Anxiety and Depressive Symptoms in Patients with COPD: Modifiable Explanatory Factors

Abstract

Anxiety and depressive symptoms affect up to 80% of people with chronic obstructive pulmonary disease (COPD). To reduce this symptom burden, clinicians should target modifiable explanatory factors while accounting for nonmodifiable explanatory factors of these symptoms. The purpose of this secondary data analysis was to examine which modifiable factors explain anxiety and depressive symptoms in COPD. This secondary data analysis of 1,760 COPD patients used multiple regression to explain anxiety and depressive symptoms from sets of modifiable patient characteristics and demographic controls. Clinically significant symptoms of anxiety or depression presented in 29.6% (n = 526) of participants, and 20.6% (n = 363) had both. Significant modifiable explanatory factors of both disorder symptoms were perceived functional status, functional capacity, psychosocial impact, symptom self-management, and significant symptoms for the other. Somatic symptom burden and dyspnea explained anxiety and depressive symptoms, respectively. Addressing these modifiable factors may reduce anxiety and depressive symptoms in patients with COPD.

Keywords

anxiety symptoms depressive symptoms symptom self-management COPD modifiable factors

Chronic obstructive pulmonary disease (COPD) is characterized by persistent pulmonary symptoms and potentially irreversible airflow limitation (Ho et al., 2019). Substantially burdensome symptoms such as cough, phlegm, fatigue, chest tightness, and dyspnea impact many patients daily (Bugajski et al., 2019). Virtually all patients experience one disease-related symptom per day, and those in moderate to severe disease stages can experience an average of 7.9 to 17.6 symptoms per day; some report experiencing up to 57 different disease-related symptoms (Christensen et al., 2016; Kinsman et al., 1983). Progression of the disease is characterized by increasing symptom burden, decreases in functional capacities, and often other comorbidities. Anxiety and depressive symptoms are two commonly occurring and compounding symptomologies in people with COPD, with approximately 33% to 50% experiencing these symptoms regularly (Tselebis et al., 2016).

Anxiety and Depressive Symptoms in COPD

The presence of anxiety and depressive symptoms in COPD are associated with more frequent somatic symptoms, impaired quality of life, and reduced adherence to treatment regimens (Tselebis et al., 2016; Yohannes & Alexopoulos, 2014). Anxiety and depressive symptoms also adversely affect healthcare-related outcomes such as costs, hospitalization, and mortality (Abrams et al., 2011). Uncontrolled anxiety symptoms are associated with an 89% increase in patients’ risk of hospitalization and uncontrolled depressive symptoms can nearly double the risk of hospitalization (Breland et al., 2015; Pooler & Beech, 2014). Moreover, they are associated with patients being hospitalized twice as long and having higher mortality rates compared to those who do not have anxiety and/or depression (Laurin et al., 2012).

Despite the substantial impact of anxiety and depressive symptoms, there is no consensus on the ideal way to treat these psychological comorbidities in people with COPD. Complicating these treatment plans are the overlapping somatic and psychological symptoms in individuals with comorbid COPD and anxiety/depression, including varying efficacy of pharmacologic treatments due to medication interactions or undesirable side effects (e.g., respiratory depression) (Tselebis et al., 2016; Yohannes & Alexopoulos, 2014). Implementation of nonpharmacological treatments, such as therapy or counseling, has increased dramatically over the past decade; however, this limits providers’ ability to provide interventions at a level less than professional support (Lipson et al., 2019; Vahratian et al., 2021). Since professional therapy/counseling is not available to everyone, there is still an impetus on researchers and clinicians to alleviate anxiety and depressive symptoms. This has largely been unaddressed in COPD literature until recently (Iovino et al., 2020; Mathew et al., 2019), further affirming the need for research that identifies modifiable factors of anxiety and depressive symptoms that could be adjuvant or independent of current therapeutic interventions.

In general, the following factors can be considered modifiable: anxiety symptoms, depressive symptoms, health-related quality of life, perceived health status, symptom self-management, functional capacity, and symptom burden (Clark et al., 2015; Fjeldsoe et al., 2012; Noar et al., 2007; Santos et al., 2021). On the contrary, nonmodifiable factors involve indicators of disease progression (e.g., Global Initiative for Chronic Obstructive Lung Disease [GOLD] Stage) and some sociodemographic factors (e.g., age, biological sex) (Raghavan et al., 2017). As most of the scientific focus regarding anxiety and depressive symptoms in COPD speaks to how these symptoms affect distal outcomes (e.g., hospitalization, exacerbations), the above factors should be considered when collecting data to formulate interventions that address important intermediate outcomes in people with COPD—anxiety and depressive symptom burden.

This study is framed using the Middle-Range Theory of Unpleasant symptoms (Lenz et al., 1997), which recognizes that symptoms are subjective experiences influenced by antecedent physiological, psychological, and situational factors. We applied this theory through a combination of past literature and clinically relevant antecedent modifiable factors which could contribute to the presence of anxiety and depressive symptoms. Lastly, a fundamental component of this theory guided our work in that concomitant symptoms may interact with one another on several levels/dimensions, which increases the complexity of identifying modifiable antecedents, as well as distal treatment regimens.

Purpose

The purpose of this secondary data analysis is to separately examine which modifiable factors explain anxiety symptoms and which modifiable factors explain depressive symptoms, while controlling for clinical and sociodemographic variables among a sample of COPD patients. Modifiable explanatory variables for this study were anxiety symptoms (only in depression models), depressive symptoms (only in anxiety models), psychosocial impact of COPD on daily life, somatic symptom burden, dyspnea, symptom self-management, perceived functional status, and functional capacity. Clinical and sociodemographic controls were age, biological sex, and lung function.

Methods

Participants and Procedure

This was a secondary data analysis of pre-intervention/baseline data from the National Emphysema Treatment Trial (NETT) of the National Heart, Lung, and Blood Institute (Fishman et al., 2003). The NETT was a multicenter trial completed between 1998 and 2002, which aimed to examine the efficacy, morbidity, and mortality of lung volume reduction surgery compared to normal medical treatment of those with emphysema-COPD. The NETT investigators screened 3,777 patients to achieve an analytic sample of 2,500. For our purposes, we chose to only include patients with complete data, which resulted in a sample of 1,760 patients with COPD. All subjects in the NETT provided written informed consent to participate after the nature of the procedures had been fully explained. Full description of the NETT and its primary findings have been described elsewhere (Fishman et al., 2003). All baseline measures were obtained after the completion of 6 to 10 weeks of pulmonary rehabilitation, and all self-report measures were self-administered (Fishman et al., 2003). This cross-sectional (baseline data only), secondary data analysis was carried out in accordance with the latest version of the Declaration of Helsinki and was reviewed and approved by the authors’ Institutional Review Board. We used the STROBE cross-sectional checklist when writing our report (von Elm et al., 2007).

