Living with dialysis : patients' perceptions and outcomes
Thong, M.S.Y.
Citation
Thong, M. S. Y. (2009, February 26). Living with dialysis : patients' perceptions and outcomes.
Retrieved from https://hdl.handle.net/1887/13526
Version: Corrected Publisher’s Version
License: Licence agreement concerning inclusion of doctoral thesis in the Institutional Repository of the University of Leiden
Downloaded from: https://hdl.handle.net/1887/13526
Note: To cite this publication please use the final published version (if applicable).
1
General introduction
The physician should look upon the patient as a besieged city and try to rescue him with every means that art and science place at his command
-Alexander of Tralles (c.525-c.605)-
10
END-STAGE RENAL DISEASE
For patients with end-stage renal disease (ESRD), the need to start renal replacement therapy to prolong life represents the final stage of living with a progressive chronic illness. The annual growth in the number of ESRD patients receiving treatment is approximately 7%.1 By the end of 2005, there was an estimated 1.9 million ESRD patients worldwide receiving some form of renal replacement therapy.1 This figure is predicted to increase considerably, mainly contributed by an aging population and the rising incidence of diabetes worldwide.2-8
This trend is similarly reflected in the Netherlands. Between 1990 and 2005, the total number of newly diagnosed ESRD patients rose from 1,005 to 1,584, representing a 58% increase.9 The greatest increase of newly diagnosed ESRD patients was in the age group ≥65 years, which rose from 362 (36%) in 1990 to 842 (53%) in 2005. Diabetes was the largest identified cause of renal failure in the Netherlands.10
RENAL REPLACEMENT THERAPY
Current available treatment options for ESRD include renal transplantation, haemodialysis (HD), and peritoneal dialysis (PD). Due to a shortage of donors and the associated side effects of transplantation, dialysis is the prescribed treatment for the majority of ESRD patients. Of the 1.9 million ESRD patients treated worldwide, approximately 80% receive dialysis, with the remaining 20% receiving transplantation.1
Globally, HD is the most prevalent dialysis modality.11 With HD, waste products accumulated in the blood are removed via an artificial dialyser connected to a fistula fitted in the patients’
forearm. Treatment is usually conducted at an in-hospital dialysis unit, where attendance 3 times a week for up to 4 hours per visit is the norm.
Patients on PD can self-dialyse at home with regular infusions of sterile dialysis solution into the peritoneal cavity, thus offering greater flexibility and privacy for patients.
With its technological improvements over the last four decades, dialysis treatments are now viable even for the elderly and those with comorbid diseases.4;12;13 Nevertheless, mortality rate among dialysis patients in Europe and the US remains high at 10-20% annually, even after
11 adjustment for age, sex, and primary diagnosis.10;14 The Netherlands has a comparable mortality rate of 19%.9
HEALTH-RELATED QUALITY OF LIFE (HRQL)
Although improving survival of patients on dialysis is paramount, clinicians now also recognise the importance of assessing the quality of this survival. Patients on dialysis are wholly dependent on a machine for their survival. Despite its lifesaving qualities, dialysis treatment is time- consuming, intrusive and can be burdensome for patients.15 Therefore, patients’ perceptions of the impact of dialysis on the quality of their remaining life is also an important consideration when providing care.
Compared with the general population, dialysis patients consistently perceive themselves as having a poor health-related quality of life (HRQL), in particular the dimension of physical functioning.16;17 Reduced physical functioning can compromise employment opportunities, and participation in social and leisure activities, resulting in poorer HRQL and higher risk of mortality.18-22 Poorer HRQL could increase mortality risk through poorer adherence to the strict dietary and medical regiments of dialysis.23
In clinical practice, the focus is to optimise parameters of clinical variables to achieve better HRQL in dialysis patients. Some studies suggest that the management of anaemia with recombinant human erythropoietin 24;25 and improving nutritional status by increasing the serum albumin levels of dialysis patients 26 have been associated with improved HRQL. In general, however, observational studies have shown weak or no support of associations between clinical variables with HRQL of dialysis patients.27-30 Although this poor association between clinical variables and HRQL is gaining recognition in clinical practice, the understanding of this phenomenon is still far from clear.
