Upscaling of medication adherence interventions to routine care is still challenging. This realist theory-inspired review aimed to assess which intervention aspects are potentially important for the scalability of effective cardiovascular disease (CVD) medication adherence interventions and how they are reported in effectiveness studies. A total of 4097 articles from four databases were screened of which ultimately 31 studies were included. Relevant information on scalability was extracted using a theoretic framework based on the scalability assessment tool used in the QUALIDEC study for the following domains: (i) innovation, (ii) implementers and patients, (iii) adopting organizations and health system, and (iv) socio-political context. Extracted articles were analysed for themes and chains of inference, which were grouped based on commonality and source of evidence to form new hypotheses. Six different domains relevant for scalability of adherence interventions were identified: (1) Complexity of the intervention; (2) training; (3) customization of the intervention; (4) drivers of the intervention; (5) technical interventions; and (6) stakeholder involvement. These six domains might be useful for the development of more scalable interventions by bridging the gap between research and practice. Data relevant for scalability is not well reported on in effectiveness trials for CVD medication adherence interventions and only limited data on scalability has been published in additional papers. We believe the adoption and reach of effective CVD medication adherence interventions will improve with increased awareness for the necessity of scalability in all phases of intervention development.
PurposeThe purpose of this study is to investigate medication intake, perceived barriers and their correlates in adults with type 1 or type 2 diabetes.MethodsIn this cross-sectional study, 3,383 Dutch adults with diabetes (42% type 1; 58% type 2) completed the 12-item ‘Adherence Starts with Knowledge’ questionnaire (ASK-12; total score range: 12-60) and reported socio-demographics, clinical and psychological characteristics and health behaviors. Univariable and multivariable logistic regression analyses were used.ResultsAdults with type 1 diabetes had a slightly lower mean ASK-12 score (i.e. more optimal medication intake and fewer perceived barriers) than adults with non-insulin-treated type 2 diabetes. After adjustment for covariates, correlates with suboptimal intake and barriers were fewer severe hypoglycemic events and more depressive symptoms and diabetes-specific distress. In type 2 diabetes, correlates were longer diabetes duration, more depressive symptoms and diabetes-specific distress.ConclusionsAdults with type 1 diabetes showed slightly more optimal medication intake and fewer perceived barriers than adults with non-insulin treated type 2 diabetes. Correlates differed only slightly between diabetes types. The strong association with depressive symptoms and diabetes-specific distress in both diabetes types warrants attention, as improving these outcomes in some people with diabetes might indirectly improve medication intake.
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