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An integrated model for defining the scope of psychogeriatrics: the five Cs

Published online by Cambridge University Press:  09 June 2009

Joel Sadavoy*
Affiliation:
Professor and Sam and Judy Pencer and Family Chair in Applied General Psychiatry at the University of Toronto, and Head of Geriatric and Community Psychiatry Programs, Mount Sinai Hospital, Toronto, Canada Email: [email protected]
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Extract

Psychogeriatrics is a specialty defined by its many contrasts and complexities. Over-reliance on biological models sometimes artificially narrows the breadth and content of psychogeriatric research, educational programs, service delivery and management models to the detriment of patient care. This guest editorial proposes a conceptual model that defines the scope of the field and provides a structure that overlays standard approaches to diagnosis and formulation. Five key defining elements of psychogeriatrics – the five “Cs” – are explored: complexity, chronicity, comorbidity, continuity and context.

Type
Guest Editorial
Copyright
Copyright © International Psychogeriatric Association 2009

Psychogeriatrics is a specialty defined by its many contrasts and complexities. Over-reliance on biological models sometimes artificially narrows the breadth and content of psychogeriatric research, educational programs, service delivery and management models to the detriment of patient care. This guest editorial proposes a conceptual model that defines the scope of the field and provides a structure that overlays standard approaches to diagnosis and formulation. Five key defining elements of psychogeriatrics – the five “Cs” – are explored: complexity, chronicity, comorbidity, continuity and context.

Complexity

Psychogeriatric practitioners recognize that multiple interacting factors create a complex picture in virtually every case. An illustration of the degree of complexity inherent in psychogeriatrics is the intriguing relationship among life experience, stress, personality and psychological developmental factors, and core physiological and neuropathological processes. An array of relatively recent data supports the importance of refining a “complex model” of formulation and intervention which may be especially relevant to the elderly.

Old age is inevitably associated with various stressful life events and it is well recognized that many elders become depressed under their impact. Despite the fact that depression is arguably the most common psychiatric disturbance of old age I suggest that it is surprisingly uncommon, when one considers the array of challenges posed by old age. Because the majority of elders do not become depressed, it stands to reason that the stressors associated with aging only induce depression if mediated by other vulnerability factors in a given individual. The data suggest that these factors include the complex interplay of three key elements that appear to mediate increased vulnerability to depressive symptoms: physiological and immunological reactions, personality structure, and early psychological development.

Stress has wide ranging physiological and immunological effects on the vulnerable body. Mood disorders, closely associated with stress, also are associated with increased allostatic load including increased adrenocortical activity, raised concentrations of insulin growth factor (IGF)-1, initiation of the inflammatory response, impaired immunity, induction of arteriosclerosis, increased obesity, bone demineralization, and atrophy of brain cells (McEwen, Reference McEwen2004). Animal data suggest that stress-mediated alterations in brain-derived neurotrophic and corticotropin releasing factors may also be associated with major depressive disorder and anxiety (Anisman, Reference Anisman2009). A particularly interesting line of investigation that has the potential to integrate links among personality, physiology and psychopathology is the association of depression with elevated serum pro-inflammatory cytokine levels (especially interleukin-1β, interleukin-6, tumour necrosis factor- α and interferon-α) (Brebner et al., Reference Brebner, Hayley, Zacharko, Merali and Anisman2000; Anisman, Reference Anisman2009).

