Disentangling personalized treatment effects from "time-of-the-day" confounding in mobile health studies.

ABSTRACT: Ideally, a patient's response to medication can be monitored by measuring changes in performance of some activity. In observational studies, however, any detected association between treatment ("on-medication" vs "off-medication") and the outcome (performance in the activity) might be due to confounders. In particular, causal inferences at the personalized level are especially vulnerable to confounding effects that arise in a cyclic fashion. For quick acting medications, effects can be confounded by circadian rhythms and daily routines. Using the time-of-the-day as a surrogate for these confounders and the performance measurements as captured on a smartphone, we propose a personalized statistical approach to disentangle putative treatment and "time-of-the-day" effects, that leverages condi

SUBMITTER: Chaibub Neto E 

PROVIDER: S-EPMC9352058 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature