2025
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
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
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
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 sodium-chloride associated with hypertension and albuminuria in hot-dry northern Kenya: A two-year panel study. Hypertension, 82(8), 1368 - 1378. https://doi.org/10.1161/HYPERTENSIONAHA.125.24751
Hunter, M., Kirkpatrick, R., & Neale, M. (). Show Me Some ID: A Universal Identification Program for Structural Equation Models. Psychometrika, 90, 418-441. https://doi.org/10.1017/psy.2025.19
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
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
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
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. https://doi.org/10.1080/10410236.2025.2536314
Lyu, X., Burt, S., Hunter, M., Good, R., Carroll, S., & Garrison, S. (). Detecting mtDNA effects with an Extended Pedigree Model: An Analysis on Statistical Power and Estimation Bias. Behavior Genetics, 55, 320-337. https://doi.org/10.1007/s10519-025-10225-1
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
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
Li, Y., Williams, L., Muth, C., Heshmati, S., Chow, S., & Oravecz, Z. (). A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes. Structural Equation Modeling, 32(2), 237-250. https://doi.org/10.1080/10705511.2024.2402328
Burt, S., Garrison, S., Lyu, X., Rodgers, J., Carroll, S., Smith, K., & Hunter, M. (). Inherited mtDNA contributes 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
Lee, S., Fisher, Z., & Almeida, D. (). Daily reciprocal relationships between affect, physical activity, and sleep in middle and later life. Annals of Behavioral Medicine, 59(1). https://doi.org/10.1093/abm/kaae072
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
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
Chen, M., Hunter, M., & Chow, S. (). Detecting critical change in dynamics through outlier detection with time-varying parameters in dynamic models. British Journal of Mathematical and Statistical Psychology. https://doi.org/10.1111/bmsp.70010
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
Oravecz, Z., Vandekerckhove, J., Hakun, J., Kim, S., Katz, M., Wang, C., Lipton, R., Derby, C., Roque, N., & Sliwinski, M. (). Computational Phenotyping of Cognitive Decline With Retest Learning. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 80(7). https://doi.org/10.1093/geronb/gbaf030
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
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
2024
Kim, Y., Fisher, Z., & Pipiras, V. (). Group Integrative Dynamic Factor Models With Application to Multiple Subject Brain Connectivity. Biometrische Zeitschrift, 66(8). https://doi.org/10.1002/bimj.202300370