Predictors Of Noncompliance Research Articles

Prevalence and Predictors of Non-Compliance with Pharmacological Treatment in Diabetes

Although the incidence of failure to comply to prescribe drugs is very varied, it may be the most frequent cause of suboptimal treatment results in diabetic patients. In the research region, there are little data on the extent of non-adherence to medicines and related causes. Objective: To determine the prevalence of non-adherence to medications in patients with diabetes and the factors leading to such practices. Methods: A descriptive study designed was chosen to evaluate 191 patients with diabetes enrolled at the department of medicine, combined military hospital, Nowshera, during the period May 2022 to May 2023. Non-adherence was confirmed clinically by taking history and biochemically by poor glycemic profile. SPSS version 24 was used to analyze the data. Results: The age of the patients ranged from 18 to 60 years. The mean age of the patients was 36.17 years with standard deviation 7.53. Age group 18 to 40 years comprised of 113 (59.2%) participants. The male participants were 129 (67.5%) in number. Non-adherence was observed in 86(45.5%) patients. Factors leading to non-adherence included financial constraints 32(37.2%), medications related to complications 16(18.6%). Conclusions: Diabetes patients often fail to comply with their prescribed prescriptions in the study region. To reduce disengagement among diabetes patients, public health programs should be reinforced.

Predictors of Non-Compliance with a National Early Care and Education-Based Obesity Prevention Initiative: Go NAPSACC.

The purpose is to examine predictors of intervention non-compliance and develop a risk stratification score. Prospective cohort. Early care and education (ECE). Early care and education programs (n = 3883) randomly allocated (3:1) to a development (n = 2909) or validation (n = 974) sample. Go NAPSACC provides a structured, web-based process to help improve the health of children around 7 modules (nutrition, physical activity, oral health, breast/infant feeding, farm to ECE, outdoor play, and screen time). Program characteristics and participation data are collected via Go NAPSACC tool. Multivariable Lasso logistic regression was used to identify predictors. Discriminative ability was based on area under the ROC curve (AUC). Overall, ECE program non-compliance (lack of valid pre-/post self-assessment) was 65.5%. Six predictors were retained in the final development model: type of program (P = .002), Child and Adult Care Food Program (CACFP) participation (P = .065), acceptance of subsidies (P < .001), past modules attempted (P < .001), past modules completed (P < .001), and action plans created (P < .001). These factors generated a non-compliance risk score which showed good discrimination in the validation sample (AUC: .922, 95% CI: .903-.940). Lack of qualitative data limits the ability to fully understand the context of non-compliance; however, this study demonstrates readily available data captured by Go NAPSACC are strong predictors of future success. Early identification of high-risk programs will inform targets for future implementation strategies geared toward improving program success.

Noncompliance and Decision-Making of Airline Pilots: An Analysis of Narratives From the Aviation Safety Reporting System

The purpose of this study was to identify self-reported flight deck noncompliance in aviation safety reports and explore the relationship between adaptive expertise, deliberate vs. non-deliberate actions (errors), and intentional vs. unintentional noncompliance. The heuristics for assessing adaptive thinking and behavior were based on subscales of the Adaptive Expertise Survey (AES; Fisher &amp; Peterson, 2001). We analyzed a random sample of 200 ASRS reports from 2019 and coded them with respect to (a) whether they described intentional or unintentional noncompliance by one or more flightcrew members, (b) whether the decision making was deliberate, and (c) whether the decision-making process involved correlates of adaptive or routine (non-adaptive) expertise. We found that unintentional noncompliance was associated most frequently with non-deliberate actions and non-adaptive behaviors. Adaptive behaviors were strongly associated with deliberate actions and intentional noncompliance. Our on-going research to investigate adaptive expertise and its relationship with predictors of noncompliance is discussed.

