Correlation between Noncompliance Behavior and Biochemical Parameters of Chronic Kidney Disease Patients Undergoing Hemodialysis

Background and Objectives Compliance with dietary, fluid, and medication instructions is a critically significant factor for the health and well-being of patients undergoing hemodialysis for an extended period. The current study assessed the correlation between noncompliance behavior and biochemical parameters of chronic kidney disease (CKD) patients undergoing hemodialysis. The study's objectives were 1) to assess patients' noncompliance behavior using a questionnaire, 2) to determine the biochemical parameters of CKD patients having noncompliance behavior, and 3) to find the correlation between biological parameters and noncompliance behavior. Methods A cross-sectional study was conducted from July 12, 2018, to February 10, 2019. A purposive sampling technique was used to recruit the participants, and 100 participants were included in the study. The End-Stage Renal Disease–Adherence Questionnaire was used to assess the non-compliance behavior. Results Most dialysis patients (70%) were compliant with the therapeutic regime, while 30% failed to comply. The study revealed a significant positive correlation between noncompliance behavior and biochemical parameters of CKD patients undergoing hemodialysis (r = 0.578, p < 0.05). Conclusion Noncompliance behavior is significantly correlated with the biochemical parameters among patients with CKD on dialysis. Optimal health is possible through fluid and dietary compliance in these patients. Hence, adherence behavior plays a significant role in the health and recovery of dialysis patients with CKD.

Trajectories of Adherence to Biologic Disease-Modifying Anti-Rheumatic Drugs in Tuscan Administrative Databases: The Pathfinder Study

Scanty information on clustering longitudinal real-world data is available in the medical literature about the adherence implementation phase in rheumatoid arthritis (RA). To identify and characterize trajectories by analyzing the implementation phase of adherence to biologic Disease-Modifying Anti-Rheumatic Drugs (DMARDs), we conducted a retrospective cohort drug-utilization study using Tuscan administrative databases. RA patients were identified by a validated algorithm, including the first biologic DMARD supply from 2010 to 2015, RA specialist visit in the year before or after the first supply date and RA diagnosis in the five years before or in the year after the first supply date. We observed users for three years or until death, neoplasia, or pregnancy. We evaluated adherence quarterly through the Medication Possession Ratio. Firstly, we identified adherence trajectories and described the baseline characteristics; then, we focused on the trajectory most populated to distinguish the related sub-trajectories. We identified 952 first ever-biologic DMARD users in RA (712 females, mean age 52.7 years old, standard deviation 18.8). The biologic DMARD mostly supplied was etanercept (387 users) followed by adalimumab (233). Among 935 users with at least 3 adherence values, we identified 49 fully-adherent users, 829 continuous users, and 57 early-discontinuing users. Significant differences were observed among the index drugs. After focusing on the continuous users, three sub-trajectories were identified: continuous-steady users (556), continuous-alternate users (207), and continuous-declining users (66). No relevant differences emerged at the baseline. The majority of first ever-biologic DMARD users showed a continuous adherence behavior in RA. The role of adherence potential predictors and the association with effectiveness and safety outcomes should be explored by further studies.

Dynamics of inhaled corticosteroid use are associated with asthma attacks

Inhaled corticosteroids (ICS) suppress eosinophilic airway inflammation in asthma, but patients may not adhere to prescribed use. Mean adherence—averaging total doses taken over prescribed—fails to capture many aspects of adherence. Patients with difficult-to-treat asthma underwent electronic monitoring of ICS, with data collected over 50 days. These were used to calculate entropy (H) a measure of irregular inhaler use over this period, defined in terms of transitional probabilities between different levels of adherence, further partitioned into increasing (Hinc) or decreasing (Hdec) adherence. Mean adherence, time between actuations (Gapmax), and cumulative time- and dose-based variability (area-under-the-curve) were measured. Associations between adherence metrics and 6-month asthma status and attacks were assessed. Only H and Hdec were associated with poor baseline status and 6-month outcomes: H and Hdec correlated negatively with baseline quality of life (H:Spearman rS = − 0·330, p = 0·019, Hdec:rS = − 0·385, p = 0·006) and symptom control (H:rS = − 0·288, p = 0·041, Hdec: rS = − 0·351, p = 0·012). H was associated with subsequent asthma attacks requiring hospitalisation (Wilcoxon Z-statistic = − 2.34, p = 0·019), and Hdec with subsequent asthma attacks of other severities. Significant associations were maintained in multivariable analyses, except when adjusted for blood eosinophils. Entropy analysis may provide insight into adherence behavior, and guide assessment and improvement of adherence in uncontrolled asthma.

