Predictors of Depression in Chronic Obstructive Pulmonary Disease

Monday, 22 July 2013: 11:05 AM

Mary Patricia Wall, PhD, RN
College of Nursing, Seton Hall University, South Orange, NJ

Learning Objective 1: The learner will be able to identify three predictors of depression in patients with COPD.

Learning Objective 2: The learner will be able to state two reasons to assess for depression in chronically ill persons.

Purpose: Chronic obstructive pulmonary disease (COPD) is a chronic, complex, and progressive disease that affects millions of adults worldwide. Depression is a frequent concomitant diagnosis of chronic illnesses, and is known to influence adherence to patients’ prescribed health care regimens. The purpose of this study was to identify predictors of depression in people with COPD. Findings presented here represent secondary analyses of data from a study of community-dwelling COPD patients.

Methods: Participants were recruited from a pulmonary medicine practice in the mid-Atlantic region of the United States. A total of 119 people participated in the parent study. The mean age (68 + 8 years) was consistent with that of other studies of people with COPD. The sample was fairly equally divided by gender, and was predominately Caucasian. Analyses were conducted with the SPSS software package. Statistical significance was set, a priori, at p < .05.

Results: Measures of well-being (anxiety, life satisfaction, happiness), coping resources (mastery, social support), and physiologic status (functional performance, severity of COPD, comorbid illness), as well as selected demographic variables (age, gender) were included in the regression analysis. Only social support, comorbid illness, and severity of COPD were not statistically significant predictors of depression in this sample (R square = .710, R square adjusted = .683, F [10, 108] = 26.463, p = .000).

Conclusion: Depression is an important consideration in studies of persons with medical diagnoses. It is a common finding in both chronically ill individuals and in the aging population. Variables in several categories were predictors of depression in this group. Knowledge of the multi-faceted nature of depression in this population may give researchers and clinicians insight into potential areas for interventions to address this important issue.