Published on in Vol 8, No 12 (2020): December
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/21703, first published
.
![Using Smartphone Sensor Data to Assess Inhibitory Control in the Wild: Longitudinal Study Using Smartphone Sensor Data to Assess Inhibitory Control in the Wild: Longitudinal Study](https://asset.jmir.pub/assets/ac0abaecfb24b2f070764bf92627fb17.png 480w,https://asset.jmir.pub/assets/ac0abaecfb24b2f070764bf92627fb17.png 960w,https://asset.jmir.pub/assets/ac0abaecfb24b2f070764bf92627fb17.png 1920w,https://asset.jmir.pub/assets/ac0abaecfb24b2f070764bf92627fb17.png 2500w)
Journals
- Cook D, Schmitter-Edgecombe M. Fusing Ambient and Mobile Sensor Features Into a Behaviorome for Predicting Clinical Health Scores. IEEE Access 2021;9:65033 View
- Brockmeyer T, Febry H, Leiteritz-Rausch A, Wünsch-Leiteritz W, Leiteritz A, Friederich H. Cognitive flexibility, central coherence, and quality of life in anorexia nervosa. Journal of Eating Disorders 2022;10(1) View
- Lauvsnes A, Gråwe R, Langaas M. Predicting Relapse in Substance Use: Prospective Modeling Based on Intensive Longitudinal Data on Mental Health, Cognition, and Craving. Brain Sciences 2022;12(7):957 View
- Lauvsnes A, Hansen T, Ankill S, Bae S, Gråwe R, Braund T, Larsen M, Langaas M. Mobile Assessments of Mood, Cognition, Smartphone-Based Sensor Activity, and Variability in Craving and Substance Use in Patients With Substance Use Disorders in Norway: Prospective Observational Feasibility Study. JMIR Formative Research 2023;7:e45254 View