Adherence to Immunosuppression Medications among Heart Transplant Recipients: Challenges, Opportunities, and Potential Role of Digital Approaches in the COVID-19 Era

Society and medical practice have been restructured dramatically to avoid further spread of the COVID-19 virus; telehealth/telemedicine, mask wearing, and nationwide social distancing practices have become widespread. However, we still face unprecedented challenges in fields where patients require frequent and active follow-up visits for monitoring, including that of solid-organ transplant, and in particular, heart transplant. Adherence to immunosuppression remains a unique challenge in heart transplantation, especially during the COVID-19 pandemic. Failure to adhere to immunosuppression can have disastrous consequences, including graft rejection and death. In this article, we discuss challenges related to adherence to immunosuppression medications among heart transplant recipients, as well as opportunities to leverage digital approaches and interventions to monitor and optimize adherence behavior and health outcomes in this population.

AB0915-PARE DEVELOPMENT AND USABILITY OF A WEB-BASED PATIENT-TAILORED TOOL TO SUPPORT ADHERENCE TO URATE-LOWERING THERAPY IN GOUT PATIENTS

Background:Adherence to prescribed urate-lowering therapy (ULT) among gout patients is considered to be among the poorest of all chronic conditions. eHealth programs can be a possible opportunity to foster ULT adherence.Objectives:This study describes the development and usability evaluation of a web-based tool to support ULT adherence among gout patients, specifically designed for a complement to usual care.Methods:The Integrated Change (I-Change) model was used as theoretical basis for the development. The model combines various socio-cognitive theories and differentiates between three phases: a pre-motivational, a motivational, and a post-motivational phase. In practices, the I-Change gout tool contains three sessions, following the three phases of the I-Change model. Patients receive tailored feedback based on their answers in the form of animated videos and text messages after each session, and are prompted to set specific goals and action plans for their ULT adherence. The content and development of the I-Change gout tool was determined along an iterative process within a steering group of clinicians and researchers, supported by patient interviews and gout specific literature related to key aspects of medication adherence behavior. A cross-sectional mixed methods design was used to test usability of the support tool consisting of a think aloud method and a usability questionnaire.Results:The steering group decided on the content of the three sessions of the I-Change gout tool. Depending on the intention to change ULT adherence behavior patients were navigated through the I-Change gout tool, patients with a low intention go through all 3 sessions and patients with a high intention go through the pre- and post-motivational session (figure 1). In total, the I-Change gout tool contains three sessions with 80 questions, 66 tailored textual feedback messages, and 40 tailored animated videos.Figure 1.Flowchart of the computer-tailored I-Change gout tool for urate-lowering therapy adherence.Twenty gout patients and seven healthcare professionals participated in the usability tests. The program end score rating for the gout tool was on average 8.4±0.9 (range 6-10) for patients and 7.7±1.0 (range 6-9) for healthcare professionals. Furthermore, participants reported a high intention to use and/or recommend the program in the future. Yet, participants identified some issues for further improvement of the systems user-friendliness by addressing barriers (e.g. more explicitly navigation) and weaknesses (e.g. technical and health literacy). The I-Change gout tool was updated according suggestions of improvements of the participants.Conclusion:This study provides initial support for the usability by patients and healthcare professionals of a ULT adherence I-Change gout tool. Further studies need to be conducted to assess its efficacy and (cost-) effectiveness in daily practice.Disclosure of Interests:None declared

