Cardiac Denial and Psychological Predictors of Cardiac Care Adherence in Adults With Congenital Heart Disease

Abstract

The current study examined cardiac denial and psychological predictors (i.e., depression, anxiety) of health outcomes including medical nonadherence and physical health in a sample of 80 adults with congenital heart disease (ACHD). Results indicated that denial of impact was elevated in this patient group compared with reference groups, and denial was negatively associated with depression and anxiety at ps < .01. Results indicated that depression, anxiety, and denial predicted unique variance in medical nonadherence, and gender moderated the relationships between these psychological factors and nonadherence. For depression, men and women showed similar relationships between depression and nonadherence at high levels of depression; however, at low levels of depression (i.e., a more normal mood state), men were less adherent compared with women. For anxiety, men and women did not differ in adherence at low levels of anxiety; however, men experiencing high anxiety were less adherent compared with women experiencing high anxiety. Implications of this study are discussed including the role of gender and denial and the impact of denial functioning to reduce negative affect. Depression was the only significant predictor of physical functioning. Results of this study suggest that psychological interventions aimed at depression and anxiety may function differently across gender to improve patient medical adherence and improve physical functioning in ACHD.

Keywords

congenital heart disease negative affect denial physical functioning adherence

Congenital heart disease is a global health problem, and it is the most prevalent birth defect, accounting for nearly one third of all congenital anomalies (van der Linde et al., 2011). Recent advancements in cardiovascular medicine and surgery have enabled most infants born with congenital heart disease to survive into adulthood, and this increasing population of adults with congenital heart disease (ACHD) requires lifelong specialized cardiac care (Engelfriet et al., 2005; Warnes et al., 2001). ACHD patients are at increased risk of developing serious cardiac complications and are at elevated risk for cardiac mortality (Verheugt et al., 2010). ACHD patients can face a range of biopsychosocial challenges, including physical limitations, interpersonal difficulties, and diminished educational opportunities and occupational attainment (Foster et al., 2001; Kovacs, Sears, & Saidi, 2005). Patients frequently endure lifelong medical follow-up visits, and they may face difficult treatment decisions and formidable demands adhering to treatment (Kovacs, Silversides, Saidi, & Sears, 2006). Researchers speculate that such mechanisms (e.g., treatment adherence) may underlie the relationship between psychological factors, such as depression, and negative health outcomes in chronic heart failure (Pelle, Gidron, Szabó, & Denollet, 2008). As such, it is increasingly important to investigate how psychological factors contribute to health outcomes and physical functioning in ACHD.

An emerging literature has accumulated on the psychological experiences of ACHD patients. Since the first study to report elevated rates of major depression (14%) and dysthymic disorder (38%) in ACHD (Horner, Liberthson, & Jellinek, 2000), increasingly, research has been aimed at understanding the psychological experiences of ACHD patients who have grown up in the context of an often stressful chronic illness. However, research is mixed as to whether ACHD patients experience more psychological adjustment difficulties compared with healthy samples. Some research has indicated that those with ACHD are at increased risk for psychological difficulties. Consistent with the work by Horner and colleagues (2000), studies using clinical interview estimate that 28% to 50% of patients with congenital heart disease have lifetime Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) anxiety and/or mood disorders (Bromberg, Beasley, D’Angelo, Landzberg, & DeMaso, 2003; Kovacs et al., 2009). Other investigations using self-report methods have shown that ACHD patients experience elevated symptoms of depression (Brandhagen, Feldt, & Williams, 1991), anxiety (Berghammer, Karlsson, Ekman, Erikson, & Dellborg, 2013; Eslami, Sundin, Macassa, Khankeh, & Soares, 2013), and psychological stress (via Symptom Checklist-90; Brandhagen et al., 1991) compared with patients without disease or reference groups. Contrary to these findings, however, other researchers have found low levels of neuroticism among patients with congenital heart disease compared with reference groups (Utens et al., 1998; van Rijen et al., 2003). For instance, Cox and colleagues found similar rates of anxiety and depression in ACHD outpatients compared with orthopedic patients (D. Cox, Lewis, Stewart, & Murphy, 2002). Gender also seems to affect rates. Although women consistently have higher prevalence rates of anxiety (McLean, Asnaai, Litz, & Hofmann, 2011) and depression (Piccinelli & Wilkinson, 2000) in outpatient samples, less is known about how gender affects the presentation of depression and anxiety in ACHD.

Some research groups (Utens et al., 1998) have speculated that denial mechanisms might have led to the low rates of psychopathology in ACHD. Perhaps in an attempt to cope, individuals with congenital heart disease may overcompensate by overstating their positive emotion ratings and minimizing their emotional distress. Although similar denial mechanisms exist in other medical populations (e.g., cancer, acquired heart disease), the risks faced by ACHD patients who acquire their disease at birth urge further investigation into the phenomenon. Research is needed to examine how negative psychological factors, such as depression and anxiety, relate to denial and physical health outcomes in patients with congenital heart disease.