Utilization of Radiation Therapy and Predictors of Noncompliance Among Syrian Refugees in Turkey

Utilization of Radiation Therapy and Predictors of Noncompliance Among Syrian Refugees in Turkey

PO-1297: Utilization of Radiation Therapy and Predictors of Noncompliance among Syrian Refugees in Turkey

PO-1297: Utilization of Radiation Therapy and Predictors of Noncompliance among Syrian Refugees in Turkey

Utilization of Radiation Therapy and Predictors of Noncompliance among Syrian Refugees with Cancer Living in Turkey

Utilization of Radiation Therapy and Predictors of Noncompliance among Syrian Refugees with Cancer Living in Turkey

Abstract 173: Predictors of Medication Noncompliance in Patients with an Acute Myocardial Infarction

Background: Aspirin, P2Y12 inhibitors, Statins, Angiotensin-Converting-Enzyme Inhibitor/Angiotensin II Receptor Blockers and Beta Blockers improve outcomes for patients with an Acute Myocardial Infarction (AMI). Despite this, some patients remain noncompliant with medications. We investigated potential predictors of medication noncompliance in patients with an AMI. Method: We examined adult patients with an AMI enrolled in a quality improvement program (QIP). Patients discharged prior to enrollment or those discharged to skilled nursing facilities were excluded. The primary outcome was medication noncompliance at the first follow up visit - defined as not taking at least 1 of the medications listed above. Multivariate logistic regression was used to identify risk factors for noncompliance. Results: Among 173 patients enrolled in the QIP, 119 patients (Mean age 64 +/- 1 year; 32% Females) had data regarding their follow-up office visit, of which 32% of patients were noncompliant. Table 1 lists the univariate and multivariate predictors of noncompliance. Among 25 clinical and socio-demographic variables examined, we found that needing help with medical care, or being a primary care giver to others were each associated with a roughly 5 fold higher risk of medication noncompliance. Conclusion: A significant number of patients with an AMI are noncompliant with their medications. Social support programs should focus efforts on providing patients with the help needed at home to ensure compliance with care.

Frequency and Predictors of Non-Compliance to Aspirin Therapy in Post Myocardial Infarction Patients

BACKGROUND: Aspirin non-adherence or discontinuation is associated with an almost three-fold increase in risk of major adverse cardiac events. Compliance, commonly known as adherence, has been a major health care issue. Some studies have reported non-adherence rates to aspirin as high as fifty percent. The main objective of this study was to determine the frequency and predictors of non-compliance to aspirin in post myocardial infarction patients.METHODS: This cross sectional study was conducted over a period of 3 months from May 2015 to July 2015 at Civil Hospital, Karachi. All patients visiting Cardiology out-patient department (OPD) with previously diagnosed myocardial infarction were included in the study. Patients who were not prescribed aspirin or those with contraindication to aspirin therapy such as hemophiliacs and peptic ulcer disease patients, and those with memory problems were excluded from the study. A pre-coded questionnaire was presented to the selected sample of 456 patients. Compliance was assessed through self-report. Chi square test was used as the primary statistical test.RESULTS: Out of 456 patients, 39% (n=178) were non-compliant to aspirin therapy. The most common reported cause for non-compliance was the failure to remember taking the drug reported by 40.7% (n=72) of the people. The second most common cause was the lack of awareness of the importance of the drug and the possible side effects of not taking it 31.4% (n =56).CONCLUSION: It can be concluded that non-compliance to aspirin is a major problem present in Pakistan. With the number of cardiovascular deaths increasing around the globe and in Pakistan, it is vital that non-compliance to aspirin should be taken as a serious issue.

Demographic Predictors of NPO Violations in Elective Pediatric Surgery.

The parents of pediatric patients are routinely instructed to abstain from food and liquids before elective surgeries. Our objectives were to determine if demographic factors were associated with fasting violations and to identify reasons for noncompliance. This was a matched case-control pilot study. A total of 63 patients who violated fasting guidelines were identified and matched to three controls within the same surgical service. Demographic and clinical variables were evaluated as predictors of noncompliance in a multivariate regression model. Qualitative data were coded into the most commonly identified reasons for non per os (Latin)-nothing by mouth violations. Parents of children who did not comply commonly reported that they did not receive or did not understand the fasting guidelines. Noncompliant patients were significantly more likely to experience surgical delays and cancellations. None of the demographic and clinical variables assessed were significantly associated with non per os (Latin)-nothing by mouth violations in this pilot study. Quality improvement actions may be necessary to ensure that parents receive and understand fasting guidelines for their children. This might include use of teach-back methods, modification of instructional materials, or providing follow-up information after the initial encounter.

