How Accurate & Consistent are Self-Report responses via Visual Analogue Scales (VAS) in Ecological Momentary Assessment & Digital Studies? Examined in a large EMA study (N = 3,761) w/@LjrCloos Siepe @MarilynPicciri1 @EikoFried @ShirleyBWang @MariekeHelmich Hoffart & Johnson 🧵:

Update: Postdoc applications are live! Postdoctoral Fellow in Digital health - Intervention Development:  https://t.co/IYUBT9N8ol Postdoctoral Fellow in Digital Health - Digital Therapeutics: https://t.co/SjMN5r04wv Postdoctoral Fellow in Digital Health Systems:

7/ Want to learn more? Join me for a workshop at the SIPS online conference, where I’ll dive deeper into these topics! ✨ #SIPS2025

6/ To address these pitfalls, we present recommendations for aligning validation and evaluation strategies with the intended use case scenario and created a tool to help researchers investigate whether their strategies and goals are misaligned: https://t.co/ZdKcEJd0jI💡.

5/ Third, selecting appropriate baseline models is key. Some models may look effective (e.g., AUC = 0.77) but actually underperform compared to simple baselines (e.g., AUC = 0.96). ⚖️

4/ Second, ensuring adequate variability in the outcome variable is crucial. If outcomes are stable, frequent predictions may offer little practical benefit for JITAI.

3/ Centering predictor variables within individuals can improve within-person accuracy but may reduce overall performance.

2/ First, models may perform well overall (AUC = 0.77), but their ability to predict within-person change can be much lower (AUC = 0.56, SD = 0.11). For JITAIs, this will prevent the model from identifying intervention delivery moments and will only discriminate between people.

1/ Many researchers are focused on building prediction models for JITAIs. But a major challenge is the mismatch between model development, evaluation, and application. We use simulations to illustrate three pitfalls.

✨ Excited to share our new preprint: https://t.co/B0rr7HNSHt ✨ In this paper, @NC_Jacobson and I dive into the challenges researchers face when developing prediction models for just-in-time adaptive interventions (JITAI). 🧵👇 #EMA #JITAI #CrossValidation #PassiveSensing

Brief reminder that folks in Leuven have written an open, free handbook on #EcologicalMomentaryAssessment you can download here: https://t.co/3sHRDtrH0I

1/3 Tutorial on exploring ecological momentary data is online at AMPPS, with: -Accessible ways to visualize data for better understanding -Models to get some first insights -Further reading boxes for more advanced topics -Reproducible pipeline you can run over your own data

📢m-Path Innovative Research Grant (MIRG) Announcement 📢 Apply now to run your original and innovative #EMA / #ESM study with a free m-Path premium account!📱 RT = kind!

To all researchers! 🎓📚 Submit your case study for the Open Research Award! Celebrate openness in research & teaching. Win €500 + present your work on 21 Nov! Submit by 15 Oct 2024! 💡 Questions: openresearchaward@rug.nl Submission form: https://t.co/k8CnpFJxhe #OSCG

So you want to do ESM? ✨then take a look at our hot-off-the-press AMPPS paper on “Ten Essential Topics for Implementing the Experience Sampling Method": https://t.co/v6p5bcyT1g ✨I'm really proud of the result & hope you enjoy reading it as much as I enjoyed working on it! 1/6

I'll give a brief intro to open science, then tackle the unique challenges of using passive measures—and how open science practices, like preregistration, can help to address them.

Curious about incorporating open science in research with passive measures? 🤔 Join us this Wednesday! 12-2pm More details: 🔗  https://t.co/KZNu2HlO4O @DartmouthCTBH #openscience #preregistration #digitalphenotyping

We launched a Swiss-wide survey on #mentalhealth and #workingconditions in academia! Please take part if you work in🇨🇭academia ➡️

My dissertation can be found here: https://t.co/lRMVp5bdWV 📖✨

A special thanks to my amazing paranymphs @hoffmann_tabea, Angèle Picco, and to all my family, friends, and colleagues who joined me on this unforgettable day—thank you for making this moment even more special! ❤️