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Olaf Borghi

@olafborghi.com

420 followers 1.4K following 33 posts

Researching the political mind and how political beliefs develop 🧠 Doctoral candidate in the MSCA Network ippad.eu & Centre for the Politics of Feelings - @rhulpsychology.bsky.social 👥 Previously research assistant @univie.ac.at 🐕

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Olaf Borghi @olafborghi.com · 19h

🔍How does young people's anxiety about the future relate to their political attitudes?

Find out in my first PhD paper, just published in the special issue "The Psychology of Pushback" at advances.in/psychology/1...

Facing a dark future: Young people’s future anxiety and political attitudes in the UK and Greece

Study finds future anxiety linked to more conservative views among young men, but not young women, in the UK and Greece.

Olaf Borghi @olafborghi.com · 15h

Finally, thanks to the European Union Marie Skłodowska-Curie Actions and UKRI for funding this work, and to all my colleagues in the IP-PAD Doctoral Network (you can find out more about our work on www.ippad.eu)

Reposted by Olaf Borghi

Olaf Borghi @olafborghi.com · 19h

🔍How does young people's anxiety about the future relate to their political attitudes?

Find out in my first PhD paper, just published in the special issue "The Psychology of Pushback" at advances.in/psychology/1...

Facing a dark future: Young people’s future anxiety and political attitudes in the UK and Greece

Study finds future anxiety linked to more conservative views among young men, but not young women, in the UK and Greece.

Olaf Borghi @olafborghi.com · 19h

Huge thanks also to the team at @advances.in: The feedback from the editors, peer-reviewers, and production team was beyond exceptional! Bonus, peer-reviewers get paid for their work, which they more than deserve for the helpful feedback we received!!

Olaf Borghi @olafborghi.com · 19h

This work is the result of a cross-country collaboration with my great colleagues and co-authors from the IP-PAD Doctoral Network Melina Niraki and Ermioni Seremeta, and my amazing supervisors @mtsakiris.bsky.social and Kaat Smets!

Olaf Borghi @olafborghi.com · 19h

Today's younger generations will live the longest with the consequences of current political, societal, and natural crises, but they also have the potential to defend democratic values in the future!

Olaf Borghi @olafborghi.com · 19h

Why this matters: Our findings suggest that understanding the futures that young people imagine—and how they feel about the future—is of considerable political relevance.
🌱 The focus on young people is also particularly important:

Olaf Borghi @olafborghi.com · 19h

🧠 In follow-up analyses, we show how these associations differ not just by gender, but also depending on young people's emotion regulation strategies.

Olaf Borghi @olafborghi.com · 19h

😨 Surprisingly though, future anxiety across genders was also associated with 🚨 stronger support for democratic principles (e.g., equal rights to vote) and greater political participation 🚨

Olaf Borghi @olafborghi.com · 19h

🙍 Our UK data further revealed that only among young men future anxiety was associated with more support for authoritarian principles and lower open-minded thinking

Olaf Borghi @olafborghi.com · 19h

👫 Future anxiety is associated with the ideological gender gap: Young men—but not young women—who are more anxious about the future also report being more politically conservative and right-wing. This results in ideological gender polarisation, but only among young people high in future anxiety!

Olaf Borghi @olafborghi.com · 19h

😨 In times of multiple crises, converging reports show many young people are anxious about the future. Yet how this relates to their political attitudes remains unclear. We here provide insights from survey data from close to 2,000 adolescents in the UK and Greece. Key findings:

Olaf Borghi @olafborghi.com · 19h

🔍How does young people's anxiety about the future relate to their political attitudes?

Find out in my first PhD paper, just published in the special issue "The Psychology of Pushback" at advances.in/psychology/1...

Facing a dark future: Young people’s future anxiety and political attitudes in the UK and Greece

Study finds future anxiety linked to more conservative views among young men, but not young women, in the UK and Greece.

Olaf Borghi @olafborghi.com · 29d

thank you for all the extremely helpful papers and blog posts!! so many of them are my go-to resources, and they came out surprisingly often with perfect timing for my work :)

Olaf Borghi @olafborghi.com · 29d

marginaleffects is one of my favourite R packages and this is such a great paper!! extremely recommended, alongside all other papers from the two authors and also the amazing and free Model to Meaning book marginaleffects.com

Julia M. Rohrer @dingdingpeng.the100.ci · Aug 25

Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...

Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities

Abstract
Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).

Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.

A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals).

Illustrated are
1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals
2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and
3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.

Reposted by Olaf Borghi

Julia M. Rohrer @dingdingpeng.the100.ci · 29d

New paper out with @boryslaw.bsky.social 🥳 In which we sketch out how to rethink measurement invariance causally for applied researchers. And provide a causal definition of measurement invariance!

www.sciencedirect.com/science/arti...