The psychological concept of denial has been investigated extensively in patients with acquired cardiac disease (for reviews, see Covino, Stern, & Stern, 2011; Sirosis, 1992)—however, denial has yet to be investigated in patients with congenital heart disease. Denial may exert either a positive or negative influence on illness. On one hand, denial has been defined as an avoidance of an external or internal threat (Wool & Goldberg, 1986), and it is thought to function by distorting an anxiety-provoking reality (e.g., Freud, 1961; Vandereycken, 2005). In the context of a chronic illness, denial has been defined as the tendency to negate stressful reality and the painful affect associated with acknowledgment of the implications of one’s chronic illness (Livneh, 2009). In other words, individuals may use denial to downplay the long-term consequences of an illness because of their psychological implications. In patients with acquired cardiac disease, denial is associated with lower levels of psychological and emotional distress (Folks, Freeman, Sokol, & Thurstin, 1998), and in some cases, denial is coupled with improved medical outcomes (Levinson, Kay, Monteferrante, & Herman, 1984; Levinson, Mishra, Hamer, & Hastillo, 1989). On the other hand, denial reduces retention of important medical knowledge and has been found to reduce adherence with medical treatment (Croog, Shapiro, & Levine, 1971; Shaw, Cohen, Doyle, & Palesky, 1985). Lazarus’s (1983) classic theory of stress and coping regarded denial (and “denial-like processes,” p. 16) as an action-directed method of coping employed to regulate emotional distress. As such, according to this theory, partial denial could serve an adaptive role if used in situation-dependent circumstances in the early phases of an illness.

An important distinction in the study of psychological denial is the difference between denial of one’s illness and denial of the impact of one’s illness (Lazarus, 1983; Lazarus & Folkman, 1984). These two separate dimensions are empirically distinct (Havik & Maeland, 1986), the former being an uncommon, extreme manifestation of denial, and the latter occurring much more frequently (Havik & Maeland, 1988). To illustrate, some individuals may deny having an illness altogether (i.e., denial of illness), whereas others might acknowledge they have an illness, but deny it prevents them from engaging in desired activities (i.e., denial of impact). Given the degree of medical care and attention often received by ACHD patients since birth (i.e., surgeries, medical visits, medications, missed school), denial of illness among this patient population is likely to be an exceedingly rare phenomenon. Hence, this study focuses on the denial of impact of one’s illness. Only a few studies have investigated the role of denial of the impact of one’s condition in cardiac samples. In one study of acute myocardial infarction patients, Havik and Maeland (1988) found that patients who more strongly denied impact of their cardiac episode reported less anxiety and depression. The same investigation also found that high levels of denial of impact were related to increased mortality (Havik & Maeland, 1988). Results of this study suggest that although denial of impact may improve patient-perceived health in the short term, it may have negative implications for patient health in the long term. Despite some evidence that denial functions to reduce anxiety and depression, it is unknown how denial of impact is related to these phenomena in ACHD.

Given that cardiac denial of impact may influence emotional distress and both psychological factors may negatively relate to health outcomes in cardiac patients, the present study aimed to investigate whether cardiac denial of impact has an added value over depression and anxiety in the prediction of health outcomes in ACHD. Our major aims were therefore as follows: to assess the extent of cardiac denial of impact in patients with congenital heart disease in comparison with other chronically ill populations and to examine the extent to which physical health outcomes, including adherence to cardiac care and perceived physical functioning, are explained by psychological factors, namely, depression, anxiety, and cardiac denial of impact. First, we examined the interrelationships between depression, anxiety, and cardiac denial of impact; we hypothesized that both depression and anxiety would be negatively associated with denial of impact. Based on past research, we examined the role of gender on these relationships. Next, we examined the relationships between gender, psychological factors, and health outcomes, including general health perceptions, perceptions of physical functioning, and adherence with cardiac care. We hypothesized that better health outcomes would be associated with less psychological vulnerability. Finally, we investigated the extent that gender and psychological vulnerability interacted to predict variability in health outcomes.

