2026
Albers, C., & Hunter, M. (). Editorial: Special Issue on Multiple multivariate multimodal time series data analysis in psychological research. British Journal of Statistical Psychology, 79(2), 233-236. https://doi.org/10.1111/bmsp.70046
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
Hunter, M., Garrison, S., Lyu, X., Good, R., Carroll, S., & Burt, S. (). Tracing the Right Path: Determination of Large Pedigree Segmentation and Relatedness. Behavior Genetics. https://doi.org/10.1007/s10519-026-10259-z
Whitney, J., Suhy, V., Pauley, A., Shao, D., Khan, O., Moore, A., Chow, S., Rivera, D., & Downs, D. (). Game, Set, and Match: A Scoping Review of Matching Characteristics for Control and Intervention Groups in Adaptive Behavioral Interventions for Physical Activity or Healthy Eating Designs for Populations with Overweight and Obesity. Journal of Human Stress. https://doi.org/10.1080/08964289.2026.2641440
Brick, T. (). Adaptive Intervention Designs for Studies of Human Development. , 349-369. https://doi.org/10.1002/9781119880851.ch15
2025
Singh, M., Hunter, M., Assary, E., Verhulst, B., Peterson, R., Maes, H., Dolan, C., Eley, T., & Neale, M. (). Causation Between Smoking Quantity and Depressive Symptoms in Young Adults: Evidence From Novel Cross-Lagged Twin Models. medArXiv, 1-40. https://doi.org/10.1101/2025.11.18.25340516
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, 104941. https://doi.org/10.1016/j.drugpo.2025.104941
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), e2511835. 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
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
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
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. JAMA Pediatrics. https://doi.org/10.1001/jamapediatrics.2024.6824
Skurka, C., Troy, C., Yang, Y., Smith, R., Tornello, S., Rosenberger, J., Brick, T., & Myrick, J. (). “It Is in the Air”: Seeking and Scanning for Information About Pre-Exposure Prophylaxis Among Young-Adult Men Who Have Sex with Men in the US. Health Communication, 1-12. https://doi.org/10.1080/10410236.2025.2536314
Alexander, J., Duffy, K., Freis, S., Chow, S., Friedman, N., & Vrieze, S. (). Investigating the Magnitude and Persistence of COVID-19–Related Impacts on Affect and GPS-Derived Daily Mobility Patterns in Adolescence and Emerging Adulthood: Insights From a Smartphone-Based Intensive Longitudinal Study of Colorado-Based Youths From…. Journal of Medical Internet Research, 27, e64965. https://doi.org/10.2196/64965
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
Long, J., Cunningham, P., Maksi, S., Keller, K., Brick, T., Klippel, A., Boot, L., Cheah, C., Edwards, C., Rolls, B., & Masterson, T. (). Energy Density Selected in Immersive Virtual Reality Buffet Meals Is Associated with Both Energy Density Consumed and Energy Intake in Laboratory Meals. , 27-35. https://doi.org/10.1109/ICVR66534.2025.11172660
Long, J., Cunningham, P., Maksi, S., Keller, K., Cheah, C., Boot, L., Klippel, A., Brick, T., Edwards, C., Kort, J., Grabusky, P., Rolls, B., & Masterson, T. (). Variety-seeking behavioral markers in an immersive virtual reality food buffet are associated with greater food and energy intake in laboratory meals. Appetite, 210(1), 107988. https://doi.org/10.1016/j.appet.2025.107988
Chen, M., Hunter, M., & Chow, S. (). Detecting Critical Change in Dynamics Through Outlier Detection with Time-Varying Parameters. British Journal of Statistical Psychology. https://doi.org/10.1111/bmsp.70010
Knapp, K., Petrie, D., Brick, T., Deneke, E., Bunce, S., & Cleveland, H. (). Within-Person Affect Dynamics Among Individuals in Residential Treatment for Opioid Use Disorder: An Ecological Momentary Assessment Study. Journal of Psychopathology and Clinical Science, 134(2), 184-200. https://doi.org/10.1037/abn0000975
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