2012
Buffart, L. M., Thong, M. S. Y., Schep, G., Chinapaw, M. J. M., Brug, J., & van de Poll-Franse, L. V. (2012). Self-reported physical activity: Its correlates and relationship with health-related quality of life in a large cohort of colorectal cancer survivors. PLoS ONE, 7(5), e36164.
2016
Edwards, S. W., & Rodak, M. (2016). Youth at risk: A global challenge. US-China Education Review B, 6(11), 665-670.
2015
Barnett, R. V., Payne-Purvis, C., & Culen, G. R. (2015). Perceptions of community and risk behavior exposure for youth in at-risk environments. National Youth Advocacy and Resilience Journal, 1(1), 46-59.
2026
Pine, A. E., Forehand, R., & Compas, B. E. (2026). Competence and coping in the Family Group Cognitive Behavioral (FGCB) preventive intervention: A moderated mediation model in youth at risk for depression. Prevention Science. Advance online publication.
2019
Wüstner, A., Otto, C., Schlack, R., Hölling, H., Klasen, F., & Ravens-Sieberer, U. (2019). Risk and protective factors for the development of ADHD symptoms in children and adolescents: Results of the longitudinal BELLA study. PLoS ONE, 14(3), e0214412.
2023
Bordás, A. (2023). Investigation of Resilience among Teachers and in Teacher Education. Central European Journal of Educational Research, 5(1), 24–36.
2014
Diehl, L., & Carlotto, M. S. (2014). Knowledge of teachers about the burnout syndrome: Process, risk factors and consequences. Psicologia em Estudo, 19(4), 741-752.
2026
Nordlöf Callbo, P., Junus, K., Lindberger, E., Lindström, L., Sundström Poromaa, I., Bergman, L., Lager, S., & Wikström, A.-K. (2026). A case–control study of mid-pregnancy circulating cardiovascular proteins in women with subsequent preeclampsia and small for gestational age births. Scientific Reports, 16, 20767.
2025
Xu, L., Sun, X., Wang, N., Wang, Y., Li, Y., & Zhang, C. (2025). Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study. Scientific Reports, 15, 3792.
2022
Walther, F., Heinrich, L., Schmitt, J., Eberlein-Gonska, M., & Roessler, M. (2022). Prediction of inpatient pressure ulcers based on routine healthcare data using machine learning methodology. Scientific Reports, 12, 5044.