2026
Pohlmann, K., Tawil, N., Brick, T., & Kühn, S. (). Style mixing houses: The role of high- and low-level visual features in human house facade evaluation. Acta Psychologica, 262. https://doi.org/10.1016/j.actpsy.2025.106126
Li, Y., Xiong, X., Oravecz, Z., & Chow, S. (). Simultaneous detection of gradual and abrupt structural changes in Bayesian longitudinal modelling using entropy and model fit measures. British Journal of Statistical Psychology. https://doi.org/10.1111/bmsp.70029
2025
Pohlmann, K., Tawil, N., Brick, T., Yaghoubi, E., & Kühn, S. (). Visualising and understanding human evaluation of house facades: GAN applied to environmental psychology. Journal of Environmental Psychology, 107. https://doi.org/10.1016/j.jenvp.2025.102803
Lancaster, J., Brick, T., & Cleveland, H. (). The effects of dynamic recovery identity on lapse risk and the role of daily recovery meetings. International Journal of Drug Policy, 145. https://doi.org/10.1016/j.drugpo.2025.104941
Cho, Y., Chow, S., Li, J., Wang, S., Wang, W., Ji, L., Chinchilli, V., Intille, S. S.,, , & Dunton, G. (). Within- and Between-Individual Compliance in Mobile Health: Joint Modeling Approach to Nonrandom Missingness in an Intensive Longitudinal Observational Study. JMIR mHealth and uHealth, 13, e65350. https://doi.org/10.2196/65350
Oravecz, Z., Sliwinski, M., Kim, S., Williams, L., Katz, M., & Vandekerckhove, J. (). Partially Observable Predictor Models for Identifying Cognitive Markers. Computational Brain and Behavior, 8(3), 410-420. https://doi.org/10.1007/s42113-025-00238-8
Williams, L., Kim, S., Li, Y., Heshmati, S., Vandekerckhove, J., Roeser, R., & Oravecz, Z. (). How much we express love predicts how much we feel loved in daily life. PLoS One, 20(7). https://doi.org/10.1371/journal.pone.0323326
Coles, N., Perz, B., Behnke, M., Eichstaedt, J., Kim, S., Vu, T., Raman, C., Tejada, J., Huynh, V., Zhang, G., Cui, T., Podder, S., Chavda, R., Pandey, S., Upadhyay, A., Padilla-Buritica, J., Barrera Causil, C., Ji, L., Dollack, F., Kiyokawa, K., et al (). Big team science reveals promises and limitations of machine learning efforts to model physiological markers of affective experience. Royal Society Open Science, 12(6). https://doi.org/10.1098/rsos.241778
Rosinger, A., McGrosky, A., Jacobson, H., Hinz, E., Sadhir, S., Wambua, F., Otube, T., Baker, L., Sherwood, A., Chrissy-Mbeng, T., Broyles, L., Musumeci, C., Meriwether, N., Bobbie, N., Farrar, Z., Todd, M., Nguyen, Z., Berger, G., Ford, L., Braun, D., et al (). Drinking Water NaCl Is Associated With Hypertension and Albuminuria: A Panel Study. Hypertension, 82(8), 1368-1378. https://doi.org/10.1161/HYPERTENSIONAHA.125.24751
Heshmati, S., Muth, C., Li, Y., Roeser, R., Smyth, J., Vandekerckhove, J., Chow, S., & Oravecz, Z. (). Who benefits from mobile health interventions? A dynamical systems analysis of psychological well-being in early adults. Applied Psychology: Health and Well-Being, 17(3). https://doi.org/10.1111/aphw.70037
Liu, C., Chow, S., Aris, I., Dabelea, D., Neiderhiser, J., Leve, L., Blair, C., Catellier, D., Couzens, L., Braun, J., Ferrara, A., Aschner, J., Deoni, S., Dunlop, A., Gern, J., Rivera-Spoljaric, K., Hartert, T., Hershey, G., Karagas, M., Kennedy, E., et al (). Early-Life Factors and Body Mass Index Trajectories Among Children in the ECHO Cohort. JAMA network open, 8(5). https://doi.org/10.1001/jamanetworkopen.2025.11835
Hunter, M., Kirkpatrick, R., & Neale, M. (). Show Me Some ID: A Universal Identification Program for Structural Equation Models. Psychometrika, 90(2), 418-441. https://doi.org/10.1017/psy.2025.19