Pill burden does not influence compliance with oral medication in recipients of renal transplant.

Objectives:Insights about the predictors of noncompliance are key to develop compliance enhancing strategy in a given therapeutic situation. Renal transplantation is a critical surgical procedure that imposes a large medication burden on patients. There is a suspicion that the large pill burden may lead to noncompliance. Our objective was to ascertain the influence of pill burden on medication compliance in renal transplant patients in the Indian sociocultural context.Methods:A longitudinal observational study was conducted in two Tertiary Care Hospitals in Kolkata running renal transplant program – one each from the government and private sectors. Totally 120 literate adult transplant recipients were recruited through purposive sampling and followed up at 3 months intervals for 1 year. Data were collected through interview and review of prescriptions and medical records.Results:Data of 110 subjects were analyzed. The pill burden was high – ranging from 10-21 (median 14) at first visit shortly after discharge to 7–22 (median 11) at last visit at 12 months in the government sector; corresponding figures in the private sector were 14–32 (median 21) and 10–28 (median 17). Pill burden increased with age. Only 60.91% of the patients were fully compliant until 1 year after transplantation. The rate of immunosuppressant noncompliance was 27.78% in government sector and 25.00% in private sector. There was no significant association between median pill burden and medication compliance. Satisfaction with caregiver support was associated with better immunosuppressant compliance.Conclusions:Noncompliance in renal transplant recipients is likely to be multifactorial. Contrary to popular belief, pill burden was not a major determinant of noncompliant behavior.

Personality Assessment Inventory Scores as Predictors of Treatment Compliance and Misconduct among Sex Offenders Participating in Community-Based Treatment

This study examined the ability of the Personality Assessment Inventory scores to predict noncompliance and probation revocations among a sample of sex offenders mandated to participate in community-based treatment. Scores on the Borderline Features (BOR) scale and subscales were the strongest predictors of noncompliance, with effect sizes as large as d = 1.50, outperforming scores on scales designed to predict treatment rejection and antisocial traits. Relatively low BOR cut scores (e.g., 50T, 55T) appeared to be most useful for identifying those at risk for noncompliance, suggesting that those with even moderate levels of borderline or personality disorder traits may be at risk for noncompliance.

Predictors of noncompliance in an oral contraceptive clinical trial

To identify participant characteristics associated with noncompliance in an oral contraceptive (OC) clinical trial.

Predictors of Non-Compliance With Radiotherapy Among Patients With Squamous Cell Carcinoma of the Head and Neck Treated at a Veterans Affairs Hospital

Predictors of Non-Compliance With Radiotherapy Among Patients With Squamous Cell Carcinoma of the Head and Neck Treated at a Veterans Affairs Hospital

Predictors of Noncompliance with Warfarin Therapy in an Outpatient Anticoagulation Clinic

To test variables associated with the Health Belief Model, the Patient Satisfaction Model, and patient demographics in predicting compliance with warfarin therapy. Descriptive study using chart and pharmacy database review as well as patient questionnaires. Outpatient anticoagulation clinic in an academic medical center. Seventy-five patients who had received warfarin therapy over the previous 6 months. Clinicians interviewed patients using a subscale of the Beliefs About Anticoagulation Survey and a Patient Satisfaction Model. Perceived barriers to compliance with warfarin therapy and marital status explained 21.7% of the variance in calculations of refill adherence (p<0.001). Compliance with warfarin therapy was assessed using a validated compliance self-report survey and outpatient pharmacy dispensing data. Perceived barriers and current living conditions explained 33.2% of the variance in self-reported noncompliance (p<0.001). Logistic regression analysis, conducted to attempt to predict patients with an 80% refill adherence threshold, correctly classified compliance 85.3% of the time. This investigation provided some insight into the factors predictive of noncompliance in a low-income, outpatient population. Perceived barriers, marital status, living arrangements, and drug regimen played significant roles in warfarin noncompliance. Our results provide more evidence supporting the use of refill adherence and patient self-report as measures of noncompliance. This linkage helps validate compliance as a useful surrogate of patient health outcomes. This study also offers a model that can help clinicians identify patients at significant risk of noncompliant behavior.