Measurements

Anxiety

Anxiety symptoms were measured using the state subscale of the State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983). The state subscale is self-report and evaluates patients’ current (in the moment) state of anxiety. Concepts such as apprehension, nervousness, worry, and tension are measured in this subscale, which is composed of 20 questions using a 4-point Likert-type scale ranging from 1 (not at all) to 4 (very much so). The range of scores is 20–80, where higher scores indicate more anxiety symptoms. In general populations, scores ≥39 are considered clinically significant symptoms of anxiety (Knight et al., 1983). We dichotomized the instrument into 0 for scores less than 38 and 1 for scores ≥39 to indicate clinically significant anxiety symptoms. An a priori choice to dichotomize the variable was deployed to reflect clinical significance or not, which aligns with standard practices when assessing COPD patients for psychological distress. As most patients with COPD live with mild anxiety related to the anxiety-dyspnea cycle (Bailey, 2004), treatment or resources are often not administered unless a clinical threshold is reached. The STAI-state has been shown to demonstrate results producing an internal consistency (α = 0.85) and acceptable convergent validity with other measures of anxiety symptoms in a sample of older adults (>55 years), supporting the appropriateness for use in this population, especially at the time of the NETT (Stanley et al., 1996).

Depression

The Beck Depression Inventory (Beck et al., 1987) was used to measure depressive symptoms. The Beck Depression Inventory is self-report instrument composed of 21 items measuring four domains of depressive symptoms: cognitive, affective, somatic, and vegetative. Scores can range from 0 to 63, where higher scores indicate higher symptoms of depression. Scores ≥11 indicate mild depressive symptoms and warrant further investigation. For this study, we dichotomized Beck Depression Inventory scores into 0 (scores < 11) and 1 (scores ≥ 11) to indicate clinically significant depressive symptoms to reflect Beck’s suggested cutoff (Beck et al., 1987). The dichotomization of this variable to reflect the presence of clinically significant depressive symptoms or not is in alignment with many current practices of psychological distress screening in COPD. In a sample of primary care patients, the BDI demonstrated results producing excellent internal consistency (α = 0.94) and acceptable-good convergent validity with the Mental Health SF-20 subscale (Arnau et al., 2001).

Psychosocial impact of COPD on daily life

The St George Respiratory Questionnaire’s Impact component (SGRQ-Impact; Jones et al., 1991) was operationalized to assess the psychosocial impact of COPD on patients’ daily life. We chose to omit the Activity component of the SGRQ due to excessive overlap with the main measure of dyspnea (San Diego Shortness of Breath Questionnaire [SOBQ]). The Symptom component is used as an operationalization of somatic symptom burden, further described later. The Impact component aims to assess how COPD has impacted the psychosocial components of patients’ daily life; for example, questions may pertain to disease-related interruptions of daily living, social acceptance/perception, and distress of limitations. Impact component scores are standardized to range from 0 to 100, where higher scores indicate more limitations and greater negative impact of the disease on daily life. The SGRQ impact has a strong body of evidence supporting its reliability and validity in a COPD population. In a sample specifically for adults from the United States, Cronbach’s α was .82 and produced significant correlations to key indices related to COPD, such as dyspnea and health-related quality of life (SF-36; Barr et al., 2000).

COPD Symptoms

Somatic symptom burden

The SGRQ’s Symptom component (Jones et al., 1991) was operationalized to assess the overall somatic symptom burden related to COPD, as it serves as an indicator of the concept by assessing the frequency and severity of presenting symptoms. The Symptoms component is comprised of eight items assessing the frequency and severity of coughing, phlegm/sputum, dyspnea, wheezing, and general characterizations of symptom-related “good days.” Component scores are standardized to range from 0 to 100, with 0 indicating no burden/limitation and 100 indicating maximal burden/limitation. Internal consistency of the SGRQ Symptoms component has been demonstrated to be α = .72 in a U.S. population and has demonstrated significant, albeit weak, correlations with domains of other health assessment measures including the SF-36 when utilizing a 1-month recall (Barr et al., 2000).

Dyspnea

The San Diego SOBQ (Eakin et al., 1998) for perceived dyspnea was used to assess dyspnea in the NETT. This was used instead of the related dyspnea measure in the SGRQ because of its thoroughness and to avoid potential multicollinearity in analyses. The San Diego SOBQ is a 24-item Likert-type questionnaire assessing small perceived changes in dyspnea related to daily activities. Each question is scored from 0 (not at all) to 5 (maximally or unable to do because of breathlessness). Scores range from 0 to 120, where higher scores indicate more severe effects of dyspnea on daily life. The SOBQ has previously demonstrated excellent internal consistency (α = 0.96) and good validity as evidenced by high correlations with physiologic measures of disease (FEV₁), health-related quality of life (Quality of Well-Being Scale; QWB), exercise tolerance (6MWT), Borg Scale ratings, lung indices, and depression (Eakin et al., 1998).

Self-Management of Symptoms

The QWB Scale (Seiber et al., 2008) was used to assess self-management of symptoms. The QWB was originally intended to measure quality of life and aid in quantifying quality-adjusted life years. In the NETT and other studies, the QWB Scale was also used to quantify the self-management of symptoms in COPD (Park & Larson, 2014). The instrument prompts patients to identify acute and chronic symptoms and identify strategies with which they manage those symptoms. This approach is readily used in disease-specific measures of symptom self-management in other chronic conditions (Bugajski et al., 2022; Matarese et al., 2020; Riegel et al., 2018a). Scores are then weighted and standardized to result in total scores ranging from 0 to 1. A score of zero indicates the inability to manage symptoms and severe impairment, whereas a score of one indicates perfect management, no impairment. Normative scores range from 0.62 to 0.67 in healthy populations (Kaplan et al., 1984). In those with COPD, the QWB has demonstrated adequate test-retest reliability (r ≥ .80; Anderson et al., 1989) and validity, as a significant correlation with related performance measures (walking efficacy r = .49, exercise tolerance = 0.41), and physiologic measures of disease (FEV₁) have been observed (Kaplan et al., 1984).

Physical Functioning

Perceived functional status

The Medical Outcomes Study Short Form (MOS SF-36) (Ware & Sherbourne, 1992; Ware Jr. et al., 1995) is a 36-item questionnaire in which items may be aggregated to create a Mental Component Summary (MCS) and Physical Component Summary (PCS). The MCS score was chosen to be omitted from these analyses due to conceptual overlap with anxiety and depression instrumentation. Scores on the PCS were used to assess participants’ perceived functional status. The PCS is comprised of questions regarding perceived physical function, bodily pain, general health, and role limitations due to physical health problems. Since scaling for each subscale varies, scores were summed, transformed, and standardized to generate the PCS score, which ranges from 0 to 100. A higher score indicates better perceived functional status. In a sample of adults with various chronic illnesses, the PCS demonstrated an internal consistency of α = 0.92 and a strong relative validity (RV = 0.79) in assessing changes related to physical health, indicating appropriate reliability and validity of results produced by the PCS in this population (Ware Jr. et al., 1995).

