Objectives: Lack of clarity on the definition of "patient engagement" has been highlighted as a barrier to fully implementing patient engagement in research. This study identified themes within existing definitions related to patient engagement and proposes a consensus definition of "patient engagement in research." Methods: A systematic review was conducted to identify definitions of patient engagement and related terms in published literature (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018). Definitions were extracted and qualitatively analyzed to identify themes and characteristics. A multistakeholder approach, including academia, industry, and patient representation, was taken at all stages. A proposed definition is offered based on a synthesis of the findings.Results: Of 1821 abstracts identified and screened for eligibility, 317 were selected for full-text review. Of these, 169 articles met inclusion criteria, from which 244 distinct definitions were extracted for analysis. The most frequently defined terms were: "patient-centered" (30.5%), "patient engagement" (15.5%), and "patient participation" (13.4%). The majority of definitions were specific to the healthcare delivery setting (70.5%); 11.9% were specific to research. Among the definitions of "patient engagement," the most common themes were "active process," "patient involvement," and "patient as participant." In the research setting, the top themes were "patient as partner," "patient involvement," and "active process"; these did not appear in the top 3 themes of nonresearch definitions. Conclusion:Distinct themes are associated with the term "patient engagement" and with engagement in the "research" setting. Based on an analysis of existing literature and review by patient, industry, and academic stakeholders, we propose a scalable consensus definition of "patient engagement in research."

IntroductionThe obesity epidemic has drawn attention to food marketing practices that may increase the likelihood of caloric overconsumption and weight gain. We explored the associations of discounted prices on supermarket purchases of selected high-calorie foods (HCF) and more healthful, low-calorie foods (LCF) by a demographic group at high risk of obesity.MethodsOur mixed methods design used electronic supermarket purchase data from 82 low-income (primarily African American female) shoppers for households with children and qualitative data from focus groups with demographically similar shoppers.ResultsIn analyses of 6,493 food purchase transactions over 65 weeks, the odds of buying foods on sale versus at full price were higher for grain-based snacks, sweet snacks, and sugar-sweetened beverages (odds ratios: 6.6, 5.9, and 2.6, respectively; all P < .001) but not for savory snacks. The odds of buying foods on sale versus full price were not higher for any of any of the LCF (P ≥ .07). Without controlling for quantities purchased, we found that spending increased as percentage saved from the full price increased for all HCF and for fruits and vegetables (P ≤ .002). Focus group participants emphasized the lure of sale items and took advantage of sales to stock up.ConclusionStrategies that shift supermarket sales promotions from price reductions for HCF to price reductions for LCF might help prevent obesity by decreasing purchases of HCF.

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A 1 -A 3 1 8 sequence of medication initiation for prevention of these two events among type 2 diabetic patients in Singapore. Our study patients are newly diagnosed type 2 diabetic patients at National Healthcare Group polyclinics of Singapore in 2007 and patients are followed up for 8 years. We also compare model-derived treatment strategy with current protocol and no control baseline in Singapore by evaluating the cost-effectiveness. The effectiveness is measured by patients' quality adjusted life years (QALYs) and the cost includes patient direct cost. A Markov decision process model has been developed to determine optimal treatment decisions on timing and sequence of medication initiation for controlling blood pressure and cholesterol level over patients' lifetime. The model considers the following major risk factors, age, HbA1c, systolic blood pressure, total cholesterol, high-density lipoprotein. These are used to describe patient health states. We use Singapore Coronary Risk Score and the calibrated United Kingdom Prospective Diabetic Study model to estimate the risks of CHD and stroke among Singapore diabetic population, respectively. Treatment decisions are made on a yearly basis from age 40 to 100. Using the developed model, preliminary analysis demonstrates the reduction on the total medication initiations and the improvement on expected QALYs compared with the current practice. The proposed model would facilitate evidencebased clinical decision making process and help clinicians to make informed and comprehensive treatment decisions for type 2 diabetic patients by incorporating the comparative cost-effectiveness.