Prevalence and characteristics of noncompliant behaviour and its risk factors in kidney transplant recipients

Noncompliance with therapy is one possible explanation for the observation that long-term graft survival is not sufficiently improved by the development in immunosuppression. The aim of the study was to explore the prevalence, characteristics and risk factors of noncompliance with immunosuppression. A total of 161 adult kidney transplant recipients were interviewed about their self-rated health, social support, education, stress from adverse effects and compliance with the immunosuppression. The prevalence of subclinical noncompliance was 54%. Noncompliant patients declared significantly worse self-rated health, less satisfaction with social support and higher stress from adverse effects. Male gender (OR 7.5, CI 2.4-23.39), high stress from adverse effects (OR 12.27, CI 2.44-61.88), fair self-rated health (OR 4.45, CI 1.04-19.55) and fair satisfaction with social support (OR 4.55, CI 1.08-19.24) were predictors of noncompliance. Standardized detection methods should be developed with the aim of identifying patients who are at risk of noncompliance in order to prevent graft loss.

Obesity as a risk factor for antipsychotic noncompliance

Objective: Weight gain is a common side effect of antipsychotic medications and is of particular concern with most of the newer “atypical” antipsychotics. It is, therefore, increasingly important to understand the impact of obesity and perceived weight problems on compliance with these medications. Methods: A survey of treatment and health issues was mailed to local chapters of the National Alliance for the Mentally Ill (NAMI) and National Mental Health Association (NMHA), who distributed them to people with schizophrenia. Noncompliance was defined as a self-report of missing any antipsychotic medication in the previous month. The primary independent variables were (1) body mass index (BMI; weight [kg]/height [m 2])—categorized as normal (<25, n=73), overweight (25–30, n=104), or obese (>30, n=100)—and (2) subjective distress over weight gain. Other independent variables included demographics, medication attitudes, and treatment satisfaction. Result: BMI status and subjective distress from weight gain were predictors of noncompliance. Obese individuals were more than twice as likely as those with a normal BMI to report missing their medication (OR=2.5; CI 1.1–5.5). A comprehensive model suggested that the primary mediator of noncompliance was distress over weight gain. Conclusions: There appears to be a significant, positive association between obesity and subjective distress from weight gain and medication noncompliance, even when accounting for other possible confounding factors.

Predictors of noncompliance in patients with schizophrenia.

Around 50% of patients with schizophrenia do not fully comply with treatment, and noncompliance is linked to relapse, rehospitalization, poor outcome, and high economic costs. The health belief model views noncompliance as a decision made by the patient, arrived at after weighing the perceived risks and benefits of treatment. A MEDLINE search for the years 1980-2002 using combinations of the keywords schizophrenia, compliance, adherence, antipsychotics, tolerability, and side effects was used to identify articles investigating the factors influencing compliance in schizophrenia. Many factors influence compliance, including those that affect patients' beliefs about their illness and the benefits of treatment (e.g., insight into illness, belief that medication can ameliorate symptoms), perceived costs of treatment (e.g., medication side effects), and barriers to treatment (e.g., ease of access to treatment, degree of family or social support). Medication side effects that are distressing to patients and linked to noncompliance include extrapyramidal side effects, neuroleptic dysphoria, akathisia, sexual dysfunction, and weight gain. Compliance can be improved by cognitive-behavioral therapies, such as compliance therapy, and other psychosocial interventions associated with improved social functioning and a lower risk of rehospitalization. Treatment adherence may also be improved by use of atypical antipsychotics with few perceived side effects. By considering the factors leading to noncompliance and adopting a comprehensive strategy for improving compliance, encompassing psychosocial intervention and optimum choice of medication, the management of schizophrenia could be greatly improved.

Role of APD in compliance with therapy.