THEORETICAL MODELS
BIOPSYCHOSOCIAL MODEL
Renal medicine, as medicine in general, tends to be dominated by the biomedical model. In reaction to what he considered the inadequacy of the biomedical to include the patient and
12
his/her attributes as a person as the central focus of study,Engel proposed as an alternative, the biopsychosocial model.31 In this model, social and psychological factors are explicitly incorporated into research and clinical care for patients with physical disorders. Interactions run both ways from cell to society and from society to cell, with the person/patient in the central position (Figure 1). In this thesis, the empirical studies clearly belong in the domain of the biopsychosocial model as outlined by Engel.
EXPLANATORY MODELS
While patients’ stories of their illness complaints and symptoms have time and again fascinated clinicians, this fascination is often coupled with some perplexity as clinicians note discrepancies between these ‘idiosyncratic’ stories of patients on the one hand and ‘scientific, objective’
medical or behavioural explanations on the other. For instance, a clinician might be at a loss to explain a patient’s complaints of uraemic symptoms such as itch, muscles cramps and fatigue even though clinical indicators suggest that this patient is receiving optimal dialysis. At the same time, social scientists regard these discrepancies between the subjective and objective narrations of disease a rich source of research opportunities. By exploring patients’ (and healthy persons’) explanations of their illnesses and complaints, social scientists aim at understanding the motivations underlying patients’ subsequent behaviour. Illness representations (or illness perceptions) and explanatory models are two major concepts explored in this research.32 As illness perceptions form the conceptual framework of this thesis, it will be discussed in depth further in this chapter. Briefly, an explanatory model refers to the notions that patients and those in their social environment have about a specific illness episode. According to Kleinman,
“…these informal descriptions of [the illness] have enormous clinical significance [and] to ignore them may be fatal. Explanatory models are responses to urgent life circumstances. Thus, they are justifications for practical action more than statements of a theoretical and rigorous nature”
(1988, p. 121)33
Persons diagnosed with ESRD become patients with a serious life-threatening illness, and these persons/patients make sense of ESRD and its impact by telling stories of the illness to themselves and to relevant persons around them. These stories or explanatory models are not vague, ‘unscientific’ or to be dismissed.34 Instead, stories of illness are representations of the identity, causes, course, consequences and timeline of a given symptom or illness congruent to a patient. In turn, these representations or illness perceptions determine the actions of a patient regarding that symptom or illness.35,36 Only having made sense of the illness, can a patient start adapting to the illness, its treatment and its consequences.
13 SELF-REGULATION MODEL
Beginning in 1956 with Bard & Dyk 37 interviews with patients regarding their stories or narratives on the causes of their illness have been published. In 2006 Broadbent et al38 published the Brief Illness Perception Questionnaire (B-IPQ) comprising of eight questions assessing various dimensions in the stories of how patients make sense of their illness. In these 50 years, scientists from the biomedical and behavioural domains have developed models and various instruments to assess the stories of patients. One of the most influential models, the Common Sense Model of self-regulation, also known as the Self-Regulation Model (SRM) was developed by Leventhal.39
The SRM outlines the process in which physical sensations and illnesses are stimuli for persons/patients in constructing a model which encompasses a cognitive and an emotional representation of those stimuli and their meaning (Figure 2).40 The cognitive representation pathway is distinguished by five dimensions: causes (pertains to beliefs of causes responsible for illness); identity (beliefs regarding the labels and symptoms associated with the disease);
timeline (relates to beliefs on the duration of the illness); consequences (beliefs pertaining to the impact of illness on quality of life and functioning); and controllability (pertains to the beliefs of self-empowerment and the efficacy of treatment). Emotional representation determines emotional outcomes. The emotional representation encompasses concepts such as anxiety, depression, and coherence. This latter component of the model is only recently receiving attention in research literature.41 Together these two pathways can influence subsequent coping strategies and health behaviors which in turn determine patients’ outcomes.