Functional capacity

The six-minute walk test (6MWT; American Thoracic Society, 2002) was delivered per the American Thoracic Society’s guidelines to examine functional capacity. The maximum distance walked in feet traveled was used for this secondary analysis. In COPD, the six-minute walk test is a well-validated measure of functional capacity, which is highly correlated with oxygen consumption, exercise capacity, and is a consistent predictor of COPD exacerbations and death (Puhan et al., 2008).

Demographic and Clinical Characteristics

Patients underwent interviews, physical exams, and completed self-administered demographic forms to report on relevant covariate characteristics. For this analysis, the following variables were included: age, biological sex, smoking status/history, employment status, marital status, arterial blood gas values, and pulmonary function tests. The measures used from the arterial blood gases were partial pressure of oxygen and partial pressure of carbon dioxide. Measures used from the pulmonary function testing were forced vital capacity and forced expiratory volume in one second. Patients were categorized into disease stages based upon pulmonary function testing values per the GOLD (2021).

Data Analysis

Descriptive statistics (e.g., frequencies, proportions, means, ranges, and standard deviations) were used to characterize the sample and variables studied. Participants were then categorized based on their anxiety and depressive symptoms to determine the proportion of the sample that had clinically relevant symptoms of anxiety and/or depression; these categorizations were determined using the established cutoffs for clinically significant symptoms as measured by the State-Trait Anxiety Inventory and Beck Depression Inventory (Beck et al., 1987; Knight et al., 1983). Two multiple linear regressions were constructed to model continuous self-reported symptoms of depression (Beck Depression Inventory) and anxiety (State-Trait Anxiety Inventory). To compare explanatory factors between models, the same variables were tested: anxiety symptoms (STAI-state), depressive symptoms (BDI), psychosocial impacts of COPD on daily life (SGRQ-Impact), somatic symptom burden (SGRQ-Symptoms), dyspnea (SOBQ), symptom self-management (QWB), perceived functional status (PCS), and functional capacity (6MWT), while controlling for nonmodifiable demographic and clinical variables (age, biological sex, and GOLD stage). When depressive symptoms were the response variable, only anxiety symptoms were used as an explanatory variable—depressive symptoms were not also input into this model. Similarly, only depressive symptoms were treated as an explanatory variable when anxiety symptoms were the response variable. We did not discern participants into groups as we did in Table 1. We chose to group participants into those with clinically significant symptoms of anxiety/depression or those without; participants had significant symptoms of neither anxiety nor depression, only one, or both.

Table 1.

Demographic and Clinical Characteristics of the Sample (N = 1,760).

Characteristics	Whole SampleN = 1,760	No Clinically Significant Symptoms of Anxiety or DepressionN = 876	Clinically Significant Anxiety Symptoms OnlyN = 257	Clinically Significant Depressive Symptoms OnlyN = 264	Clinically Significant Symptoms of Anxiety and DepressionN = 363	p-Value
Age	67.5 (5.5)	67.5 (5.5)	67.3 (5.7)	67.4 (5.5)	67.3 (5.4)	.935
Sex (male)	1,083 (61.5%)	581 (66.3)	148 (57.6)	159 (60.2)	195 (53.7)	<.001
Retired or disabled?						.021
Yes	1,484 (84.3%)	758 (96.5)	218 (84.8)	219 (83.0)	289 (79.6)	.021
Marital status						.03
Single	53 (3%)	25 (2.9)	7 (2.7)	7 (2.7)	14 (3.9)
Divorced/separated	305 (17.4%)	150 (17.1)	45 (17.5)	43 (16.3)	67 (18.5)
Widowed	269 (15.3%)	134 (15.3)	33 (12.8)	39 (14.8)	63 (17.4)
Married	1,133 (64.4%)	567 (64.7)	172 (66.9)	175 (66.3)	219 (60.3)
Educational level						<.001
Did not complete high school	345 (19.6%)	125 (14.3)	59 (23.0)	66 (25.0)	95 (26.2)
Completed high school	544 (30.9%)	264 (30.1)	84 (32.7)	73 (27.7)	123 (33.9)
Some college	582 (33.1%)	310 (35.4)	81 (31.5)	84 (31.8)	107 (29.5)
Bachelors or higher	289 (16.4%)	177 (20.2)	33 (12.8)	41 (15.5)	38 (10.5)
Previously participated in pulmonary rehabilitation program						.361
Yes	1,080 (61.4%)	524 (59.8)	159 (61.9)	174 (65.9)	223 (61.4)	.361
Smoker or previously smoked?						n/a
Yes	1,763 (100%)	876 (100)	257 (100)	264 (100)	363 (100)	n/a
GOLD stage						.116
Stage 3	626 (35.6%)	327 (37.3)	99 (38.5)	82 (30.5)	118 (32.5)
Stage 4	1,134 (64.4%)	549 (62.7)	158 (61.5)	182 (68.9)	245 (67.5)
BMI	24.9 (4.1)	25.1 (4.0)	24.7 (4.1)	24.6 (4.2)	24.5 (4.3)	.05
BDI score	9.5 (6.05)	5.7 (2.65)	7.1 (2.36)	14.1 (3.5)	(17.2)	<.001
STAI—State scores	34.9 (10.9)	27.5 (5.6)	45.1 (5.3)	30.8 (4.9)	48.7 (7.5)	<.001
SGRQ symptoms score	58.9 (19.1)	55.7 (19.7)	59.4 (18.2)	61.5(18.4)	64.3 (17.8)	<.001
SGRQ activity score	81.1 (13.3)	77.8 (13.9)	81.5 (12.4)	84.5 (11.7)	86.5 (10.7)	<.001
SGRQ impact score	41.4 (16.8)	35.5 (15.5)	40.9 (16.1)	47.1 (14.0)	52.3 (15.4)	<.001
SGRQ overall score	56.4 (13.2)	51.7 (12.8)	56.3 (12.2)	60.9 (10.5)	64.7 (11.4)	<.001
6MWT distance (feet)	1130.8 (335.6)	1183.4 (346.7)	1106.7 (309.1)	1098.4 (318.4)	1044.7 (316.8)	<.001
SF36 physical component summary score (PCS)	28.2 (52.4)	29.4 (7.9)	28.2 (7.3)	26.0 (6.5)	27.0 (6.2)	<.001
SF36 mental component summary score (MCS)	52.4 (10.4)	57.4 (7.6)	51.9 (9.2)	49.5 (9.5)	42.8 (9.8)	<.001
Dyspnea scores (SOBQ)	64.8 (19.4)	58.6 (18.9)	64.9 (18.5)	71.4 (16.8)	74.9 (17.4)	<.001
Symptom self-management scores (QWB)	0.53 (0.12)	0.57 (0.11)	0.55 (0.12)	0.49 (0.11)	0.46 (0.12)	<.001

Abbreviations: GOLD, Global Initiative for Obstructive Lung Disease Stage; FEV₁, forced expiratory volume per second; FVC, forced vital capacity; BMI, body mass index; BDI, Beck Depression Inventory; STAI, State-Trait Anxiety Inventory; SGRQ, St. George Respiratory Questionnaire; 6MWT, six-minute walk test; SF36, Medical Outcome Study Short Form Survey; SOBQ, University of California San Diego Shortness of Breath Questionnaire; QWB, quality of well-being.

