Dataset Information

Diabetes self-management in three different income settings: Cross-learning of barriers and opportunities.

ABSTRACT: The burden of type 2 diabetes is increasing rapidly, not least in Sub-Saharan Africa, and disadvantaged populations are disproportionally affected. Self-management is a key strategy for people at risk of or with type 2 diabetes, but implementation is a challenge. The objective of this study is to assess the determinants of self-management from an implementation perspective in three settings: two rural districts in Uganda, an urban township in South Africa, and socio-economically disadvantaged suburbs in Sweden. Data collection followed an exploratory multiple-case study design, integrating data from interviews, focus group discussions, and observations. Data collection and analysis were guided by a contextualized version of a transdisciplinary framework for self-management. Findings indicate that people at risk of or with type 2 diabetes are aware of major self-management strategies, but fail to integrate these into their daily lives. Depending on the setting, opportunities to facilitate implementation of self-management include: improving patient-provider interaction, improving health service delivery, and encouraging community initiatives supporting self-management. Modification of the physical environment (e.g. accessibility to healthy food) and the socio-cultural environment (i.e. norms, values, attitudes, and social support) may have an important influence on people's lifestyle. Regarding the study methodology, we learned that this innovative approach can lead to a comprehensive analysis of self-management determinants across different settings. An important barrier was the difficult contextualization of concepts like perceived autonomy and self-efficacy. Intervention studies are needed to confirm whether the pathways suggested by this study are valid and to test the proposed opportunities for change.

SUBMITTER: De Man J

PROVIDER: S-EPMC6424475 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Diabetes self-management in three different income settings: Cross-learning of barriers and opportunities.

De Man Jeroen J Aweko Juliet J Daivadanam Meena M Alvesson Helle Mölsted HM Delobelle Peter P Mayega Roy William RW Östenson Claes-Göran CG Kirunda Barbara B Kasujja Francis Xavier FX Guwattude David D Puoane Thandi T Sanders David D Peterson Stefan S Tomson Göran G Sundberg Carl Johan CJ Absetz Pilvikki P Van Olmen Josefien J

PloS one 20190319 3

The burden of type 2 diabetes is increasing rapidly, not least in Sub-Saharan Africa, and disadvantaged populations are disproportionally affected. Self-management is a key strategy for people at risk of or with type 2 diabetes, but implementation is a challenge. The objective of this study is to assess the determinants of self-management from an implementation perspective in three settings: two rural districts in Uganda, an urban township in South Africa, and socio-economically disadvantaged su ...[more]

PMID: 30889215

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Project description:BackgroundFor adolescents living with type 1 diabetes (T1D), completion of multiple daily self-management tasks, such as monitoring blood glucose and administering insulin, can be challenging because of psychosocial and contextual barriers. These barriers are hard to assess accurately and specifically by using traditional retrospective recall. Ecological momentary assessment (EMA) uses mobile technologies to assess the contexts, subjective experiences, and psychosocial processes that surround self-management decision-making in daily life. However, the rich data generated via EMA have not been frequently examined in T1D or integrated with machine learning analytic approaches.ObjectiveThe goal of this study is to develop a machine learning algorithm to predict the risk of missed self-management in young adults with T1D. To achieve this goal, we train and compare a number of machine learning models through a learned filtering architecture to explore the extent to which EMA data were associated with the completion of two self-management behaviors: mealtime self-monitoring of blood glucose (SMBG) and insulin administration.MethodsWe analyzed data from a randomized controlled pilot study using machine learning-based filtering architecture to investigate whether novel information related to contextual, psychosocial, and time-related factors (ie, time of day) relate to self-management. We combined EMA-collected contextual and insulin variables via the MyDay mobile app with Bluetooth blood glucose data to construct machine learning classifiers that predicted the 2 self-management behaviors of interest.ResultsWith 1231 day-level SMBG frequency counts for 45 participants, demographic variables and time-related variables were able to predict whether daily SMBG was below the clinical threshold of 4 times a day. Using the 1869 data points derived from app-based EMA data of 31 participants, our learned filtering architecture method was able to infer nonadherence events with high accuracy and precision. Although the recall score is low, there is high confidence that the nonadherence events identified by the model are truly nonadherent.ConclusionsCombining EMA data with machine learning methods showed promise in the relationship with risk for nonadherence. The next steps include collecting larger data sets that would more effectively power a classifier that can be deployed to infer individual behavior. Improvements in individual self-management insights, behavioral risk predictions, enhanced clinical decision-making, and just-in-time patient support in diabetes could result from this type of approach.

