HF self-management score by .47 and Table 3 Hypotheses Testing of patient activation, heart failure knowledge, and health literacy pathways on heart failure self-management Hypothesisa

Independent Variable

Regression Coefficient

Univariate P-Value

Model P-Value

Heart Failure Knowledge Patient Activation

.75 460

.30 .0008

-

Health Literacy Heart Failure Knowledge

−2.9 1.12

.23 .16

.28

Patient Activation Heart Failure Knowledge

457.2 .699

.0009 .32

.0023

1

2

3

a

Self-management was the dependent variable of each pathway.

a 1-level increase in the patient activation level (of 4 possible levels) increased the estimate of the HF self-management score by 5.2. Discussion This study tested a model of relationships between health literacy, HF knowledge, patient activation, and HF self-management (Figure 1). The relationships of patient characteristics with selfmanagement were also examined. Positive relationships were found between patient activation level and age with self-management of HF. The other two independent variables, health literacy and HF knowledge, and the remaining demographic variables, were not related with self-management. The findings of the study were consistent with those of previous studies demonstrating a positive relationship between patient activation and self-management behaviors in HF38,39 and other chronic conditions.30 This study’s finding that adults with HF are more likely to perform self-management behaviors if sufficiently activated, irrespective of their knowledge about the condition, was identified in a literature update on self-care behaviors.40 Selfmanagement and patient activation both address level of adherence to self-care, which may explain their correlation. In studies measuring both attributes, patient activation level can provide rationale for self-management scores, and development of implications for practice. Further, more research is needed to identify strategies for promoting patient activation and self-management in adults with HF, as well as to determine other factors that influence selfmanagement. Interventions that promote activation, rather than knowledge, may be more effective in promoting HF self-management. In this study, patient activation did not increase HF knowledge, and HF knowledge did not improve self-management. In a recent summary of findings supporting the middle range theory of self-care of chronic illness, Jaarsma and colleagues pointed out that knowledge was a necessary, but insufficient, requirement for selfcare behavior; skill to apply the knowledge was necessary to achieve self-management.40 Their findings may help explain why age was associated with HF self-management in this and other studies,21,40 since older individuals may have more experience with managing health conditions. Additional studies incorporating measurement of skill in self-management are necessary. In our sample, the majority of patients had adequate health literacy (83.45%). In other studies, investigators reported greater variability in health literacy levels14,41; and in a systematic review of 23 studies, 39% of participants with HF had low health literacy.42 Low health literacy was associated with older age, lower socioeconomic status and education, and more comorbidities.43 Differing levels of health literacy may require different approaches to promoting HF self-management. The American Association of Heart Failure Nurses recommended assessing patient literacy levels, and employing strategies for educating patients with low literacy.6 Limitations This study used self-report survey instruments, which are subject to reporting bias from respondents, such as inaccurate recall of behaviors and social desirability in responses. The convenience sample of patients from a single health care system in 4 community centers limits generalizability to adults in other locations, where patient characteristics and treatment patterns may vary. Also limiting generalizability was the exclusion of adults who could not read, write or speak English, or chose not to participate. Cognitive function was not formerly assessed. Patients with known cognitive impairment were not invited to participate.

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In data collection, participants were given questionnaires to complete independently while waiting for their office visit, which could have contributed to missing data. Nurses who solicited participation and distributed questionnaires were clinician investigators who cared for participants. Patients with low literacy levels or those with inadequate knowledge may have chosen not to participate, or may have left items blank. The study design did not include a dedicated data collector. Design of future studies should incorporate methods to promote collection of complete data and increase the variability of the sample in key variables. Clinical characteristics that could be important confounding factors were not collected; such as medical comorbidities, HF severity and functional status. For example, in one study, persons who had diabetes in addition to HF reported poorer self-care.41 New research that examines the role of comorbidities along with the variables in this study’s model are needed.

Conclusions In this study, patient activation level and patient age, but not health literacy level or HF knowledge, were positively related to HF self-management behaviors. More research is needed to identify strategies for promoting patient activation and self-management in adults with HF and determine the strength of other factors that influence self-management.

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