Note: All p-values reported are on the overall analysis of variance or chi-square test of independence between groups.

All categorical variables were dichotomized prior to model construction, including biological sex (0 = male, 1 = female); GOLD stage (Stage 3= 0, Stage 4 =1); clinically relevant symptoms of anxiety (0 = no, 1 = yes); and clinically relevant symptoms of depression (0 = no, 1 = yes). Prior to interpretation, the assumptions of multiple linear regression were met, including linearity, independence of residuals, normality, homoscedasticity, and multicollinearity (Field, 2013). All data analyses were conducted using SPSS version 25.0 (IBM Corp., 2017) with an a priori α = 0.05 to determine significance.

Results

The total analytic sample for these analyses was 1,760 patients with COPD (Table 1). The average age was 68 (SD = 5.5) years with 61.5% male. All participants were former smokers and most had severe/end-stage COPD as evidenced by 1,137 (64.5%) being in GOLD Stage 4. The average forced expiratory volume in one second (observed/predicted) was 26% (SD = 7.6%), which indicates severe airflow limitation. Next, 14.6% of the sample reported clinically significant symptoms of anxiety only, 15% reported clinically significant symptoms of depression only, and 20.6% reported clinically significant symptoms of both anxiety and depression.

Anxiety

There were six modifiable factors, which were significant explanatory factors for anxiety scores (Table 2): perceived functional status (PCS; b = .120, p = .007), somatic symptom burden (SGRQ-Symptom; b = .027, p = .049), psychosocial impacts of COPD on daily life (SGRQ-Impact; b = .116, p < .001), symptom self-management (QWB; b = −4.826, p = .036), functional capacity (6MWT; b = −.002, p = .038), and clinically significant symptoms of depression (BDI; b = 7.230, p < .001). Being female resulted in higher anxiety scores (STAI-state; b = 1.315, p = .007), and was the only nonmodifiable explanatory factor. The model explained approximately 23.7% of the variance (F [10, 1749] = 54.386, R² = .237; p < .001).

Table 2.

Multiple Regression Analysis of Anxiety Scores (N = 1,760).

Variable	b	SE	β	p	95% CI for “b”(Lower, Upper)
Age	−.027	.41	−.014	.513	−.109, .054
Sex (female)	1.315	.488	.059	.007	.357, 2.273
GOLD Stage (Stage 4)	−.692	.498	−.031	.165	−1.669, .284
Perceived functional status scores (PCS)	.120	.037	.081	.001	.047, .192
Somatic symptom burden scores (SGRQ Symptom)	.027	.014	.047	.049	.000, .053
Psychosocial impact of COPD on daily life scores (SGRQ impact)	.116	.019	.179	< .001	.078, .154
Symptom self-management scores (QWB-SA)	−4.826	2.296	−.054	.036	−9.329, −.323
Dyspnea scores (SOBQ)	.024	.017	.043	.146	−.009, .057
Functional capacity (6MWT)	−.002	.001	−.050	.038	−.003, .001
Clinically significant symptoms of depression (BDI ≥ 11)	7.230	.532	.317	< .001	6.186, 8.275

Abbreviations: GOLD, Global Initiative for Obstructive Lung Disease Stage; PCS, Medical Outcomes Study Short Form 36 Physical Component Summary; BDI, Beck Depression Inventory; STAI, State-Trait Anxiety Inventory; SGRQ, St. George Respiratory Questionnaire; 6MWT, six-minute walk test; SF36, Medical Outcome Study Short Form Survey; UCSD SOBQ, University of California San Diego Shortness of Breath Questionnaire; QWB-SA, quality of well-being.

Depression

Results from the multiple regression are aggregated in Table 3. Overall, the regression model was significant (F[10, 1749] = 98.79, R² = .361; p < .001), and produced six significant modifiable explanatory factors of depressive symptoms scores: perceived functional status (PCS; b = .041, p = .030), psychosocial impacts of COPD on daily life (SGRQ-Impact; b = .108, p < .001), symptom self-management scores (QWB; b = −8.875, p < .001), dyspnea (SOBQ; b = .029, p = .001), functional capacity (6MWT; b = .001, p = .018) and clinically significant symptoms of anxiety (STAI-state; b = 3.655, p < .001). For nonmodifiable factors, being female, as compared to male (b = .768, p = .002), was found to be a significant explanatory factor of depression scores.

Table 3.

Multiple Regression Analysis of Depression Scores (N = 1,760).

Variable	b	SE	β	p	95% CI for “b”(Lower, Upper)
Age	−.020	.021	−.018	.343	−.061, .021
Sex (female)	.768	.248	.062	.002	.281, 1.255
GOLD stage (Stage 4)	.434	.253	.035	.086	−.062, .930
Perceived functional status scores (PCS)	.041	.019	.050	.030	.004, .078
Somatic symptom burden scores (SGRQ Symptom)	−.007	.007	−.022	.319	−.020, .007
Psychosocial impact of COPD on daily life scores (SGRQ Impact)	.108	.010	.299	<.001	.089, .127
Symptom self-management scores (QWB)	−8.875	1.148	−.179	<.001	−11.127, −6.624
Dyspnea scores (SOBQ)	.029	.009	.094	.001	.013, .046
Functional capacity (6MWT)	.001	.000	.052	.018	.000, .002
Clinically significant symptoms of anxiety (STAI ≥ 39)	3.655	.256	2.88	<.001	3.153, 4.157

Discussion

Although the prevalence of anxiety and depressive symptoms in those with COPD are well-documented, the modifiable explanatory factors are not. We aimed to identify modifiable factors (concomitant anxiety and/or depressive symptoms, symptom self-management, perceived functional status, somatic symptom burden of COPD, psychosocial impact of COPD on daily life, dyspnea, functional capacity) that explain depressive and anxiety symptoms in a sample of individuals diagnosed with moderate to severe COPD, while controlling for nonmodifiable factors of age, biologic sex, and disease progression (GOLD stage). Approximately 35% of our sample for this secondary analysis reported clinically significant symptoms of anxiety and/or depression. When explaining anxiety and depressive symptoms, we found there are both overlapping and distinct explanatory factors for each. Specifically, symptom self-management scores and concomitant clinically significant symptoms of the other disorder (e.g., anxiety symptoms when explaining depressive symptoms, or vice versa) were the most heavily weighted explanatory factors in each model (Tables 2 and 3). Nonetheless, the results of this study highlight that there are numerous and overlapping opportunities for researchers and clinicians to target in order to reduce anxiety or depressive symptoms in those with moderate to severe COPD.

