Predicting Factors of Uncertainty in Illness among Persons with Colorectal Cancer
Keywords:
Uncertainty in Illness, Social support, Stage of the disease, Colorectal cancer, Predicting FactorsAbstract
Colorectal cancer is a major cause of morbidity in many countries. Similar to other cancers, uncertainty always exists among persons in illness situations including ambiguous, complex, and unpredictable. This predictive correlative research aimed to identify predicting factors of uncertainty in illness among persons with colorectal cancer. The study sample consisted of 100 persons with colorectal cancer who received treatment at a provincial hospital in southern Thailand. Social support and stage of disease were selected as the predicting factors. The stage of disease based on phases of treatment was reviewed from patient records. Data relating to social support were collected using the Personal Resource Questionnaire (PRQ 85–Part II) and uncertainty in illness data were collected using the Mishel’s Uncertainty in Illness Scale (MUIS). Data from these questionnaires were collected by air mailing. Predictive relationships between social support, stage of disease, and uncertainty in illness were analyzed using Logistic Regression analysis.
The findings from this study revealed that 75 % of the study sample had uncertainty in illness at moderate level and 16 % at high level. Social support and stage of disease accounted for 81% of predictors of overall uncertainty in illness. Social support and stage of disease accounted for 92 % of predictors of moderate level uncertainty in illness and 75 % of high level uncertainty in illness.
The findings of this study demonstrate the significance of social support and stage of disease based on phases of treatment as the predictors of uncertainty in illness among persons with colorectal cancer. The findings can be used to guide clinical practice in terms of seeking appropriate ways to decrease uncertainty in illness. The experimental research is recommended for further study in order to identify nursing interventions.
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