Method

Sample Recruitment and Response Rate

A total of 106 adult outpatients with congenital heart disease consented to participate in this study that included medical assessment, cognitive assessment, questionnaire, and medical record review. All 106 patients completed medical assessment, cognitive assessment, and medical record review, and the majority completed the questionnaire battery (n = 80, 76% response rate); 29 patients did not complete questionnaires. Analyses were conducted to test for differences between those who completed the questionnaire battery and those who did not complete the questionnaire battery. No differences were found for patient years of age between study completers (M_COM = 45.04 years, SD_COM = 16.08) and non-completers (M_NC = 40.17 years, SD_NC= 13.01), F(1, 102) = 1.843, p = .178. Similarly, no differences were found between groups for sex, χ²(1, N = 103) = 3.66, p = .545, or total years of education between study completers (M_COM = 15.18 years, SD_COM = 2.16) and non-completers (M_NC = 14.58 years, SD_NC = 2.90), F(1, 95) = 1.138, p = .289.

Measures

Demographic questionnaire

A demographic measure was administered as part of a questionnaire battery to assess general personal information including gender, race/ethnicity, years of education completed, highest educational degree obtained, family background, employment and/or retirement history, and household income.

Depression

The Beck Depression Inventory–Version II (BDI-II; Beck, Steer, & Brown, 1996) was used to measure depression in this study. The BDI-II is one of the most commonly used measures for assessing mood and estimating the severity of depression in the past week. The BDI-II was designed to act as an indicator of depressive symptoms based on diagnostic criteria in the DSM-IV, and according to the authors, the 21 items in the BDI-II are representative of the DSM-IV criteria for depression. The total score characterizes the patient’s mood state as normal mood or whether they are experiencing mild, moderate, or major depression. The scale includes 21 items that are self-rated on a 4-point scale ranging from 0 to 3, and total raw scores can range from 0 to 63. Scores can be converted to descriptive clinical classifications: a total score of 0 to 13 is considered normal mood or minimal depression (<13), mild depression (14-19), moderate depression (20-28), and serious depression (29-63). The scale has demonstrated reliability and convergent and discriminant validity in psychiatric and academic samples. The scale is routinely used in medical populations. Cronbach’s alpha in this sample was .93.

Anxiety

The Beck Anxiety Inventory (BAI; Beck & Steer, 1990) was used to measure anxiety. The BAI is a widely used, well-researched self-report questionnaire that consists of 21 items meant to measure the severity of somatic, affective, and cognitive symptoms associated with panic and generalized anxiety in the past week. Each item is formulated as a 4-point Likert-type item, ranging from 0 to 3, that scores severity and/or frequency of symptoms, with higher scores indicating more severe anxiety symptoms. Ratings are summed to obtain a total score that can range from 0 to 63. The scale has been found to have high internal consistency, and the BAI has been found to discriminate anxiety from depression (Cox, Cohen, Direnfeld, & Swinson, 1996). The BAI has been shown to have good reliability and validity (Beck, Epstein, Brown, & Steer, 1988). Cronbach’s alpha in this study was .92.

Cardiac denial of impact

The Cardiac Denial of Impact Scale (CDI; Fowers, 1992) measures the extent that patients minimize the emotional impact of having cardiac disease and deny feeling worried or afraid about cardiac disease. Two items on the scale were adapted for use in this study by replacing the words heart attack with the words congenital heart disease. Example items include “My friends worry much more about my well-being than I do” and “I am not at all afraid when heart-related symptoms occur.” Questions are rated on a 5-point scale ranging from agree completely to disagree completely, and items are summed to yield a total score. The original version of the CDI was developed with patients with cardiovascular disease and has test–retest reliability and criterion, construct, and discriminant validity (Fowers, 1992). A factor analysis has indicated that the scale has a two-factor item structure (Gattellari, Butow, Tattersall, Dunn, & MacLeod, 1999). Recent research conducted in cardiac patients, however, found poor intercorrelations for two items and weak internal consistency for the original eight-item scale, and thus, the researchers concluded support for the single factor six-item solution of the CDI (Perkins-Porras, Whitehead, Strike, & Steptoe, 2008). Similarly, our data supported the six-item version, and therefore, we used the six-item version of the CDI in this study. Cronbach’s alpha for six-item CDI in this study was .76. Total scores range from 6, indicating minimal denial (reflected by low scores), to 24, indicating maximal denial (reflected by high scores).

Nonadherence with cardiac care (NAC) visits

NAC was assessed using the online medical record system. Patient outpatient visit data were tabulated based on the frequency of outpatient visits arrived/kept, no-showed (i.e., had a schedule appointment and failed to come without calling, rescheduling, or canceling), and canceled. Physician directed changes were not included in this analysis. The NAC index used a ratio according to the following formula: (Number of visits to which a patient arrived) / (Number of visits for which a patient no-showed + Number of visits which a patient canceled + 1). A lower ratio indicates less adherence with cardiac care visits (i.e., more cancelations, fewer attended visits, less attendance), and a higher ratio indicates more adherence with cardiac care visits (i.e., more attendance, fewer cancelations, no-shows). This index permits comparison of longtime patients with relatively new patients. Correlation of the NAC with age suggests lack of conflation; r(102) = −158, p = .144.

