Some ongoing projects 

Here we list some of the projects we are working on these days. You can find our published studies here.

A mega-study testing the effectiveness of scaleable digital interventions  targeting wellbeing

We are now in the preparatory phase of a large-scale (n > 100 000 ) multi-arm randomized control trial where we will compare the effectiveness of different kinds of scaleable interventions improving happiness and wellbeing, and build a model to predict which works for whom.

Before starting the intervention phase, we are working on two sub-projects: 1) We conduct a mega meta-analysis where we aim to collect all the available scientific evidence on the effectiveness of different interventions. 2) We review the 50 most popular books to investigate which ideas appear the most strongly and we also collect aim to collect further intervention ideas. 

Improving family life through increasing the involvement of fathers 

Fathers' involvement is critical to the mental and physical well-being of children and their future. Yet, fathers are sorely missing from families. To bring back fathers to families, we aim to conduct a large-scale multi-arm randomized control trial (with the involvement of 100 000+ families) where we compare the effectiveness of different kinds of scaleable interventions that increase the involvement of fathers in the life of families and we aim to build a model to predict which intervention works for which family

In the first phase of the project, we worked with Telekom, and in a systematic exploration process involving +200 family therapists and deep interviews with families, we identified good and bad paternal behaviors in families, their potential impact on family functioning, and then selected and propose target behaviors that can be changed to achieve the greatest social impact. 


Reducing educational inequality

The performance difference of rich and poor children on high-stakes exams can influence the life course of disadvantaged children by affecting their access to secondary and higher education and thus to economic opportunities. If the content of these high-stakes examinations has a disproportionately negative effect on low socioeconomic status (SES) children, it could aggravate socio-economic disparities by changing access to education. In the present study, we examine data from real-life testing situations involving 350 million question responses from, 3 million children and +30 countries to reveal when and to what extent does the wording of the exams deteriorate the performance of low SES children disproportionately and how these inequities can be avoided. Our goal is 1) to predict in previously unseen exam texts whether the text negatively affects the poor children and 2) to develop a guideline on how to create fairer examinations across the globe.


Estimating analytical robustness of empirical sciences (Multi100, Multiverse100)

In these projects, we recruited multiple analysts to independently test a selected hypothesis from 100 published papers from the behavioral and social sciences. More than +1000 research analysts volunteered from all over the world to independently analyze the selected claims for each study. Results from the project provide insights into the extent to which different analysts arrive at the same conclusions and at the same effect estimates. By this, we aim to increase the robustness of scientific results by estimating the degree to which published conclusions and results are robust to the analytical choices of analysts.


Citizens are insensitive to the income of the Top 1%

In many developed countries, the growth in economic inequality is primarily driven by rising income shares at the very top of the income distribution. Here, we argue that citizens uniquely underestimate the amount of income held by the top 1% of the population, and provide supporting evidence from five studies in support of this prediction (total N = 78,002), including representative samples, longitudinal data from 40 countries, and pre-registered incentive-compatible experiments. Our studies reveal that this misperception is a uniquely defining feature of the top 1% of the income distribution and does not extend to lower income percentiles. Critically, we find that this effect is driven in part by scope insensitivity, a cognitive bias that reduces how sensitive citizens are to increases in income at higher absolute income levels. While the perception of inequality is often touted as a critical facilitator to more widespread support of redistributive policies, our theory and findings highlight a key challenge to citizens’ recognition of inequality when it is concentrated among the top 1%.