Leventhal’s model has been tested in a range of populations, including individuals at risk for venous thrombosis,42 and chronic physical illnesses including myocardial infarction, venous thrombosis, chronic obstructive pulmonary disease, breast cancer, chronic fatigue syndrome, psoriasis, multiple sclerosis, rheumatoid arthritis, and Huntington’s disease.43 Results from these studies indicate that positive beliefs in controllability and curability of the illness are positively associated with well-being.
14
Biosphere
Society-Nation
Culture-Subculture
Community
Family
Two-persom
Person (experience & behaviour)
Nervous System
Organs/Organ Systems
Tissue
Cells
Organelles
Molecules
Atoms
Subatomic Particles
Figure 1. The biopsychosocial model hierarchy of natural systems (adapted from Engel, pg 537)31
15 Exploring patients’ perceptions of a chronic illness such as ESRD and its treatments is especially relevant. Undeniably, how patients make sense of their illness can have repercussions on their responses to the disease and its treatments, and their subsequent health outcomes. Compared with other chronic illnesses,44-46 the illness perceptions of dialysis patients have been less well- studied. The few studies limited to relatively small samples of HD patients suggest that patients who perceive that they have more control over and fewer consequences as a result of their disease had better health outcomes.47-51 A patient’s negative perceptions of illness have been associated with an increased risk of depression,52 poorer adjustment to the disease and treatment,53 and poorer HRQL. Perceiving ESRD as a negative intrusion into lifestyle is more likely to be associated with poorer treatment compliance54 and higher symptom burden.55
Figure 2. Leventhal’s Self-Regulation Model (adapted from Hagger & Orbell, 2003)40
Cognitive illness representation Cause Consequence Control/Cure Identity Timeline
Coping strategies and style Avoidance/denial
Cognitive reappraisal Expressing emotions Problem-focused coping Seeking social support
Illness outcomes Disease state Physical functioning Psychological well-being Role functioning Social functioning Vitality
Emotional outcomes Emotional distress
Coping strategies used to deal with emotional reaction Emotional illness
representation Illness stimuli
Pool of lay information stored in memory Information given by external sources Somatic and symptomatic information
16
OBJECTIVE OF THIS THESIS
While clinical associations with health outcomes in dialysis patients are at best weak, psychosocial factors have shown to be stronger determinants of HRQL and survival. However, the role of illness perceptions in determining health outcomes in dialysis patients is still not well understood. With Leventhal’s SRM providing an elegant theoretical framework, this thesis aims to investigate the perceptions that dialysis patients have on ESRD and its treatment, and its effect on their HRQL and survival.
STUDY SAMPLE
Participants in the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD-2) provided the data used in all the studies in this thesis. NECOSAD-2 is a prospective observational study involving up to 38 dialysis centres throughout The Netherlands. From 1997 to 2007, over 2,000 ESRD patients with no previous history of renal replacement therapy were recruited. Data on demographics, clinical parameters, and psychosocial variables were collected from start of dialysis, and at three and six months after start of dialysis, and every six months thereafter. Patients were followed-up until kidney transplantation or death.
THESIS OUTLINE
This thesis begins with a review chapter which focuses on the determinants of HRQL (Chapter 2). This chapter was limited to PD patients as HRQL of PD patients is under-researched compared to those on HD.
To explore the role of psychological factors, specifically patients’ perceptions on health outcomes, we studied several components of Leventhal’s SRM. First, we examined the association between symptoms and clinical variables, and quality of life dimensions (Chapter 3).
Dialysis patients have high symptom burden although the underlying pathophysiology is not well understood. Differential symptom clusters in dialysis patients were identified and the associations between these clusters and clinical variables and HRQL dimensions were studied.
17 Second, another concept in the theoretical model that guided our work is the research tradition on the subject of general perceptions of health. We therefore investigated the robustness of a self-rated health item in predicting mortality, after correcting for a range of demographics and clinical variables (Chapter 4). In addition, the interaction of age on self-rated health and mortality was examined.