RAND Short Form–36 Health Survey

The RAND Short Form–36 (SF-36) Health Survey is a 36-item self-report health survey that assesses patient health domains (Hays, Sherbourne, & Mazel, 1993). The scale consists of eight scaled scores that are weighted sums, and each scale is transformed into a 0 to 100 scale on the assumption that each question carries equal weight. Lower scores indicate more impairment, and higher scores indicate less impairment. The composite physical health scales from the SF-36 were examined in this study: General Health Perceptions Scale (GEN) and Physical Functioning Scale (PHY). Each dimension was scored from 0 to 100 with higher scores indicating better physical health and/or higher general health perceptions. The RAND SF-36 Health Survey has demonstrated good reliability and validity in medical populations including cardiac populations (Chau et al., 1999; Yu, Li, Ho, & Lau, 2003). Cronbach’s alpha for the GEN in this study was .70. Cronbach’s alpha for the PHY in this study was .92.

Procedure

This cross-sectional research study recruited patients from an Adult Congenital Heart Disease Clinic at a university-affiliated medical center. Patients were invited to participate in this research study by their cardiologist, and a trained research assistant completed the informed consenting process. Inclusion criteria were (a) at least 18 years of age and (b) diagnosis of congenital heart disease. Patients were only excluded for medical evidence of a cognitive impairment that would present a communication barrier. Research participation included completion of an assessment of cognitive ability and impairment and questionnaire. The participant also consented to a medical record review. At the end of the outpatient visit, the research assistant completed an informed consenting procedure. A medical fellow administered the cognitive assessment and presented the questionnaire battery to patients. A medical fellow was trained to administer the cognitive ability assessment, and the cognitive ability measure was scored and interpreted by a clinical psychologist. Patients were encouraged to complete the battery after their appointment but were allowed to return the questionnaire by mail if they were not able to stay and complete the measure at the time of their visit. Participation was voluntary and not compensated. The Institutional Review Boards of Washington University School of Medicine located in St. Louis and the University of Missouri, St. Louis approved this research study.

Results

Sample Characteristics

The demographic characteristics for the total sample (N = 80) and group differences for men (n = 43, 54%) and women (n = 37, 46%) with congenital heart disease are reported in Table 1. Average age was 45 years (SD = 16.08 years).

Table 1.

Demographic Characteristics for the Total Sample (N = 80) and Across Groups for Men (n = 43) and Women (n = 37) With Congenital Heart Disease.

Characteristic	Total sample		Men (n = 43)		Women (n = 37)		Test	Effect size
Characteristic	%	n	%	n	%	n	Test	Effect size
Ethnicity^a
Black or African American	3.8	3	4.7	2	2.7	1
White not Hispanic or Latino/a	95.0	76	93.0	40	97.3	36
Hispanic or Latino/a	1.3	1	2.3	1	0.0	0
Educational background							χ²(6, N = 80) = 8.737, p = .189	.072
Less than high school	1.2	1	0.0	0	2.7	1
12th grade or equivalent	14.8	12	18.6	8	8.1	3
Vocational school/some college	1.2	1	13.9	6	18.9	7
Associates degree	13.6	11	9.3	4	18.9	7
Bachelor’s degree	30.9	25	39.5	17	21.6	8
Postgraduate degree	23.6	19	18.6	8	29.7	11
Household income							F(1, 74) = 0.636, p = .394	.185
Less than US$15,000	16.2	12	10.3	4	22.9	8
US15,001-US$30,000	18.9	14	25.6	10	11.4	4
US$30,001-US$45,000	14.9	11	10.3	4	20.0	7
US$45,001-US$60,000	10.8	8	10.3	4	11.4	4
US$60,001-US$75,000	6.8	5	7.7	3	5.7	2
More than US$75,001	32.4	24	35.9	14	28.6	10
Relationship status							χ²(1, N = 80) = 4.299, p = .507	.192
Married/cohabitating	61.3	49	25.6	11	18.9	7
Never married	22.5	18	65.1	28	51.4	19
Divorced/separated	14.1	12	9.3	4	45.6	9
Widowed	1.3	1	0.0	0	2.2	1

Note. Follow-up tests were conducted and there were no significant group differences.

No study participants self-identified as American Indian or Alaskan Native, Asian or Asian American, or Other; therefore, analyses were not calculated for ethnicity due to few participants.

