Christian Bean

Congrats @yinrulong.bsky.social! We had a great time at SRP catching up with friends and hearing about new research in psychopathology. Very grateful for this community!

Life satisfaction mostly declines with age. Previous findings (esp. the famous U-shaped age-SWB trajectory) were artifacts of misspecified models. doi.org/10.1093/esr/...

Transformation starts at the periphery of networks where pushback is less - Scientific Reports Scientific Reports - Transformation starts at the periphery of networks where pushback is less

Intervening on a central node in a network likely does little given that its connected neighbors will "flip it back" immediately. Happy to see this position supported now.

"Change is most likely [..] if it spreads first among relatively poorly connected nodes."

www.nature.com/articles/s41...

🚨 New preprint: We compared 13 methods for detecting momentary careless responding in the WARN-D data (206k+ obs.). Tutorials guide you through each method. The takeaway? Diverging results, inherent subjectivity (to varying degrees), and a clear need for further validation.
osf.io/preprints/ps...

I’m starting a suicide prevention research lab at UMass Amherst! I’ll be reviewing applications for our clinical psychology PhD program. Come to our virtual open house to learn more about the program and speak with faculty accepting students.
www.umass.edu/psychologica...

Vanderbilt University's Peabody College is hiring a TT Assistant Prof in Clinical Psychology (child/family focus) with expertise in AI methods (ML, NLP, LLMs, CV).

📅 Review begins Nov 15, 2025

👉 apply.interfolio.com/174418

Please share!

I am barely on this app, because of *gestures wildly* life, the universe, and everything, but I should announce that I plan to review apps for clinical psychology PhD admissions this cycle! Please read my website for more info! www.sarahevictor.com/contact

Don't miss our wonderful MED Lab members at SRP this week! #SRP2025

A diagram showing dozens of brain regions densely interconnected by complicated loops

I think about this diagram a lot. This is a *simplified* schematic of *some of* the brain regions and circuits involved in behavioral control. (From: www.sciencedirect.com/science/arti...)

Ecological Momentary Assessment as a Measure of Intervention Change: Evaluation in 4 Digital Mental Health Trials Background: Ecological momentary assessment (EMA) is increasingly being incorporated into intervention studies to acquire a more fine-grained and ecologically valid assessment of change. The added uti...

📱EMA is increasingly used in intervention studies to acquire a more fine-grained and ecologically valid assessment of change. But EMA is relatively burdensome. What's the added value? We tried to address this question in our new paper now out @jmirpub.bsky.social www.jmir.org/2025/1/e69297 1/n

We present our new preprint titled "Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation". We quantify LLM hacking risk through systematic replication of 37 diverse computational social science annotation tasks. For these tasks, we use a combined set of 2,361 realistic hypotheses that researchers might test using these annotations. Then, we collect 13 million LLM annotations across plausible LLM configurations. These annotations feed into 1.4 million regressions testing the hypotheses. For a hypothesis with no true effect (ground truth $p > 0.05$), different LLM configurations yield conflicting conclusions. Checkmarks indicate correct statistical conclusions matching ground truth; crosses indicate LLM hacking -- incorrect conclusions due to annotation errors. Across all experiments, LLM hacking occurs in 31-50\% of cases even with highly capable models. Since minor configuration changes can flip scientific conclusions, from correct to incorrect, LLM hacking can be exploited to present anything as statistically significant.

🚨 New paper alert 🚨 Using LLMs as data annotators, you can produce any scientific result you want. We call this **LLM Hacking**.

Paper: arxiv.org/pdf/2509.08825

Old Dominion University (ODU) has launched a solo Clinical Psychology PhD program. ODU led the administration of the APA-Accredited Virginia Consortium Program in Clinical Psychology, training doctoral clinical psychologists for >43 years. Check out the department at www.odu.edu/clinicalpsycphd

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).

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...

