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. 2016 May;45(5):710–712.

Illness Perceptions and Disability Levels among Older Adults with Chronic Illness

Salah ABERKANE 1,*
PMCID: PMC4935721  PMID: 27398350

Dear Editor-in-Chief

The world’s population is ageing rapidly. Between 2000 and 2050, the proportion of the world’s older adults is estimated to double from about 11% to 22%. In absolute terms, this is an expected increase from 605 million to 2 billion people over the age of 60. Older adults can encounter some specific physical and mental health drawbacks that require being treated efficiently (1). In Algeria, approximately 15% of adults aged 60 and over suffer from one chronic condition at least (2). Chronic illnesses have a major impact on the physical, psychological, and social functioning of the elderly. These illnesses often are accompanied by chronic conditions such as pain, disability, and functional limitations that contribute to poor health-related quality of life (HRQOL) (3); a condition which may be influenced by illness perception which is: The manner that an individual identifies and understands one’s disease. Emotional state seems to make a difference with positive mood and disposition associated with slower declines in health and harmful attitudes and beliefs related to poor physical and mental outcomes (4). The Illness Perception Model (IPM) states that there exists a close relationship between perceived illness/treatment and quality of life. The main suggestions of IPM consist in the impact of illness representations on HRQOL thanks to the chronic illness self-management (5). The IPM has been extended to delineate the influence of illness perceptions and health status on performance level such as disability levels. Additionally, it has been suggested that the IPM holds promise for understanding health care in older adults with chronic illness.

In this study we administered nine subscales (Illness Consequences, Illness Coherence, Illness Timeline—Cyclical, Personal Control, Treatment Control, Illness Representations, Illness Identity, and Causal Attributions) of the Illness Perception Questionnaire— Revised (IPQ-R). Multivariable linear regression analyses explored the associations between illness perception dimensions and HRQOL(Physical Functioning, Role Physical, Vitality, General Health and Social Functioning), as measured by SF36v2. A sample of 76 respondents (39.47% women; mean age, 64.53±6.93 years) with chronic illness living in the region of Banta (Algeria) has been adopted in this study. The characteristics of the four illness groups are presented in Table 1. This study has provided insights about the relationship between illness perception and HRQOL. Therefore, it has proved that there is an association with causal attributions, illness identity, illness coherence, treatment control and HRQOL. Elders suffering from chronic illness show a significant assimilation of their disease, perceive the critical illness consequences, and are convinced about the link between the illness coherence and the treatment control(6).

Table 1:

Characteristics of patient samples

Illness Group N Gender (%) Length of Illness Mean (SD) years Age Mean (SD) years
Asthma 6 7.89 67.67(11.6) 27.67(7.64)
Diabetes 16 21.05 8.5(5.76) 67.63(10.47)
HBP 48 63.16 10.5(7.45) 64.5(7.49)
Chronic Kidney disease 6 7.89 11.33(10.0) 63.0(5.2)

Illness perceptions did not vary with increased age or worsening disease severity, suggesting that illness perceptions may develop during aging. Illness perceptions were associated with causal attributions, illness identity, illness coherence and treatment control. Predictability and the effect of each of illness perception subscales on the quality of life in patients with chronic illness were tested by multiple variable Regression test and its results are shown in Table 2. As indicated, regression coefficients showed that predictability was dedicated to six subscales of medical, psychological, and biological attributions, Illness identity, Illness coherence, Treatment control whereas the other subscales did not have any influence on this prediction.

Table 2:

Regression analysis in predicting quality of life of sample

Variables R2 Adjusted R2 F B standardized
Physical Functioning
Medical attributions 0.18 0.15 5.78 −0.43
Role functioning
Medical attribution 0.36 0.34 14.17 −0.60
Illness Coherence 0.50 0.46 12.13 −0.41
Emotional Role
Medical attribution 0.24 0.21 7.94 −0.49
Vitality
External attribution 0.21 0.18 6.63 0.46
Treatment control 0.41 0.36 8.35 −0.45
General Health
Medical attribution 0.28 0.25 9.80 0.53
Psychological attribution 0.51 0.48 12.97 −0.66
Biological attribution 0.62 0.57 12.61 −037
Social Functioning
Illness Identity 0.24 0.21 7.91 −0.49

Our obtained results suggest that personal beliefs have an additional impact over psychosocial well-being in older adults with chronic illness and reflect other studies on psychosocial health in chronic illness that have demonstrated the importance of coping and social support in improved health outcomes.

As an assessment of HRQOL, the use of instruments such as the SF 36v2, becomes more common in routine clinical monitoring of patients with chronic illness. Clinicians need to be aware of how HRQOL can be affected and modified by individual illness perception. In this context, changes in HRQOL may be followed by intervention, assessing and incorporating illness perception into overall chronic illness self-management strategies.

Acknowledgements

The authors declare no conflict of interest.

References

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Articles from Iranian Journal of Public Health are provided here courtesy of Tehran University of Medical Sciences

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