There is reason to be particularly concerned about the vulnerability of elders to cytokine activity and immunological factors. Cytokines are stimulated not only by stress but also by inflammatory disorders and diseases especially common in elders including cardiovascular disease, osteoporosis, arthritis, type 2 diabetes, various cancers, lymphoproliferative diseases, Alzheimer's disease and some treatments such as interferon in cancer (Anisman et al., Reference Anisman, Merali and Hayley2008; Dantzer and Kelly, Reference Dantzer and Kelley2007; Konsman et al., Reference Konsman, Parnet and Dantzer2002). Depression is associated with increased cardiovascular disease, although the underlying mechanisms are not well understood. Inflammatory markers such as interleukin 6 and C-reactive protein are associated with age and predict functional decline, mortality, decreased functional status, and disability (Hamerman et al., Reference Hamerman1999; Currie et al., Reference Currie, Rao, Blazer and Cohen1994; Cohen et al., Reference Cohen1997; Pieper et al., Reference Pieper2000; Ferrucci et al., Reference Ferrucci1999; Harris et al., Reference Harris1999). Distress or depression seems to be associated with greater immunological impairments in older adults (Graham et al., Reference Graham, Christian and Kiecolt-Glaser2006; Kiecolt-Glaser et al., Reference Kiecolt-Glaser, Preacher, MacCallum, Atkinson, Malarkey and Glaser2003). IL-6 may be a marker for impending deterioration in health status in older adults and IL-6 levels increase with age (Ferrucci et al., Reference Ferrucci1999). Aging spousal caregivers of individuals with Alzheimer's disease are at greater risk of impaired immunological function particularly if they have poor levels of social support (Kiecolt-Glaser et al., Reference Kiecolt-Glaser, Dura, Speicher, Trask and Glaser1991; Bauer et al., Reference Bauer, Vedhara, Perks, Wilcock, Lightman and Shanks2000).

Beyond depression and stress per se, there is an association between elevated cytokine levels and personality traits that predispose to negative emotional states such as pessimism, sense of meaninglessness and negative self perceptions (Kiecolt-Glaser et al., Reference Kiecolt-Glaser2002; Maruta et al., Reference Maruta2000). The mechanism of how a personality-emotion-immune interaction works is not entirely clear yet but some data support the hypothesis that personality structure may predispose an individual to greater relative positive or negative emotions including depression, which in turn influence immune function reflected in immune cell counts in peripheral blood (Segerstrom, Reference Segerstrom2000). For example, one personality factor that is associated with negative emotional states and that may be particularly important in predicting late-onset depression is sociotropy, defined as an unusual need for approval and reassurance in interpersonal relationships. This trait combined with negative interpersonal events, poorer physical functioning and medical illness has been found to be a primary predictive factor for late life depression (Mazure et al., Reference Mazure, Maciejewski, Jacobs and Bruce2002).

Data from other studies help further specify the nature of these positive and negative emotional states. Positive emotions that may be an indicator of resilience in the face of stress and adversity include the following: the ability to make a positive reappraisal of stressful life experiences and to find meaning in life and events, developing positive illusions about the self and situational optimism (Maruta et al., Reference Maruta2000). Some have hypothesized that these characteristics can have a positive effect on health outcomes possibly mediated through endocrine and immune mechanisms (Kiecolt-Glaser et al., Reference Kiecolt-Glaser2002). Conversely, data support the contention that pessimism (vs. optimism) may predict physical illness and mortality in initially healthy adults (Maruta et al., Reference Maruta2000).

Taken together this research suggests a model of depression based on a highly complex feedback system in which negative emotional states associated with less adaptive personality structures induce physiological and neuroimmunological changes that in turn further exacerbate the negative emotional states. A complex cascade can now be hypothesized for late life depression as follows: elders are at risk of depressive symptoms when stress – i.e. their environment, illness or life events – interact with personality-based vulnerabilities to induce negative emotions causing demoralization and fear. In turn, these emotional states alter immune responses to produce proinflammatory changes that raise cytokine levels and induce depressive symptoms. Alternatively or concurrently, certain illnesses like diabetes or heart disease (Anisman, Reference Anisman2009) may themselves be both pro-inflammatory (raising cytokines) and inducing negative emotional states which then go on to auto-induce further depression.

This growing array of data illustrates how important it is to consider complexity when clinically evaluating depressive symptoms in elders. Training and practice must adapt current diagnostic systems to capture the full array of complex elements which the psychogeriatrician must address in each case, i.e. personality and development, physical health, psycho-neuroimmunological function, and sources and psychological impact of stress.

Chronicity

Old age is characterized both by longstanding problems and by diseases which, once they start in old age, often become chronic. The line between acute reversible illness and chronic irreversible illness is often blurred in elders, as illustrated by this clinical vignette.

