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Record W3159880460 · doi:10.1093/sleep/zsab072.667

669 Increased Nightmares During the COVID-19 Pandemic: Exploring the Role of Resilience and Emotions

2021· article· en· W3159880460 on OpenAlexaff
Jérémie Potvin, Laura Ramos Socarras, Geneviève Forest

Bibliographic record

VenueSLEEP · 2021
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsPsychologyPandemicCoronavirus disease 2019 (COVID-19)Psychological resilienceYoung adultMental health2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Multilevel modelPittsburgh Sleep Quality IndexDevelopmental psychologyClinical psychologyDemographyPsychiatrySleep qualitySocial psychologyMedicineInsomniaOutbreakSociology

Abstract

fetched live from OpenAlex

Abstract Introduction COVID-19 had a tremendous impact on many aspects of our lives and has caused an increase in stress and mental health issues in many people. We have recently found that there was an increase in nightmares during the pandemic in young adults. Since emotions have been associated with both resilience and nightmares, the objective of this study was to investigate the role of resilience and emotional changes in the increase in nightmares observed during the pandemic, in a group of young adults. Methods Resilience, emotions and nightmares were assessed using the Connor-Davidson Resilience Scale-10, the Differential Emotions Scale-IV and an adapted version of the Pittsburgh Sleep Quality Index. Measures were administered to 209 young adults (18–25 years old, 76.1% females). Hierarchical multiple regression models were computed to examine the unique contribution of changes in positive and negative emotions during the pandemic to the increase in nightmares during the pandemic. Analyses were controlled for nightmares and emotions prior to COVID-19, and for gender. The sample was separated in two groups: resilient and less resilient young adults. Results Results show that in less resilient young adults, nightmares prior to COVID-19 (β=.79, p<.001) and increase in negative emotions (β=.21, p=.033) significantly predicted nightmares during the pandemic and explained 67.0% of their variance. In resilient young adults, nightmares prior to COVID-19 (β=.56, p<.001) and gender (β=-.15, p=.04) significantly predicted nightmares during the pandemic and explained 52.0% of the variance. Conclusion Our results show that increase in negative emotions during the pandemic is associated with an increase in nightmares in less resilient young adults, but not in resilient young adults. Furthermore, our results show that in resilient young adults, being a woman is associated with an increase in nightmares during the pandemic. These results suggest that resilience may be a protective factor in managing the impact of negative emotions on nightmares, but only in men. Support (if any):

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.289
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2021
Admission routes1
Has abstractyes

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