Descriptive Findings

The mean, standard deviation, range, and zero-order correlations for all study variables are reported for the total sample and separately by sex in Tables 2 and 3, respectively. With regard to psychological functioning, 68.4% of patients scored in the normal range for mood on the BDI-II (n = 54), and 10% of patients scored in the mildly depressed to borderline clinically depressed range of depression (n = 15). Of the remaining patients, 12.7% scored in the moderately depressed (n = 8), severely depressed (n = 1), or extremely depressed (n = 1) categories of clinically elevated depression. Thoughts of suicide were endorsed by 6.3% (n = 5) of patients (i.e., BDI-II, Question 9). Depression did not differ by gender. Sixty-five percent (n = 51) of patients scored in the minimal range of anxiety, 19% scored in the mild range (n = 15), and 13% scored in the moderate (8.9%, n = 7) or severe (7.9%, n = 6) range of clinically elevated anxiety. Anxiety varied by gender, with women reporting significantly more anxiety compared with men (d = .49). Cardiac denial of impact also varied by gender, with men reporting significantly more denial of illness compared with women, with a large effect size (d = .457). Inspection of the item-level data indicated that 25% (n = 25) of the sample agreed or strongly agreed with the item “I am not at all afraid when heart symptoms occur” and 36.3% (n = 29) of the sample endorsed agreement with the statement “I do not fear dying at all.” A large percentage of patients (42.5%, n = 34) also agreed with the statement “I am not at all afraid when I receive information about my congenital heart disease.”

Table 2.

Mean, Standard Deviation, Range, and Zero-Order Correlations for All Study Variables for Combined Sample of Adults With Congenital Heart Disease (N = 80).

Variable	1	2	3	4	5	6
1. Depression (BDI)	—
2. Anxiety (BAI)	.65**	—
3. Cardiac denial of impact (CDI)	−.41**	−.28**	—
4. NAC	.24*	.36**	−.34*	—
5. Physical functioning (PHY)	−.37**	−.27*	.04	−.03	—
6. General health perceptions (GEN)	−.51**	−.31**	.29*	−.14	.58**	—
M	10.10	8.61	19.41	6.55	72.67	60.33
SD	8.69	9.34	4.45	17.21	26.67	21.42
Range (R)	2-45	0-42	9-29	0-50	0-100	5-100

Note. BDI = Beck Depression Inventory–Version II; BAI = Beck Anxiety Inventory; CDI = Cardiac Denial of Impact Scale; NAC = NonAdherence with Cardiac Care; PHY = Physical Functioning Scale–RAND Health Survey; GEN = General Health Perceptions Scale–RAND Health Survey.

p < .05. **p < .001.

Table 3.

Mean, Standard Deviation, Range, and Zero-Order Correlations for All Study Variables Reported Separately for Male (n = 43, Below the Diagonal) and Female (n = 37, Above the Diagonal) Adults With Congenital Heart Disease.

Variable	1	2	3	4	5	6	M	SD	R	p
1. Depression (BDI)	—	.59**	.29	.37**	−.38*	−.66**	11.45	8.54	2-36	.195
2. Anxiety (BAI)	−.70**	—	.18	.26	−.70**	−.32*	11.02	10.03	0-42	.030
3. Cardiac denial of impact (CDI)	.46*	.30*	—	−.35*	.20	−.16	17.68	4.06	7-27	.042
4. NAC	.20	.48**	.37*	—	−.13	−.36*	8.23	23.06	0-50	.348
5. Physical Functioning (PHY)	−.36*	−.36*	−.16	.02	—	.61**	70.41	23.96	5-100	.482
6. General Health Perceptions (GEN)	−.37*	−.21	−.32*	−.03	.56**	—	56.08	20.75	5-100	.100
M	8.90	6.47	15.66	6.55	74.67	63.98
SD	8.74	8.14	4.59	17.21	28.98	21.55
Range (R)	2-45	0-36	8-24	0-50	0-100	25-100
F	1.71	4.90	4.27	0.89	0.50	2.76

p < .05. **p < .001.

With regard to physical functioning, mean scores on the PHY and the GEN of the SF-36 were both lower than comparison sample reference groups. Patients in this sample reported their mean physical functioning on the SF-36 just lower than adult patients with long-standing illness (M = 78.3, SD = 23.2; Jenkinson, Coulter, & Wright, 1993), New York Heart Association (NHYA) Class I congestive heart failure (M = 79.2, SD = 20.4), and hepatitis (M = 79.3, SD = 23.3; Juenger et al., 2002). Average GEN score in this sample was approximately the same as adults with long-standing illness (M = 60.8, SD = 23.2; Jenkinson et al., 1993), Class I congestive heart failure (NHYA; M = 63.8, SD = 17.1; Jenkinson et al., 1993), and hepatitis (M = 52.7, SD = 25.7; Juenger et al., 2002). Mean scores on physical functioning and general health did not significantly differ across gender. Nonadherence was variable in this sample, however, the majority of patients were adherent with cardiac care appointments: 71% of patients attended scheduled outpatient appointments and the remaining 29% of patients demonstrated some failure to attend (i.e., no-shows) at scheduled cardiac care appointments.

