The dynamic relationship between daily caffeine intake and sleep duration in middle-aged and older adults.

The effect of caffeine on sleep has been well documented. However, most studies examined this relationship in laboratories or used a cross-sectional design analysing between-person differences. This study investigated the within-person relationship between caffeine intake and sleep duration at home. In a national database, 377 participants (aged 35-85 years) completed a 7-day diary study. Sleep duration was measured by Actigraphy and caffeine intake was self-reported in sleep logs. Three analytic strategies were used. The average sleep duration and the average caffeine intake were not significantly correlated. Multilevel regressions using daytime caffeine intake to predict night-time sleep, and using night-time sleep to predict next day caffeine intake, also did not detect any significant effect. Then dynamical systems analysis was performed, where the daily change rate and change tendency of caffeine and sleep were estimated, and the relationship among these momentums was examined. Results revealed a significant effect of sleep duration on the change tendency of caffeine use: a shorter sleep duration predicted a stronger tendency to consume caffeine, and this phenomenon was only found in middle-aged adults (aged 35-55 years) not in older adults (aged 55+). This study did not detect any effect of daily caffeine intake on sleep duration, implying that habitual use of caffeine in real life may not coincide with laboratory findings, and that using caffeine to compensate for sleep loss is the habit of middle-aged adults, not the elderly. The advantage of using a dynamic approach to analyse interrelated processes with uncertain time lags is also highlighted.

Bayesian analysis of multimethod ego-depletion studies favours the null hypothesis.

Ego-depletion refers to the purported decrease in performance on a task requiring self-control after engaging in a previous task involving self-control, with self-control proposed to be a limited resource. Despite many published studies consistent with this hypothesis, recurrent null findings within our laboratory and indications of publication bias have called into question the validity of the depletion effect. This project used three depletion protocols involved three different depleting initial tasks followed by three different self-control tasks as dependent measures (total n = 840). For each method, effect sizes were not significantly different from zero When data were aggregated across the three different methods and examined meta-analytically, the pooled effect size was not significantly different from zero (for all priors evaluated, Hedges' g = 0.10 with 95% credibility interval of [-0.05, 0.24]) and Bayes factors reflected strong support for the null hypothesis (Bayes factor > 25 for all priors evaluated).