Factors Associated with Level of Patient Activation and Its Role to Glycemic Control and among Adults with Type II Diabetes Attending Diabetic Clinic at Hospitals in Addis Ababa

Assefa, Selomon; Endris, Kedir; Ashencho, Demeke; Eyasu, Mebrahtu

doi:10.9734/ijtdh/2019/v37i430170

Cited by 4 publications

(9 citation statements)

References 22 publications

(33 reference statements)

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“…27 The proportion with high activation level among patients with diabetes in Ethiopia was even lower at 24.4%. 46 Comparatively, the percentage of patients with high activation level was higher at 65.1% among frequent users of primary health care services in Canada. 47 Variations in the activation levels in the various populations could be explained by the differences in the comorbidities, cultural background, and the health care…”

Section: Discussionmentioning

confidence: 90%

“…7 Various other factors such as social support, patient-physician relationship and health literacy have been associated with patient activation levels. 46,[51][52][53] However, these were beyond the scope of our study. Analyzing the complex paradigm of human behaviors and the interaction of different mediators of self-management is also beyond the scope of this study.…”

Section: Discussionmentioning

confidence: 96%

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Factors Associated with High Patient Activation Level among Individuals with Metabolic Syndrome at a Primary Care Teaching Clinic

Bahrom

Ramli

Isa

et al. 2020

J Prim Care Community Health

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Background: High activation level has been associated with higher education background, better self-rated health status, and having adequate health literacy. However, there is a gap in the literature regarding the level of activation and the factors associated with it among patients with metabolic syndrome (MetS) in the Malaysian primary care setting. Objectives: This study aims to determine activation levels and the factors associated with high activation among individuals with MetS in primary care. Methods: A cross-sectional study was conducted at a university primary care clinic. Patient activation was measured using the Patient Activation Measure®–13 Malay version. Activation levels were dichotomized into “low activation” (levels 1 and 2) and “high activation” (levels 3 and 4). To determine the factors associated with high activation, simple logistic regressions (SLogR) followed by multiple logistic regressions (MLogR) were performed. Results: Of 333 participants, 280 (84.1%) were included in the final analysis. The mean activation score was 59.4 (SD ±10.20) and 61.8% had high activation level. Two variables were found to be significant on MLogR. Those who were employed have the odds of 3.135 (95% CI 1.442-6.816) of having high activation compared with those who were unemployed. Those with good self-reported health status have the odds of 6.482 (95% CI 1.243-33.792) of having high activation compared to those with poor self-reported health status. Conclusions: The majority of participants had high activation levels. Those who were employed and those who had good self-reported health status were more likely to have high activation levels. Findings of this study could be used to develop patient activation interventions to improve self-management skills among individuals with MetS in primary care. These may include problem solving support, individualized care plans, peer or family support, and skill building. Those in high activation group can be trained to become mentors to support their peers who have low activation level.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 96%

Factors Associated with High Patient Activation Level among Individuals with Metabolic Syndrome at a Primary Care Teaching Clinic

Bahrom

Ramli

Isa

et al. 2020

J Prim Care Community Health

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“…In terms of the studies included in estimating the good prevalence of glycemic control, the lowest proportion (17.8%) was reported in a study conducted among T2DM patients in Addis Ababa, whereas the highest prevalence (71%) was reported in a study conducted in SNNP among both diabetic cases. Similarly, the lowest and highest rates of poor glycemic control were 29% 24 and 82%, 25 respectively. In this study, 43 articles were cross sectional studies and 4 (2 each) were cohort 48 , 56 and case control studies.…”

Section: Resultsmentioning

confidence: 97%

“…Poor glycemic control, for example, ranges from 29% 24 to 82.2%. 25 A meta-analysis of 16 studies found that only one-third of patients have good glycemic control. 26 As a result, aggregated evidences about the magnitude of poor or good glycemic control, as well as potential factors associated with poor glycemic control, are scarce in Ethiopia.…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis

Bitew

Alemu

Jember

et al. 2023

INQUIRY

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The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor glycemic control and associated factors in Ethiopia. Findings will be crucial to reduce the burden of poor glycemic control. Comprehensive search was performed from databases: PubMed, Global Health, CINAHL, IRIS, and FSTA. Gray literature sources were also explored. This document was prepared based on the PRISMA flowchart. The protocol is registered in PROSPERO (ID: CRD42022296583). STATA software was used for data analyses and I2 test with Cochrane Q statistics, and forest plot were used to verify heterogeneity. When the I2 value was higher than 50% and the p-value was 0.05, heterogeneity was deemed significant. To confirm publication bias, a funnel plot with an Egger’s regression test was performed. The factors related to poor glycemic control were reported using pooled odds ratios (POR) and a 95% confidence interval. In this study, 46 papers totaling 15 457 people were used to calculate the pooled estimates. It was determined that 32.6% (95% CI: 28.3, 36.9) and 61.92% (95% CI: 57.92, 65.92) of the subjects, respectively, had good and poor glycemic control. Being male protected against poor glycemic control, while poor diet adherence, lack of exercise, poor adherence to anti-diabetic medications, and smoking increased the likelihood of poor glycemic control. Lack of formal education, no family history of diabetes, lack of glucometer for blood glucose monitoring, comorbidity, being overweight and prolonged length of stay with diabetes all contributed to poor glycemic control. Ethiopia had a fairly high rate of poor glycemic control. The main determinants are lifestyle factors. Therefore, it is important to focus on behavioral interventions.

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“…The nding is in line with the study in Australia (24) and China (26). But study in Ethiopia showed no signi cant association between duration of diagnosis and engagement in health care decision making (27).…”

Section: Discussionmentioning

confidence: 94%

Patient Engagement in Decision Making and Associated Factors among Outpatients with Selected Non-Communicable Chronic Diseases in Public Hospitals of West Shoa, Ethiopia,2020

Emana

2021

Preprint

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Background: Despite the importance of patient engagement in health care decision-making in the care of patients with chronic diseases, there is limited information about it and the factors affecting it in Ethiopia in general and in the Public Hospitals of West Shoa in particular. Thus this study is designed to assess the engagement of patients with selected chronic non-communicable diseases in health care decision making and associated factors in public hospitals of West Shoa Zone, Oromia, Ethiopia.Methods: Facility-based cross-sectional study design was used. Systematic sampling was used for the selection of study participants from June 7 – July 26, 2020. Standardized, pretested, and structured Patient Activation Measure was used to measure patient engagement in healthcare decision-making. Descriptive analysis was done to determine the magnitude of patient engagement in health care decision-making. Multivariate logistic regression analysis was used to determine factors associated with patients’ engagement in the health care decision-making process. Adjusted odds ratio with a 95% confidence interval was calculated to measure the strength of association. Statistical significance was declared at p<0.05. The results were presented by tables and graphs.Results: A total of 406 patients with chronic diseases participated in the study yielding a response rate of 96.2%. Less than a fifth [19.5% (95% CI: 15.5, 23.6)] of participants in the study area had a high engagement in their health care decision-making. Educational level (college or above) [AOR=5.2, 95% CI (1.76-15.46)], duration of diagnosis >5 years [AOR= 1.8, 95% CI (1.03-3.2)], health literacy [AOR=1.15, 95% CI (1.06-1.24)], autonomy preference in decision making [AOR=1.35, 95% CI (1.03-1.96)] were factors significantly associated with participants’ engagement in health care decision making among patients with chronic diseases. Conclusion- Low number of respondents had a high engagement in their health care decision-making. Preference for autonomy in decision making, educational level, health literacy, duration of diagnosis with the disease were factors associated with patient engagement in health care decision making among patients with chronic diseases in the study area. Thus individualized patient-centered care and patient empowerment is essential among patients with chronic non-communicable diseases.

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Factors Associated with Level of Patient Activation and Its Role to Glycemic Control and among Adults with Type II Diabetes Attending Diabetic Clinic at Hospitals in Addis Ababa

Cited by 4 publications

References 22 publications

Factors Associated with High Patient Activation Level among Individuals with Metabolic Syndrome at a Primary Care Teaching Clinic

Factors Associated with High Patient Activation Level among Individuals with Metabolic Syndrome at a Primary Care Teaching Clinic

Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis

Patient Engagement in Decision Making and Associated Factors among Outpatients with Selected Non-Communicable Chronic Diseases in Public Hospitals of West Shoa, Ethiopia,2020

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