From general perceptions, we next investigated the impact of specific cognitive representations of illness on patients’ outcome (Chapter 5). This cross-sectional study examined aspects of patients’ illness perceptions as proposed by Leventhal’s SRM, and their associations with HRQL.
Differences in illness perceptions between HD and PD patients were examined.
Leventhal’s model suggests that coping strategies can affect outcome. We explored the association between social support and survival of patients over a 3-year follow-up (Chapter 6).
Two aspects of social support were examined: 1) the perceived amount of social support received, and 2) the perception of discrepancy between desired and received levels of social support. Differences between HD and PD patients on their social support needs were identified.
Lastly, we provide a general discussion on the major results found in our studies (Chapter 7).
Clinical implications and future research conclude this thesis.
REFERENCES
1. Grassmann A, Gioberge S, Moeller S, Brown G. End-stage renal disease: global demographics in 2005 and observed trends. Artif Organs 2006; 30: 895-897
2. Jager KJ, van Dijk PC, Dekker FW, Stengel B, Simpson K, Briggs JD for the NECOSAD Study Group. The epidemic of aging in renal replacement therapy: an update on elderly patients and their outcomes. Clin Nephrol 2003; 60: 352-360
3. Glassock RJ. The rising tide of end-stage renal disease: what can be done? Clin Exp Nephrol 2004; 8: 291-296 4. Lok CE, Oliver MJ, Rothwell DM, Hux JE. The growing volume of diabetes-related dialysis: a population based
study. Nephrol Dial Transplant 2004; 19: 3098-3103
5. Hossain P, Kawar B, El Nahas M. Obesity and diabetes in the developing world--a growing challenge. N Engl J Med 2007; 356: 213-215
6. Meguid EN, Bello AK. Chronic kidney disease: the global challenge. Lancet 2005; 365: 331-340
7. The ESRD Incidence Study Group. Divergent trends in the incidence of end-stage renal disease due to Type 1 and Type 2 diabetes in Europe, Canada and Australia during 1998-2002. Diabet Med 2006; 23: 1364-1369
8. van Dijk PC, Jager KJ, Stengel B, Grönhagen-Riska C, Feest TG, Briggs JD. Renal replacement therapy for diabetic end-stage renal disease: data from 10 registries in Europe (1991-2000). Kidney Int 2005; 67: 1489-1499 9. Stichting Renine. Statistisch verslag 2007. www.renine.nl. 2008.
10. ERA-EDTA Registry. ERA-EDTA Registry 2006 Annual Report. Amsterdam, The Netherlands: Academic Medical Center, Department of Medical Informatics, 2008