Project description:BackgroundDiabetic retinopathy (DR) can lead to visual impairment and blindness if not detected and treated in time. Knowing the barriers/enablers in advance in contrasting different country income settings may accelerate development of a successful DR screening (DRS) program. This would be especially applicable in the low-income settings with the rising prevalence of DR.ObjectivesThe aim of this systematic review is to identify and contrast the barriers/enablers to DRS for different contexts using both consumers i.e., people with diabetes (PwDM) and provider perspectives and system level factors in different country income settings.MethodsWe searched MEDLINE, Embase, CENTRAL in the Cochrane Library from the databases start date to December 2018. We included the studies reported on barriers and enablers to access DRS services based at health care facilities. We categorised and synthesized themes related to the consumers (individuals), providers and the health systems (environment) as main dimensions according to the constructs of social cognitive theory, supported by the quantitative measures i.e., odds ratios as reported by each of the study authors.Main resultsWe included 77 studies primarily describing the barriers and enablers. Most of the studies were from high income settings (72.7%, 56/77) and cross sectional in design (76.6%, 59/77). From the perspectives of consumers, lack of knowledge, attitude, awareness and motivation were identified as major barriers. The enablers were fear of blindness, proximity of screening facility, experiences of vision loss and being concerned of eye complications. In providers' perspectives, lack of skilled human resources, training programs, infrastructure of retinal imaging and cost of services were the main barriers. Higher odds of uptake of DRS services was observed when PwDM were provided health education (odds ratio (OR) 4.3) and having knowledge on DR (OR range 1.3-19.7).ConclusionKnowing the barriers to access DRS is a pre-requisite in development of a successful screening program. The awareness, knowledge and attitude of the consumers, availability of skilled human resources and infrastructure emerged as the major barriers to access to DRS in any income setting.

Project description:ObjectiveThe study aimed to identify the common gaps in skills and self-efficacy for diabetes self-management and explore other factors which serve as enablers of, and barriers to, achieving optimal diabetes self-management. The information gathered could provide health professionals with valuable insights to achieving better health outcomes with self-management education and support for diabetes patients.MethodsInternational online survey and telephone interviews were conducted on adults who have type 1 or type 2 diabetes. The survey inquired about their skills and self-efficacy in diabetes self-management, while the interviews assessed other enablers of, and barriers to, diabetes self-management. Surveys were analysed using descriptive and inferential statistics. Interviews were analysed using inductive thematic analysis.ResultsSurvey participants (N = 217) had type 1 diabetes (38.2%) or type 2 diabetes (61.8%), with a mean age of 44.56 SD 11.51 and were from 4 continents (Europe, Australia, Asia, America). Identified gaps in diabetes self-management skills included the ability to: recognize and manage the impact of stress on diabetes, exercise planning to avoid hypoglycemia and interpreting blood glucose pattern levels. Self-efficacy for healthy coping with stress and adjusting medications or food intake to reach ideal blood glucose levels were minimal. Sixteen participants were interviewed. Common enablers of diabetes self-management included: (i) the will to prevent the development of diabetes complications and (ii) the use of technological devices. Issues regarding: (i) frustration due to dynamic and chronic nature of diabetes (ii) financial constraints (iii) unrealistic expectations and (iv) work and environment-related factors limited patients' effective self-management of diabetes.ConclusionsEducational reinforcement using technological devices such as mobile application has been highlighted as an enabler of diabetes self-management and it could be employed as an intervention to alleviate identified gaps in diabetes self-management. Furthermore, improved approaches that address financial burden, work and environment-related factors as well as diabetes distress are essential for enhancing diabetes self-management.