Regression Analyses

Preliminary analyses were conducted to examine normality, linearity, and homoscedasticity. Normal probability plots were used to assess whether predictor variables were from a normal distribution. The distributions of each of the predictor and criterion measures were examined for skewness and kurtosis. The distributions of all measures indicated a lack of skewness or kurtosis (i.e., values were less than 3). Scatterplots provided evidence of linearity. The correlations among the predictor variables (depression, anxiety, cardiac denial of impact) included in this study were weakly to moderately strong. Regression analyses were structured, tested, and interpreted according to recommendations (Aikens & West, 1991; Holmbeck, 1997). Consistent with recommendations for interpretation of complex models (Aguinis & Gottfredson, 2010), we orthogonalized our regression models to fit full models, accepted final models based on model parsimony, and plotted interactions terms to facilitate interpretation in the context of main effects. Continuous-level predictors were standardized and multiplied to form interaction terms to facilitate the interpretation of interaction effects. Data were analyzed with unstandardized data first and produced identical results to the standardized data presented here.

Hierarchical regression analyses were conducted to examine the relationship between gender, psychological factors (i.e., depression, anxiety, and cardiac denial), and health outcomes (i.e., nonadherence, general health, and physical functioning). For each of the equations, the main effect of gender was entered on Step 1. The main effects of the psychological factors were entered on Step 2. Prior theoretical rationale and preliminary data analyses suggested that gender might interact with the emotional vulnerability variables, therefore, two-way interactions between gender and the emotional vulnerability variables were entered on Step 3. Because outliers can misrepresent relations between predictor and criterion variables, particularly in smaller samples, it was necessary to evaluate the influence outliers may have on regression equations (Neter, Wasserman, & Kutner, 1989). One multivariate outlier was removed based on Cook’s distance measure D (Cook & Weisberg, 1982).

First, results of the regression predicting NAC are reported in Table 4. Main effects were found for the psychological factors. Depression, anxiety, and cardiac denial each predicted unique variance in NAC. Two significant two-way interactions were found for Gender × Depression and Gender × Anxiety that predicted variance in nonadherence. Plots of the regression weights indicated that relationship between depression and nonadherence differed as a function of gender. Both men and women showed similar nonadherence at high levels of depression. However, at low levels of depression, the predicted decrease in nonadherence per unit of depression was −6.19 lower for males than for females. In other words, when depression was low (i.e., mood closer to the normal range), males were more nonadherent in their cardiac care compared with females. For the second interaction, plots of the regression weights indicated that the relationship between anxiety and nonadherence differed as a function of gender (see Figure 1). At low levels of anxiety, men and women did not differ in their NAC. However, at high levels of anxiety, the difference in slopes illustrated a large sex difference in adherence. Men showed a steeper slope such that at high levels of anxiety, the predicted increase in adherence per unit of anxiety was 7.661 points higher for men than women. The overall fit of Model 1 provided a good fit to the data, F(7, 69) = 4.46, p < .001, and accounted for 31% of the variation in NAC follow-up at a large effect size (f² = .45).

Table 4.

Hierarchical Regression Models for Gender, Psychological Vulnerability Variables, and the Moderating Effect of Gender on Health Outcomes (N = 80).

Step and predictor variable	B	SE B	β	R ²	f ²	p
NonAdherence Cardiac Care (NAC)
Step 1
Gender	0.57	2.08	.03	.00	.01	.787
Step 2
Depression (BDI)	0.29*	0.12	.28	.21	.27	.001
Anxiety (BAI)	0.34*	0.14	.33
Cardiac denial of impact (CDI)	−0.62*	0.24	−.30
Step 3
Gender × BDI	−6.19*	2.57	−.51	.31	.45	.001
Gender × BAI	7.66*	2.62	.54
Gender × CDI	−1.67	2.05	−.14
Constant	10.36
General Health Perceptions (GEN)
Step 1
Gender	5.74	4.30	.20	.04	.04	.082
Step 2
Depression (BDI)	−1.39**	0.33	−.57	.31	.45	.001
Anxiety (BAI)	0.26	0.29	.11
Cardiac denial of impact (CDI)	0.16	0.52	−.03
Step 3
Gender × BDI	1.15	5.77	.04	.33	.49	.001
Gender × BAI	6.66	5.83	.23
Gender × CDI	3.46	4.67	.13
Constant	77.51
Physical Functioning (PHY)
Step 1
Age	−0.37*	0.19	−.23	.06	.06	.114
Gender	2.25	6.08	.04
Step 2
Depression (BDI)	−1.17*	0.45	−.38	.21	.27	.004
Anxiety (BAI)	−0.22	0.41	−.08
Cardiac denial of impact (CDI)	−0.72	0.71	−.12
Step 3
Gender × BDI	−10.75	7.91	−.25	.25	.33	.008
Gender × BAI	6.41	7.91	.17
Gender × CDI	8.07	6.35	.23
Constant	135.13