Our findings provide additional insight into the relationships among self-management of symptoms and anxiety and depressive symptoms. We determined that poorer self-management of symptoms can result in patients being at a higher risk of experiencing anxiety and depressive symptoms. Interestingly, dual consideration of anxiety and depressive symptoms have largely been unexamined in those with COPD; however, there has been recent literature on similar chronic illnesses that examined the relationship between depression and self-management. Most recently, Lin et al. (2020) concluded a strong inverse relationship between depressive symptoms and symptom-related self-management, which is in alignment with prior research as well (Hwang et al., 2014). Similarly, Iovino et al. (2020) set to explore the relationship between self-management and depression in older adults with multiple chronic illnesses; they concluded there was no significant relationship between self-management and depressive symptoms. Although intriguing, Iovino’s conclusions are not comparable to the results of this study for two reasons. First, they only had 53 patients with primary COPD and did not examine self-management among this group alone. Second, they examined for associations of depressive symptoms and self-management by comparing self-management scores between “depressed” and nondepressed groups—where “depressed” was determined by categorizing participants as depressed if they scored a five or more on the Patient Health Questionnaire-9, a substantially lower, subclinical threshold, for depression when compared to our threshold, the recommended clinical cutoff of the Beck Depression Inventory. Given our large sample size and more stringent depression cutoff, our results conclude with Lin et al. (2020) that there is a significant relationship between symptom self-management and depressive symptoms. This notion also speaks to the relevance of NETT data in the context of self-management research—the data produced from this approximately 20-year-old trial are consistent with results as recent as 2020.

Previously, several studies aimed at improving self-management skills in COPD found no effect on 12-month follow-up of anxiety or depressive symptoms. However, this has largely been attributed to very low symptoms of anxiety and depression in those study samples (Zwerink et al., 2014). Successful self-management requires patients to be active, daily participants in their own care by repeatedly assessing their symptom status and determining if care is needed to alleviate distressful symptoms. The anxiety and depressive constructs measured in the NETT are naturally inhibitory to successful self-management. Therefore, it is unsurprising that there is an inverse relationship in self-management of symptoms with both anxiety and depressive symptoms.

An interesting addition to the relationship between symptom self-management and anxiety/depressive symptoms is that there is a similar, albeit differently weighted, association between the two constructs. While an inverse relationship exists between self-management and anxiety/depressive symptoms, data suggest that self-management of symptoms may be more impactful on depressive symptoms rather than anxiety symptoms. Depressive symptoms are inherently manifested in longer timespans, which patients may deal with over the course of months to years. Additionally, as depressive symptoms become more prominent with disease progression, these symptoms may be more familiar to patients who experience them and allow for greater adaptability in the performance of self-management techniques. In regard to the relationship between anxiety symptoms and symptom self-management, patients may not necessarily understand how symptom self-management may be able to alleviate anxiety’s sudden onset, as anxiety symptoms in COPD are highly variable, quickly evolving, and strongly tied to momentary perceptions of breathlessness (Bailey, 2004; Breland et al., 2015). It is possible that the participants’ momentary report of anxiety (measured by the State-Trait Anxiety Inventory state subscale) is not the best measure when examining the association with the longitudinal recall of their self-management of symptoms. Therefore, it may be beneficial to use nonmomentary assessments of anxiety (such as the Beck Anxiety Inventory) to further explore the relationship between anxiety symptoms and self-management, as self-management behaviors may not be entirely useful unless patients can anticipate known triggers, such as planned exercise or emotional situations.

Perceived functional status (PCS) and the psychosocial impact of COPD on the patients’ daily lives (SGRQ-Impact) were statistically significant explanatory factors in both regression models. While the SGRQ-Impact results were clinically significant (Jones, 2002) the PCS scores should be treated with caution when addressing clinical relevance due to their relatively small coefficients in each model. These are expected findings; as COPD progresses, physical limitations increase and the disease can have an increasingly negative impact on psychosocial aspects of patients’ lives, increasing anxiety and depressive symptoms (Park et al., 2013). These findings highlight the need to implement or design interventions aimed to promote physical functioning and alleviate the impact of the disease on social functioning and psychological disturbances for people with COPD.

Interestingly, dyspnea was only a statistically and clinically (Ries, 2005) significant explanatory factor in the depression models. Recently, a group of investigators highlighted a potential causal relationship between dyspnea and symptoms of depression by showing that dyspnea frequency, emotional responses elicited from dyspnea, and impairments in functioning from dyspnea are related to somatic depressive symptoms (i.e., fatigue and sleep loss; Schuler et al., 2018). The nonsignificant relationship between dyspnea and anxiety may be due to the momentary assessment of anxiety symptoms measured by the state subscale of the State-Trait Anxiety Inventory. During data collection in the NETT, participants’ anxiety may have been low in anticipation of a potentially life changing intervention (lung volume reduction surgery). Dyspnea was measured by the SOBQ, which frames the participant to think of prior experiences. Thus, there is another mismatch in concepts similar to those described above between symptom self-management and anxiety, as dyspnea may have been a significant explanatory factor if a nonmomentary recall of anxiety was used; this has been reported in numerous other studies (Breland et al., 2015; Pooler & Beech, 2014).

Being female was the only significant, nonmodifiable explanatory factor of anxiety and depressive symptoms. Until recently, sex has not been considered to be associated with psychological symptoms in COPD. However, there are consistent findings that being female is related to negative psychological symptoms and may result in more severe symptoms in general (DeMeo et al., 2018; Tselebis et al., 2016).

As expected, although clinically insignificant, functional capacity as demonstrated by feet walked during the 6MWT was a significant explanatory factor of depressive symptoms. Although statistically significant, the coefficients in the models were too small to practicably make a difference. This finding is seen in other studies although at a much larger effect (Moullec & Ninot, 2010; Weingaertner et al., 2014). It is recommended that rather than solely targeting functional capacity as a means to improve anxiety or depressive symptoms, improving functional capacity should be a component of a multifaceted approach to improve patient outcomes.