Lack of compliance with prescribed treatment is an important cause of inadequate dialysis in patients on peritoneal dialysis (PD). The reported prevalence of noncompliance with treatment in PD varies from 5 to 38%. The predictors of noncompliance, its consequences, methods to identify and monitor compliance, differences in frequency between continuous ambulatory PD (CAPD) and automated PD (APD), and management are reviewed. The risk of noncompliance is greater in CAPD than in APD. Noncompliance should be managed by patient education and appropriate modification of therapy, including consideration of APD.

Noncompliance with medical follow-up after pediatric intensive care.

To describe the medical follow-up ordered, the health care utilization, the appointment compliance, and the risk factors associated with noncompliance in patients who are discharged after a pediatric intensive care unit (PICU) stay. A prospective, analytic, cohort study of 111 critically ill children, age 1 day to 16 years, who were admitted to a 30-bed PICU in an urban, tertiary-care, pediatric teaching hospital compared children who were compliant with medical follow-up with those who were not. The main outcomes measured were emergent and unscheduled physician visits during the first 6 weeks after hospital discharge; compliance with ordered medical follow-up after hospital discharge; and comparisons of socioeconomic, demographic, and medical need factors between compliant and noncompliant children. Discharge orders for follow-up appointments with general pediatricians and subspecialists were collected from the chart at hospital discharge. Patients were contacted after hospital discharge to determine whether and when they received medical follow-up; 28% were found to be noncompliant. Risk factors associated with noncompliance were evaluated. Emergent and unscheduled physician visits were tracked during the first 6 weeks after hospital discharge. Lack of follow-up orders at hospital discharge did not affect the frequency of emergent visits. Children fell into 2 groups: those who were 100% compliant and those with < or =67% compliance. No socioeconomic or demographic risk factors could be identified between the 2 groups. Compared with the 100% compliant patients, patients who were compliant with < or =67% of appointments were more severely ill, as defined by higher peak pediatric risk of mortality scores during their PICU stay (11.5 vs 8.4), longer PICU length of stays (10.1 days vs 4.6 days), and longer hospital length of stays (25.5 days vs 14 days). Most predictive of noncompliance was the number of medical appointments ordered by physicians. Patients with 3 or more appointments were less likely to be compliant with follow-up. After hospital discharge, children were more likely to visit a primary care physician compared with a subspecialist (95% vs 82%). When patients were ordered to see a specialist, scheduled appointments were much better attended than the recommended appointments (92% vs 67%). Lack of ordered medical follow-up did not affect emergent visits. In this group of critically ill children, a significant percentage (28%) did not receive timely medical follow-up. No socioeconomic or demographic risk factors were identified in noncompliant children. However, severity of illness (higher peak pediatric risk of mortality score, longer PICU stay, and longer hospital stay) and the number of follow-up appointments ordered were predictors of noncompliance. Potential exists for implementing strategies to improve compliance in identified populations.

Predictors of noncompliance in males with first-episode schizophrenia, schizophreniform and schizoaffective disorder

Purpose. Many factors influencing compliance in schizophrenia have been reported in the literature. Our aim was to assess predictors of noncompliance in male patients with first-episode schizophrenia, schizophreniform and schizoaffective disorder in a naturalistic setting. Subjects and methods. Fifty-six male patients, discharged from hospital, were included in a 1-year follow-up study. Psychopathological symptoms were assessed with positive and negative syndrome scale at admission and discharge, while extrapyramidal side effects were recorded weekly during hospitalisation using the Simpson–Angus and Barnes akathisia scales. Socio-demographic and some other variables were also recorded. Results. Thirty patients (53.6%) dropped out of treatment in the first year and 21 of them relapsed. With the Cox survival analysis three predictors of noncompliance were found: diagnosis of schizophrenia versus the other two diagnoses, positive symptoms at admission, and lack of insight at discharge. Discussion. In spite of a specific methodology and selection of only first-episode male patients, the results are in accordance with the findings of other authors. This confirms the universality of noncompliance in psychotic patients. Conclusions. First-episode patients have a high dropout rate. However, in compliant patients, the relapse rate was low, and therefore special attention and compliance-promoting interventions in first-episode patients are needed.