The question of which factors drive human eating and nutrition is a key issue in many branches of science. We describe the creation, evaluation, and updating of an interdisciplinary, interactive, and evolving "framework 2.0" of Determinants Of Nutrition and Eating (DONE). The DONE framework was created by an interdisciplinary workgroup in a multiphase, multimethod process. Modifiability, relationship strength, and population-level effect of the determinants were rated to identify areas of priority for research and interventions. External experts positively evaluated the usefulness, comprehensiveness, and quality of the DONE framework. An approach to continue updating the framework with the help of experts was piloted. The DONE framework can be freely accessed (http://uni-konstanz.de/DONE) and used in a highly flexible manner: determinants can be sorted, filtered and visualized for both very specific research questions as well as more general queries. The dynamic nature of the framework allows it to evolve as experts can continually add new determinants and ratings. We anticipate this framework will be useful for research prioritization and intervention development.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289713 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171077 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
TAD-SIE: sample size estimation for clinical randomized controlled trials using a Trend-Adaptive Design with a Synthetic-Intervention-Based Estimator.
Trials
January 2025
Department of Electrical and Computer Engineering, Princeton University, Princeton, 08544, NJ, USA.
Background: Phase-3 clinical trials provide the highest level of evidence on drug safety and effectiveness needed for market approval by implementing large randomized controlled trials (RCTs). However, 30-40% of these trials fail mainly because such studies have inadequate sample sizes, stemming from the inability to obtain accurate initial estimates of average treatment effect parameters.
Methods: To remove this obstacle from the drug development cycle, we present a new algorithm called Trend-Adaptive Design with a Synthetic-Intervention-Based Estimator (TAD-SIE) that powers a parallel-group trial, a standard RCT design, by leveraging a state-of-the-art hypothesis testing strategy and a novel trend-adaptive design (TAD).
Physician wellbeing in a national rehabilitation hospital, a qualitative study utilizing Maslow's hierarchy of needs as a framework for analysis.
BMC Health Serv Res
January 2025
Henley Business School, University of Reading, Reading, RG9 3AU, UK.
Background: Globally, healthcare systems are experiencing a workforce crisis which has been exacerbated by the COVID19 pandemic. Numerous reports have documented the deterioration of healthcare professional wellbeing with burnout being called the new pandemic. Rehabilitation Medicine Physicians are among the most likely specialties to experience burnout.
View Article and Find Full Text PDFEvaluation of undergraduate forensic medicine education in Nepal: a critical analysis using Schwab's five commonplaces and Schubert's curriculum images.
BMC Med Educ
January 2025
Department of Forensic Medicine, Karnali Academy of Health Sciences, Chandannath, Jumla, 21200, Nepal.
Following the establishment of Nepal's first medical college in 1972, forensic medicine was introduced in 1978. To date, 25 medical colleges in the country have included forensic medicine as a compulsory subject in the undergraduate medical curriculum. Although this subject has been introduced into the medical curriculum, the outcome is unsatisfactory, as reflected by the poor medico-legal reports prepared by newly graduated medical students.
View Article and Find Full Text PDFAI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
Statistical flaws of the fitness-fatigue sports performance prediction model.
Sci Rep
January 2025
Seenovate, Paris, 75009, France.
Optimizing athletic training programs with the support of predictive models is an active research topic, fuelled by a consistent data collection. The Fitness-Fatigue Model (FFM) is a pioneer for modelling responses to training on performance based on training load exclusively. It has been subject to several extensions and its methodology has been questioned.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!