Medication adherence by Palestine refugees living in Jordan who have diabetes: a cross-sectional study

Canali, Giulia; Tittle, Victoria; Seita, Akihiro

doi:10.1016/s0140-6736(18)30379-9

Cited by 9 publications

(12 citation statements)

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“…Dissatisfaction with health care resulted in significantly low adherence rates, similar to diabetic Palestinian refugees in Jordan. 36 One explanation can be derived from what Syrians reported on their negative experiences with the health workers and their preference for Syrian staff, and from another perspective what staff reported of an unbearable workload, sometimes predisposing them to clinical burnout. 10 In turn, clinical burnout, can lead to a range of physical and psychological manifestations that can result in lower quality of care and therefore negatively impacting patients’ satisfaction with the service.…”

Section: Discussionmentioning

confidence: 99%

Factors Associated with Suboptimal Adherence to Hypertensive Medications Among Syrian Refugees – Cross-Sectional Study at the Zaatari Camp, Jordan

Khudair¹,

Khader²,

Morrissey³

et al. 2021

PPA

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Objective This study aimed to assess the level of medication adherence and associated factors among Syrian refugees with hypertension in Jordan. Methods This cross-sectional study included 180 randomly selected Syrian refugees diagnosed with hypertension residing in Zaatari camp, Jordan. The Adherence to Refills and Medications Scale (ARMS) was used to assess adherence to antihypertensive medications. Additional data were collected on sociodemographics, therapy-related factors, patients’ behaviors and knowledge of hypertension disease and therapy, and health system-related factors. Multivariate linear regression was used to assess the association between adherence scores and other variables. Results The mean (SD) of ARMS scores was 15.7 (2.9). Based on ARMS scores, 22.8% of patients were adherents and 77.2% were non-adherents. Multivariate analysis showed that newly initiated therapy (≤2 years) and illiteracy were both strong predictors of lower adherence with p < 0.001 and p = 0.012, respectively. Other variables that were significantly associated with lower adherence included discontinuation of antihypertensive medications due to side effects (p = 0.032), reporting irregular availability of free antihypertensive medications dispensed by non-governmental organizations (NGOs) (p = 0.024), and dissatisfaction with health services (p = 0.022). Conclusion Suboptimal adherence to antihypertensive medications remains a substantial unmet need among Syrian refugees with hypertension. As illiteracy appears to have a negative impact on adherence levels, educational interventions that promote medication adherence and favorable health behaviors through auditory and visual aids are needed to better reach and engage people with limited literacy skills. Strengthening the pharmaceutical supply chain at various levels is strongly recommended to respond quickly to changes in demand and prevent an indirect negative impact on adherence levels.

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Section: Discussionmentioning

confidence: 99%

Factors Associated with Suboptimal Adherence to Hypertensive Medications Among Syrian Refugees – Cross-Sectional Study at the Zaatari Camp, Jordan

Khudair¹,

Khader²,

Morrissey³

et al. 2021

PPA

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“…A systematic review showed that the rate of adherence to oral hypoglycemic agents ranged from 36%–93% and 62%–64% to insulin in patients with T2DM 27. Twenty-seven percent of Palestine refugees who have diabetes living in Jordan were not adherent to their regimens 28. Many variables are reportedly considered to be related to patient medication compliance such as gender, dyslipidemia, medication, and so on 29 30.…”

Section: Discussionmentioning

confidence: 99%

Predictive models of medication non-adherence risks of patients with T2D based on multiple machine learning algorithms

