Selected Publications

People have never played more video games, and many stakeholders are worried that this activity might be bad for players. So far, research has not had adequate data to test whether these worries are justified and if policymakers should act to regulate video game play time. We attempt to provide much-needed evidence with adequate data. Whereas previous research had to rely on self-reported play behaviour, we collaborated with two games companies, Electronic Arts and Nintendo of America, to obtain players’ actual play behaviour. We surveyed players of Plantsvs.Zombies: Battle for Neighborville and Animal Crossing: New Horizons for their well-being, motivations and need satisfaction during play, and merged their responses with telemetry data (i.e. logged game play). Contrary to many fears that excessive play time will lead to addiction and poor mental health, we found a small positive relation between game play and affective well-being. Need satisfaction and motivations during play did not interact with play time but were instead independently related to well-being. Our results advance the field in two important ways. First, we show that collaborations with industry partners can be done to high academic standards in an ethical and transparent fashion. Second, we deliver much-needed evidence to policymakers on the link between play and mental health.
Royal Society Open Science, 2021

Through communication technology, users find themselves constantly connected to others to such an extent that they routinely develop a mind-set of connectedness. This mind-set has been defined as online vigilance. Although there is a large body of research on media use and well-being, the question of how online vigilance impacts well-being remains unanswered. In this preregistered study, we combine experience sampling and smartphone logging to address the relation of online vigilance and affective well-being in everyday life. Seventy-five Android users answered eight daily surveys over five days (N = 1,615) whilst having their smartphone use logged. Thinking about smartphone-mediated social interactions (i.e., the salience dimension of online vigilance) was negatively related to affective well-being. However, it was far more important whether those thoughts were positive or negative. No other dimension of online vigilance was robustly related to affective well-being. Taken together, our results suggest that online vigilance does not pose a serious threat to affective well-being in everyday life.
Media Psychology, 2020

In the last 10 years, many canonical findings in the social sciences appear unreliable. This so-called “replication crisis” has spurred calls for open science practices, which aim to increase the reproducibility, replicability, and generalizability of findings. Communication research is subject to many of the same challenges that have caused low replicability in other fields. As a result, we propose an agenda for adopting open science practices in Communication, which includes the following seven suggestions: (1) publish materials, data, and code; (2) preregister studies and submit registered reports; (3) conduct replications; (4) collaborate; (5) foster open science skills; (6) implement Transparency and Openness Promotion Guidelines; and (7) incentivize open science practices. Although in our agenda we focus mostly on quantitative research, we also reflect on open science practices relevant to qualitative research. We conclude by discussing potential objections and concerns associated with open science practices.
Journal of Communication, 2020

Recent Posts

What this post is about There’s quite the fuzz about ‘objective’ measures of technology use. When we study the effects of tech use on well-being, we often just ask people to report how much they used tech. Turns out, people aren’t really good at estimating their tech use. When we compare their subjective estimates to logged tech use (hence ‘objective’), the correlation between the two is rather low as this meta-analysis reports.

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What this post is about Creating data Creating a violin plot (with wrong errors bars) Creating another plot (with error bars that’re still wrong) The last plot (this time correct) What this post is about Personally, I find violin plots with error bars a great way to present repeated-measures data from experiments, as they show the data distribution as well as the uncertainty surrounding the mean. However, there is some confusion (at least for me) about how to correctly calculate error bars for within-subjects designs.

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What this post is about Reference Manager Note-taking Keep track of the literature Follow blogs Join Twitter Give podcasts a try Familiarize yourself with preregistration and open science Learn R Freshen up your stats Closing remarks What this post is about The new academic semester is almost upon us, and that means lots of new grad students. As I’m entering the fourth and final year of my own PhD, this got me thinking: What tools would I have liked to know about when I started?

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Thanks for popping by my website. I just created it, so expect to see the first post soon.

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Teaching

2018 / 2019

  • Research Project 3: Thesis, Bachelor Psychology (Supervisor)

2017 / 2018

  • Introduction to Psychology: Part B, Bachelor Psychology (Workgroup Instructor)
  • Research Project 3: Experiments, Bachelor Communication Science (Lecturer)
  • Research Project 3: Thesis, Bachelor Psychology (Supervisor)
  • Minor Research Master Project, Research Master Behavioral Science (Supervisor)
  • Research Topics in Communication Science, Bachelor Communication Science (Lecturer)