The aim of this study was to examine the validity of the English version of the PREvencion con DIetaMEDiterranea (PREDIMED) 14-item Mediterranean Diet Adherence Screener (MEDAS), a brief questionnaire assessing adherence to the Mediterranean diet (MedDiet), which was used in the PREDIMED trial for assessment and immediate feedback. This instrument (MEDAS) was administered to 96 adults with a high cardiovascular risk (66% women, mean age 68.3 ± 6.0 years), recruited from general practices in Bristol, UK. Participants then completed a 3-day estimated food record, and the MEDAS was administered again one month later. A MedDiet score (range = 0–14) was calculated from the MEDAS’ administrations and food record to assess concurrent validity and test-retest reliability. Predictive validity was assessed by examining the association of the MEDAS-derived score with cardiometabolic risk factors and dietary intakes derived from the food records. The MEDAS-derived MedDiet score was higher by 1.47 points compared to food records (5.47 vs.4.00, p < 0.001), correlated moderately with the record-derived score (r = 0.50, p < 0.001; ICC = 0.53, p < 0.001) and there was borderline fair agreement between the two methods (κ = 0.19, 95% CI 0.07–0.31, p = 0.002; 95% limits of agreement −2.2, 5.1). Exact agreement within score categories and gross misclassificationwere 45.8% and 21.9%, respectively. The distribution of dietary intakes, reported on the food records by the MEDAS-derived total MedDiet score, was in the expected direction, but no association was observed with cardiometabolic risk factors. The two administrations of the MEDAS produced similar mean total MedDiet scores (5.5 vs. 5.4, p = 0.706), which were correlated (r and ICC = 0.69, p < 0.001) and agreed fairly (κ = 0.38, 95% CI 0.24–0.52, p < 0.001; 95% limits of agreement −3.1, 3.2). The English version of the MEDAS has acceptable accuracy and reliability for assessing MedDiet adherence among individuals with a high cardiovascular risk, in the UK, and can be used to rank individuals according to MedDiet adherence in research and practice.

Diagnosis with Type 2 Diabetes is an opportunity for individuals to change their physical activity and dietary behaviours. Diabetes treatment guidelines recommend theory-based, patient-centred care and advocate the provision of support for patient motivation but the motivational experiences of people newly diagnosed with diabetes have not been well studied. Framed in self-determination theory, this study aimed to qualitatively explore how this patient group articulate and experience different types of motivation when attempting lifestyle change. A secondary analysis of semi-structured interview data collected with 30 (n female = 18, n male = 12) adults who had been newly diagnosed with type two diabetes and were participants in the Early ACTID trial was undertaken. Deductive directed content analysis was performed using NVivo V10 and researcher triangulation to identify and describe patient experiences and narratives that reflected the motivation types outlined in self-determination theory and if/how these changed over time. The findings revealed the diversity in motivation quality both between and within individuals over time and that patients with newly-diagnosed diabetes have multifaceted often competing motivations for lifestyle behaviour change. Applying self-determination theory, we identified that many participants reported relatively dominant controlled motivation to comply with lifestyle recommendations, avoid their non-compliance being “found out” or supress guilt following lapses in behaviour change attempts. Such narratives were accompanied by experiences of frustrating slow behaviour change progress. More autonomous motivation was expressed as something often achieved over time and reflected goals to improve health, quality of life or family time. Motivational internalisation was evident and some participants had integrated their behaviour change to a new way of life which they found resilient to common barriers. Motivation for lifestyle change following diagnosis with type two diabetes is complex and can be relatively low in self-determination. To achieve the patient empowerment aspirations of current national health care plans, intervention developers, and clinicians would do well to consider the quality not just quantity of their patients’ motivation. ISRCTN ISRCTN92162869 . Retrospectively registered

