Policy-makers are increasingly turning to behavioral science for insights about how to improve citizens’ decisions and outcomes.
Typically, different scientists test different intervention ideas in different samples using different outcomes over different time intervals. The lack of comparability of such individual investigations limits their potential to inform policy.
Recently, to address this limitation and accelerate the pace of discovery, researchers introduced the mega-study—a massive field experiment in which the effects of many different interventions are compared in the same population on the same objectively measured outcome for the same duration.
In a mega-study targeting physical exercise among 61,293 members of an American fitness chain, 30 scientists from 15 different US universities worked in small independent teams to design a total of 54 different four-week digital programs (or interventions) encouraging exercise.
Scientists show that 45% of these interventions significantly increased weekly gym visits by 9% to 27%; the top-performing intervention offered micro-rewards for returning to the gym after a missed workout.
Only 8% of interventions induced behavior change that was significant and measurable after the four-week intervention.
Conditioning on the 45% of interventions that increased exercise during the intervention, they detected carry-over effects that were proportionally similar to those measured in previous research.
Forecasts by impartial judges failed to predict which interventions would be most effective, underscoring the value of testing many ideas at once and, therefore, the potential for mega-studies to improve the evidentiary value of behavioral science.
Published: 08 December 2021
source:
https://www.nature.com/articles/s41586-021-04128-4
https://doi.org/10.1038/s41586-021-04128-4
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