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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Diabetes Educ. Author manuscript; available in PMC May 3, 2011.
Published in final edited form as:
PMCID: PMC3085853
NIHMSID: NIHMS202653

Role of Motivation in the Relationship between Depression, Self-Care, and Glycemic Control in Adults with Type 2 Diabetes

Leonard E. Egede, MD1,2,3 and Chandra Y. Osborn, PhD MPH4,5,6

Abstract

Objective

The mechanism by which depression influences health outcomes in persons with diabetes is uncertain. The purpose of this study was to test whether depression is related to self-care behavior via social motivation; and indirectly related to glycemic control via self-care behavior.

Methods

Patients with diabetes were recruited from an outpatient clinic. Information gathered pertained to demographics, depression, diabetes knowledge (information); diabetes fatalism (personal motivation); social support (social motivation); diabetes self-care (behavior). Hemoglobin A1C values were extracted from the patient medical record. Structural equation models tested the predicted pathways.

Results

Higher levels of depressive symptoms were significantly related to having less social support, and decreased performance of diabetes self-care behavior. In addition, when depressive symptoms were included in the model, fatalistic attitudes were no longer associated with behavioral performance.

Conclusions

Among adults with diabetes, depression impedes the adoption of effective self-management behaviors (including physical activity, appropriate dietary behavior, and appropriate self-monitoring of blood glucose behavior) through a decrease in social motivation.

Introduction

Multiple studies have documented significantly higher rates of depression among persons with diabetes relative to the general population.15 Depression affects approximately 30% of adults with diabetes 4, and is strongly associated with poor glycemic control 6, 7, increased risk of complications 8, increased disability 2, 9, lost productivity 2, 10, increased health care costs 11, and increased mortality.12

Multiple studies have also documented that depression is associated with poor perceived control of diabetes and poor self-care behaviors. 1316 However, the mechanism by which depression influences health outcomes in persons with diabetes is uncertain. Depression has been hypothesized to decrease physical health by a combination of biological and psychological mechanisms including: 1) psychological distress and subsequent neurohormonal and immunologic changes that increase susceptibility to disease, 2) persistent somatic symptoms of depression, which are thought to worsen physical health over time, and 3) interference with physical recovery by impeding treatment seeking, adherence to treatment, and adoption of healthy lifestyles.15 We previously proposed a conceptual framework of the relationship between depression and diabetes health outcomes based on the premise that depression exerts its influence on diabetes-related health outcomes through decreased motivation to maintain behaviors that are protective against worsening of metabolic control and development of complications.15 In that paper, we proposed that depression impedes treatment seeking behavior, medication adherence, and adoption of effective self-management behaviors (including physical activity, appropriate dietary behavior, and appropriate self-monitoring of blood glucose behavior) via a decrease in motivation.15

The information-motivation-behavioral skills model 1720 provides a rational theoretical framework to test this hypothesis and improve understanding of the psychological mechanisms underlying the relationship between depression, self-care behavior, and glycemic control in adults with type 2 diabetes (T2DM). The Information—Motivation—Behavioral skills (IMB) model of health behavior change posits that behavior-specific information, motivation (e.g., positive personal beliefs and attitudes towards a behavior or outcome, and social support for the behavior), and requisite skills to execute a behavior and the confidence in one’s ability to do so across various situations are critical determinants of behavioral performance.17, 18, 20, 21 Essentially, one who is well informed and motivated to act is thought to develop and enact the skills necessary to perform the behavior at focus, and is likely to ultimately reap greater health benefits. 18, 21 The model’s constructs and relationships among them have been well-supported across populations and health promotion behaviors 18, 21; however, very minimal work has been done in diabetes.

The objective of this study was: 1) to determine whether the relationship between depression and self-care behavior is a direct relationship or indirect via the IMB model’s information (diabetes knowledge) and motivation (personal: fatalistic attitudes; and social: social support) determinants of behavior, and 2) to determine whether the relationship between depression and glycemic control is a direct relationship or indirect relationship via self-care behaviors. We hypothesized that, among adults with T2DM, depression would be related to self-care behavior via social motivation (not information); and that depression would be indirectly related to glycemic control via self-care behavior.

Research Design and Methods

Participants

We recruited consecutive patients with diagnosed T2DM and scheduled appointments at the Medical University of South Carolina (MUSC) Internal Medicine Clinic, Charleston, South Carolina. The institutional review board at MUSC approved all procedures prior to study enrollment. Eligible participants were clinic patients, age 18 years or older with a diagnosis of T2DM in the medical record, and a clinic appointment between June-August 2008. Patients were ineligible if they did not speak English, or if the research assistants determined (by interaction or chart documentation) they were too ill or cognitively impaired to participate.

