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Predictors Of Immunosuppressant Adherence In Long-term Renal Transplant Recipients

To sustain the health and viability of renal transplants, adherence to immunosuppressant therapy (IST) medications is critical. Studies continue to identify decreased adherence rates as time from transplant increases (Chisholm-Burns, Kwong, Mulloy & Spivey, 2008; Chisholm, Lance, Mulloy, 2005; Chisholm, Mulloy, & DiPiro, 2005; Nivens & Thomas, 2009). While previous research has explored the effect of variables known to influence IST adherence in adult renal transplant recipients, limited studies have explored these variables in a population of renal transplant recipients with longer time posttransplant intervals. The purpose of this study was to examine demographic variables, time posttransplant, immunosuppressive agents, health beliefs, social support, and symptom experience and test their relationship to adherence in a population of long-term renal transplant recipients. A cross-sectional correlational design was used to collect data from a convenience sample of 98 adult renal transplant recipients who were three or more years from transplant. Participants completed five instruments: 1) demographic survey, 2) the Beliefs About Medicines Questionnaire (BMQ), 3) the Medical Outcomes Study (MOS) Modified Social Support Survey (MSSS), 4) the Basel Assessment of Adherence with Immunosuppressive Medication Scales (BAASIS), and 5) the Modified Transplant Symptom Occurrence and Symptom Distress Scale- 59R (MTSOSD-59R). A composite adherence score (CAS) consisting of a self-report measure of adherence (BAASIS), nontherapeutic serum drug assay, and collateral report of adherence as provided by two transplant clinic professionals was used to determine final adherence group classification (adherent/nonadherent). Analysis of the relationship between all independent variables and adherence was conducted using Spearman’s rho correlation coefficient. Mean scores for medication complexity, health beliefs, social support, and symptom experience were 4 compared between age, gender, and time posttransplant groups using independent-samples t tests. A logistic regression prediction of probability was conducted to determine which of the variables that demonstrated a significant relationship to adherence were most predictive of adherence. Of the total sample population (N = 98), 39.8% (n = 39) were classified as adherent and 60.2% (n = 59) were nonadherent. Results demonstrated no significant relationship between age (continuous variable), time posttransplant, immunosuppressant medications (measured by a medication complexity index), health beliefs, symptom experience, and adherence. Weak, but significant relationships between age groups (r = -.213, p=.035), tangible social support (r = .215, p =.017), emotional informational social support (r = .274, p = .003), positive social interaction support (r = .199, p = .025), total overall social support (r = .274, p =.003) and composite adherence group classification were found. Older participants ( > 55 yrs) were significantly less adherent than younger ( < 54 yrs) participants. Mean scores for emotional / informational (EMI), positive social interaction (POS), and total social support (MSSS) were significantly lower in nonadherent participants. Regression results indicated the overall model of two predictors (age grouped [ < 54 yrs; > 55 yrs] and EMI social support subscale) was statistically reliable in distinguishing between adherent and nonadherent participants (-2 Log Likelihood 116.244; Goodness-of-Fit x 2 (2) = 13.664, p = .001), correctly classifying 69.1% of the cases. Findings from this study contribute to the body of research exploring predictors of immunosuppressant adherence in long-term renal transplant recipients. Data suggest both younger age (< 55) and categories of social support predict adherence in long-term renal transplant recipients. Healthcare providers caring for renal transplant recipients long-term 5 should consider annually assessing older participants for adherence as well as for changes in social networks.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-3129
Date01 January 2012
CreatorsGalura, Sandra J
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceElectronic Theses and Dissertations

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