Implications for practice in modulating the presence of anxiety symptoms include optimizing perceived functional status, functional capacity, self-management behaviors, and coping with the psychosocial impacts of COPD while reducing the somatic symptom burden and addressing concomitant depressive symptoms. Modulation of depressive symptoms may include the optimization of functional status, self-management behaviors, coping with psychosocial impacts of COPD, and breathing technique education to mitigate shortness of breath while addressing concomitant anxiety symptoms.

Findings from this study can best be understood in the context of limitations. This secondary data analysis utilized a cross-sectional methodology; therefore, causality may not be strongly inferred, as the original trial did not assess anxiety and depressive symptoms longitudinally. Although the NETT was conducted over 20 years ago, we believe the data are still pertinent to the state of the science regarding anxiety, depression, and modifiable factors, as our results align with similar studies into present day. A potential confounding effect throughout this sample is the potential of these patients to receive lung volume reduction surgery. During the original study, the impact of surgery was unknown, which may have had a paradoxical effect. Some patients may have been desperate for intervention leading to inflated scores of anxiety or depressive symptoms. Or, some patients may have been optimistic at the possibility of surgical intervention, thus artificially reducing anxiety and depression scores. Additionally, this sample primarily represents those experiencing emphysematous-dominant COPD; therefore, these results should only be generalized to those experiencing this form of the disease and may not apply to other subtypes of COPD. Lastly, the instruments included in this secondary analysis are self-report; however, self-report was the only feasible method to obtain the constructs of interest.

These findings contribute evidence for the role of modifiable and nonmodifiable factors in the explanation of clinically significant symptoms of depression and anxiety among those diagnosed with COPD. Within the clinical practice, our data suggest that transdisciplinary teams of health care providers should consider these modifiable factors associated with comorbid anxiety and/or depressive symptoms for patients with COPD.

Supplemental Material

sj-pdf-1-wjn-10.1177_01939459221129949 – Supplemental material for Anxiety and Depressive Symptoms in Patients with COPD: Modifiable Explanatory Factors

Supplemental material, sj-pdf-1-wjn-10.1177_01939459221129949 for Anxiety and Depressive Symptoms in Patients with COPD: Modifiable Explanatory Factors by Andrew Bugajski, Hailey Morgan, Walter Wills, Kellcee Jacklin, Shirley Alleyne, Bishoy Kolta, Alexander Lengerich and Kaitlyn Rechenberg in Western Journal of Nursing Research

Footnotes

Acknowledgements

The authors have no acknowledgments

Authorship Statement

All authors meet the authorship criteria as outlined by the latest guidelines of the International Committee of Medical Journal Editors, and all authors agree with the manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

This retrospective study was carried out in accordance with the latest version of the Declaration of Helsinki and was reviewed and approved by the authors’ Institutional Review Board (University of South Florida IRB, #Pro00041483).

ORCID iD

Walter Wills

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Andrew Bugajski (ORCID 0000-0001-8065-7288) is involved in the conception and design of the work, acquisition, and interpretation of the data in the work, drafting of the manuscript, critical revision for important intellectual content and final approval of the version to be published and agreement to be accountable for all aspects of the work.

Hailey Morgan (ORCID 0000-0002-6229-7431) is involved in the design of the work, acquisition of the data in the work, drafting of the manuscript, and final approval of the version to be published and agreement to be accountable for all aspects of the work.

Kaitlyn Rechenberg (No ORCID) is involved in the conception and design of the work, interpretation of the data in the work, critical revision for important intellectual content, drafting of the manuscript, and final approval of the version to be published and agreement to be accountable for all aspects of the work.

Walter Wills (ORCID 0000-0002-5179-3325) is involved in the interpretation of the data in the work, drafting of the manuscript, critical revision for important intellectual content, and final approval of the version to be published and agreement to be accountable for all aspects of the work.

Alex Lengerich (ORCID 0000-0002-1470-7854) is involved in the drafting of the manuscript, critical revision for important intellectual content, and final approval of the version to be published and agreement to be accountable for all aspects of the work.

Kellcee Jacklin (No ORCID).

Bishoy Kolta (ORCID 0000-0002-0644-0766).

Shirley Alleyne (ORCID 0000-0002-7950-437X) is involved in critical revision for important intellectual content, drafting of the manuscript, and final approval of the version to be published and agreement to be accountable for all aspects of the work.

References

Abrams

T. E.

Vaughan-Sarrazin

Vander Weg

M. W.

(2011). Acute exacerbations of chronic obstructive pulmonary disease and the effect of existing psychiatric comorbidity on subsequent mortality. Psychosomatics, 52(5), 441–449. https://doi.org/10.1016/j.psym.2011.03.005

American Thoracic Society. (2002). ATS statement: Guidelines for the six-minute walk test. American Journal of Respiratory & Critical Care Medicine, 166, 111–117. https://doi.org/10.1164/ajrccm.166.1.at1102

Anderson

J. P.

Kaplan

R. M.

Berry

C. C.

Bush

J. W.

Rumbaut

R. G.

(1989). Interday reliability of function assessment for a health status measure: The quality of well-being scale. Medical Care, 27(11), 1076–1084. http://www.jstor.org/stable/3765526

Arnau

R. C.

Meagher

M. W.

Norris

M. P.

Bramson

(2001). Psychometric evaluation of the Beck Depression Inventory-II with primary care medical patients. Health Psychology, 20(2), 112–119. https://doi.org/10.1037//0278-6133.20.2.112

Bailey

P. H.

(2004). The dyspnea-anxiety-dyspnea cycle—COPD patients’ stories of breathlessness: “It’s scary/when you can’t breathe.” Qualitative Health Research, 14(6), 760–778. https://doi.org/10.1177/1049732304265973

Barr

J. T.

Schumacher

G. E.

Freeman

LeMoine

Bakst

A. W.

Jones

P. W.

(2000). American translation, modification, and validation of the St. George’s Respiratory Questionnaire. Clinical Therapeutics, 22(9), 1121–1145. https://doi.org/10.1016/S0149-2918(00)80089-2

Beck

A. T.

Steer

R. A.

Brown

G. K.

(1987). Beck Depression Inventory. Harcourt Brace Jovanovich.

Breland

Hundt

Barrera

Mignogna

Petersen

Stanley

Cully

(2015). Identification of anxiety symptom clusters in patients with COPD: Implications for assessment and treatment. International Journal of Behavioral Medicine, 22(5), 590–596. https://doi.org/10.1007/s12529-014-9450-2

Bugajski

Frazier

S. K.

Cousin

Rechenberg

Brown

Lengerich

Moser

D. K.

Lennie

T. A.

(2019). Effects of a digital self-care intervention in adults with COPD: A pilot study. Western Journal of Nursing Research, 42(9), 736–746. https://doi.org/10.1177/0193945919892282

10.