A 78-year-old man was referred for management of unresolved grief following his wife's death. Examination revealed mild impairments in memory and some personality changes. From being a dominant rather aggressive business man he had become uncertain, worried and vulnerable. He spoke of mild, but clearly perceptible, subjective problems in recent memory, concentrating on complex business matters that he had handled easily in the past, and very occasional lapses of orientation when driving for which he could compensate with effort. Formal mental status testing showed mild memory and some mild executive dysfunction which did not cross the threshold for dementia. However, these symptoms pointed to early cognitive decline and a diagnosis of mild cognitive impairment of uncertain origin. If the diagnosis was accurate the likelihood was that he would progress to some form of dementia. In other words, this patient, while referred for an acute depressive response to a life event, had concurrently entered the domain of chronic and incurable illness.

Dementia is an obvious example of chronicity, but there are other less obvious pathways to chronic illness in elders, for example anxiety. Schuurmans et al. (Reference Schuurmans2005) reported that, after six years of follow-up, about 70% of geriatric patients continued to meet criteria for full-blown or subsyndromal anxiety disorder. Chronic anxiety in elders has important implications, including increased disability and mortality rates, impaired quality of life and psychosocial functioning (de Beurs et al., Reference de Beurs1999; Beekman et al., Reference Beekman, Copeland and Prince1999; Wetherell et al., Reference Wetherell, Thorp, Patterson, Golshan, Jeste and Gatz2004; van Hout et al., Reference van Hout2004). Depression in late life often has a prolonged course and variable treatment outcome in late life. Clinicians are given conflicting guidelines on how long to continue maintenance therapy which for some elders can be very prolonged. For example, Reynolds et al. (Reference Reynolds2006) found that at least a two-year maintenance period is important to prevent relapse.

While chronicity is obviously an important consideration in many patients our clinical and research paradigms generally do not systematically address its key components such as suffering or demoralization. Chronic illness implies chronic suffering that arises especially from conditions that induce demoralization and hopelessness, anxiety, withdrawal and loneliness. These emotional reactions often do not reach thresholds for DSM diagnosis but represent significant burden. The rather abstract and philosophical nature of suffering makes it difficult to operationalize, but it is important to be able to measure suffering if we are to address it. Attempts have been made to do so. Gurland et al. (Reference Gurland, Katz and Chen1997), for example, developed the Index of Affective Suffering, a scale that measures subjective symptom severity which is highly relevant to chronic illness. The elements of the index include “intensity” and “extensity” of distress (including number and variety of life events, duration and frequency of episodes, and activities that are pervaded by distress). The scale defines levels of severity: Minor/moody, Background, Dominant, Desperate, Intolerable. It is notable that the discourse and focus of this scale differ from the phenomenologically based discourse of the standard diagnostic manuals.

Chronicity raises many therapeutic questions such as how long should the patient be followed, what is the best array of treatments to produce continued improvement in a given condition, which symptoms can be treated and which are unlikely to change? By adding the perspective of chronicity to clinical formulations important practical implications emerge. For example, chronicity redefines criteria and measures of outcomes of intervention, such as degree of amelioration of suffering in addition to symptom relief.

To incorporate chronicity systematically into routine clinical practice and formulation means adding some concepts and practices to training programs and recognizing that many training programs are not well designed to teach about chronicity. For example, supervisors will readily recognize that training rotations often are of short duration and follow-up of patients after initial evaluation is often inconsistent or non-existent. Because of relatively short rotations on a given service, medical residents of various specialties trained in North American programs often get experience in initiating treatment but disturbingly little experience in maintaining and adjusting it. Psychogeriatric training requires a stronger emphasis on monitoring, adjusting and integrating interventions over time.

Psychogeriatric clinical training also needs to address the professional's reactions to confronting chronicity. If, in the face of chronic illness, one loses hope or is intolerant of dealing with problems that cannot be cured but only endured, then there is a danger of favoring dealing with problems cross-sectionally or focusing only on symptoms that can be cured rather than those to which one must adapt. In doing this clinicians are in danger of abandoning many patients to their suffering.

