Resources

The Blursday database contains repeated measures of subjective time and related processes collected during the COVID-19 pandemic. The more isolated individuals felt, the slower time seemed to pass.

Van Bree et al. present the Brain Time Toolbox which warps electrophysiology data in line with the brain’s dynamics. This procedure overcomes the issue that the clock time format of brain data is out of synchrony with a dynamic brain that uses its own regime of time.

This Resource describes the data from a survey on COVID-19 related behaviours, beliefs and norms. From July 2020 to March 2021, the authors fielded a global survey on people’s baseline beliefs, behaviours and norms related to COVID-19 in 67 countries, yielding over 2 million responses.

Yaron and colleagues collected and classified 412 experiments relating to four leading theories in consciousness research, providing a comprehensive overview of the field and unravelling trends and methodological biases.

Benjamin et al. construct polygenic indexes (DNA-based predictors) for 47 phenotypes and make them available to researchers in 11 datasets. They also present a theoretical framework and estimator to help interpret analyses using polygenic indexes.

The Our World in Data COVID-19 vaccination tracker charts the scale and rate of global vaccinations against COVID-19, making the data available to scientists, policymakers and the general public

This study introduces a public dataset that finds that school closures in the United States have been more common in schools with lower math scores and higher rates of students from racial minorities, who experience homelessness, and who have lower incomes.

The Oxford COVID-19 Government Response Tracker (OxCGRT) records data on 19 different government COVID-19 policy indicators for over 190 countries. Covering closure and containment, health and economics measures, it creates an evidence base for effective responses.

The COVID-19 Real-Time Event Risk Assessment Planning Tool allows individuals to assess risk associated with attending events of different sizes via a real-time, interactive website and helps individuals assess whether this risk is worth taking.

Specification curve analysis enables large numbers of alternative empirical analyses to be performed on the same data, showcasing how analytical decisions influence results and allowing joint inference over all analyses.

The COVID-19 Government Response Event Dataset (CoronaNet v.1.0) compiles real time, publicly available (https://coronanet-project.org) data on policy announcements made in response to the COVID-19 pandemic across the world.

On the basis of the IMAGEN database of 2,000 Caucasian adolescents, Jia et al identify neural patterns of activity during reward anticipation and motor inhibition associated with different externalising symptoms for ADHD and conduct problems.

This Resource introduces a new public database that enables researchers to re-analyse a large corpus of studies into meta-cognitive confidence judgements.

What techniques can individuals use to change their own behaviour? Knittle et al. assembled a compendium of 123 self-enactable techniques individuals can use to change or self-manage their motivation and behaviour.

Human electrocorticographic (ECoG) data are of great value but are not widely available. Miller shares ECoG data and analysis code from 16 experiments involving 34 different patients for open re-use.

Behaviour-change theories need to be more precisely specified. Five of the major theories can be formally represented using a system involving construct labels, construct definitions and defined binary relationships between constructs.

Hollands and colleagues classify possible interventions regarding the selection, purchase and consumption of food, alcohol and tobacco. The TIPPME framework enables systematic reporting and analysis of health-related behavioural change interventions.