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Record W3108153348 · doi:10.1177/1403494820971493

The effect of physical-activity intervention on children’s health-related quality of life

2020· article· en· W3108153348 on OpenAlexaff
Silje Eikanger Kvalø, Inger Karin Natlandsmyr

Bibliographic record

VenueScandinavian Journal of Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsCollege & Association of Registered Nurses of Alberta
FundersUniversitetet i Stavanger
KeywordsQuality of life (healthcare)Intervention (counseling)MedicinePhysical activityGerontologyEnvironmental healthPhysical therapyPsychiatryNursing

Abstract

fetched live from OpenAlex

Aims: We investigated the effect of a school-based physical-activity intervention on children’s health-related quality of life (HRQoL) and the potential influence of moderate to vigorous physical activity (MVPA). Methods: A randomised, controlled trial (Active School) involving fifth-grade children was conducted during the 2014/15 school year. The sample included 435 children (10–11 years old) at five intervention schools and four control schools. The weekly interventions concerned two 45 min of physically active lessons, five 10 min of physically active breaks and five 10 min of physically active homework. The children’s HRQoL was measured using KIDSCREEN-27 and a self-report questionnaire, while physical activity was measured using accelerometers. Results: The results of multilevel analysis showed a significant effect on psychological wellbeing ( p = 0.005), social support and peers ( p = 0.005) and school environment ( p = 0.013). No gender differences were observed. Children’s MVPA did not influence their KIDSCREEN-27 score. Conclusions: The school-based physical-activity intervention (Active School) shows positive effects on children’s self-reported psychological wellbeing, social support and peers, and school environment.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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

Citations19
Published2020
Admission routes1
Has abstractyes

Explore more

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