Factors Associated With Adherence to Lockdown Measures in Uganda

Background While the debate regarding the usefulness of the lockdown goes on in research, it has been highlighted that this debate is pointless unless studies demonstrate to what extent people are actually abiding by the lockdown. Studies on factors associated with adherence of COVID-19-related lockdowns have largely been conducted in western countries. However, similar studies are still lacking in low income countries like Uganda. This study fills this gap by investigating factors associated with adherence to lockdown in Uganda. Methods A qualitative cross sectional survey was conducted online via the AfriSight platform with a sample size of 1249. These participants were selected randomly from all across Uganda. The data was analyzed descriptively and for inferential statistics we analyzed the data using probit regression. This allowed us to investigate the various motivations, socioeconomic, and demographic factors that help predict adherence or lack thereof to lockdown measures. Based on this probit analysis, we further generated marginal effects to ascertain the probabilities of adhering to lockdown. Results Our study reports the complexity that characterizes adherence to the lockdown in Uganda. Various socioeconomic and demographic factors particularly, age, gender, size of household, religion, income level, and employment status all seem to uniquely interact in shaping adherence behavior. Conclusion This study demonstrates that any lockdown-related efforts to minimize the spread of COVID-19 must pay attention to how these factors playout in the context of Uganda. Whereas most of the factors observed can more easily be handled in wealthier countries which provide social benefits during lockdowns, Uganda must rethink the uncritical adoption of such measures without localizing them. There is a need for Uganda to invest in a COVID-19 response that is alive to local context and reality, and one which commands wide support and adherence.

Medication Adherence: Expanding the Conceptual Framework

Interventions targeting traditional barriers to antihypertensive medication adherence (AHMA) have been developed and evaluated, with evidence of modest improvements in adherence. Translation of these interventions into population-level improvements in adherence and clinical outcomes among older adults remains suboptimal. From the Cohort Study of Medication Adherence among Older adults (CoSMO), we evaluated traditional barriers to AHMA among older adults with established hypertension (N=1544; mean age=76.2 years, 59.5% women, 27.9% Black, 24.1% and 38.9% low adherence by proportion of days covered (i.e., PDC&lt;0.80) and the 4-item Krousel-Wood Medication Adherence Scale (i.e., K-Wood-MAS-4≥1), respectively), finding that they explained 6.4% and 14.8% of variance in pharmacy refill and self-reported adherence, respectively. Persistent low adherence rates, coupled with low explanatory power of traditional barriers, suggest that other factors warrant attention. Prior research has investigated explicit attitudes toward medications as a driver of adherence; the roles of implicit attitudes and time preferences (e.g., immediate versus delayed gratification) as mechanisms underlying adherence behavior are emerging. Similarly, while associations of individual-level social determinants of health (SDOH) and medication adherence are well-reported, there is growing evidence about structural SDOH and specific pathways of effect. Building on published conceptual models and recent evidence, we propose an expanded conceptual framework that incorporates implicit attitudes, time preferences and structural SDOH, as emerging determinants that may explain additional variation in objectively and subjectively measured adherence. This model provides guidance for design, implementation and assessment of interventions targeting sustained improvement in implementation medication adherence and clinical outcomes among older women and men with hypertension.

Selecting relevant and changeable determinants and underlying beliefs of university students’ adherence to COVID-19-guidelines and translating the findings into a small intervention

Background: When reopening universities in times of COVID-19, students still have to adhere to COVID-19 behavioral guidelines. We explored what behavioral determinants (and underlying beliefs) related to the adherence to guidelines are both relevant and changeable, as input for future interventions.Methods: A cross-sectional online survey was conducted (Oct-Nov 2020), identifying behavioral determinants (and underlying beliefs) of university students’ adherence to COVID-19-guidelines, including keeping 1.5m distance, getting tested, and isolating (N = 255).Results: Attitude, perceived norm, self-efficacy, and several beliefs (e.g., risk perception beliefs ‘I am not afraid because I am young’; attitudinal beliefs, e.g., ‘I feel responsible for telling people to adhere to guidelines’; self-efficacy beliefs, e.g., ‘COVID-19-prevention guidelines are difficult to adhere to’) were strongly associated with intention to adhere to guidelines, and for those beliefs there was room for improvement, making them suitable as possible intervention targets.Conclusions: Students mostly adhere to COVID-19 guidelines, but there is room for improvement. Interventions need to enhance students’ adherence behavior by targeting the most relevant determinants as identified in this study. Based on these findings, a small intervention was introduced targeting the determinants of students’ adherence to guidelines.