Program

You can find the program here (subject to change without notice). 

The conference starts Tuesday, August 6, 2024 at 18:00 (6:00 p.m.). 

The conference dinner will be Thursday, August 8, 2024 at 20:00 (8:00 p.m.).

The Early Career Evening will take place on Wednesday, August 7, 2024 at 20:30 (8:30p.m.).

The workshops will be held on August 5, 2024.

VENUE ADDRESS

The conference will be held at the following address:

Humboldt-Universität zu Berlin
Universitätsgebäude am Hegelplatz 
Dorotheenstraße 24
10117 Berlin

The dinner will take place at the Wasserwerk:

Wasserwerk Berlin
Hohenzollerndamm 208 a
10717 Berlin

The early career evening (for registered participants) will be at:

Bar Abgedreht Friedrichshain
Karl-Marx-Allee 140
10243 Berlin

Attention: Workshops will be held on August 5, here:

Psychological Institute
Rudower Chaussee 18
12489 Berlin

You can find more information about the preliminary timeline in the following tables.
Time information corresponds to the Eastern European time zone.

Booklet

You can find the booklet with information about the conference, the city, and the abstracts under this link:
https://docs.google.com/document/d/1tqA1Gv7Lzj7hXvMTXMgpfzre3Jtdnrfi9FW_kdC5fY4/edit?usp=sharing

Please note that the booklet is updated regularly.
Current status: August 2nd, 2024. 

You can also find a PDF version of the booklet here.

Preparing your talk

Each talk is alotted a 15 minute window. We suggest to use 12 minutes for presentation and keep 3 minutes for questions. Please bring your talk as power point or pdf omn a USB drive and upload it on the computer in your presentation room. 

Schematic overview

Keynotes

Keynote speakers:

ANNA BROWN, University of Kent


© University of Kent


Measuring personality in the presence of faking

Every year millions of applicants to jobs or educational programs complete self-report measures of personality. Despite assumed validity and utility in selection, such measures are open to intentional manipulation by applicants who want to create a desired impression. These impression management behaviours are prevalent and typically involve exaggerating positive characteristics and downplaying negative ones in line with social norms (socially desirable responding) or perceived job/program demands (faking). Faking is motivated and purposeful behaviour that can result in substantial distortions to test scores, when they no longer reflect the attributes that the test intends to measure. The negative consequences of faking are well researched and documented, with the most fundamental problem being that faking changes the true ordering of applicants, thus destroying the validity and fairness of selection decisions.

This talk will provide an overview of research on measuring personality in high stakes, discussing the evolution of views on the impact of faking on test scores. I will present the emerging methods of detection and statistical control for faking, which incorporate faking behaviour in psychometric response models (Böckenholt, 2014; Brown & Böckenholt, 2022). These methods are revolutionary in overcoming the simplifying assumption that faking behaviour is consistent throughout the assessment, and offer a great promise as well as natural limitations in their applicability and scope. Unlike cheating on knowledge or ability test, faking behaviour on personality questionnaires cannot be observed and therefore is extremely challenging to identify reliably after it had occurred. This is why many practitioners are turning to methods that prevent faking from occurring in the first place.

In terms of faking prevention methods, I will focus on forced-choice questionnaires that make it impossible for a test taker to endorse all desirable characteristics. Popularity of such questionnaires have been growing steadily since proper scaling methods became available for them, overcoming the problems of ipsative (or relative-to-self, interpersonally incomparable) test scores (e.g. Stark, Chernyshenko, & Drasgow, 2005; Brown & Maydeu-Olivares, 2011). This facilitated rapid progress in development of new personality assessments that are more fake-resistant than the traditional Likert scales (e.g. Cao & Drasgow, 2019). However, many controversies and unanswered questions remain about the effectiveness of comparative judgements (of which forced choice is only one type) in preventing faking. Individual differences in cognitive ability, emotional intelligence, and ability to identify selection criteria, as well as item properties such as valence or ambiguity – all play part. I will report latest findings in this area and share my views and recommendations on the use of comparative judgements in personality assessments going forward.

 

CORNELIA WRZUS, Universität Heidelberg


© Universität Heidelberg, KuM


Processes of personality development in adulthood: Insights from the past, outlook into the future

Over the last decades, evidence cumulated that personality characteristics continue to develop across the entire adult lifespan. While research solely focusing on the occurrence of life events often obtained inconsistent findings, process-oriented research provides promising insights into when, how, and how strongly personality characteristics (do not) change. This talk follows recent theoretical accounts and discusses evidence on pre-behavioral factors, behavioral changes, and post-behavioral factors, drawing from own and others’ multi-methodological research. While Big Five traits serve as concrete examples, I will emphasize the generalizability to further personality characteristics as well as the multimodal nature of traits and processes. The talk ends with outlooks into epigenetic processes of personality development and immersive Virtual Reality as a tool for personality assessments and interventions.

 

AIDAN WRIGHT, University of Michigan, LSA


© Aidan G. C. Wright

Persons and their Problems: On the Relation between Personality and Psychopathology

Our understanding of personality and psychopathology has always been closely intertwined, but recent years has seen dramatic convergences in the scientific study of each. So much so, that it can be hard to distinguish where one begins and the other ends. For instance, the Big-5 and the quantitative structure of psychopathology could be argued to be largely the same at the domain levels. That the domains that define individual differences in basic psychological functioning would align with the domains of psychological dysfunction would seem to be a necessity. At the same time, it is deeply counterintuitive to think that personality and psychopathology are wholly one and the same. I will review the state of the science pointing to convergence in personality and psychopathology, raise the potential for contextualized dynamic processes to differentiate the two, and present some recent findings that seek to address their distinction.