11. Nissenson AR, Prichard SS, Cheng IK, Gokal R, Kubota M, Maiorca R, Riella MC, Rottembourg J, Stewart JH.
ESRD modality selection into the 21st century: the importance of non medical factors. ASAIO J 1997; 43: 143-150 12. Hoenich N, Lindley E, Stoves J. Technological advances in renal care. J Med Eng Tech 2003; 27: 1-10
13. Kurella M, Covinsky KE, Collins AJ, Chertow GM. Octogenarians and nonagenarians starting dialysis in the United States. Ann Intern Med 2007; 146: 177-183
18
14. US Renal Data System. USRDS 2007 annual data report: atlas of chronic kidney disease and end-stage renal disease in the United States. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2007
15. Polaschek N. Living on dialysis: Concerns of clients in a renal setting. J Adv Nurs 2003; 41: 44-52
16. Curtin RB, Lowrie EG, DeOreo PB. Self-reported functional status: an important predictor of health outcomes among end-stage renal disease patients. Adv Ren Replace Ther 1999; 6: 133-140
17. Merkus MP, Jager KJ, Dekker FW, Boeschoten EW, Stevens P, Krediet RT. Quality of life in patients on chronic dialysis: self-assessment 3 months after the start of treatment. The NECOSAD Study Group. Am J Kidney Dis 1997; 29: 584-592
18. Molsted S, Aadahl M, Schou L, Eidemak I. Self-rated health and employment status in chronic haemodialysis patients. Scand J Urol Nephrol 2004; 38: 174-178
19. van Manen JG, Korevaar JC, Dekker FW, Reuselaars MC, Boeschoten EW, Krediet RT for the NECOSAD Study Group. Changes in employment status in end-stage renal disease patients during their first year of dialysis. Perit Dial Int 2001; 21: 595-601
20. Klang B, Clyne N. Well-being and functional ability in uraemic patients before and after having started dialysis treatment. Scand J Caring Sci 1997; 11: 159-166
21. Kutner NG, Brogan D, Fielding B. Physical and psychosocial resource variables related to long-term survival in older dialysis patients. Geriatr Nephrol Urol 1997; 7: 23-28
22. Mapes DL, Lopes AA, Satayathum S, McCullough KP, Goodkin DA, Locatelli F, Fukuhara S, Young EW, Kurokawa K, Saito A, Bommer J, Wolfe RA, Held PJ, Port FK. Health-related quality of life as a predictor of mortality and hospitalization: the Dialysis Outcomes and Practice Patterns Study (DOPPS). Kidney Int 2003; 64: 339-349 23. Kimmel PL, Peterson RA, Weihs KL, Simmens SJ, Alleyne S, Cruz I, Veis JH. Psychosocial factors, behavioral
compliance and survival in urban hemodialysis patients. Kidney Int 1998; 54: 245-254
24. Beusterien KM, Nissenson AR, Port FK, Kelly M, Steinwald B, Ware JE Jr. The effects of recombinant human erythropoietin on functional health and well-being in chronic dialysis patients. J Am Soc Nephrol 1996; 7: 763-773 25. Valderrabano F. Quality of life benefits of early anaemia treatment. Nephrol Dial Transplant 2000; 15 Suppl 3: 23-28 26. Mingardi G, Cornalba L, Cortinovis E, Ruggiata R, Mosconi P, Apolone G. Health-related quality of life in dialysis patients: a report from an Italian study using the SF-36 Health Survey. DIA-QOL Group. Nephrol Dial Transplant 1999; 14: 1503-1510
27. Bakewell AB, Higgins RM, Edmunds ME. Quality of life in peritoneal dialysis patients: decline over time and association with clinical outcomes. Kidney Int 2002; 61: 239-248
28. Barrett BJ, Vavasour HM, Major A, Parfrey PS. Clinical and psychological correlates of somatic symptoms in patients on dialysis. Nephron 1990; 55: 10-15
29. Kimmel PL, Emont SL, Newmann JM, Danko H, Moss AH. ESRD patient quality of life: symptoms, spiritual beliefs, psychosocial factors, and ethnicity. Am J Kidney Dis 2003; 42: 713-721
30. Merkus M, Jager K, Dekker F, de Haan RJ, Boeschoten EW, Krediet RT. Predictors of poor outcome in chronic dialysis patients: The Netherlands Cooperative Study on the Adequacy of Dialysis. Am J Kidney Dis 2000; 35: 69- 79
31. Engel G. The clinical application of the biopsychosocial model. Am J Psychiatr 1980; 137: 535-544
32. Kaptein AA, Scharloo M, Weinman J. Assessment of illness perceptions. In A. Vingerhoets (ed). Assessment in behavioural medicine. Hove, UK: Brunner Routledge, 2001, pp. 179-194
33. Kleinman A. The illness narratives. New York: Basic Book, 1988
34. Kleinman A. Catastrophe and caregiving: the failure of medicine as an art. Lancet 2008; 371: 22-23
35. Leventhal H, Weinman J, Leventhal EA, Phillips LA. Health psychology: the search for pathways between behaviour and health. Annu Rev Psychol 2008; 59: 477-505
36. Blagg CR. Home haemodialysis. BMJ 2008; 336: 2-3
37. Bard M, Dyk RB. The psychodynamic significance of beliefs regarding the cause of serious illness. Psychoanal Rev 1956; 43: 146-162
38. Broadbent E, Petrie KJ, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res 2006; 60:
631-637
39. Leventhal H, Brissette I, Leventhal EA. The common-sense model of self-regulation of health and illness. In LD Cameron & H Leventhal (eds). The self-regulation of health and illness behaviour. London: Routledge, 2003, pp.
