Comorbidity of Depression and Chronic Illness Acquired During Adulthood
Steven Gemignani
California School of Professional Psychology
Chronic illnesses and disabling conditions affect approximately 54 million Americans. Of this number, more than 9 million Americans are unable to work or attend school due to their disabilities (Livneh & Antonak, 2005). The impact of these illnesses on individuals is profound. Individuals with chronic illness and disabilities face many challenges in their lives. These challenges include functional limitations, impaired ability to perform daily activities, uncertain prognosis, prolonged course of treatment and interventions, psychosocial stresses, impact on family and friends, and negative impact on financial resources. Not surprisingly, a large volume of data exists which demonstrates high rates of comorbidity of depression and chronic illness. While the incidence rate of depression is approximately 10-15% for the general population, the rate for those with chronic illnesses has been estimated to be between 25-50% (Chronic Illness and Depression, 2003). This paper examines the comorbidity data, reviews the critical factors and variables that define the relationship between chronic illness and depression, and presents current treatment alternatives.
According to Rodgers and Bland (1996), chronic illness and disability is generally associated with a disease (e.g., multiple sclerosis, cancer, heart disease) or a traumatic injury (e.g., brain or spinal cord injury). These illnesses are also described as either congenital or are acquired after birth, later in life. This paper focuses on the psychosocial adjustment to chronic illness and disability acquired during adulthood.
Table I provides the estimated incidence rate of depression for each chronic illness in this report as provided by Davis and Gershtein (2003) and in Chronic Illness and Depression (2003).
Table I
Chronic Illnesses with Rates of Depression
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Illness Rate of depression
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Chronic fatigue syndrome (CFS) 40%-60%
Heart attack 40%-60%
Multiple sclerosis (MS) 40%-50%
Parkinson’s disease (PD) 40%-50%
Rheumatoid arthritis (RA) 27%
Cancer 25%
Diabetes 25%
Thyroid 24%
Stroke 10%-27%
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In addition to these much higher rates of depression among chronic illness sufferers, data also supports increased severity among this population. In 2005, Dalton and Heinrichs found that more than 50% of MS sufferers had higher levels of depressive symptoms than controls. Rao, Huber and Bornstein (1992) discussed similar findings for suffers of PD. In addition, Feinstein (2004) found that 30% of MS sufferers had experienced suicidal intent and that their suicide rates are 7 times higher than rates in the general population.
It is apparent that depression more greatly affects the chronic illness population. Available research supports the critical role of several variables and factors in this relationship, namely illness intrusiveness, illness uncertainty, and neurological factors. Let us consider each of these variables and factors.
Mullins et al. (2001) defined illness intrusiveness as the extent to which illness adversely impacts valued activities. There are two paths by which illness intrusiveness affects quality of life: by reducing positive experiences due to decreased participation in valued activities, and by reducing perceived control over important outcomes. It has been shown that illness intrusiveness is significantly and uniquely correlated with depressive symptoms, and other quality-of-life measures. This relationship has been shown across a variety of chronic illnesses including end-stage renal disease, MS, RA, diabetes and laryngeal cancer (e.g., Mullins et al., 2001; Devins and Binick, 1996; Devins, Binick, Hutchinson, Hollomby, Barre & Guttman, 1983; Devins, Edworthy, Guthrie & Martin, 1992; Devins, Mandlin, Hons, Burgess, Klassen, Taub, Schorr, Letourneau & Buckle, 1990; Talbot, Nouwen, Gingras, Belanger & Audet, 1999). In fact, in several different studies, researchers found that illness intrusiveness mediates the psychological adjustment to chronic illness. For example, Talbot et al. (1999) found that illness intrusiveness was not only strongly correlated to depressive symptoms in Type 2 diabetes, but that it actually mediated depression. In this study, Talbot et al, found illness intrusiveness had a direct effect on depressive symptoms and an indirect effect mediated by personal control (i.e., perceived internal locus of control). This model accounted for 65% of the variance in depressive symptomology. Devins and colleagues consistently found that illness intrusiveness mediated psychological adjustment to chronic illness (e.g., Devins et al., 1992; Devins et al., 1996). However in several studies, researchers were unable to satisfy the statistical conditions to support that illness intrusiveness serves as a mediator variable for psychological adjustment and depressive symptoms. For example, Mullins et al. (2001) found that illness intrusiveness was significantly correlated to psychological distress, but not to the level to establish intrusiveness as a mediator variable.
