New paperAlert! We show that generative AI can quantitatively assess personality from brief, open-ended text—with surprising accuracy. 🧠✨
Preprint: osf.io/preprints/ps...
Postprint (pending mod approval): osf.io/preprints/ps...
1/10
New paper out today in JCCAP! We outline future directions for mathematical, computational, & digital methods in suicide research @leilyb.bsky.social @sharinahamm.bsky.social @francesghart.bsky.social
www.tandfonline.com/doi/full/10....
(1/9)
New year, new preprint alert!! 🤩🚨
We provide new evidence linking intolerance of uncertainty and death anxiety in religious/spiritual individuals.
Link: doi.org/10.31234/osf...
See 🧵 for a brief summary 👇
#deathanxiety #intoleranceofuncertainty
We're hiring! The Computational Clinical Science Lab @ Yale is seeking a full-time lab manager/research coordinator to start in early summer 2026.
For more information about the position and to apply: forms.gle/LtQwVgPUfaGk...
Please share widely & consider applying!
#NewPaperAlert 😎! We developed a prototype for an Augmented Reality (#AR) smartphone app (NST-SPARK) that delivers recovery-oriented cognitive therapy targeting negative symptoms of schizophrenia and completed a preliminary study... 1/5
dx.doi.org/10.1111/eip....
And yes! I totally agree that examining latent embedding dimensions or supervised projections to characterize the endpoints vs. the gray zone would be a great next step.
Thank you so much! One thing we noticed is the “I don’t know” topic also peaked in the mid range, suggesting people experience the middle of the scale as harder to pin down. So part of the grey zone may be heterogeneity and genuine uncertainty about what the mid range represents.
Awesome work!
New preprint alert! (1/5)🌟
I’m thrilled to share the preprint of my first first-authored PhD paper! We test whether shared reinforcement functions help explain why adolescents who engage in one self-destructive behavior often engage in others.
Summary⬇
osf.io/preprints/ps...
New paper alert! Check out our new manuscript in @SchizRes Cognition, led by Sunghye Cho. Here we used automated speech and language analysis to compare verbal fluency responses from people with psychosis, depression, and healthy controls. 1/5
lnkd.in/eg8Y-gGJ
A HUGE thank you to all of my collaborators Dr. Ruben Van Genugten, @kathrynfox.bsky.social @sharinahamm.bsky.social @francesghart.bsky.social and my brilliant advisor @shirleybwang.bsky.social for supporting and contributing to this project!
6/6
These findings challenge assumptions in our field: that numeric ratings function as uniformly interpretable indicators of suicidal thinking.
Mid scale ratings often reflect qualitatively different experiences, not merely different intensities.
5/6
What we found:
1️⃣ Shared meaning emerged only at the ends of the scale.
2️⃣ The middle of the scale was a conceptual gray zone.
3️⃣ Between person consistency never exceeded ~ 20%.
4️⃣ Within person consistency was strongest at scale endpoints.
5️⃣LLM refinement outperformed BERTopic alone.
4/6
Using a 2 stage NLP pipeline (BERTopic -> LLM refinement), we extracted coherent themes from thousands of participant responses and mapped them onto the numeric rating scale.
We also looked at within person consistency (across time) and between person consistency (across people).
3/6
Across 2 independent cohorts of adolescents and young adults, participants were randomly assigned number ratings (0-10) of suicide urge and provided open ended descriptions of what thoughts they would be having at those ratings.
2/6
We usually treat numeric ratings as if they directly reflect suicide risk. But psychological measurement tells us something trickier:
People map internal states onto numbers in highly personal ways.
New preprint alert🚨
We often rely on 0-10 scales to assess suicide urges in EMA and clinical settings. But we rarely ask a surprisingly important question:
What do these numbers mean?
In our new paper, we examine what these ratings mean and how consistently people use them.
More info ⬇️
What a week! After 5 days, the #mitnb workshop has come to an end. We had a keynote on time scales and two workshops on careless responding and reliability. The central part of the workshops were the hackathons. We had super diverse hackathons, all designed to assess measurement in #ESM. (1/4)
Excited to share our new paper entitled Multisystem Environmental Factors Elucidate Shared and Distinct Associations With Brain and Behavior in Adolescents.
Link: www.jaacap.org/article/S089....
@kavliatyale.bsky.social
Excited to share our new preprint! We conducted a spatial meta-analysis of community violence and mental health, synthesizing 155 articles (k = 769) to test how exposure to community violence is associated with mental health problems, and how state social service investments moderate the link. 💵
Participants of the MITNB workshop, where we stand outside in a group of around 40 people
1st day of #MITNB meeting at @tesc-tilburgu.bsky.social. Excited for the week ahead, where we'll tackle measurement issues in #ESM, e.g. modeling processes across timescales, building a formal theory on measurement, and evaluating statistical assumptions in #ESM data.
Go teamwork <3
Last weekend my lab attended our first conference together @harvardwipsych.bsky.social! It was an *incredible* way to wrap up our first year 😍
@sharinahamm.bsky.social @francesghart.bsky.social
Almost exactly one year after starting my lab (!), I'm thrilled to share our first preprint! 🥳 @leilyb.bsky.social @sharinahamm.bsky.social @francesghart.bsky.social
We propose future directions for mathematical, computational, & digital methods to advance suicide research: osf.io/preprints/ps...
(6/6) Big thank you to co-authors @sharinahamm.bsky.social , @leilyb.bsky.social , @kathrynfox.bsky.social , @shirleybwang.bsky.social- and bluesky-less Kathryn Coniglio, Erin Reilly, and Leah Somerville- for their support in this project!