Redefinition of psychogeriatric models that takes chronicity into account requires a more refined evidence-base for the management of chronicity to improve treatment and service delivery models and research design. Table 1 outlines the key elements of such a model.

Table 1. The key elements in the management of chronicity to improve treatment and service delivery

Comorbidity

Psychogeriatric clinical care is characterized by multiple interacting concurrent illnesses and treatment modalities. This truth becomes evident from the epidemiology of psychogeriatric disorders. The greatest prevalence of mental disorders in the elderly is found in medical clinics and hospitals. Comorbidity is illustrated by looking at rates of depression in various medical settings and disease associations as illustrated in Table 2.

Table 2. Rates of comorbid depression in various settings and diseases

MD = major depression; CVA = cerebrovascular accident.

Sources: Table from Sadavoy, Reference Sadavoy2004. See also Cummings and Masterman, Reference Cummings and Masterman1999; Lyketsos et al., Reference Lyketsos2000; Devanand, Reference Devanand1997; Harwood et al., Reference Harwood, Barker, Ownby and Duara1999.

Not all comorbidity is alike or has a significant impact on elders. For example, Oslin et al. (Reference Oslin, Datto, Kallan, Katz, Edell and ten Have2002) suggested that chronic illnesses which produce functional decline or disability are the most likely form of comorbidty to negatively affect the treatment and outcome of depression. Arthritis is particularly implicated. Conversely, depression can lead to poorer outcomes for specific chronic medical disorders such as diabetes mellitus and myocardial infarction, although the mechanisms are not clear, perhaps related to poor self care, nutrition and adherence (Oslin et al., Reference Oslin, Datto, Kallan, Katz, Edell and ten Have2002). A similar conclusion can be derived from the work of Rovner et al. (Reference Rovner, Casten, Hegel, Hauck and Tasman2007) whose results suggest that the psychological impact of macular degeneration varies according to the meaning and import of the visual decline on the aging person.

The nature of depression associated with disability is perhaps best understood as demoralization (as opposed to depressive disorder) and, as noted earlier, may be most appropriately characterized by the level of affective suffering rather than the diagnostic category or symptom profile. This position is supported by the work of Newmann et al. (Reference Newmann, Klein, Jensen and Essex1996) who examined the results obtained by using different measures of depression. They suggested that depressive symptom scales produce two groups of depressive symptoms: a “depressive syndrome” which is less common in the elderly and a “depletion syndrome” which is more common. The depletion syndrome is characterized by loneliness, lack of energy and sleep disturbance. Flint (Reference Flint2002) incorporates this type of thinking when he suggests that a dimensional rather than a categorical threshold is a better model for describing depressive symptoms in elders and that a dimensional approach may provide a “framework for studying the complex interactions between depression, anxiety, medical illness, cognitive impairment, personality factors and life stress.” If this is true then treatment, at a minimum, likely requires both somatic therapy and psychotherapy to restore self esteem, find adaptive solutions, reestablish sense of mastery or control and help preserve engagement. Incorporating comorbidity into the formulation requires tailoring of educational programs to help students learn how to assess comorbidity and intervene in a specific fashion, including appropriate integration of consultative and support disciplines. The elements of comorbidity define the reciprocal importance of the comorbid condition in the production and treatment of psychogeriatric disorders and the impact of psychogeriatric disorders on treatment of comorbid conditions. Factors relevant to comorbidity in psychogeriatric clinical, educational and research practice are summarized in Table 3.

Table 3. Factors relevant to comorbidity

Continuity

Continuity, as it is used here, refers to the concept that each elderly person is the product of the lifelong cumulative effect of their environmental, psychological and physiological development. Every aged person brings into old age the legacy of their lifestyle, capacity for forming and maintaining relationships, genetic vulnerabilities, physical makeup and illnesses. Of particular importance are factors of psychological development and continuity. For example, personality evolves from the earliest childhood experiences and remains remarkably stable into old age, although certain traits may evolve as the individual adapts to contextual and interpersonal forces associated with aging (Roberts et al., Reference Roberts, Walton and Viechtbauer2006). The unconscious is commonly referred to as timeless and endures, albeit somewhat modified, into old age. Psychogeriatricians, to be most effective, must be alert to the influence of these lifelong factors on psychogeriatric illnesses and the capacity of the patient to adapt to late life illnesses without undue or overwhelming anxiety or depression. Moreover, personality traits such as conscientiousness, activity and emotional stability appear to have a direct impact not only on the capacity to adapt to aging but to longevity itself (Terracciano et al., Reference Terracciano, Löckenhoff, Zonderman, Ferrucci and Costa2008).

