Eiko Fried
@eikofried.bsky.social
13K followers 980 following 1.7K posts
Associate Prof Leiden Uni. Studying mental health problems as systems. http://eiko-fried.com. Building an early warning system for depression at http://WARN-D.com.
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eikofried.bsky.social
So many new followers!​! Hi folks, nice to meet you all. 🖤

I'll introduce my core research interests by showing you some of the work we've done in recent years on the conceptualization, measurement, modeling, and theories of mental health (problems).

🧪 #PsychSciSky #psychiatry #statssky

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Reposted by Eiko Fried
eikofried.bsky.social
Found this and couldn't resist ..
eikofried.bsky.social
Two days ago, they replaced 75% of mom's knee, who is in her mid 70s. Today, she is walking stairs again. Given how slow progress has been in psychiatry, I sometimes forget how much progress has been made in other areas of medicine.
eikofried.bsky.social
Excellent detailed intro paper on open scholarship in clinical psychology by some of my favourite authors on the topic, including @drlynam.bsky.social @dsbarra.bsky.social @jnfrltackett.bsky.social @aidangcw.bsky.social @jdmiller.bsky.social and others. Perfect paper to turn into an intro lecture!
psyarxivbot.bsky.social
The Open Science Movement and Clinical Psychology Training: Rigorous Science is Transparent Science: https://osf.io/s46wd
Reposted by Eiko Fried
jdmiller.bsky.social
New paper led by @drlynam.bsky.social on the need for more training in and engagement with open science practices in clinical psych programs. It has been difficult to make progress due to a variety of barriers, including students working in labs uninterested or hostile to these approaches.
psyarxivbot.bsky.social
The Open Science Movement and Clinical Psychology Training: Rigorous Science is Transparent Science: https://osf.io/s46wd
eikofried.bsky.social
exactly, a trillion co authors haha
eikofried.bsky.social
It'll be so much worse for so many more people
eikofried.bsky.social
Oh God that wasn't the intention o_O sorry
eikofried.bsky.social
I spent too much time on this but in my situation, I estimate this would be around ≥100,000 emails per month.
eikofried.bsky.social
I would suggest we please don't do this, pretty please :)
eikofried.bsky.social
Chilling in his own, extremely cozy and unexpectedly warm, dark blue “pond” :)
eikofried.bsky.social
Yes, in the same league as the elegant paper by Andy Maul on measuring nonsense, with great psychometric properties for a questionnaire measuring a random word “gavagai”
Reposted by Eiko Fried
dingdingpeng.the100.ci
A lot of psych is already conducted with online convenience samples & ppl are probably excited about silicon samples bc it would allow them to crank out more studies for even less 💸

How about we reconsider the idea that sciencey science involves collecting own data.
www.science.org/content/arti...
AI-generated ‘participants’ can lead social science experiments astray, study finds
Data produced by “silicon samples” depends on researchers’ exact choice of models, prompts, and settings
www.science.org
eikofried.bsky.social
HOLD ON A MINUTE but theorists will still be testing their own theories right ... right?!
eikofried.bsky.social
They took the same psychometric procedure as the original authors without, I believe, arguing that this is a good or sensible way to do validation
eikofried.bsky.social
Had missed this absolutely brilliant paper. They take a widely used social media addiction scale & replace 'social media' with 'friends'. The resulting scale has great psychometric properties & 69% of people have friend addictions.

link.springer.com/article/10.3...
Development of an Offline-Friend Addiction Questionnaire (O-FAQ): Are most people really social addicts? - Behavior Research Methods
A growing number of self-report measures aim to define interactions with social media in a pathological behavior framework, often using terminology focused on identifying those who are ‘addicted’ to engaging with others online. Specifically, measures of ‘social media addiction’ focus on motivations for online social information seeking, which could relate to motivations for offline social information seeking. However, it could be the case that these same measures could reveal a pattern of friend addiction in general. This study develops the Offline-Friend Addiction Questionnaire (O-FAQ) by re-wording items from highly cited pathological social media use scales to reflect “spending time with friends”. Our methodology for validation follows the current literature precedent in the development of social media ‘addiction’ scales. The O-FAQ had a three-factor solution in an exploratory sample of N = 807 and these factors were stable in a 4-week retest (r = .72 to .86) and was validated against personality traits, and risk-taking behavior, in conceptually plausible directions. Using the same polythetic classification techniques as pathological social media use studies, we were able to classify 69% of our sample as addicted to spending time with their friends. The discussion of our satirical research is a critical reflection on the role of measurement and human sociality in social media research. We question the extent to which connecting with others can be considered an ‘addiction’ and discuss issues concerning the validation of new ‘addiction’ measures without relevant medical constructs. Readers should approach our measure with a level of skepticism that should be afforded to current social media addiction measures.
link.springer.com
eikofried.bsky.social
Thanks will check it out, this was done quickly with the scholar package
eikofried.bsky.social
Thanks to everyone I got to work with over the last decade 🖤

(Quick and dirty so please ignore the fact that many of your names will be butchered .. )
eikofried.bsky.social
Awesome, happy to contribute with our WARN-D data if it helps at all (4/day time series data for 3 months in ~1800)
eikofried.bsky.social
Good point — and the model interestingly does not behave like this in the 0/1 case, I believe. Will have to do a bit more reading, only gave this a cursory glance.
eikofried.bsky.social
Different views on this, I think a modern view inform by a lot of sound modeling and statistical work would be that you only get stable states, attractors, phase transitions and the like with at least *some* vicious cycles and feedback loops, keeping people in their current state.
eikofried.bsky.social
Yes depends on structure and mechanisms of change in the network, among other things. But it holds for -1/+1 Ising Model which is a common mental model in 'our' field I would say