A component of illness intrusiveness is the physiological burden chronic illnesses place on individuals. These individuals suffer from symptoms which limit their physical or cognitive abilities and activities, and negatively affect their body image. We would expect to see a strong correlation between higher levels of physical symptoms and higher levels of psychological distress. Generally, research data supports this expectation. In addition to the findings of Talbot et al. (1999), Gatchel (2004) discusses findings that demonstrate a correlation of 0.5 between psychological distress scales and physical symptom measures. He also states that patients with anxiety and depressive disorders have more physical symptoms, and as the number of symptoms increases, so does the occurrence of mood disorders. Guereje, Simon and Von Korff (2001) studied more than 5,000 patients across 15 sites in 14 counties and found that there was a fourfold increase in mood disorders in patients suffering from persistent pain (i.e., more than six months).
Interestingly, there is quite a bit of conflicting data surrounding the hypothesis that physiological symptom severity is correlated with psychological distress. When examining the relationship between disease severity and depression, some studies have shown weak correlation, no correlation or negative correlation. For example, depression severity was found to be lower for individuals with higher rates of disability who suffered from MS (Dalton et al., 2005). Rao et al. (1992) discuss findings for PD, where there was only a modest correlation. Huber, Paulson, & Shuttleworth (1988) found that there was no correlation between disease severity and depression, and Rao et al. (1992) note that investigators have not found a direct relationship between disability (or illness severity) and depression in PD patients.
Researchers have suggested that locus of control and perceived helplessness could help explain this seemingly confusing relationship between disease severity and depression (e.g., Rao et al., 1992; Dalton et al., 2005). However, there does not appear to be definitive data supporting this hypothesis. Chaney et al. (1996) did find that decreased perceptions of daily illness control accentuate the adverse influence of negative event appraisal in patients with RA. They stated, “Our results suggest that emotional adjustment in RA is compromised when individuals simultaneously assume personal responsibility for negative outcomes across a wide variety of life domains (i.e., internal and global attributions) and perceive that they have minimal control over daily aspects of their illness.” However, even though Shnek, Irvine, Stewart, and Abbey (2001) found that helplessness and self-efficacy were significantly associated with depressive symptoms. Neither factor was significantly associated in the final regression analysis. So this complex relationship between disease severity and depression is still not fully understood.
Mullins et al., (2001) defined illness uncertainty as “an individual’s perception of ambiguity around his or her diagnosis, prognosis, relationship with caregivers, a lack of adequate information about one’s illness, and unpredictability of illness course.” Research across a variety of diseases has consistently demonstrated the link between lower levels of psychological adjustment and increased levels of perceived illness uncertainty (Mullins, et al., 1997; Mullins et al., 2001). Mullins et al. (2001) discuss that it was further discovered that the greater the illness uncertainty (in MS), the higher the risk that patients will interpret the effects of their illness as adversely affecting their mood – regardless of their functional abilities. In this study, the cognitive appraisal of illness uncertainty was uniquely and positively correlated to psychological distress. In addition, McNulty, Livneh, and Wilson (2004) write that illness uncertainty was found to be associated with diminished mood and hopefulness. The results of their study indicated that illness uncertainty was uniquely and significantly correlated to overall psychosocial adjustment to chronic illness in MS. Interestingly there is a small amount of conflicting data. When Sanders-Dewey, Mullins, and Chaney studied perceived uncertainty and distress in individuals with PD in 2001, they did not find perceived uncertainty to be a predictor of psychological distress. Their multiple regression analysis found that uncertainty did not make a significant contribution to psychological distress.
There are some unique facets to neurological diseases that warrant discussion. Since these illnesses impact the central nervous system, they may exert an influence over specific brain functions and, therefore, directly impact an individual’s mood. It is interesting to note that emotional disorders have been found to be more common and more severe in neurological illnesses than in illnesses which cause a similar level of disability. Rao et al. (1992) confirmed this assertion for MS and PD patients, and noted that in some cases the depressive episodes occurred prior to an onset of motor symptoms.
Researchers have proposed several different theories to explain this increase in mood disorders for individuals who suffer from neurological conditions. Feinstein (2004) states that MS patients suffering from depression were found to be more likely to have greater hypointense lesion (i.e., larger, dark lesions which indicate significant axonal damage) volume as well as discrete areas of cerebral atrophy. It was found that combining the effects of hypointense lesion load, cerebral atrophy and hyperintense lesions (i.e., newer, smaller lesions) accounted for 40% of depression score variance. However, Rao et al. (1992) describe the results of a study in which the severity of psychiatric morbidity was not significantly correlated to total lesion score. This may be explained by the fact that MS is a subcortical disease that most often involves the frontal lobes. Rodgers (1996) states, these lobes are significantly involved in cognitive, characterological, and affective functioning. Thus damage (e.g., lesions or atrophy) involving the frontal lobes can negatively impact an individual’s mood state.