Rethinking measurement invariance causally

Highlights:
It is preferable to work with a causal definition of measurement invariance
A violation of measurement invariance is a potentially substantively interesting observation
Standard tests for measurement invariance rely on strong assumptions
Group differences can be thought of as descriptive results

Conceptual graph illustration the central points of the manuscript. A group variable is potentiall connected to a construct of interest which affects items. Measurement invariance is violated if the group variable directly affects the items, for example by modifying the loadings from the construct to the items, or by directly affecting an item

To make this less abstract, consider a scenario where students take an exam, R, meant to capture some ability, T, and then are admitted to a program, V, depending on their exam results: R → V. This is sufficient to result in a violation of the statistical definition of measurement invariance. Exam results and admission are not independent given ability because exam results have a direct effect on admission. Even if we know somebody’s ability (e.g., we know it’s very high), learning about their admission status (e.g., they were not admitted) can tell us something about their exam result (e.g., it may have been worse than expected). According to the causal definition, this in itself does not constitute measurement bias, which seems a sensible conclusion here. After all, the scenario does not involve any reason to believe that the measurement process varied systematically by admission status. Admission happens after the exams took place, it cannot retroactively influence the measurement process (and, for example, lead to unfair treatment depending on admission status).

Olaf Borghi @olafborghi.com · Jul 22

This is incredible work, such an insanely cool paper and findings! Quite alarming that "[post-training and prompting methods that] increased AI persuasiveness [...] also systematically decreased factual accuracy"

Kobi Hackenburg @kobihackenburg.bsky.social · Jul 21

Today (w/ @ox.ac.uk @stanford @MIT @LSE) we’re sharing the results of the largest AI persuasion experiments to date: 76k participants, 19  LLMs, 707 political issues.

We examine “levers” of AI persuasion: model scale, post-training, prompting, personalization, & more!

🧵:

Reposted by Olaf Borghi

Mariana von Mohr @marianavonmohr.bsky.social · Jul 17

In previous work with Manos Tsakiris @mtsakiris.bsky.social , we showed that interoception can act as a buffer against political stress. We now extend this research to the 2024 U.S. Presidential elections, capturing data before and after

Check out our preprint 👇

osf.io/preprints/ps...

Reposted by Olaf Borghi

Leonardo Carella @leonardocarella.bsky.social · Jul 9

I'm glad someone did basic due diligence on the wolf paper. (Although - worth noting - PNAS has an impact factor of 9 and Electoral Studies an impact factor of 2: a familiar pattern with replications of fundamentally flawed findings.) www.sciencedirect.com/science/arti...

The East in wolf’s clothing. Wolf attacks correlate with but do not cause far-right voting

The resurgence of wolves in Germany has sparked intense debate, particularly in rural areas where wolf attacks on livestock are frequent. Prior resear…

www.sciencedirect.com

Reposted by Olaf Borghi

Mariana von Mohr @marianavonmohr.bsky.social · Jul 8

Sharing our work at #ISPP in beautiful Prague on affective prescription —and how this shapes the kind of political leader we’re drawn to based on their appearance.
Preprint coming soon!

Olaf Borghi @olafborghi.com · Jul 4

This book is highly recommended! Bonus is that I genuinely enjoyed working through it when it first came out

Mike Frank @mcxfrank.bsky.social · Jul 1

Experimentology is out today!!! A group of us wrote a free online textbook for experimental methods, available at experimentology.io - the idea was to integrate open science into all aspects of the experimental workflow from planning to design, analysis, and writing.

Experimentology cover: title and curves for distributions.

Reposted by Olaf Borghi

Mariana von Mohr @marianavonmohr.bsky.social · Jul 3

Great talk by @olafborghi.com on cognitive control and politically motivated reasoning, even in the face of unexpected interference 👇😂 #ISPP2025

Reposted by Olaf Borghi

Olaf Borghi @olafborghi.com · Jul 2

(1/6) #ISPP2025 is just one day away and I can't wait to be in Prague! It will be the first conference I attend during my PhD - looking forward to all the interesting sessions, catching up with friends, and meeting new people! 🤩 #PsychSciSky #polisky #CogSci #polpsy

Reposted by Olaf Borghi

Lisa DeBruine @debruine.bsky.social · Jul 2

As one of my favourite colleagues Etienne Roesch just whispered to me in response to a #MetaScience2025 speaker suggesting AI could act as an additional grant reviewer:

A👏I👏is👏not👏an👏analytic👏tool

Reposted by Olaf Borghi

Manos Tsakiris @mtsakiris.bsky.social · Jul 1

That’s the correct link :
www.jobs.london.ac.uk/Job/JobDetai...

Olaf Borghi @olafborghi.com · Jul 2

(6/6) You can find a curated collection of our contributions to ISPP 2025 here: docs.google.com/document/d/1...

ISPP 2025 Annual Meeting in Prague IP-PAD Program Interdisciplinary Perspectives on the Politics of Adolescence & Democracy Conference days Thursday, 3rd of July 3 10:15-11:30 Gustavo Cout...

docs.google.com