For example, a 68-year-old woman was referred for depression which developed after somewhat mutilating cancer surgery. On first impression, her symptoms were understandable as a reaction to a significant life stress. However, her intent in seeking out treatment was more subtle. First, she had a difficult time during the lead-up to and following her surgery especially associated with rather callous handling by one of her physicians. This experience in turn was associated with the quite sudden reemergence of long dormant memories of severe physical and emotional abuse at the hands of her parents leading to some depressive symptoms but, more importantly, to the return of severe post-traumatic stress disorder symptoms that had been well controlled through her adult life. The psychodynamics are complex, but the vignette succinctly illustrates the crucial importance of a longitudinal perspective on careful evaluation of the patient with attention to understanding the continuity of each patient's life and incorporating it into the therapeutic frame.

Personality-based factors have demonstrable impact on treatment outcome. Data suggest that personality disorders (PD) negatively impact the effectiveness of treatment (Karp et al., Reference Karp1993; Thompson et al., Reference Thompson, Gallagher and Czirr1988) and personality disorders contribute to functional disability after antidepressant treatment (Abrams et al., Reference Abrams1998). Cluster C personality disorders, i.e. avoidant, dependent, obsessive-compulsive, and self-defeating types, have been associated with less stable remission and with a slower response time to therapy (15 versus 10 weeks) (Morse et al., Reference Morse, Pilkonis, Houck, Frank and Reynolds2005).

To operationalize the concept of psychological continuity in the elderly requires training in how to acquire the data and techniques for using it. Table 4 presents an outline of elements to be assessed in the evaluation of continuity factors, while Table 5 presents elements that can help to operationalize continuity into psychogeriatric practice.

Table 4. Elements to be assessed in the evaluation of continuity factors

Table 5. Elements that can help to operationalize continuity into psychogeriatric practice

Context

Psychiatric illness and psychological disturbances in old age cannot be separated from the physical, psychological, social and environmental context within which that illness emerges. For example, while grief is an almost universal experience, the context of the grief can modify its expression. Aberrant grief is more likely to emerge if the loss occurs in the context of a prior psychologically conflicted relationship with the lost person associated with insecure attachment patterns in the bereaved (Shear and Shair, Reference Shear and Shair2005). Such reactions may not be responsive to medication and often do not resolve simply with the passage of time, as does normal grief.

Environmental, social and physical contexts interact and different settings such as community, long-term care or an acute care hospital each imply different management issues and outcome profiles. An example would be the patient who developed a paranoid state in a long-term care (LTC) home and began to refuse clinical care leading to loss of diabetes control. In the general hospital the very rapid evaluation and management of physically ill elders may place the psychogeriatric patient at particular risk of being misdiagnosed and inappropriately treated. For example, an elderly man developed a clear delirium associated with pneumonia. The physician, who knew very little about the patient's prior state and life, insisted that there was no need to investigate the acute change in the patient's mental state stating that it was dementia that was being uncovered by the move to the hospital. Instead of investigating the delirium, this precipitous and wrong diagnosis led him to ask that an application to a LTC facility be initiated. Occupational and other key functions, such as driving, impact the context of illness in the elders: for example, the dementing surgeon who had to be compelled to stop practicing while helping him and his family to face giving up the career satisfaction, money, prestige and security that went with his high profile career. Table 6 lists key contextual issues to be considered in psychogeriatric formulation.

Table 6. Contextual issues

Conclusion

The practice of psychogeriatrics includes, but extends far beyond, the narrow confines of neuropsychiatry. Clinical models of effective diagnosis and management must be comprehensive and of broad enough scope to encompass all the factors that affect assessment, treatment and outcome. While the models used for general adults are often useful for elders they are also incomplete in defining the complexities that are especially relevant to clinical interventions for the elderly. In this guest editorial I have tried to expand these models by suggesting a more comprehensive approach which I believe is practical and can be operationalized and incorporated into training and clinical practice. This model suggests a matrix approach. Along one axis are the standard phenomenological diagnostic elements while along the other are the factors that elaborate special essential elements associated with the elderly – the five Cs of psychogeriatrics.

References

Abrams, R. C. et al. (1998). Personality disorder symptoms and functioning in elderly depressed patients. American Journal of Geriatric Psychiatry, 6, 2430.Google Scholar
Alexopoulos, G. S., Kiosses, D. N., Murphy, C. and Heo, M. (2004). Executive dysfunction, heart disease burden, and remission of geriatric depression. Neuropsychopharmacology, 29, 22782284.Google Scholar
Anisman, H. (2009). Cascading effects of stressors and inflammatory immune system activation: implications for major depressive disorder. Journal of Psychiatry and Neuroscience, 34, 420.Google ScholarPubMed
Anisman, H., Merali, Z. and Hayley, S. (2008). Neurotransmitter, peptide and cytokine processes in relation to depressive disorder: comorbidity between depression and neurodegenerative disorders. Progress in Neurobiology, 85, 174.Google Scholar
Bauer, M. E., Vedhara, K., Perks, P., Wilcock, G. K., Lightman, S. L. and Shanks, N. (2000). Chronic stress in caregivers of dementia patients is associated with reduced lymphocyte sensitivity to glucocorticoids. Journal of Neuroimmunology, 103, 8492.Google Scholar
Beekman, A. T. F., Copeland, J. R. M. and Prince, M. J. (1999). Review of community prevalence of depression in later life. British Journal of Psychiatry, 174, 307311.Google Scholar
Brebner, K., Hayley, S., Zacharko, R., Merali, Z. and Anisman, H. (2000). Synergistic effects of interleukin-1, interleukin-6, and tumor necrosis factor: central monoamine, corticosterone, and behavioral variations. Neuropsychopharmacology, 22, 566580.Google Scholar
Cohen, H. J. et al. (1997). The association of plasma interleukin-6 levels with functional disability in community-dwelling elderly. Journal of Gerontology: Medical Science, 52A, M201M208.Google Scholar
Cui, X., Lyness, J., Tang, W., Tu, X. and Conwell, Y. (2008). Outcomes and predictors of late-life depression trajectories in older primary care patients. American Journal of Geriatric Psychiatry, 16, 406415.Google Scholar
Cummings, J. L. and Masterman, D. L. (1999). Depression in patients with Parkinson's disease. International Journal of Geriatric Psychiatry, 14, 711718.Google Scholar
Currie, M. S., Rao, K. M. K., Blazer, D. G., and Cohen, H. J. (1994). Age and functional correlations of markers of coagulation and inflammation in the elderly – functional implications of elevated cross linked fibrin degradation products (D-dimers). Journal of the American Geriatrics Society, 42, 738742.Google Scholar
Dantzer, R. and Kelley, K. W. (2007).Twenty years of research on cytokine-induced sickness behavior. Brain, Behavior and Immunity, 21, 153160.CrossRefGoogle ScholarPubMed
de Beurs, E. et al. (1999). Consequences of anxiety in older persons: its effect on disability, well-being and use of health services. Psychological Medicine, 29, 583593.CrossRefGoogle ScholarPubMed
Devanand, D. P. et al. (1997). The course of psychopathologic features in mild to moderate Alzheimer disease. Archives of General Psychiatry, 54, 257263.Google Scholar
Ferrucci, L. et al. (1999). Serum IL-6 level and the development of disability in older persons. Journal of the American Geriatrics Society, 47, 639646.Google Scholar
Flint, A. (2002). The complexity and challenge of non-major depression in late life. American Journal of Geriatric Psychiatry, 10, 229232.CrossRefGoogle ScholarPubMed
Gitlin, L. N. et al. (2003). Effect of multicomponent interventions on caregiver burden and depression: the REACH multisite initiative at 6-month follow-up. Psychology and Aging, 18, 361374.Google Scholar
Graham, J. E., Christian, L. M. and Kiecolt-Glaser, J. K. (2006). Stress, age, and immune function: toward a lifespan approach. Journal of Behavioral Medicine, 29, 389400.CrossRefGoogle Scholar
Gurland, B. J., Katz, S. and Chen, J. (1997). Index of affective suffering: linking a classification of depressed mood to impairment in quality of life. American Journal of Geriatric Psychiatry, 5, 192210.CrossRefGoogle ScholarPubMed
Hamerman, D. et al. (1999). Emerging evidence for inflammation in conditions frequently affecting older adults: report of a symposium. Journal of the American Geriatrics Society, 47, 10161025.CrossRefGoogle Scholar
Harris, T. B. et al. (1999). Associations of elevated interleukin-6 and C-reactive protein levels with mortality in the elderly. American Journal of Medicine, 106, 506512.CrossRefGoogle ScholarPubMed
Harwood, D. G., Barker, W. W., Ownby, R. L. and Duara, R. (1999). Association between premorbid history of depression and current depression in Alzheimer's disease. Journal of Geriatric Psychiatry and Neurology, 12, 7275.CrossRefGoogle ScholarPubMed
Kalayam, B. and Alexopoulos, G. (1999). Prefrontal dysfunction and treatment response in geriatric depression. Archives of General Psychiatry, 56, 713–18.Google Scholar
Karp, J. F. et al. (1993). Time-to-remission in late-life depression: analysis of effects of demographic, treatment, and life-events measures. Depression, 1, 250256.CrossRefGoogle Scholar
Kiecolt-Glaser, J. K., Dura, J. R., Speicher, C. E., Trask, O. J. and Glaser, R. (1991). Spousal caregivers of dementia victims: longitudinal changes in immunity and health. Psychosomatic Medicine, 53, 345362.Google Scholar
Kiecolt-Glaser, J. et al. (2002). Emotions, morbidity, and mortality: new perspectives from psychoneuroimmunology. Annual Review of Psychology, 53, 83107.CrossRefGoogle ScholarPubMed
Kiecolt-Glaser, J. K., Preacher, K. J., MacCallum, R. C., Atkinson, C., Malarkey, W. B. and Glaser, R. (2003). Chronic stress and age-related increases in the proinflammatory cytokine IL-6. Proceedings of the National Academy of Science, 100, 90909095.Google Scholar
Konsman, J. P., Parnet, P. and Dantzer, R. (2002). Cytokine-induced sickness behaviour: mechanisms and implications. Trends in Neurosciences, 25, 154159.Google Scholar
Lyketsos, C. G. et al. (2000). Mental and behavioral disturbances in dementia: findings from the Cache County Study on memory in aging. American Journal of Psychiatry, 157, 708714.CrossRefGoogle Scholar
Maruta, T. et al. (2000). Optimists vs. pessimists: survival rate among medical patients over a 30-year period. Mayo Clinic Proceedings, 75, 140143.CrossRefGoogle Scholar
Mazure, C., Maciejewski, P. K., Jacobs, S. C. and Bruce, M. L. (2002). Stressful life events interacting with cognitive/personality styles to predict late-onset major depression. American Journal of Geriatric Psychiatry, 10, 297304.CrossRefGoogle ScholarPubMed
McEwen, B. S. (2004). Protection and damage from acute and chronic stress: allostasis and allostatic overload and relevance to the pathophysiology of psychiatric disorders. Annals of the New York Academy of Science, 1032, 17.Google Scholar
Mittelman, M., Brodaty, H., Wallen, A. and Burns, A. (2008). A three-country randomized controlled trial of a psychosocial intervention for caregivers combined with pharmacological treatment for patients with Alzheimer disease: effects on caregiver depression. American Journal of Geriatric Psychiatry, 16, 893904.CrossRefGoogle ScholarPubMed