42-65
40. Hagger MS, Orbell S. A meta-analytic review of the common-sense model of illness representations. Psych Health 2003; 18: 141-184
41. Cameron LD, Leventhal H. Self-regulation, health, and illness: an overview. In LD Cameron & H Leventhal (eds).
The self-regulation of health and illness behaviour. London: Routledge, 2003, pp. 1-13
42. Kaptein AA, van Korlaar IM, Cameron LD, Vossen CY, van der Meer FJM, Roosendaal FR. Using the common- sense model to predict risk perception and disease-related worry in individuals at increased risk for venous thrombosis. Health Psychol 2007; 26: 807-812
43. Kaptein AA, Scharloo M, Helder DI, Kleijn WC, van Korlaar IM, Woertman M. Representations of chronic illnesses.
In: LD Cameron, H Leventhal (eds). The self-regulation of health and illness behaviour. London: Routledge, 2003, pp. 97-118
44. Scharloo M, Kaptein AA, Weinman J, Hazes JM, Willems LN, Bergman W, Rooijmans HG. Illness perceptions, coping and functioning in patients with rheumatoid arthritis, chronic obstructive pulmonary disease and psoriasis. J Psychosom Res 1998; 44: 573-585
19 45. Scharloo M, Baatenburg de Jong RJ, Langeveld TP, van Velzen-Verkaik E, Doorn-opden Akker MM, Kaptein AA.
Quality of life and illness perceptions in patients with recently diagnosed head and neck cancer. Head Neck 2005;
27: 857-863
46. Weinman J, Petrie KJ, Sharpe N, Walker S. Causal attributions in patients and spouses following first-time myocardial infarction and subsequent lifestyle changes. Br J Health Psychol 2000; 5: 263-273
47. O'Connor SM, Jardine AG, Millar K. The prediction of self-care behaviors in end-stage renal disease patients using Leventhal's self-regulatory model. J Psychosom Med 2008; 65: 191-200
48. Covic A, Seica A, Gusbeth-Tatomir P, Gavrilovici O, Goldsmith DJA. Illness representations and quality of life scores in haemodialysis patients. Nephrol Dial Transplant 2004; 19: 2078-2083
49. Fowler C, Baas LS. Illness representations in patients with chronic kidney disease on maintenance hemodialysis.
Nephrol Nurs J 2006; 33: 173-186
50. Krespi R, Bone M, Ahmad R, Worthington B, Salmon P. Haemodialysis patients' beliefs about renal failure and its treatment. Patient Educ Couns 2004; 53: 189-196
51. Pucheu S, Consoli SM, D'Auzac C, Francais P, Issad B. Do health causal attributions and coping strategies act as moderators of quality of life in peritoneal dialysis patients? J Psychosom Res 2004; 56: 317-322
52. Guzman SJ, Nicassio PM. The contribution of negative and positive illness schemas to depression in patients with end-stage renal disease. J Behav Med 2003; 26: 517-534
53. Cvengros JA, Christensen AJ, Lawton WJ. Health locus of control and depression in chronic kidney disease: a dynamic perspective. J Health Psychol 2005; 10: 677-686
54. Kutner NG, Zhang R, McClellan WM, Cole SA. Psychosocial predictors of non-compliance in haemodialysis and peritoneal dialysis patients. Nephrol Dial Transplant 2002; 17: 93-99
55. Mucsi I, Molnar MZ, Rethelyi J, Vamos E, Csepanyi G, Tompa G, Barotfi S, Marton A, Novak M. Sleep disorders and illness intrusiveness in patients on chronic dialysis. Nephrol Dial Transplant 2004; 19: 1815-1822
