Identification of Immunosuppressive Medication Nonadherence Factors Through a Combined Theory Model in Renal Transplant Recipients

Abstract

Background: Immunosuppressive medication (IM) nonadherence is associated with poor transplant outcomes. Therefore, it is of great importance to identify predictive factors with IM nonadherence. We aimed to improve the predicted capacity of the theory of planned behavior (TPB) by adding health belief model’s (HBM) variables in renal transplant patients (RTPs).Methods: This cross-sectional study distributed questionnaires to patients who had undergone renal transplant and follow-up regularly in the transplant center of Third Xiangya Hospital in China. The self-developed questionnaire collected data in three aspects: general data questionnaire, TPB, HBM-specific questionnaire, and Basel Assessment of Adherence to Immunosuppressive Medications scale.Results: A total of 1,357 of 1,480 patients completed the survey, with a participation rate of 91.69% and IM nonadherence rate of 33.53%. The marital status, household income, preoperative drinking history, the time after transplantation, and religion showed independent predictive factors with IM nonadherence (p < 0.05). Strikingly, adding HBM variables to the TPB theory model significantly increased its prediction ability to IM nonadherence (52%). Also, HBM manifested the highest coefficient of effect (−0.620). Particularly, perceived barriers and perceived seriousness, the variables of the HBM model, played a vital influence on medication nonadherence (−0.284 and 0.256).Conclusion: Our study here reveals the first investigation of the combined effects of the TPB and HBM model on IM nonadherence in Chinese RTPs, which could significantly improve the predictive ability of any single model. Meanwhile, future interventions should be conducted to both increase perceived seriousness and reduce perceived barriers for taking IM, which will effectively decrease IM nonadherence rates and improve transplant outcomes.

Prediction Model of Immunosuppressive Medication Non-adherence for Renal Transplant Patients Based on Machine Learning Technology

“…In this study, the IM non-adherence of the patients was 38.5%, and taking IM more than 2 h before or after the recommended dosing time in the last 4 weeks was the most common issure of IM non-adherence, which occurred at a rate of 27.8%. This result was similar to the results of our previous study (5), which also suggested that the problem of medication non-adherence in RTPs remains serious, especially not taking medication on time. Therefore, there is an urgent need to predict the risk factors for IM non-adherence and to undertake targeted intervention methods to improve the situation.…”

“…A study conducted in 99 US-based transplant centers showed that 71.1% of health care professionals acknowledged not having a prospective medication non-adherence screening protocol, and little is known about strategies currently utilized by transplant centers to monitor or manage this issue (38). To solve this common problem, some scholars have attempted to establish predictive models of non-adherence in patients after kidney transplantation, such as HBM and TPB models (5,8,20,39). However, models currently constructed has several limitations, such as insufficient coverage variables, inability to quantify risk prediction, inability to be directly applied to clinical practice, and only providing theoretical reference value.…”

“…Successful long-term kidney graft outcomes remain suboptimal, with IM non-adherence considered as an important contributing factor. Nevertheless, non-adherence is common, occurring in 23.21-44.2% of Chinese renal transplant recipients in our previous studies (4)(5)(6). IM nonadherence is a major issue among transplant recipients that can lead to misdiagnosis, rejection, graft loss or death.…”

Reliability and Validity of the Japanese Version of the Basel Assessment of Adherence to Immunosuppressive Medications Scale in Kidney Transplant Recipients

“…The prevalence of MNA using the BAASIS in KTRs was previously reported to be 34% to 66% and that of the present study was within this range. 13,[28][29][30][31][32][33][34] This prevalence range of MNA using the BAASIS was relatively >36% reported by a previous meta-analysis. 10 This is probably because the BAASIS uses an intentionally strict scoring method and includes timing adherence as a criterion.…”

Effects of Nursing Intervention Based on Health Belief Model on Self‐Perceived Burden, Drug Compliance, and Quality of Life of Renal Transplant Recipients

“…HBM is widely employed in health education, such as explaining the transformation and maintenance of various healthy behaviors, or forming an important theoretical framework to guide behavior intervention. HBM is applied through the analysis of individual health beliefs; the use of pictorials, brochures, and WeChat education platform; and other ways to promote the relevant content of healthy behavior, give individuals correct cognition to establish a good health belief, make them take the initiative to complete healthy behavior, and finally achieve the goal of preventing adverse consequences [ 9 ]. Based on this, the current study focuses on the effects of nursing intervention based on HBM on self-perceived burden, drug compliance, and quality of life of renal transplant recipients.…”