When the night is too short. Bedtime procrastination, self-compassion, and sleep in a daily diary study

Abstract

Objective

Since sleep is an important part of life and too little sleep can lead to disastrous consequences, it is important to look at the factors that may disturb healthy sleep. While procrastination and in particular bedtime procrastination is such a disruptive factor, self-compassion on the other side might be a protective factor.

Methods

For this reason, in this study, we took a closer look at the interplay between bedtime procrastination, self-compassion, as well as at the actual sleep outcomes in a longitudinal diary study over 1 week. Our assumption was that bedtime procrastination has a negative impact on sleep outcomes, yet self-compassion could be a protective factor buffering this influence. To enable comparability with a previous study, analyses of variance were carried out.

Results

Utilizing frequentist and Bayesian analyses, we found a consistent negative influence of bedtime procrastination and a positive influence of self-compassion on almost all sleep outcomes. While self-compassion did not entirely mitigate the effect of bedtime procrastination on sleep, its positive impact on sleep outcomes was evident.

Conclusions

These findings highlight the significance of self-compassion and procrastination in relation to actual sleep behaviour, adding to the existing body of literature on sleep research.

Keywords:

• Sleep
• self-compassion
• health behaviour
• bedtime procrastination

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data are available on OSF: https://osf.io/5njwy/?view_only=9c09ca436ba042ad80061a7da5250e01.

Notes

1 Please note: Since there is a distinction in German between the expressions bedtime as going to bed and bedtime as sleeping, we decided to ask for both. However, there were no differences in the calculations between these constructs. For this reason, the following calculations are made and reported from the participants’ statements on bedtime in the sense of going to bed.

2 In general, Bayesian analysis allows for a direct comparison of likelihoods. For example, the Bayes Factor (BF₁₀) indicates the relative likelihood of the alternative hypothesis (demarked as 1) over the null hypothesis (demarked as 0). A BF₁₀ of 8 would suggest that the alternative hypothesis is about 8 times more likely than the null hypothesis, indicating a more direct relation between the two compared to classical inference statistics. BF_M represents the probability of the model compared to other models considering the data.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.