Note. BDI-II = Beck Depression Inventory–Version II; BAI = Beck Anxiety Inventory; CDI = Cardiac Denial of Impact Scale; GEN = General Health Perceptions Scale–RAND Health Survey; PHY = Physical Functioning Scale–RAND Health Survey.

p < .05. **p < .001.

Figure 1.

Plots of regression lines of anxiety (i.e., BAI standardized scores) on nonadherence for male and female patients.

A second regression analysis was performed to investigate the ability of gender and the emotional vulnerability factors to predict general health perception (GEN). Depression was the only main effect for general health perceptions. There were no significant interactions. At the final step of the model, the regression model provided a good fit to the data, F(7, 70) = 4.97, p < .001, and accounted for 31% of the variation in general health perceptions with a large effect size (f² = .49).

A final regression model was performed to investigate the ability of age, gender, and psychological factors to predict physical functioning (PHY). Age was included in this model to covary for the association between age and physical health functioning in ACHD patients. At Step 1, age predicted 6% of the variance in physical functioning. The main effect of depression predicted an additional 15% of variance in physical functioning (PHY) at Step 2. No other variables predicted unique variance in physical functioning, and interactions were nonsignificant. The model provided a good fit to the data, F(8, 68) = 2.89, p = .008, and accounted for 25% of the variation in physical functioning at a medium effect size (f² = .33).

Discussion

Previous studies have found mixed findings on the psychological health of ACHD patients. Our aim in the present study was to investigate the relation between depression, anxiety, and health outcomes in ACHD and to examine if cardiac denial was significantly related to these relationships. Results of this study inform the literature on the psychological experiences of ACHD in some important ways. First, this study suggests that depression may pose a health risk for ACHD. Specifically, depression was indicative of low physical functioning and worse general health perceptions. Increased health risk associated with depression has been found in other cardiac conditions. For example, in heart failure patients, depression has been found to be predictive of prognosis (Friedman et al., 2006). Other research has found both depression and anxiety to be associated with declines in physical functioning (Shen et al., 2011). In this study, anxiety was not independently predictive of reduced general and physical health in combination with other psychological factors; yet, the relationship between anxiety and poor treatment adherence may pose an indirect risk to the health of ACHD outpatients. Although this study could not establish a causal link, if replicated, these findings suggest that depression and anxiety relate, directly or indirectly, to inferior health outcomes in ACHD.

Second, our results indicate that cardiac denial exerts some influence on ACHD. Few previous studies have examined denial of impact in cardiac populations, and this study is one of the first to investigate denial of impact among ACHD patients. Compared with other patient groups (Perkins-Porras et al., 2008), denial of impact in this patient group was elevated and was nearly the same as inpatients with acute coronary syndrome (ACS). Although not entirely unexpected, denial of impact was negatively associated with depression and anxiety, suggesting that it may be psychologically protective for patients to deny the impact of their illness. Moreover, although rates of clinically significant (i.e., at least “moderate”) depression (12.6%) and anxiety (16.5%) as determined by the BDI-II and BAI were somewhat elevated in this ACHD sample compared with healthy populations, results were lower than expected and lower compared with studies that have used diagnostic clinical interviews (Bromberg et al., 2003; Horner et al., 2000). Perhaps ACHD do not show elevated rates of psychological distress on self-report inventories partly because of their coping responses or of a tendency to minimize or deny the impact of their congenital disease. These results may partly help to explain why there are some seemingly contradictory findings with regard to examination of depression and anxiety in ACHD. Because ACHD patients have managed a demanding and chronic illness since birth, it may be that they are prone to downplay the consequences of their illness and its implications. Moreover, denial of impact was associated with higher general health perceptions in this study. This finding is consistent with studies that have linked denial to decreased anxiety and tension in patients with acquired cardiac disease (Dimsdale & Hackett, 1982; Esteve, Valdés, Riesco, Inmaculada, & de Flores, 1992), with some exceptions (Billing, Lindell, Sederholm, & Theorell, 1980). Alternatively, it may be that because ACHD patients are accustomed to receiving negative health–related information, they may perceive themselves as particularly resilient because they have already overcome some measured set of odds. In turn, they rate their general health perceptions particularly (or artificially) high.

