MétaCan
Menu
Back to cohort
Record W4403384525 · doi:10.1080/00049530.2024.2408019

Adolescent and young adult sleep and sleep-related behaviour change before and during the COVID-19 pandemic lockdown in Canada

2024· article· en· W4403384525 on OpenAlexafffundabout
Nicole E. Carmona, Samlau Kutana, David Sumantry, Onkar Marway, Alison E. Carney, Maya E. Amestoy, Aleksandra Usyatynsky, Colleen E. Carney

Bibliographic record

VenueAustralian Journal of Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsToronto Metropolitan University
FundersCanadian Institutes of Health Research
KeywordsCoronavirus disease 2019 (COVID-19)PandemicPsychologyYoung adultSleep (system call)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Developmental psychologyClinical psychologyPsychiatryMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Background: Sleep disturbance is common in adolescents and young adults (AYAs), impacted by stress and academic/scheduling demands that conflict with biological phase delay. COVID-19 lockdowns allowed us to study sleep in AYAs when there are lessened scheduling demands. Additionally, we could test whether a sleep self-management app was helpful during lockdowns. Method: = 40) completed sleep diaries on the app; set goals based on generated feedback; and completed more sleep diaries pursuing whatever post-feedback goals they set. Results: The Lockdown group reported later and less variable rise times (RT) and spent more time in bed (TIB), both awake and asleep. Pre-Lockdown set a goal to reduce RT variability whereas Lockdown set a goal to decrease TIB, and AYAs made behaviour changes to meet their goals. For both groups, sleep onset, duration of awakenings, sleep duration and efficiency, and insomnia severity significantly improved at endpoint. Conclusions: AYAs slept differently during lockdowns, perhaps due to decreased scheduling. The pandemic revealed the need for accessible strategies to improve sleep health. Findings support the feasibility of using evidence-based apps, and that AYAs can effectively use self-management tools across variable global and social contexts to improve their sleep.

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.

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 score0.261
Threshold uncertainty score0.895

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 integrity0.0000.001
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 head0.031
GPT teacher head0.323
Teacher spread0.293 · 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".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueAustralian Journal of PsychologySame topicSleep and related disordersFrench-language works237,207