Data and procedure

Research assistants reviewed the electronic clinic roster daily to identify eligible patients. Eligible patients were approached in the clinic waiting room, and provided a description of the study. Those interested and eligible were consented and taken to a private area in the clinic to complete the study instruments. Participants completed the assessment before or after their scheduled clinic appointments, depending on clinic flow. One hundred and twenty-six subjects were consented and completed all study measures.

We collected data on self-reported age, sex, race/ethnicity, education, household income, and marital status. Additional measures included validated surveys of depressive symptoms, diabetes knowledge, diabetes fatalism, social support, and diabetes self-care behavior. Hemoglobin A1C values were extracted from the electronic medical records.

Depressive symptoms

Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ-9).22 The PHQ-9 has demonstrated usefulness as a screening tool for depression with acceptable reliability, validity, sensitivity, and specificity.23 The nine items of the PHQ-9 come directly from the nine DSM-IV signs and symptoms of major depression.22 Higher scores on the PHQ-9 represent more depressive symptomatology with a range of 0–27. Depression was treated as a continuous variable, but was also categorized as no depression (PHQ-9 score <5), mild depression (PHQ-9 score 5–9) and major depression (PHQ-9 score ≥10) based on established guidelines. 22

Diabetes knowledge

Diabetes knowledge served as the measure of information, and was assessed with the Diabetes Knowledge Questionnaire (DKQ).24 The DKQ is a valid and reliable measure of diabetes knowledge, with high internal consistency reliability ranging from α=0.73 to 0.83, and construct validity reported in other studies.24 The DKQ elicits information about respondent’s understanding of the cause of diabetes, types of diabetes, self-management skills, and complications of diabetes. Responses are graded as “yes”, “no”, or “don’t know”. The final score was based on the percentage of correct scores, with a maximal possible score of 100.

Fatalistic attitudes

Diabetes fatalism served as the measure of personal motivation25, and was assessed with the 18-item Diabetes Fatalism Scale (DFS-18). The DFS-18 has good internal consistency, α=0.73, and response variability (range 30–90; mean 58.2.; SD 6.8). Diabetes fatalism is operationally defined as “a complex psychological cycle characterized by perceptions of despair, hopelessness, and powerlessness.” A summary score consisting of the sum of individual items is created, such that higher summary scores represent greater diabetes fatalism.

Social support

Social support served as the measure of social motivation, and was assessed with the 19-item Medical Outcomes Study (MOS) Social Support Survey.26 The MOS is a valid and reliable measure of social support that has demonstrated test-retest reliability, and internal consistency reliabilities greater than 0.91.26 The MOS measures perceived general functional support in four domains, including emotional/informational, tangible, positive social interaction, affection; and yields an overall support index, which was used in our analyses.

Diabetes self-care behavior

Self-care behavior was assessed with the 11-item Summary of Diabetes Self-Care Activities (SDSCA) scale.27 The SDSCA measures frequency of self-care activity in the last 7 days for five aspects of the diabetes regimen: general diet (followed healthful diet), specific diet (ate fruits/low fat diet), foot care, blood-glucose testing, exercise, and cigarette smoking.

Glycemic control

Patients’ most recent hemoglobin A1C value was extracted from the medical record, and served as the measure of glycemic control.

Data analyses

Structural equation models (SEM), specifying the relationships between variables, were estimated using AMOS, version 17. Advantages of this procedure include the generality and flexibility of model specification and the ability to assess fit of the hypothesized model to the observed data.

In a prior analysis with the current sample of diabetes patients, we found that a single factor (or latent variable, we are calling “diabetes self-care”) loaded onto the SDSCA’s subscales: specific diet, general diet, foot care and self-monitoring of blood glucose.28 In that same analyses, we also showed that having more information (greater diabetes knowledge), more personal motivation (less diabetes fatalism), and more social motivation (more social support) was associated with the latent variable diabetes self-care behavior; and behavior was the sole predictor of glycemic control.28 Those analyses prompted the current analytic approach, which was to explore the role of depression in explaining these relationships.

The current SEM was estimated using AMOS 17.0. The sample size of 126 cases was sufficient for these analyses.29, 30 Hypotheses regarding the specific structural relations of the constructs in the model were evaluated through inspection of the direction and magnitude of the path coefficients. Consistent with the IMB model assumptions, diabetes knowledge (as a measure of information), fatalistic attitudes (as a measure of personal motivation), and social support (as a measure of social motivation) were hypothesized to predict diabetes self-care behavior, not glycemic control (A1C). Only behavior was predicted to relate to A1C.