Third, the findings of our present study suggest that all psychological factors assessed (depression, anxiety, and cardiac denial of impact) were unique and significant predictors of nonadherence with cardiac care follow-up, and that gender moderated some of these relationships. In particular, denial of impact of one’s illness was predictive of nonadherence to cardiac care follow-up. That is, patients who were prone to downplay the impact of their illness were less likely to attend their cardiac appointments. In general, men tended to adhere more with cardiac care compared with women, and this difference in adherence was particularly apparent at high levels of anxiety. This finding requires replication, but, if replicated in future studies, it suggests that high anxiety may prompt patients to attend follow-up medical care appointments, particularly for men with ACHD. These findings suggest that although denial of impact may function to reduce anxiety, there may be a consequence for patients’ as they may be less apt to adhere to follow-up appointments. Of course, the alternative hypothesis must also be considered: It may be that elevated anxiety may prompt some patients to reduce or avoid follow-up medical care appointments, particularly for women with ACHD. In other cardiac samples, the research is also mixed on the impact of gender on medical adherence (Chung et al., 2006; Dolansky, Stepanczuk, Charvat, & Moore, 2010). Nevertheless, these findings suggest medical adherence may be negatively affected by the degree to which one denies the impact of their illness.

There are limitations to this study. Our sample was selected among patients seeking outpatient cardiac care at a university-affiliated specialty clinic, and therefore, our sample may not represent all ACHD outpatients. This limits generalizability because our patient sample was apt to be somewhat higher in adherence. Also, this sample is less ethnically and culturally diverse than would be expected of most community or metropolitan hospitals. With the exception of the outpatient follow-up data, data were obtained by patient self-report, and their accuracy cannot be confirmed. Based on empirical review, Kovacs and colleagues (2005) have speculated that reliance on self-report compared with clinical interview is apt to underestimate problems in emotional adjustment among patients with congenital heart disease. Another limitation might be the single time point data collection. However, the momentum of the study focuses on the relationships between denial, psychological distress, and their impact on cumulative health outcomes. Even so, it would be beneficial to document longitudinal changes in depression, anxiety, and cardiac denial of impact along with objective indicators of health to study their causal associations over time. The future studies would benefit from innovative research designs that outreach to patients who are lost-to-follow-up. Finally, the comparison of our patients with reference samples was limited to published reports on cardiac patients and healthy samples. Future research on ACHD may increase reference samples of patients with congenital heart disease (Apers et al., 2015).

In conclusion, our findings show that depression and anxiety are related to negative health perceptions in ACHD. Measures of health (i.e., physical functioning, general health perceptions) were associated with depression, and an objective measure of health adherence (i.e., attendance of cardiac care) was associated with denial of the impact of illness. Rates of depression and anxiety were somewhat elevated in this sample, and our results suggest that cardiac denial of impact may interact with depression and anxiety in ACHD. We found that anxiety, depression, and cardiac denial of impact are related to health outcomes, but in incongruous ways. Potential determinants of the depression–anxiety–denial relationship should be explored. For instance, it may be that denial of impact (or episodic denial of impact) might indirectly contribute to the physical limitations of CHD patients through avoidance of cardioprotective health behaviors, including treatment adherence. Furthermore, research is needed to elucidate the complexities of denial of impact (e.g., content validity, construct validity) in ACHD such that the nuances around its role as a risk factor (or episodic protective factor) are better understood. From a clinical standpoint, identifying the ways in which denial of impact may be detrimental to the well-being of ACHD provides potential avenues for intervention. In this study, denial of impact was related to treatment nonadherence. If this finding is replicated, this may have implications for how care providers approach patients with high levels of nonadherence. Also, in this study, anxiety and depression were elevated in a significant proportion of patients, and these psychological factors often cannot be deduced from routinely obtained clinical variables. Research is needed to clarify how psychological factors may directly relate to health outcomes and improve medical adherence of ACHD.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Kamila S. White, PhD is an associate professor in the clinical psychology program in the Department of Psychological Sciences at the University of Missouri–St. Louis.

Caleb Pardue, MA is a doctoral student in the clinical psychology graduate program in the Department of Psychological Sciences at the University of Missouri–St. Louis.

Philip Ludbrook, MD is a professor in the medicine and radiology departments at Washington University School of Medicine in St. Louis, School of Medicine, and Director, Center for Adults with Congenital Heart Disease.

Sandeep Sodhi, MD is a physician and medical fellow in cardiology at Washington University School of Medicine in St. Louis, School of Medicine.

Amirhossein Esmaeeli worked with the research team as a research assistant.

Ari Cedars, MD is an associate professor in the medicine department at of Medicine at Washington University School of Medicine in St. Louis, School of Medicine.

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