Running on-line studies is one efficient way to run studies with absolute social distancing, however, not everybody knows how do this (yet). During this tutorial you will hear how to set up and run studies on-line. Bastiaan Rutjens will talk about the practicalities and pitfalls of running studies on-line, and will discuss different platforms to recruit participants and to make sure that you gather high-quality data.

For those who want to move their experimentation online, NeuroTask Scripting is a good option to consider. Jaap Murre will give a brief demo of some of the possibilities.

The aim is that the tutorial is accessible for people who have never done an on-line study, but also for people who can share their experience.  Besides the speakers, several experienced on-line researchers and the people from the TOP will also be available to answer questions.

Bastiaan Rutjens (with Natalia Zarzcecna)

“Conducting research online using US and UK data markets”

In the last 2-3 years I have almost exclusively conducted my research online. Online research works well for correlational work, simple experiments, as well as various types of longitudinal design. There are various online platforms where researchers can crowdsource participants for their research. We will talk about our experiences with Amazon’s Mechanical Turk (US) and Prolific Academic (UK), focusing on participant selection, population demographics, instruction and attention checks, and data quality (e.g., compared to student samples). 

Jaap Murre

For those who want to move their experimentation online, NeuroTask Scripting is a good option to consider. 

When Psychology staff or students register at neurotask.com using heir uva.nl email, they will automatically gain full access to NeuroTask Scripting for free. This is a platform to create online experimental tasks. The NeuroTask framework is not intended for beginning casual users who want to ‘drag-and-drop’ an experiment; some programming in JavaScript is required. Having said that, simple experiments can be created in minutes or hours and quite sophisticated tasks have been made in the past five years, including reaction time experiments (e.g., IAT), memory tests, IQ tests, experiments with sound or video, game-like experiments, multi-player experiments, speech-based interaction, etc. See the demo page for runnable examples, which can be used as starting points. There is also a free online book that takes beginners step-by-stop through the process of creating experiments. Recently, a student has created a number of introductory videos.

In this Psych Forum we will have two excellent speakers that will provide a network perspective on the psychometrics and the brain.

Sacha Epskamp | Network Modeling of Feelings Cognition and Behavior: An Introduction to Network Psychometrics

In this talk I will introduce "network psychometrics" - an increasingly popular field of methods pioneered at the Psychological Methods program group aiming to map out the complex interplay between observed variables. I will present the theoretical foundations for network psychometrics show how such an analysis can be performed in R and discuss future directions in this area of research.

Many researchers are aware of the many benefits it can have to switch from classical statistics to Bayesian. And yet, almost as many are hesitant to do the switch, and all because of the priors! In Bayesian analysis, researchers must make a priori commitments, and these commitments are made transparently as part of model specification.

During this Psychological Forum you will learn about several ways to specify these a priori commitments. In the first talk, Julia Haaf will give an introduction to prior specification and the sometimes complicated terminology used around it. We will show which priors are appropriate for Bayesian estimation or Bayesian model comparison, and explain what a sensitivity analysis is.

In the second talk, Angelika Stefan will discuss different approaches that can be used to formulate priors based on existing pre-data knowledge. Specifically, we will show how results from the scientific literature, theoretical convictions, and domain expert knowledge can shape prior distributions. We will present several concrete examples, and discuss how the formulation of the prior distribution influences the results of Bayesian analyses. There will be lots of time for discussion and to ask questions. Share your favorite priors, or discuss analysis problems where you did not know which priors to chose.

Using social media in psychological science, and the psychology of social media use

In this forum we address the use of social media data to study psychological processes using high definition real world data, but also address the psychology  of social media use, that  is the impact of digital detox on well-being. These two talks highlight the novel ways in which social media is starting to play a role in psychological science. 

Connecting Social Media Digital Trace Data and Neuroimaging to Understand Mechanisms of Real-World Behavior + Trace data tutorial. 

Christin Scholz, PhD

In modern digital societies, social media facilitates and shapes social relationships and the spread of information between individuals and through entire populations. Whenever users engage with or on social media, they leave digital traces indicating, for instance, when they were active, who or what content they interacted with. As such, social media offers opportunities for unobtrusive, rich observations of naturalistic, real-life experiences and behaviors. This talk uses examples of our recent work to explore how this observational data can be used to enrich highly controlled, laboratory investigations into the psychological mechanisms that drive human decision-making and behavior. Linking these diverse data sources can enable researchers to combine the best of multiple worlds: the naturalistic, large-scale, and dynamic properties of social media digital trace data and the internally valid, precise information provided by laboratory experiments.

Hang-Yee Chan, PhD

Social media digital trace data provide many opportunities to researchers, but also come with specific challenges and limitations like any source of data. This talk uses examples from our recent work to demonstrate how social media digital trace data can be linked to laboratory data in order to investigate psychological mechanisms of real-world behavior.

‘Digital detox’: the effect of abstinence on social media use, habits and wellbeing

Tim van Timmeren

Many people want to reduce their social media use and an increasingly popular intervention to regain control is a ‘digital detox’. We recruited 120 participants motivated to reduce usage and found that a simple one-week detox significantly reduces social media use, automaticity and craving up to three weeks post-detox, while improving mental wellbeing.

This online forum addressed the topic of (political) polarisation and comprised two lectures: 

Morally Polarised Perception: Current Efforts to Examine Neural Patterns of Political Polarisation

by Frederic R. Hopp, PhD

How (political) convictions can change basic cognition: A predictive processing approach

by Marte Otten, PhD