Analysis Of Illness Uncertainty And Its Related Factors In Hospitalized Patients With End-stage Renal Disease

ObjectivesTo describe the level of illness uncertainty in hospitalized patients with end-stage renal disease, and analyse the impact on depression and coping styles, then explore the related factors that influence illness uncertainty.MethodsA descriptive and correlative design was conducted. The convenient sample was recruited from the first affiliated hospital of Zhengzhou University from Mar.2011to Aug.2011, a total of133hospitalized patients with end-stage renal disease. The instruments includes social demographic questionnaire, Mishel’s uncertainty in illness scale (MUIS), physical symptom distress scale, social support rating scale (SSRS), self-rating depression scale (SDS), medical coping method questionnaire(MCMQ). The questionaires were handed out by the researcher after obtaining patients’ informed consent. The data were collected and then input the statistic software after logical check strictly. The SPSS13.0was used to analyse the data. The statistic methods included descriptive statistical analysis, one way analysis of variance (ANOVA), Pearson and Spearman correlation analysis and multiple linear regression.Results1. The score of illness uncertainty at middle level accounted for96.7%in hospitalized patients with end-stage renal disease, and the average score was (99.92±8.84). The score of unpredictability subscale was the higher, and the complexity subscale was the lower;2. The results of ANOVA indicated that there were statistical differences in scores of illness uncertainty especially for different education background, occupation, residence, family income per month, course of disease, times of hospitalization, comorbidity and different treatment modalities;3. The subscale of ambiguity was positively correlated with symptom distress (r=0.199, P<0.05), unpredictability was negatively correlated with symptom distress (r=-0.206, P<0.05);4. Illness uncertainty was negatively correlated with social support (r=-0.260, P<0.05);5. Illness uncertainty was positively correlated with depression(r=0.134～0.264, P<0.05);6. The subscale of inconsistency was positively correlated with avoidance coping(r=0.224, P<0.05), and unpredictability was positively correlated with resignation coping (r=0.184, P<0.05);7. The results of multiple linear regression analysis showed that illness uncertainty can be predicted by the combined effects of subjective support, occupation(farmers), course of disease and regular hemodialysis(R2=0.203), the subscale of ambiguity can be predicted by education and comorbidity (R2=0.196), the subscale of complexity can be predicted by occupation(farmers), times of hospitalization, subjective support and regular hemodialysis (7R2=0.160), the subscale of inconsistency can be predicted by course of disease and level of objective support (R2=0.048), the subscale of unpredictability can be predicted by symptom distress and family income per month (R2=0.116);8. Illness uncertainty of patients at the period of induction hemodialysis was predicted by the combined effects with course of disease, comorbidity, family income per month, and social support (R2=0.419); illness uncertainty of patients at the period of regular hemodialysis was primarily derived from ambiguity and inconsistency, and could be predicted respectively with symptom distress, rural area(R2=0.239, R2=0.097); illness uncertainty of patients at the period of conservative treatment was primarily derived from complexity and unpredictability, and could be predicted respectively by comorbidity and symptom distress(R2=0.146,R2=0.091). Conclusions1. Illness uncertainty in ESRD patients is at middle level, and it primarily comes from unpredictability and ambiguity;2. Among the individual characteristics, Illness uncertainty is correlated with education, occupation(farmers), course of disease, comorbidity, times of hospitalization, and family income per month, and rural area, so we should pay attention to the patients from village with lower education level and family income, short-time course of disease, few times of hospitalization and more comorbidities;3. The influencing fators of illness uncertainty is different regarding to different treatment modalities; the patients accepting conservative treatment or regular hemodialysis who experience more symptom distress will have more perception on disease complexity and dangerous disease outcome, so the nurse should evaluate the symptom and help to manage the symptoms; as to the patients at induction hemodialysis period, nurses should provide the patients more help from emotion and information in order to enhance social support of patients, and reduce the uncertainty;4. The patients view illness uncertainty as a danger, resulting in depression moods and resignation and avoidance coping style, so one of the measures to regulate the moods and help the patients confront to the illness is to remission uncertainty;...