Mark Chen | Department of Psychology

My website is official 🙌 Excited to share that I am interested in reviewing applications for Harvard’s Clinical Science PhD program this fall as I look for the first student to join my lab! I appreciate it if you can share with your network :)
psychology.fas.harvard.edu/people/mark-...

URI receives first-ever NIH T32 award to launch transdisciplinary biomedical research training program KINGSTON, R.I. – Sept. 3, 2025 – The University of Rhode Island has received its first-ever National Institutes of Health (NIH) T32 Predoctoral Training Grant, marking a major milestone in URI’s growt...

Big news! @universityofri.bsky.social just secured its first-ever NIH T32 grant!

This T32 will bring together Psychology, Neuroscience, Engineering, and Life Sciences to train the next generation of scientists to tackle complex health challenges like addiction.

www.uri.edu/news/2025/09...

v1.108 is rolling out today 🚚

Now live, at long last: Bookmarks, aka Saved Posts. For all those posts you'll definitely plan to come back to!

Update the app and give it a try. The button is right down there 👇

The quality of online instruction and returns to instructor experience We examine student satisfaction and performance in online versus in-person sections at a large research university in the United States, exploring whe…

"students evaluate online courses as worse than in-person courses, despite minimal differences in performance ... primarily driven by student perceptions of instructor availability, concern for students, and the ability to stimulate interest in the course." www.sciencedirect.com/science/arti...

Interested in applying to graduate programs or research positions in psychology? Want more information and feedback on your submission materials? Then Harvard’s Prospective Ph.D. & RA Event in Psychology (PPREP) Is for you!! psychology.fas.harvard.edu/pprep
More info in the link!! Please retweet!

@seworonko.bsky.social maybe something you’d find interesting

The psych job market isn’t dead! Join us at UIC!!! We are looking for a clinical psychologist (assistant or associate level)!! Chicago is simply the best, and the department is incredibly lovely! I’m not on search committee, but as the “newest” hire, I’m happy to talk about my experience thus far!

Julian Burger | Department of Psychology Department of Psychology at Stony Brook University

I will be reviewing applications for Stony Brook’s Clinical Psychology doctoral program this fall. The research streams of my lab are summarized on the department website: www.stonybrook.edu/commcms/psyc...

We’re hiring an assistant or associate professor to join our psychology department at the University of Illinois Chicago! We’re a vibrant research-active department in a great city, a diverse institution with a purpose-driven mission, and a fun place to work! #psychjobs

uic.csod.com/ux/ats/caree...

✨✨ I will be reviewing applications for the University of Minnesota psychology PhD program this fall!

Information for potential applicants can be found on my lab website: ringwaldlab.psych.umn.edu/join-lab

Please spread the word!

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.

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...

Teaching/learning intro stats and R? #rstats

Explore my teaching materials, including syllabus, lecture slides, exercises, interactive graphs, and self-graded review exercises: ellaudet.github.io/dss_instructor_resources

Instructors using DSS: source files from PUP have just been updated!

Rapid Response: Reinvesting in Racial and Indigenous Health Equity Research The purpose of this call for proposals is to meet the current moment by supporting timely, actionable health equity research that has been interrupted by shifts in federal funding.

ATTN: Robert Wood Johnson has money to support “canceled” research on racial-indigenous health equity

www.rwjf.org/en/grants/ac...

I am pleased to announce that our APA accredited Counseling Psychology program at Colorado State University has officially transitioned to an APA accredited Clinical Psychology program, adopting the clinical science training model. psychology.colostate.edu/clinicalscie...

Applying for graduate studies in psychology and neuroscience can be challenging and confusing. Frequently, applicants have some support from mentors at their home institutions, but sometimes applicants are looking for additional reassurance, feedback, or perspectives on the processes.

Six Fallacies in Substituting Large Language Models for Human Participants - Zhicheng Lin, 2025 Can artificial-intelligence (AI) systems, such as large language models (LLMs), replace human participants in behavioral and psychological research? Here, I cri...

Paper on the problems of using LLMs as replacements for human participants
journals.sagepub.com/doi/full/10....