Project description:ImportanceA patient’s perceived barriers to diabetes self-management (DSM) may affect his or her risk of diabetic retinopathy (DR); however, few studies have examined this association.ObjectiveTo examine the association between perceived barriers to DSM and the severity spectrum of DR in Asian patients with type 2 diabetes.Design, setting, and participantsA cross-sectional clinic-based study, the Singapore Diabetes Management Project, was conducted from December 28, 2010, to March 20, 2013, at the Singapore National Eye Centre, a tertiary eye care institute. After excluding patients with type 1 diabetes and ungradable fundus images, 361 participants were included in the analyses. Statistical analysis was conducted from July 20 to September 8, 2017.ExposureThe degree of perceived barriers to DSM was assessed using a 23-item questionnaire comprising items about knowledge of DSM, access to care, and confidence in health care professionals. Rasch analysis was used to optimize the scale’s psychometric properties, with lower scores indicating a higher degree of self-perceived barriers.Main outcomes and measuresDiabetic retinopathy was graded from 2-field retinal images into categories of no DR (Early Treatment Diabetic Retinopathy Study levels 10-15; n = 154), mild to moderate DR (levels 20-43; n = 112), and severe DR (levels ≥53 and/or presence of clinically significant macular edema; n = 95) using the modified Airlie House classification system of DR. Multinomial logistic regression models were used to assess the association between perceived barriers and severity of DR in the worse-affected eye.ResultsAmong the 361 participants (105 women and 256 men; mean [SD] age, 57 [8] years), a greater magnitude of perceived barriers to DSM was independently associated with higher odds of having any DR (odds ratio, 1.32; 95% CI, 1.06-1.66), mild to moderate DR (odds ratio, 1.30; 95% CI, 1.01-1.68), and severe DR (odds ratio, 1.36; 95% CI, 1.03-1.79). This association was independent of diabetes control (hemoglobin A1c, blood pressure, and lipid levels), presenting visual acuity, and socioeconomic indicators.Conclusions and relevanceThese results suggest that greater perceived barriers to DSM are independently associated with severity of DR. Although longitudinal data are needed, these findings suggest that evidence-based interventions to reduce patient-, practitioner-, and system-related barriers to diabetes care may help reduce the risk of DR.

Project description:BackgroundLower socioeconomic status is associated with excess disease burden from diabetes. Diabetes self-management support interventions are needed that are effective in engaging lower income patients, addressing competing life priorities and barriers to self-care, and facilitating behavior change.ObjectiveTo pilot test feasibility, acceptability, and effect on disease control of a problem-based diabetes self-management training adapted for low literacy and accessibility.DesignTwo-arm randomized controlled trial powered to detect a 0.50% change in A1C at follow-up with a 2-sided alpha of 0.05 in a pooled analysis.ParticipantsFifty-six urban African-American patients with type 2 diabetes and suboptimal blood sugar, blood pressure, or cholesterol control recruited from a diabetes registry within a university-affiliated managed care organization.InterventionsA group, problem-based diabetes self-management training designed for delivery in an intensive and a condensed program format. Three intensive and three condensed program groups were conducted during the trial.Main measuresClinical (A1C, systolic blood pressure [SBP], diastolic blood pressure [DBP], LDL and HDL cholesterol) and behavioral (knowledge, problem solving, self-management behavior) data were measured at baseline, post-intervention, and 3 months post-intervention (corresponding with 6-9 months following baseline).ResultsAdoption of both programs was high (>85% attendance rates, 95% retention). At 3 months post-intervention, the between-group difference in A1C change was -0.72% (p?=?0.02), in favor of the intensive program. A1C reduction was partially mediated by problem-solving skill at follow-up (ß = -0.13, p?=?0.04). Intensive program patients demonstrated within-group improvements in knowledge (p?<?0.001), problem-solving (p?=?0.01), and self-management behaviors (p?=?0.04). Among the subsets of patients with suboptimal blood pressure or lipids at baseline, the intensive program yielded clinically significant individual improvements in SBP, DBP, and LDL cholesterol. Patient satisfaction and usability ratings were high for both programs.ConclusionsA literacy-adapted, intensive, problem-solving-based diabetes self-management training was effective for key clinical and behavioral outcomes in a lower income patient sample.

Dataset Information

Diabetes self-management in three different income settings: Cross-learning of barriers and opportunities.

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Diabetes self-management in three different income settings: Cross-learning of barriers and opportunities.

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