Bugajski

Szalacha

Rechenberg

Johnson

Beckie

Morgan

(2022). Psychometric evaluation of the self-care in chronic obstructive pulmonary disease inventory in the United States. Heart & Lung, 51, 1–8. https://doi.org/10.1016/j.hrtlng.2021.07.004

11.

Christensen

V. L.

Rustoen

Cooper

B. A.

Miaskowski

Henriksen

A. H.

Bentsen

S. B.

Holm

A. M.

(2016). Distinct symptom experiences in subgroups of patients with COPD. International Journal of Chronic Obstructive Pulmonary Disease, 11(1), 1801–1809. https://link.gale.com/apps/doc/A506650321/AONE?u=tamp44898&sid=bookmark-AONE&xid=106a2149

12.

Clark

McDougall

Riegel

Joiner-Rogers

Innerarity

Meraviglia

Delville

Davila

(2015). Health status and self-care outcomes after an education-support intervention for people with chronic heart failure. The Journal of Cardiovascular Nursing, 30(4S Suppl. 1), S3–S13. https://doi.org/10.1097/JCN.0000000000000169

13.

DeMeo

D. L.

Ramagopalan

Kavati

Vegesna

Han

M. K.

Yadao

Wilcox

T. K.

Make

B. J.

(2018). Women manifest more severe COPD symptoms across the life course. International Journal of Chronic Obstructive Pulmonary Disease, 13, 3021–3029. https://link.gale.com/apps/doc/A577040523/AONE?u=tamp44898&sid=bookmark-AONE&xid=86de0cca

14.

Eakin

E. G.

Resnikoff

P. M.

Prewitt

L. M.

Ries

A. L.

Kaplan

R. M.

(1998). Validation of a new dyspnea measure: The UCSD Shortness of Breath Questionnaire. Chest, 113(3), 619–624. https://link.gale.com/apps/doc/A20573346/AONE?u=tamp44898&sid=bookmark-AONE&xid=32a34160

15.

Field

(2013). Discovering statistics using SPSS (4th ed.). SAGE Publications.

16.

Fishman

Martinez

Naunheim

Piantadosi

Wise

Ries

Weinmann

Wood

D. E.

(2003). A randomized trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema. New England Journal of Medicine, 348(21), 2059–2073. https://doi.org/10.1056/NEJMoa030287

17.

Fjeldsoe

B. S.

Miller

Y. D.

Marshall

A. L.

(2012). Text messaging interventions for chronic disease management and health promotion. In Noar

S. M.

Harrington

N. G.

(Eds.), eHealth applications (pp. 180–199). Routledge.

18.

GOLD. (2021). Global strategy for the diagnosis, management and prevention of COPD, Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2021. https://goldcoped.org/

19.

Cusack

R. P.

Chaudhary

Satia

Kurmi

O. P.

(2019). Under- and over-diagnosis of COPD: A global perspective. Breathe (Lausanne, Switzerland), 15(1), 24–35. https://doi.org/10.1183/20734735.0346-2018

20.

Hwang

Moser

D. K.

Dracup

(2014). Knowledge is insufficient for self-care among heart failure patients with psychological distress. Health Psychology, 33(7), 588–596. https://doi.org/10.1037/a0033419

21.

IBM Corp. (2017). IBM SPSS Statistics for Windows, Version 25.0.

22.

Iovino

De Maria

Matarese

Vellone

Ausili

Riegel

(2020). Depression and self-care in older adults with multiple chronic conditions: A multivariate analysis. Journal of Advanced Nursing, 76(7), 1668–1678. https://doi.org/10.1111/jan.14385

23.

Jones

P. W.

(2002). Interpreting thresholds for a clinically significant change in health status in asthma and COPD. The European Respiratory Journal, 19(3), 398–404. https://doi.org/10.1183/09031936.02.00063702

24.

Jones

P. W.

Quirk

F. H.

Baveystock

C. M.

(1991). The St George’s Respiratory Questionnaire. Respiratory Medicine, 85(Supplement B), 25–31. https://doi.org/10.1016/s0954-6111(06)80166-6

25.

Kaplan

R. M.

Atkins

C. J.

Timms

(1984). Validity of a quality of well-being scale as an outcome measure in chronic obstructive pulmonary disease. Journal of Chronic Disease, 37(2), 85–95. https://doi.org/10.1016/0021-9681(84)90050-X

26.

Kinsman

R. A.

Fernandez

Schocket

Dirks

J. F.

Covino

N. A.

(1983). Multidimensional analysis of the symptoms of chronic bronchitis and emphysema. Journal of Behavioral Medicine, 6(4), 339–357. https://doi.org/10.1007/BF00846323

27.

Knight

R. G.

Waal-Manning

H. J.

Spears

G. F.

(1983). Some norms and reliability data for the State-Trait Anxiety Inventory and the Zung Self-Rating Depression scale. British Journal of Clinical Psychology, 22(4), 245–249. https://doi.org/10.1111/j.2044-8260.1983.tb00610.x

28.

Laurin

Moullec

Bacon

S. L.

Lavoie

K. L.

(2012). Impact of anxiety and depression on chronic obstructive pulmonary disease exacerbation risk. American Journal of Respiratory & Critical Care Medicine, 185(9), 918–923. https://doi.org/10.1164/rccm.201105-0939PP

29.

Lenz

E. R.

Pugh

L. C.

Milligan

R. A.

Gift

Suppe

(1997). The middle-range theory of unpleasant symptoms: An update. Advances in Nursing Science, 19(3), 14–27. https://journals.lww.com/advancesinnursingscience/Fulltext/1997/03000/The_Middle_Range_Theory_of_Unpleasant_Symptoms__An.3.aspx

30.

Lin

C. Y.

Miller

J. L.

Lennie

T. A.

Biddle

M. J.

Mudd-Martin

Hammash

Moser

D. K.

(2020). Perceived control predicts symptom status in patients with heart failure. Journal of Cardiovascular Nursing, 35(6), 30–37. https://doi.org/10.1097/JCN.0000000000000684

31.

Lipson

S. K.

Emily

G. L.

Eisenberg

(2019). Increased rates of mental health service utilization by U.S. college students: 10-year population-level trends (2007–2017). Psychiatric Services, 70(1), 60–63. https://doi.org/10.1176/appi.ps.201800332

32.

Matarese

Clari

De Marinis

M. G.

Barbaranelli

Ivziku

Piredda

Riegel

(2020). The self-care in chronic obstructive pulmonary disease inventory: Development and psychometric evaluation. Evaluation & the Health Professions, 43(1), 50–62. https://doi.org/10.1177/0163278719856660

33.

Mathew

A. R.

Yount

S. E.

Kalhan

Hitsman

(2019). Psychological functioning in patients with chronic obstructive pulmonary disease: A preliminary study of relations with smoking status and disease impact. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 21(5), 686–690. https://doi.org/10.1093/ntr/nty102

34.

