Effects of the COVID-19 pandemic on anhedonia, reward exposure and responsiveness, and sleep in college students

ABSTRACT

Objective: The COVID-19 pandemic’s effects on college student mental health and its underlying mechanisms are not fully understood. Although necessary, physical distancing abruptly restricts interaction with environmental rewards and disrupts sleep patterns, both of which may contribute to psychological symptoms (eg, depression and anhedonia). This study explored differences in psychological symptoms, reward exposure and responsiveness, and sleep before versus during the pandemic. Methods: Eighty-seven college students completed baseline questionnaires and a one-week daily diary paradigm. The sample was divided into two groups based on data collection before (pre-) or after (post-COVID-19) implementation of state-wide COVID-19 physical distancing measures. Results: Findings highlight higher anhedonia, decrements in exposure to social, professional, and exercise related rewards, lower aniticipatory reward responsiveness, and lower sleep efficiency among college students during the initial months of the pandemic. Conclusions: Findings suggest anhedonia, reward system functioning, and sleep may be important targets to mitigate against college student mental health sequelae during COVID-19.

Keywords:

• Anhedonia
• COVID-19
• reward exposure
• reward responsiveness
• sleep

Conflict of interest disclosure

The authors have no conflicts of interest to report. The authors confirm that the research presented in this article met the ethical guidelines, including adherence to the legal requirements, of the United States of America and received approval from the Committee for the Protection of Human Participants in Research of Emmanuel College.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Notes

1 Given that 30 t-tests were conducted, we accounted for increased risk of Type 1 error by using a Benjamini-Hochberg corrected p-value. Compared to the Bonferroni correction, the Benjamini-Hochberg correction is better suited for detecting true small to medium effects because it is more powerful.²⁴ The Benjamini-Hochberg correction involves rank ordering observed p-values and then comparing each p value to its Benjamini-Hochberg critical value, which is calculated as (i/m)Q. In this calculation, i represents the rank of the observed p-value, m is the total number of tests, and Q is the false discovery rate, which was set to .05 for these analyses.