Strengthening the reporting of diet item details in feeding studies measuring the dietary metabolome: The DID-METAB core outcome set statement

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Future directions in personality, occupational and medical selection: myths, misunderstandings, measurement, and suggestions

This paper has two objectives: (1) presenting recent advances in the personality field concerning the conceptualization of personality arising from the dynamic interactions of behaviour, biology, context, and states, and (2) discussing the implications of these developments for medical selection. We start by presenting evidence that traits are not longer regarded as deterministic and stable. Instead, they are found to change across generations, the life span, and in response to environmental contingencies. Next, drawing on recent research (behavioural reaction norms and the density distribution model) we posit how the expression of trait relevant behaviour changes depending on the situation, such that personality reflects both stability and plasticity across situations. Thus there is an urgent need to explore how traits change as function of medical education. Third, we demystify that some traits are better than others showing that so-called “good” traits have a dark-side. Fourth, we show how these developments impact on how personality might be assessed, thereby presenting recent evidence on the use of contextualized personality measures, Situational Judgment Tests, other reports, and implicit measures. Throughout the paper, we outline the key implications of these developments for medical selection practices

Strengthening the reporting of diet item details in feeding studies measuring the dietary metabolome: The DID-METAB core outcome set statement

Strengthening the reporting of diet item details in feeding studies measuring the dietary metabolome: The DID-METAB core outcome set statemen

A call for standardised age-disaggregated health data

The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management