Drewelies, J., Fiedler, A., Brick, T., & Kühn, S. (). Investigating associations between the physical living environment and hippocampus in adulthood and older age. Environmental Research, 267. https://doi.org/10.1016/j.envres.2024.120728
Kim, S., Hakun, J., Li, Y., Harrington, K., Elbich, D., Sliwinski, M., Vandekerckhove, J., & Oravecz, Z. (). Optimizing the Color Shapes Task for Ambulatory Assessment and Drift Diffusion Modeling: A Factorial Experiment. JMIR Formative Research, 9. https://doi.org/10.2196/66300
Ringwald, W., Creswell, K., Low, C., Doryab, A., Chung, T., Oliva, J., Fisher, Z., Gates, K., & Wright, A. (). Common and Uncommon Risky Drinking Patterns in Young Adulthood Uncovered by Person-Specific Computational Modeling. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0001055
Bai, S., Froidevaux, N., Chen, M., High, A., Ewing, K., DeFelice, J., Weaver, J., Ngigi, K., Riccio, M., Chiang, S., Bai, L., Lunkenheimer, E., & Brick, T. (). Families Being Supportive Together: A Multimethod and Multi-Informant Intensive Longitudinal Study of Family Protective Mechanisms for Adolescent Depression. Psychological Assessment, 37(10), 535-546. https://doi.org/10.1037/pas0001400
Lancaster, J., Apsley, H., Brick, T., & Cleveland, H. (). A within-person investigation of recovery identity following substance use disorder: examining the impact of recovery-focused social contexts. Frontiers in Public Health, 13. https://doi.org/10.3389/fpubh.2025.1534432
Burt, S., Garrison, S., Lyu, X., Rodgers, J., Carroll, S., Smith, K., & Hunter, M. (). Contributions of inherited mtDNA to longevity: evidence from extended pedigrees with 176 million kinship pairs. EBioMedicine, 119(105911), 1-10. https://doi.org/10.1016/j.ebiom.2025.105911
Petrie, D., Knapp, K., Freet, C., Deneke, E., Stankoski, D., Brick, T., Cleveland, H., & Bunce, S. (). Contemporaneous Link Between Pain and Craving in Patients Recovering from Prescription Opioid Use Disorder During Residential Treatment. Substance Use and Misuse, 60(7), 978-988. https://doi.org/10.1080/10826084.2025.2478590
Xiong, X., Hunter, M., & Chow, S. (). Integrated Trend and Lagged Modeling of Multi-Subject, Multilevel, and Short Time Series. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2025.2587286
Lyu, X., Burt, S., Hunter, M., Good, R., Carroll, S., & Garrison, S. (). Detecting mtDNA Effects with an Extended Pedigree Model: An Analysis of Statistical Power and Estimation Bias. Behavior Genetics, 55(4), 320-337. https://doi.org/10.1007/s10519-025-10225-1
Blahošová, J., Tancoš, M., Cho, Y., Šmahel, D., Elavsky, S., Chow, S., & Lebedíková, M. (). Examining the Reciprocal Relationship Between Social Media Use and Perceived Social Support Among Adolescents: A Smartphone Ecological Momentary Assessment Study. Media Psychology, 28(1), 70-101. https://doi.org/10.1080/15213269.2024.2310834
Noll, J., Felt, J., Russotti, J., Guastaferro, K., Day, S., & Fisher, Z. (). Rates of Population-Level Child Sexual Abuse After a Community-Wide Preventive Intervention. A.M.A. American journal of diseases of children. https://doi.org/10.1001/jamapediatrics.2024.6824
Das, J., Ji, L., Shen, Y., Kumara, S., Buxton, O., & Chow, S. (). Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting. Sleep Health, 11(2), 166-173. https://doi.org/10.1016/j.sleh.2024.10.003
Oh, H., Hunter, M., & Chow, S. (). Measurement Model Misspecification in Dynamic Structural Equation Models: Power, Reliability, and Other Considerations. Structural Equation Modeling, 32(3), 511--528. https://doi.org/10.1080/10705511.2025.2452884