In the case of PD, there is strong evidence suggesting the PD may be related to serotonin depletion (Rao et al., 1992). Levels of the principal serotogenic metabolite (5-HIAA) have been found to be significantly lower in depressed PD patients compared with non-depressed PD patients. However, research has not clearly demonstrated a strong correlation between severity of depression in PD patients and levels of 5-HIAA, and it is not clear why some PD patients with low levels are not depressed (Rao et al., 1992).
Several approaches to treating depression associated with chronic illness are supported by research. The use of antidepressant medications (e.g., SSRIs) has been found to be effective at reducing depressive symptoms in patients with chronic illness (Cleveland Clinic Health Systems. 2003, Feinstein, 2004 Rao et al, 1992). In addition, psychosocial interventions have also been found to be effective in treating depression and improving patients’ quality of life (QOL). In fact, research has found that psychosocial interventions have the following positive effects on patient suffering from chronic illness: reduction in chronic pain symptoms, lowering distress, reducing stress and cortisol levels, increasing sense of personal control, improving problem-focused coping and sense of efficacy, improved optimism and reduced hopelessness, aided benefit finding and enhanced life meaning, and generally improved QOL. In addition, psychosocial interventions have also been found to have a positive impact on mortality, disease progression and several biological factors associated with improved health (Schneidermann, 2004; Schneidermann, Antoni, Saab, & Ironson, 2001).
Several types of psychosocial interventions have been found to be effective. There is extensive research supporting the efficacy of Cognitive Behavioral Stress Management (CBSM), supportive expressive therapy, existential/experiential therapy, and psychoeducational therapy (Devins et al, 1996; Schneidermann et al, 2001). Interestingly, research does not yet provide strong support for the inclusion of family in psychosocial treatment, even though this approach has face validity (Martire & Schultz, 2007).
Psychosocial interventions found to be effective include individual and group treatment modalities. Individual interventions allow for treatment to be specifically tailored to the individual needs of each patient and for treatment of greater intensity. Group interventions provide patients with context which serves to normalize their experience. The group format also allows patients to learn from each other and benefit from the social support of the other members (Schneidermann et al, 2001).
Overall, there should be no question that depression is more prevalent among individuals who suffer from chronic illnesses. The research data mentioned in this report speak for themselves, and there is no conflict among the research supporting the increased incidence rate. Research also clearly supports the benefits of medication and psychosocial interventions to reduce depressive symptoms, improve mortality rates, slow disease progression, improve several biological factors associated with improved health, and improve overall QOL.
References
Chaney, J. M., Mullins, L. L., Uretsky, D. L., Doppler, M. J., Palmer, W. R., Wees, S. J., et al. (1996). Attributional style and depression in rheumatoid arthritis: The moderating role of perceived illness control. Rehabilitation Psychology, 41(3), 205-223.
Christensen, A. J., Turner, C. W., Smith, T. W., Holman, J. M., Gregory, M. C. (1991). Health locus of control and depression in end-stage renal disease. Journal of Consulting and Clinical Psychology, 59(3), 419-424.
Cleveland Clinic Health Systems. (2003). Chronic illness and depression. Retrieved April 10, 2008 from http://www.cchs.net/health/health-info/docs/2200/2282.asp?index=9288&dpath=http://www.cchs.net/health/health-info/docs/2200/2282.asp?index=9288.
Dalton, E. J. & Heinrichs, R. W. (2005). Depression in multiple sclerosis: A quantitative review of the evidence. Neuropsychology, 19(2), 152-158.
Davis, J. M. & Gershtein, C. M. (2003). Screening for depression in patients with chronic illness: Why and how? Disease Management Health Outcomes, 11(6), 375-378.
Devins, G. M. & Binik, Y. M. (1996). Facilitating coping with chronic physical illness. In M. Zeidner & N. S. Endler (Eds.), Handbook of coping: Theory, research, applications (pp. 640–696). New York: Wiley.
Devins, G. M., Binik, Y. M., Hutchinson, T. A., Hollomby, D. J., Barre, P. E. & Guttmann, R. D. (1983). The emotional impact of end-stage renal disease: Importance of patients' perceptions of intrusiveness and control. International Journal of Psychiatry in Medicine, 13, 327-343.
