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Effects of COVID-19 lockdown on sleep duration, sleep quality and burnout in faculty members of higher education in Mexico

2022· article· en· W4286715662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCiência & Saúde Coletiva · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsCanadian Sleep & Circadian Network
Fundersnot available
KeywordsBurnoutBedtimeCoronavirus disease 2019 (COVID-19)Sleep (system call)MedicineSleep qualityDepersonalizationPandemicCross-sectional studyEmotional exhaustionPsychologyGerontologyClinical psychologyPsychiatryInsomniaInternal medicine

Abstract

fetched live from OpenAlex

This paper aims to assess the differences and associations of the effect of COVID-19 on sleep habits, sleep quality, and burnout symptoms among faculty members of higher education in Mexico. This was a cross-sectional study with a total sample of 214 faculty members of higher education from Mexico between May 18th and June 10th of 2020. We applied questionnaires containing sociodemographic and specific questions regarding sleep habits, sleep quality, and burnout symptoms. The results show that during COVID-19 faculty members delayed their bedtime and rise time. No change was found with weekdays time in bed, however, during weekends, time in bed was more than an hour shorter. Social jetlag decreased significantly during COVID-19. Furthermore, during COVID-19, those who reported low sleep quality were more likely to report higher symptoms of emotional exhaustion and those who slept less on weekends were more likely to report higher symptoms of depersonalization. These results suggest that the COVID-19 pandemic may have an effect on sleep and sleep quality and burnout symptoms of faculty members from higher education in Mexico.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.416
Teacher spread0.371 · 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