Evaluation of a Newly Developed Smartphone App for Risk Factor Management in Young Patients With Ischemic Stroke: A Pilot Study

The contribution of various risk factors to the burden of stroke worldwide is unknown, particularly in countries of low and middle income. We aimed to establish the association of known and emerging risk factors with stroke and its primary subtypes, assess the contribution of these risk factors to the burden of stroke, and explore the differences between risk factors for stroke and myocardial infarction. We undertook a standardised case-control study in 22 countries worldwide between March 1, 2007, and April 23, 2010. Cases were patients with acute first stroke (within 5 days of symptoms onset and 72 h of hospital admission). Controls had no history of stroke, and were matched with cases for age and sex. All participants completed a structured questionnaire and a physical examination, and most provided blood and urine samples. We calculated odds ratios (ORs) and population-attributable risks (PARs) for the association of all stroke, ischaemic stroke, and intracerebral haemorrhagic stroke with selected risk factors. In the first 3000 cases (n=2337, 78%, with ischaemic stroke; n=663, 22%, with intracerebral haemorrhagic stroke) and 3000 controls, significant risk factors for all stroke were: history of hypertension (OR 2.64, 99% CI 2.26-3.08; PAR 34.6%, 99% CI 30.4-39.1); current smoking (2.09, 1.75-2.51; 18.9%, 15.3-23.1); waist-to-hip ratio (1.65, 1.36-1.99 for highest vs lowest tertile; 26.5%, 18.8-36.0); diet risk score (1.35, 1.11-1.64 for highest vs lowest tertile; 18.8%, 11.2-29.7); regular physical activity (0.69, 0.53-0.90; 28.5%, 14.5-48.5); diabetes mellitus (1.36, 1.10-1.68; 5.0%, 2.6-9.5); alcohol intake (1.51, 1.18-1.92 for more than 30 drinks per month or binge drinking; 3.8%, 0.9-14.4); psychosocial stress (1.30, 1.06-1.60; 4.6%, 2.1-9.6) and depression (1.35, 1.10-1.66; 5.2%, 2.7-9.8); cardiac causes (2.38, 1.77-3.20; 6.7%, 4.8-9.1); and ratio of apolipoproteins B to A1 (1.89, 1.49-2.40 for highest vs lowest tertile; 24.9%, 15.7-37.1). Collectively, these risk factors accounted for 88.1% (99% CI 82.3-92.2) of the PAR for all stroke. When an alternate definition of hypertension was used (history of hypertension or blood pressure >160/90 mm Hg), the combined PAR was 90.3% (85.3-93.7) for all stroke. These risk factors were all significant for ischaemic stroke, whereas hypertension, smoking, waist-to-hip ratio, diet, and alcohol intake were significant risk factors for intracerebral haemorrhagic stroke. Our findings suggest that ten risk factors are associated with 90% of the risk of stroke. Targeted interventions that reduce blood pressure and smoking, and promote physical activity and a healthy diet, could substantially reduce the burden of stroke. Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada, Canadian Stroke Network, Pfizer Cardiovascular Award, Merck, AstraZeneca, and Boehringer Ingelheim. Copyright 2010 Elsevier Ltd. All rights reserved.

Over the period 1987–1991 an inter-disciplinary five-country group developed the EuroQol instrument, a five-dimensional three-level generic measure subsequently termed the ‘EQ-5D’. It was designed to measure and value health status. The salient features of its development and its consolidation and expansion are discussed. Initial expansion came, in particular, in the form of new language versions. Their development raised translation and semantic issues, experience with which helped feed into the design of two further instruments, the EQ-5D-5L and the youth version EQ-5D-Y. The expanded usage across clinical programmes, disease and condition areas, population surveys, patient-reported outcomes, and value sets is outlined. Valuation has been of continued relevance for the Group as this has allowed its instruments to be utilised as part of the economic appraisal of health programmes and their incorporation into health technology assessments. The future of the Group is considered in the context of: (1) its scientific strategy, (2) changes in the external environment affecting the demand for EQ-5D, and (3) a variety of issues it is facing in the context of the design of the instrument, its use in health technology assessment, and potential new uses for EQ-5D outside of clinical trials and technology appraisal. Electronic supplementary material The online version of this article (doi:10.1007/s40258-017-0310-5) contains supplementary material, which is available to authorized users.

Several health behavior theories converge on the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. However, inferences regarding the relation between these cognitions and intention or behavior rest largely on correlational data that preclude causal inferences. To determine whether changing attitudes, norms, or self-efficacy leads to changes in intentions and behavior, investigators need to randomly assign participants to a treatment that significantly increases the respective cognition relative to a control condition, and test for differences in subsequent intentions or behavior. The present review analyzed findings from 204 experimental tests that met these criteria.