Moullec

Ninot

(2010). An integrated programme after pulmonary rehabilitation in patients with chronic obstructive pulmonary disease: Effect on emotional and functional dimensions of quality of life. Clinical Rehabilitation, 24(2), 122–136. https://doi.org/10.1177/0269215509346088

35.

Noar

S. M.

Benac

C. N.

Harris

M. S.

(2007). Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological Bulletin, 133(4), 673–693. https://doi.org/10.1037/0033-2909.133.4.673

36.

Park

S. K.

Larson

J. L.

(2014). Symptom cluster, healthcare use and mortality in patients with severe chronic obstructive pulmonary disease. Journal of Clinical Nursing, 23(17–18), 2658–2671. https://doi.org/10.1111/jocn.12526

37.

Park

S. K.

Meldrum

C. A.

Larson

J. L.

(2013). Subgroup analysis of symptoms and their effect on functioning, exercise capacity, and physical activity in patients with severe chronic obstructive pulmonary disease. Heart & Lung, 42(6), 465–472. https://doi.org/10.1016/j.hrtlng.2013.08.008

38.

Pooler

Beech

(2014). Examining the relationship between anxiety and depression and exacerbations of COPD which result in hospital admission: A systematic review. International Journal of Chronic Obstructive Pulmonary Disease, 9(1), 315–330. https://doi.org/10.2147/COPD.S53255

39.

Puhan

M. A.

Mador

M. J.

Held

Goldstein

Guyatt

G. H.

Schunemann

H. J.

(2008). Interpretation of treatment changes in 6-minute walk distance in patients with COPD. European Respiratory Journal, 32(3), 637–643. https://doi.org/10.1183/09031936.00140507

40.

Raghavan

Varkey

Bartter

(2017). Chronic obstructive pulmonary disease: The impact of gender. Current Opinion in Pulmonary Medicine, 23(2), 117–123. https://doi.org/10.1097/MCP.0000000000000353

41.

Riegel

Barbaranelli

Sethares

K. A.

Daus

Moser

D. K.

Miller

J. L.

Haedtke

C. A.

Feinberg

J. L.

Lee

Stromberg

Jaarsma

(2018a). Development and initial testing of the self-care of chronic illness inventory. Journal of Advanced Nursing, 74(10), 2465–2476. https://doi.org/10.1111/jan.13775

42.

Riegel

Jaarsma

Lee

C. S.

Stromberg

(2018b). Integrating symptoms into the middle-range theory of self-care of chronic illness. Advances in Nursing Science, 42(3), 206–215. https://doi.org/10.1097/ANS.0000000000000237

43.

Ries

A. L.

(2005). Minimally clinically important difference for the UCSD Shortness of Breath Questionnaire, Borg Scale, and visual analog scale. COPD, 2(1), 105–110. https://doi.org/10.1081/copd-200050655

44.

Santos

G. C.

Liljeroos

Dwyer

A. A.

Jaques

Girard

Strömberg

Hullin

Schäfer-Keller

(2021). Symptom perception in heart failure – Interventions and outcomes: A scoping review. International Journal of Nursing Studies, 116, 103524. https://doi.org/10.1016/j.ijnurstu.2020.103524

45.

Schuler

Wittmann

Faller

Schultz

(2018). The interrelations among aspects of dyspnea and symptoms of depression in COPD patients—A network analysis. Journal of Affective Disorders, 240, 33–40. https://doi.org/10.1016/j.jad.2018.07.021

46.

Seiber

W. J.

Groessl

E. J.

David

K. M.

Ganiats

T. G.

Kaplan

R. M.

(2008). Quality of well being self-administered (QWB-SA) scale. Health Services Research Center, University of California. https://hoap.ucsd.edu/qwb-info/qwb-manual.pdf

47.

Spielberger

C. D.

Gorsuch

R. L.

Lushene

R. E.

(1983). Manual for the State-Trait Anxiety Inventory. Consulting Psychologists.

48.

Stanley

M. A.

Beck

J. G.

Zebb

B. J.

(1996). Psychometric properties of four anxiety measures in older adults. Behaviour Research and Therapy, 34(10), 827–838. https://doi.org/10.1016/0005-7967(96)00064-2

49.

Tselebis

Pachi

Ilias

Kosmas

Bratis

Moussas

Tzanakis

(2016). Strategies to improve anxiety and depression in patients with COPD: A mental health perspective. Neuropsychiatric Disease and Treatment, 12, 297–328. https://doi.org/10.2147/NDT.S79354

50.

Vahratian

Blumberg

S. J.

Terlizzi

E. P.

Schiller

J. S.

(2021). Symptoms of anxiety or depressive disorder and use of mental health care among adults during the COVID-19 pandemic—United States, August 2020–February 2021. Morbidity Mortality Weekly Report, 70(13), 490–494. http://doi.org/10.15585/mmwr.mm7013e2

51.

von Elm

Altman

D. G.

Egger

Pocock

S. J.

Gotzche

P. C.

Vandenbroucke

J. P

. (2007). The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Bulletin of the World Health Organization, 85(11), 867–872. https://doi.org/10.2471/BLT.07.045120

52.

Ware

J. E.

Sherbourne

C. D.

(1992). The MOS 36-Item Short-Form Health Survey (SF-36): I. conceptual framework and item selection. Medical Care, 30(6), 473–483. http://www.jstor.org/stable/3765916

53.

Ware

J. E.

Jr. Kosinski

Bayliss

M. S.

McHorney

C. A.

Rogers

W. H.

Raczek

(1995). Comparison of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: Summary of results from the Medical Outcomes Study. Medical Care, 33(4), AS264–AS279. http://www.jstor.org/stable/3766635

54.

Weingaertner

Scheve

Gerdes

Schwarz-Eywill

Prenzel

Bausewein

Higginson

I. J.

Voltz

Herich

Simon

S. T.

(2014). Breathlessness, functional status, distress, and palliative care needs over time in patients with advanced chronic obstructive pulmonary disease or lung cancer: A cohort study. Journal of Pain and Symptom Management, 48(4), 569–581.E1. https://doi.org/10.1016/j.jpainsymman.2013.11.011

55.

Yohannes

A. M.

Alexopoulos

G. S.

(2014). Depression and anxiety in patients with COPD. European Respiratory Review, 23(133), 345–349. https://doi.org/10.1183/09059180.00007813

56.

Zwerink

Brusse-Keizer

van der Valk

P. D.

Zielhuis

G. A.

Monninkhof

E. M.

van der Palen

Firth

P. A.

Effing

(2014). Self management for patients with chronic obstructive pulmonary disease. Cochrane Database of Systematic Reviews, 2014(3), CD002990. https://doi.org/10.1002/14651858.CD002990.pub3

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