Devins, G. M., Edworthy, S. M., Guthrie, N. G. & Martin, L. (1992). Illness intrusiveness in rheumatoid arthritis: Differential impact on depressive symptoms over the adult lifespan. Journal of Rheumatology, 19, 709-715.
Devins, G. M., Mandin, H., Hons, R. B., Burgess, E. D., Klassen, J., Taub, K., Schorr, S., Letourneau, P. K. & Buckle, S. (1990). Illness intrusiveness and quality of life in end-stage renal disease. Comparison and stability across treatment modalities. Health Psychology, 9, 117-142.
Feinstein, A. (2004). The neuropsychiatry of multiple sclerosis. Canadian Journal of Psychiatry, 49, 157-163.
Gatchel, R. J. (2004). Comobidity of chronic pain and mental health disorders: The biopsychosocial perspective. American Psychologist, 59(8), 795-805.
Gureje, O., Simon, G. & Von Korff, M. (2001). A cross-national study of the course of persistent pain in primary care. Pain, 92 (1-2), 195-200.
Halligan, F. R., & Reznikoff, M. (1985). Personality factors and change with multiple sclerosis. Journal of Consulting and Clinical Psychology, 53(4), 547-548.
Huber, S.J., Paulson, G.W. & Shuttleworth, E.C. (1988). Depression in Parkinson’s disease. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 1, 47-51.
Livneh, H., & Antonak, R. F. (2005). Psychosocial adaptation to chronic illness and disability: A primer for counselors. Journal of Counseling & Development, 83, 12-19.
Martire, L.M., & Schultz, R. (2007). Involving Family in Psychosocial Interventions for Chronic Illness. Current Directions in Psychological Science, 16(2), 90-94.
McNulty, K., Livneh, H., & Wilson, L. M. (2004). Perceived uncertainty, spiritual well-being, and psychosocial adaptation in individuals with multiple sclerosis. Rehabilitation Psychology, 49(2), 91-99.
Medicenet.com’s MedTerms Medical Dictionary. (n.d.) Retrieved April 10, 2008, from http://www.medterms.com/script/main/hp.asp.
Mullins, L. L., Chaney, J. M., Hartman, V. L., Albin, K., Miles, B. & Roberson, S. (1995). Cognitive and affective features of postpolio syndrome: Illness uncertainty, attributional style, and adaptation. International Journal of Rehabilitation and Health, 1, 211-222.
Mullins, L. L., Chaney, J. M., Pace, T. M. & Hartman, V. L. (1997). Illness uncertainty, attributional style, and psychological adjustment in older adolescents and young adults with asthma. Journal of Pediatric Psychology, 22, 871-880.
Mullins, L. L., Cote, M. P., Fuemmeler, B. F., Jean, V. M., Beatty, W. W., & Paul, R. H. (2001). Illness intrusiveness, uncertainty, and distress in individuals with multiple sclerosis. Rehabilitation Psychology, 46(2), 139-153.
Rao, S. M., Huber, S. J., Bornstein, R. A. (1992). Emotional changes with multiple sclerosis and Parkinson’s disease. Journal of Consulting and Clinical Psychology, 60(3), 369-378.
Rodgers, J., & Bland, R. (1996). Psychiatric manifestations of multiple sclerosis: A review. The Canadian Journal of Psychiatry, 41, 441-445.
Sanders-Dewey, N. E. J., Mullins, L. L., & Chaney, J. M. (2001). Coping style, perceived uncertainty in illness, and distress in individuals with Parkinson’s disease and their caregivers. Rehabilitation Psychology, 46(4), 363-381
Schiaffino, K. M., Shawaryn, M. A., & Blum, D. (1998). Examining the impact of illness representations on psychological adjustment to chronic illnesses. Health Psychology, 17(3), 262-268.
Schneidermann, N. (2004). Psychosocial, behavioral, and Biological Aspects of Chronic Illness. Current Directions in Psychological Science, 13(6), 247-251.
Schneidermann, N., Antoni, M.H., Saab, P.G., & Ironson, G. (2001). Health Psychology: Psychosocial and Biobehavioral Aspects of Chronic Disease Management. Annual Review of Psychology, 52, 555-580.
Shnek, Z. M., Irvine, J., Stewart, D., & Abbey, S. (2001). Psychological factors and depressive symptoms in ischemic heart disease. Health Psychology, 20(2), 141-145.
Talbot, F., Nouwen, A., Gingras, J., Belanger, A., & Audet, J. (1999). Relations of diabetes intrusiveness and personal control to symptoms of depression among adults with diabetes. Health Psychology, 18(5), 537-542.
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