A dual-system, machine-learning approach reveals how daily pubertal hormones relate to psychological well-being in everyday life.

ABSTRACT: The two studies presented in this paper seek to resolve mixed findings in research linking activity of pubertal hormones to daily adolescent outcomes. In study 1 we used a series of Confirmatory Factor Analyses to compare the fit of one and two-factor models of seven steroid hormones (n = 994 participants, 8084 samples) of the HPA and HPG axes, using data from a field study (https://www.icpsr.umich.edu/web/ICPSR/studies/38180) collected over ten consecutive weekdays in a representative sample of teens starting high school. In study 2, we fit a Bayesian model to our large dataset to explore how hormone activity was related to outcomes that have been demonstrated to be linked to mental health and wellbeing (self-reports of daily affect and stress coping). Results reveal, first that a two-fac

SUBMITTER: Chafkin JE 

PROVIDER: S-EPMC9650000 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature