Paper
Friday, 21 July 2006
This presentation is part of : Research Theory and Methods
Longitudinal Impact of Symptom Status on the Quality of Life of Persons Living with HIV
Karen H. Sousa, RN, PhD, College of Nursing, Arizona State University, Tempe, AZ, USA and Oi-Man Kwok, PhD, Educational Psycholology, Texas A & M University, College Station, TX, USA.
Learning Objective #1: Understand the impact of symptom status on patient's perceived quality of life.
Learning Objective #2: Gain an understanding of the parallel growth process as a method to evaluate change overtime.
Aims: Effective symptom management is viewed as an essential component of nursing practice. For patients with chronic illnesses quality of life (QOL) has emerged as a potentially important outcome of health care. As shown in a previous cross-sectional study, symptom status had a significant impact on QOL in persons living with chronic illnesses. This paper describes an approach that evaluates the longitudinal impact of symptom status on QOL. Methods: Parallel process growth modeling was used to test the relationship between symptom status and QOL. There were 367 HIV+ patients in this analysis. Measurement models for symptom status and QOL were specified and tested using confirmatory factor analysis. The measurement model for symptoms status was based on the “Sign and Symptom Checklist for Persons with HIV Disease” (SSC-HIV) and the QOL measurement model was based on work from the Medical Outcomes Study. To account for the non-normal properties of the indicators, analyses were conducted using the weight least square estimation with robust standard errors and a mean-adjusted chi-square statistic test in Mplus. Results: More than 83% of the patients had three or more completed responses on both SSC-HIV and QOL scales at different times within 13 years. There was a significant positive increase in the number of symptoms and a significant decrease in QOL over time. The rate of change in the symptom status had substantial negative impact on the rate of change in QOL. A substantial proportion of the variance of the QOL slope (95%) was accounted for by the symptom status slope. Conclusions: Establishing an empirical relationship between symptom status and QOL begins to identify a means for translating the meaning of QOL for clinicians and patients. This analysis also supports the importance of effective symptom management as a means for affecting a patient’s QOL.

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