Morse, J., Pilkonis, P., Houck, P., Frank, E. and Reynolds, C. (2005). Impact of Cluster C personality disorders on outcomes of acute and maintenance treatment in late-life depression. American Journal of Geriatric Psychiatry, 13, 808814.CrossRefGoogle ScholarPubMed
Newmann, J. P., Klein, M., Jensen, J. E. and Essex, M. J. (1996). Depressive symptom experiences among older women: a comparison of alternative measurement approaches. Psychology and Aging, 11, 112126.Google Scholar
Oslin, D., Datto, C., Kallan, M., Katz, I., Edell, W. and ten Have, T. (2002). Association between medical comorbidity and treatment outcomes in late-life depression. Journal of the American Geriatrics Society, 50, 823828.CrossRefGoogle ScholarPubMed
Pieper, C. F. et al. (2000). Age, functional status and racial differences in plasma D-dimer levels in community-dwelling elders. Journal of Gerontology: Medical Science, 55A, M649M657.Google Scholar
Reynolds, C. et al. (2006). Maintenance treatment of major depression in old age. New England Journal of Medicine, 354, 11301138.Google Scholar
Roberts, B., Walton, K. and Viechtbauer, W. (2006). Patterns of mean-level change in personality traits across the life course: a meta-analysis of longitudinal studies. Psychological Bulletin, 132, 125.CrossRefGoogle ScholarPubMed
Rovner, B. W., Casten, R. J., Hegel, M. T., Hauck, W. W. and Tasman, W. S. (2007). Dissatisfaction with performance of valued activities predicts depression in age-related macular degeneration. International Journal of Geriatric Psychiatry, 22, 789931.Google Scholar
Sadavoy, J. (2004). Psychotropic Drugs and the Elderly: Fast Facts. New York: WW Norton.Google Scholar
Sadavoy, J. and Sadavoy, S. (2006) Friendship in old age. In Cohen, R., Pollack, G. and Schulman, R. (eds.), Friends and Friendship. Madison, CT: Psychosocial Press.Google Scholar
Schuurmans, J. et al. (2005). The outcome of anxiety disorders in older people at 6-year follow-up: results from the Longitudinal Aging Study Amsterdam. Acta Psychiatrica Scandinavica, 111, 420428.CrossRefGoogle ScholarPubMed
Segerstrom, S. C. (2000). Personality and the immune system: models, methods, and mechanisms. Annals of Behavioral Medicine, 22, 180190.CrossRefGoogle ScholarPubMed
Shear, K. and Shair, H. (2005). Attachment, loss, and complicated grief. Developments in Psychobiology, 47, 253267.Google Scholar
Stroebe, M., Schut, H. and Stroebe, W. (2007). Health outcomes of bereavement. Lancet, 370, 9603.Google Scholar
Terracciano, A., Löckenhoff, C., Zonderman, A., Ferrucci, L. and Costa, P. (2008) Personality predictors of longevity: activity, emotional stability, and conscientiousness. Psychosomatic Medicine, 70, 621627.CrossRefGoogle ScholarPubMed
Thompson, L. W., Gallagher, D. and Czirr, R. (1988). Personality disorder and outcome in the treatment of late-life depression. Journal of Geriatric Psychiatry, 21, 133153.Google ScholarPubMed
van Hout, H. P. et al. (2004). Anxiety and the risk of death in older men and women. British Journal of Psychiatry, 185, 399404.CrossRefGoogle ScholarPubMed
Wetherell, J. L., Thorp, S. R., Patterson, T. L., Golshan, S., Jeste, D. V. and Gatz, M. (2004). Quality of life in geriatric generalized anxiety disorder: a preliminary investigation. Journal of Psychiatric Research, 38, 305312.Google Scholar
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Table 1. The key elements in the management of chronicity to improve treatment and service delivery

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Table 2. Rates of comorbid depression in various settings and diseases

Figure 2

Table 3. Factors relevant to comorbidity

Figure 3

Table 4. Elements to be assessed in the evaluation of continuity factors

Figure 4

Table 5. Elements that can help to operationalize continuity into psychogeriatric practice

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Table 6. Contextual issues