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Record W4285223259 · doi:10.1123/jpah.2022-0018

Adolescents’ Physical Activity and Psychological Adjustment Across the First Year of the COVID-19 Pandemic

2022· article· en· W4285223259 on OpenAlexaffabout
Wendy E. Ellis, Sarah Talebi, Tara M. Dumas, Lindsey M. Forbes

Bibliographic record

VenueJournal of Physical Activity and Health · 2022
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsWestern University
Fundersnot available
KeywordsPandemicAnxietyCoronavirus disease 2019 (COVID-19)Context (archaeology)Physical activityPsychologyDepression (economics)DemographyGerontologyClinical psychologyMedicinePsychiatryPhysical therapyGeographySociologyInternal medicine

Abstract

fetched live from OpenAlex

The outbreak of the COVID-19 virus dramatically changed daily life and created many obstacles for adolescents to engage in physical activity (PA). This study tracked rates of self-reported PA and examined its impact on adjustment among adolescents during the first 14 months of the pandemic. Canadian adolescents (N = 1068, 14-18 y, meanage = 16.95 y) reported on their frequency of PA, context of activity, and adjustment across 4 time points (April 2020 to June 2021). In line with our hypothesis, higher average levels of vigorous PA across the pandemic predicted less anxiety and depression and higher self-esteem at our study's end. Vigorous PA also buffered the relationships COVID-19 stress had with anxiety and self-esteem. The results further support recommendations for PA throughout the pandemic and while dealing with lockdown situations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.285
Threshold uncertainty score0.567

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.120
GPT teacher head0.442
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2022
Admission routes2
Has abstractyes

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