Abstract
Symptoms of insomnia are an important risk factor for the development of mental disorders, especially during stressful life periods such as the coronavirus disease 2019 (COVID-19) pandemic. However, up to now, most studies have used cross-sectional data, and the prolonged impact of insomnia symptoms during the pandemic on later mental health remains unclear. Therefore, we investigated insomnia symptoms as a predictor of other aspects of mental health across 6 months, with altogether seven assessments (every 30 days, t0-t6), in a community sample (N = 166-267). Results showed no mean-level increase of insomnia symptoms and/or deterioration of mental health between baseline assessment (t0) and the 6- month follow-up (t6). As preregistered, higher insomnia symptoms (between persons) across all time points predicted reduced mental health at the 6-month follow-up. Interestingly, contrary to our hypothesis, higher insomnia symptoms at 1 month, within each person (i.e., compared to that person's symptoms at other time points), predicted improved rather than reduced aspects of mental health 1 month later. Hence, we replicated the predictive effect of averagely increased insomnia symptoms on impaired later mental health during the COVID-19 pandemic. However, we were surprised that increased insomnia symptoms at 1 month predicted aspects of improved mental health 1 month later. This unexpected effect might be specific for our study population and a consequence of our study design. Overall, increased insomnia symptoms may have served as a signal to engage in, and successfully implement, targeted countermeasures, which led to better short-term mental health in this healthy sample.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Psychologie und Pädagogik > Department Psychologie |
Themengebiete: | 100 Philosophie und Psychologie > 150 Psychologie |
URN: | urn:nbn:de:bvb:19-epub-106795-4 |
ISSN: | 0962-1105 |
Sprache: | Englisch |
Dokumenten ID: | 106795 |
Datum der Veröffentlichung auf Open Access LMU: | 11. Sep. 2023, 13:43 |
Letzte Änderungen: | 20. Nov. 2023, 10:50 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892 |