Yang

Run-zhang

et al. 2020

BMJ Open Diab Res Care

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ObjectiveMedication adherence plays a key role in type 2 diabetes (T2D) care. Identifying patients with high risks of non-compliance helps individualized management, especially for China, where medical resources are relatively insufficient. However, models with good predictive capabilities have not been studied. This study aims to assess multiple machine learning algorithms and screen out a model that can be used to predict patients’ non-adherence risks.MethodsA real-world registration study was conducted at Sichuan Provincial People’s Hospital from 1 April 2018 to 30 March 2019. Data of patients with T2D on demographics, disease and treatment, diet and exercise, mental status, and treatment adherence were obtained by face-to-face questionnaires. The medication possession ratio was used to evaluate patients’ medication adherence status. Fourteen machine learning algorithms were applied for modeling, including Bayesian network, Neural Net, support vector machine, and so on, and balanced sampling, data imputation, binning, and methods of feature selection were evaluated by the area under the receiver operating characteristic curve (AUC). We use two-way cross-validation to ensure the accuracy of model evaluation, and we performed a posteriori test on the sample size based on the trend of AUC as the sample size increase.ResultsA total of 401 patients out of 630 candidates were investigated, of which 85 were evaluated as poor adherence (21.20%). A total of 16 variables were selected as potential variables for modeling, and 300 models were built based on 30 machine learning algorithms. Among these algorithms, the AUC of the best capable one was 0.866±0.082. Imputing, oversampling and larger sample size will help improve predictive ability.ConclusionsAn accurate and sensitive adherence prediction model based on real-world registration data was established after evaluating data filling, balanced sampling, and so on, which may provide a technical tool for individualized diabetes care.

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“…The MMAS-8 has been previously used for a wide range of diseases and is validated for both DM and HTN [9,14,15]. More recently, the MMAS-8 was used in studies assessing self-reported adherence in Arabic speaking populations, such as the United Arab Emirates (UAE), Saudi Arabia, Jordan, and Palestine [5,9,[16][17][18]. The Arabic version of the MMAS-8 was tested for its reliability and validity for type 2 DM patients in Libya [19].…”

Section: Cross-sectional Componentmentioning

confidence: 99%

“…To our knowledge, only one study has looked into medication adherence rates and the associated risk factors among patients with NCDs in a refugee setting-in Palestinians living in Jordan [9]. However, this study was observational in nature and did not explore the challenges faced from patients' perspective.…”

Section: Introductionmentioning

confidence: 99%

Self-reported medication adherence among patients with diabetes or hypertension, Médecins Sans Frontières Shatila refugee camp, Beirut, Lebanon: A mixed-methods study

Mohamad

Moussally²,

Lakis³

et al. 2021

PLoS ONE

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Introduction Low adherence to medications, specifically in patients with Diabetes (DM) and Hypertension (HTN), and more so in refugee settings, remains a major challenge to achieving optimum clinical control in these patients. We aimed at determining the self-reported medication adherence prevalence and its predictors and exploring reasons for low adherence among these patients. Methods A mixed-methods study was conducted at Médecins Sans Frontières non-communicable diseases primary care center in the Shatila refugee camp in Beirut, Lebanon in October 2018. Data were collected using the validated Arabic version of the 8-items Morisky Medication Adherence Scale (MMAS-8) concurrently followed by in-depth interviews to explore barriers to adherence in patients with DM and/or HTN. Predictors of adherence were separately assessed using logistic regression with SPSS© version 20. Manual thematic content analysis was used to analyze the qualitative data. Results Of the 361 patients included completing the MMAS, 70% (n = 251) were moderately to highly adherent (MMAS-8 score = 6 to 8), while 30% (n = 110) were low-adherent (MMAS-8 score<6). Patients with DM-1 were the most likely to be moderately to highly adherent (85%; n = 29). Logistic regression analysis showed that patients with a lower HbA1C were 75% more likely to be moderately to highly adherent [(OR = 0.75 (95%CI 0.63–0.89), p-value 0.001]. Factors influencing self-reported moderate and high adherence were related to the burden of the disease and its treatment, specifically insulin, the self-perception of the disease outcomes and the level of patient’s knowledge about the disease and other factors like supportive family and healthcare team. Conclusion Adherence to DM and HTN was good, likely due to a patient-centered approach along with educational interventions. Future studies identifying additional factors and means addressing the barriers to adherence specific to the refugee population are needed to allow reaching optimal levels of adherence and design well-informed intervention programs.

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Medication adherence by Palestine refugees living in Jordan who have diabetes: a cross-sectional study

Abstract: UNRWA.

Cited by 9 publications

References 0 publications

Factors Associated with Suboptimal Adherence to Hypertensive Medications Among Syrian Refugees – Cross-Sectional Study at the Zaatari Camp, Jordan

Factors Associated with Suboptimal Adherence to Hypertensive Medications Among Syrian Refugees – Cross-Sectional Study at the Zaatari Camp, Jordan

Predictive models of medication non-adherence risks of patients with T2D based on multiple machine learning algorithms

Self-reported medication adherence among patients with diabetes or hypertension, Médecins Sans Frontières Shatila refugee camp, Beirut, Lebanon: A mixed-methods study

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