Objective: Little is known about adolescents’ non-core food intake in the UK and the eating context in which they consume non-core foods. The present study aimed to describe types of non-core foods consumed by British adolescents in total and across different eating contexts.Design: A descriptive analysis, using cross-sectional data from food diaries. Non-core foods were classified based on cut-off points of fat and sugar from the Australian Guide to Healthy Eating. Eating context was defined as ‘where’ and ‘with whom’ adolescents consumed each food. Percentages of non-core energy were calculated for each food group in total and across eating contexts. A combined ranking was then created to account for each food’s contribution to non-core energy intake and its popularity of consumption (percentage of consumers).Setting: The UK National Diet and Nutrition Survey 2008–2011.Subjects: Adolescents across the UK aged 11–18 years (n 666).Results: Non-core food comprised 39·5 % of total energy intake and was mostly ‘Regular soft drinks’, ‘Crisps & savoury snacks’, ‘Chips & potato products’, ‘Chocolate’ and ‘Biscuits’. Adolescents ate 57·0 % and 51·3 % of non-core food at ‘Eateries’ or with ‘Friends’, compared with 33·2 % and 32·1 % at ‘Home’ or with ‘Parents’. Persistent foods consumed across eating contexts were ‘Regular soft drinks’ and ‘Chips & potato products’.Conclusions: Regular soft drinks contribute the most energy and are the most popular non-core food consumed by adolescents regardless of context, and represent a good target for interventions to reduce non-core food consumption.

Objective: To conduct formative research using qualitative methods among stakeholders of secondary schools to explore their perceptions, barriers and facilitators related to healthy eating and physical activity (PA) among Malaysian adolescents.Design: A qualitative study involving eight focus groups and twelve in-depth interviews. Focus groups and interviews were recorded and transcribed verbatim. An inductive thematic analysis approach was used to analyse the data.Setting: Four secondary schools in Perak and Selangor states (two urban and two rural schools) in Malaysia.Participants: Focus groups were conducted with seventy-six adolescents aged 13–14 years, and in-depth interviews were conducted with four headmasters, four PA education teachers and four food canteen operators.Results: Stakeholders thought that adolescents’ misperceptions, limited availability of healthy options, unhealthy food preferences and affordability were important challenges preventing healthy eating at school. Low-quality physical education (PE) classes, limited adolescent participation and teachers’ commitment during lessons were perceived as barriers to adolescents being active at school. Affordability was the main challenge for adolescents from rural schools. Stakeholders perceived that a future school-based intervention should improve the availability and subsidies for healthy foods, provide health education/training for both adolescents and PE teachers, enhance active adolescent participation in PE and develop social support mechanisms to facilitate engagement with PA.Conclusions: These findings provide important insights into developing school-based lifestyle interventions to improve healthy eating and strengthening PA of Malaysian adolescents.

Established methods for nutritional assessment suffer from a number of important limitations. Diaries are burdensome to complete, food frequency questionnaires only capture average food intake, and both suffer from difficulties in self estimation of portion size and biases resulting from misreporting. Online and app versions of these methods have been developed, but issues with misreporting and portion size estimation remain. New methods utilizing passive data capture are required that address reporting bias, extend timescales for data collection, and transform what is possible for measuring habitual intakes. Digital and sensing technologies are enabling the development of innovative and transformative new methods in this area that will provide a better understanding of eating behavior and associations with health. In this article we describe how wrist-worn wearables, on-body cameras, and body-mounted biosensors can be used to capture data about when, what, and how much people eat and drink. We illustrate how these new techniques can be integrated to provide complete solutions for the passive, objective assessment of a wide range of traditional dietary factors, as well as novel measures of eating architecture, within person variation in intakes, and food/nutrient combinations within meals. We also discuss some of the challenges these new approaches will bring.

In recent years, recommender systems have been employed in domains like e-commerce, tourism, and multimedia streaming, where personalising users’ experience based on their interactions is a fundamental aspect to consider. Recent recommender system developments have also focused on well-being, yet existing solutions have been entirely designed considering one single well-being aspect in isolation, such as a healthy diet or an active lifestyle. This research introduces EvoRecSys, a novel recommendation framework that proposes evolutionary algorithms as the main recommendation engine, thereby modelling the problem of generating personalised well-being recommendations as a multi-objective optimisation problem. EvoRecSys captures the interrelation between multiple aspects of well-being by constructing configurable recommendations in the form of bundled items with dynamic properties. The preferences and a predefined well-being goal by the user are jointly considered. By instantiating the framework into an implemented model, we illustrate the use of a genetic algorithm as the recommendation engine. Finally, this implementation has been deployed as a Web application in order to conduct a users’ study.