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Record W6958366876 · doi:10.6084/m9.figshare.20799367

Supplementary Materials

2022· other· en· W6958366876 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicInformation Systems and Technology Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsycINFOCINAHLPandemicMeta-analysisOddsOdds ratio

Abstract

fetched live from OpenAlex

<em>Background:</em> The coronavirus disease (COVID-19) pandemic has greatly affected the level of physical activity (PA). However, little is known about its effect on health outcomes. This study aimed to investigate the effect of PA on psychological and behavioral problems, sleeping patterns, and quality of life (QoL) before and during the pandemic in preschoolers (£5 years), children (6-12 years), and adolescents (13-18 years). <em>Methods:</em> Articles without language restrictions published from the database inception through March 16, 2022, were retrieved using the CINAHL Complete, Cochrane Library, EMBASE, Medline, PubMed, and PsycINFO databases. High-quality articles assessing the effect of PA on psychological and behavioral problems and PA, QoL, and/or sleep problems before and during the pandemic were included. Articles without data regarding PA or involving non-general populations were excluded. The PRISMA and MOOSE guidelines were followed. Data quality of the selected articles was assessed using the Newcastle-Ottawa Scale and GRADE approach. Data were pooled using a random-effects model and sensitivity analysis if heterogenicity was high (<em>I</em>2≥50%). The relationship between PA and psychological and behavioral problems and changes in PA, QoL, and sleeping patterns before and during the pandemic in preschoolers, children, and adolescents were investigated. A meta-analysis was conducted; odds ratios (ORs), mean differences (MD), and standardized MDs (SMDs) were calculated. <em>Results:</em> Thirty-four articles involving 66,857 participants were included. The results showed an overall significant protective effect between PA and psychological and/or behavioral problems (OR=0.677; 95% CI=0.630, 0.728; <em>p</em>-value&lt;0.001; <em>I2</em>=59.79%). This relationship was also significant in the subgroup analysis of children (OR=0.690; 95% CI=0.632, 0.752; <em>p</em>-value&lt;0.001; <em>I2</em>=58.93%) and adolescents (OR=0.650; 95% CI=0.570, 0.741; <em>p</em>-value&lt;0.001; <em>I2</em>=60.85%); however, no data on the relationship in preschoolers were collected. In addition, the overall time spent on PA significantly decreased by 0.39 hours per day during the COVID-19 pandemic (95% CI=-–0.225, –0.548; <em>p</em>-value&lt;0.001; <em>I2</em>=99.82%). Moreover, the results showed an overall significant decrease in QoL (SMD=–0.894, 95% CI=–1.180, –0.609, <em>p</em>-value&lt;0.001, <em>I2</em>=96.64%). However, there was no significant difference in sleep duration during the COVID-19 pandemic (MD=0.01 hours per day, 95% CI=–0.027, 0.225; <em>p</em>-value=0.125; <em>I2</em>=98.48%). <em>Conclusion:</em> During the pandemic, less PA and longer screen times induced sedentary lifestyles and contributed to poor QoL and sleep quality. However, increases in PA are associated with reduced occurrences of psychological and behavioral problems. Implementing recovery plans to address the health effect of the pandemic is essential.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.964

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)0.9960.037

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 head0.021
GPT teacher head0.223
Teacher spread0.203 · 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