The likelihood ratio chi-square tests are reported, but model fit was primarily evaluated with the comparative fit index (CFI), and root mean square error of approximation (RMSEA).31, 32 Both the CFI and RMSEA test how well an estimated model fits the data structure. A non-significant likelihood ratio chi-square test suggests that the data fit the model well, while CFI values exceeding 0.90 and RMSEA values below 0.08 indicate adequate model fit.33

Results

A total of 126 men and women with type 2 diabetes completed all measures noted above. Participants were, on average, 63 years old. The majority were female (72.8%), African American (70.2%), not working (80.0%), and insured (96.4%). Also, in this sample, 61.9% had no depression, 23.8% had minor depression, and 14.3% had major depression (See Table 1).

Table 1
Sample Demographics (n=126).

The estimated SEM with parameters and tests of significance of individual paths appears in Figure 1. The estimated model demonstrated good data fit, χ2(23, N=126)=19.70, p=0.66, CFI=1.00, RMSEA=0.00 (90% CI: 0.00–0.06). When depressive symptoms were accounted for, more diabetes knowledge (r=0.21, p=0.02) and more social support (r=0.20, p=0.04) remained significantly related to performing diabetes self-care behaviors. Higher levels of depressive symptoms were significantly related to having less social support (r=−0.27, p=0.002), and decreased performance of diabetes self-care behaviors (r=−0.28, p=0.004). In addition, when depressive symptoms were included in the model, fatalistic attitudes were no longer associated with behavioral performance (r=−0.17, p=ns). In sum, more diabetes knowledge, more social support, and less depressive symptoms were associated with performing diabetes self-care behavior, explaining 24% of the variability in the diabetes self-care behavior score.

Figure 1
Depressive Symptoms and the Information-Motivation-Behavioral Skills Model of Diabetes Self-Care (full).

In an effort to generate a more parsimonious model, a trimmed version of the above model was estimated. The trimmed model included all significant paths from the initial model, omitting all non-significant paths. The trimmed model with structural parameters and tests of significance of individual paths appears in Figure 2. The estimated model demonstrated good data fit, χ2(18, N=126)=18.16, p=0.44, CFI=1.00, RMSEA=0.01 (90% CI: 0.00–0.08). The chi-square difference test between the trimmed and full models, χ2(5, N=126)=1.54, was non-significant, permitting the retention of the trimmed version as the final model. In both the full and trimmed models, diabetes self care behavior was marginally associated with glycemic control (r=−0.20, p=0.08 and r=−0.19, p=0.06, respectively).

Figure 2
Depressive Symptoms and the Information-Motivation-Behavioral Skills Model of Diabetes Self-Care (trimmed).

Discussion

This study shows that in this sample of adults with type 2 diabetes, depression does not have a direct effect on glycemic control; rather, the relationship is indirect via self-care behaviors. While there is a direct relationship between depression and behavior, social motivation exists in this predicted pathway, and is potentially modifiable through diabetes educational efforts . Although prior studies have documented that depression impairs self-care behaviors13, 14, 34, this is the first study, to our knowledge, that has taken the next step to examine the direct and indirect relationships among depression, self-care, and glycemic control.

This study adds to the literature in three important ways. First, it provides new evidence to support our previously published conceptual model that posits that depression exerts an influence on diabetes-related health outcomes through decreased motivation to maintain behaviors that are protective against worsening of metabolic control and development of complications. Second, the study uses a previously validated behavioral model, the IMB model to identify appropriate variables that explain self-care behaviors in people with diabetes (i.e. knowledge, personal motivation, and social motivation) that can be addressed in educational efforts. Third, the study provides good evidence that social support is an important contributor to effective self-care behavior in depressed adults with type 2 diabetes.

The study has limitations that are worth mentioning. First, we were unable to explore the role of other potential moderators (e.g., literacy level, race/ethnicity) in the evaluated models due to a restricted sample size. Second, our results speak most clearly to the population under study, and needs to be replicated in different patient groups. Third, although the IMB model proposes causal relationships between variables, the current study was cross-sectional in nature and thus can most appropriately speak to associations between constructs observed at a single point in time, not causality. Future research should be conducted to investigate the longitudinal effects of depression on an individual’s motivation to perform diabetes self-care behavior over time. In addition, future work should be guided by data that includes all the relevant constructs of the IMB model. This will provide a more comprehensive understanding of the elements that should be incorporated in diabetes self-care interventions, particularly those targeting patients with comorbid depression.

In conclusion, this study supports the hypothesis that among adults with diabetes, depression impedes treatment seeking behavior, seeking social support, and the adoption of effective self-management behaviors (including physical activity, appropriate dietary behavior, and appropriate self-monitoring of blood glucose behavior). Additional studies are needed to clarify the role of motivation on the impact of depression on self-care behaviors and glycemic control in adults with diabetes.

Acknowledgements

Dr. Osborn is supported by a Diversity Supplement Award (NIDDK P60 DK020593-30S2).

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