PRESIDENTIAL ADDRESS - Personality Science Around the World

ECP 21’s Presidential Symposium features an exciting whistlestop tour that explores the question of what it means to do personality science – and be a personality scientist – around the world. Across 7 data blitzes, representatives of EAPP’s Regional Promotion Program provide a unique window into their academic lives, experiences, and research programs from every corner of the planet. The data blitzes are followed by an interactive panel discussion.

• Session Speakers (in alphabetical order):
  
  
• Stephen Asata (Catholic University of Eastern Africa, Kenya)
• Christin Camia (Zayed University, UAE)
• Atsushi Oshio (Waseda University, Japan)
• Maria-Jose Sanchez-Ruiz (Universidad de Alcalá, Spain & Lebanese American University, Lebanon)
• Amber Gayle Thalmayer (University of Zürich, Switzerland)
• Michelle Yik (Hong Kong University of Science and Technology, Hong Kong)
• Cristian Zanon (Universidade Federal do Rio Grande do Sul, Brazil)
  
  
• Session Chairs:
  
  
• Friedrich M. Götz (University of British Columbia, Canada)
• Veronica Benet-Martínez (Universidad Pompeu Fabra, Spain)

 

Workshops (August 5th, 2024)

Best Practices and Innovative Approaches to Assessing Character Traits

Juliette Ratchford¹ & Eranda Jayawickreme^1
1Wake Forest University

In recent years there has been increased interest within personality psychology in studying moral (e.g., fairness, honesty) and other character traits (e.g., intellectual humility). However, there are distinctive challenges with studying these traits. For example, there is disagreement on the core content of such traits (e.g., recent work on honesty [Fleeson et al., 2022] and intellectual humility [Porter et al., 2022]). These traits are furthermore socially desirable, meaning that there are unique challenges with their empirical assessment. In this workshop, we will present innovative approaches (based on our own work) to conceptualizing and assessing such traits. The workshop would give 1) recommendations for how the core content of such traits should be identified and how items should be developed, 2) an overview of appropriate assessment approaches, 3) the type of research questions that can be addressed with different approaches, 3) resources pertinent to the approach (e.g., seminal method papers), 4) code/packages in both R and (when applicable) Mplus, and 5) considerations for cultural research on character traits.

 

Processing Digital Footprints of Behavior

Larissa Sust¹ & Ramona Schoedel^2 
1LMU Munich, Department of Psychology, Munich, Germany
²Charlotte Fresenius Hochschule, University of Psychology, Department of Psychology, Munich, Germany

With a strong focus on questionnaire assessments throughout the past decades, personality researchers
have largely neglected the study of actual behavior “in situ.” While investigating behavior in the field was
practically infeasible in the past, people now automatically produce behavioral data every time they use
online platforms like social media sites and streaming services or digital devices like smartphones and
fitness watches throughout the day. These large quantities of digital footprints bring researchers closer
to the goal of studying people’s everyday lives but also provide new methodological challenges.
In our workshop, we will address one of those challenges: How to get from unstructured, high temporal
resolution digital data to meaningful behavioral variables needed for modeling psychological constructs.
In the first part of the workshop, we will give a non-technical, conceptual introduction to how to process
digital data. We draw on our own experience on how to draft variables from different types of digital
data and discuss how to handle the researcher's degrees of freedom in doing so (e.g., specifying
aggregation measures or time frames). Thereby, we also explain how external data sources can help
make sense of raw digital data points (e.g., enriching GPS data with location tags). In the second part of
the workshop, we will use a smartphone-sensing dataset to practice the variable extraction from digital
data. Workshop participants will have the opportunity to extract their own variables using the statistical
software R, under the supervision of the trainers. We will pay special attention to how to perform
variable extraction at larger scales over large samples.
After the workshop, participants will have the basic tools to set up their own projects working with
digital behavioral data for personality research. Participants should have at least basic knowledge of R
and bring their own laptop.

 

Moderated factor analysis in R using OpenMx

Dylan Molenaar^1
1University of Amsterdam

Moderated factor analysis is a powerful tool to establish if the parameters in a factor model depend on one or more observed covariates (Bauer & Hussong, 2009; Bauer, 2017; Neale, 1998). For instance, in personality research, “personality differentiation” refers to the hypothesis that personality is more differentiated at the higher ends of general intelligence (Austin et al., 1997). This hypothesis can be studied for -for instance- neuroticism by testing if the neuroticism factor loadings depend on IQ. If the factor loadings decrease across IQ, there is support for the differentiation hypothesis. Other applications of moderated factor analysis include tests on measurement invariance and test fairness (i.e., testing if latent variables can meaningfully be compared across one or more covariates), testing for interactions between observed variables and latent variables, testing for age and ability differentiation (i.e., similar as above, but with the differentiation effect occurring across age and general intelligence respectively), and multi-group factor analysis with multiple grouping variables (e.g., age-group and sex) and possible interactions (e.g., age-group by sex effects on the factor variances).
In this workshop participants learn what moderated factor analysis is, how it works, and how it can be applied to real data using R-package OpenMx (Boker et al., 2011). Focus will be mainly on moderated factor analysis for continuous indicators (moderated linear factor analysis), but some directions will be given for applications to discrete indicators (moderated non-linear factor analysis). In addition, as moderated factor analysis assumes all moderation effects to be (generalized-)linear, some attention will be devoted to a non-parametric version of this method (i.e., Local Structural Equation Modeling; Hildebrandt et al., 2016).