MétaCan
Menu
Back to cohort
Record W2341340124

PARENTAL AND SCHOOL INFLUENCES ON PHYSICAL ACTIVITY LEVELS OF HIGH SCHOOL STUDENTS IN HYDERABAD, PAKISTAN.

2016· article· en· W2341340124 on OpenAlexaff
Jamil Ahmed, Vikram Mehraj, Gotam Kumar Jeswani, Shafiq ur Rehman, Sayed Masoom Shah, Randah R Hamadeh

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicinePhysical activityCross-sectional studyFamily medicinePhysical therapy
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Childhood physical activity (PA) is an important determinant of health in adults which is influenced by the environment in and outside of home. We aimed to determine the contribution of parental and school factors on student's PA in this study. METHODS: This cross sectional study was conducted on students attending public and private schools in Hyderabad, Pakistan. A random sample of 246 girls and 255 boys in grade six to ten were selected from ten schools. The PA was assessed through face to face interviews by using the adapted School Health Action Planning and Evaluation System (SHAPES) questionnaire. RESULTS: 40% of the students either walked to or rode on a cycle to travel to their school and 62% students performed individual exercises after school. They spent 6.2 and 5.3 hours on moderate and hard PA per week. About 57% of the mothers and 47% fathers of the students did some mild to moderate exercise 4 times in the week prior to the interview. Students were physically active if they lived in a nuclear family, had believed they had better athletic ability, participated in sports in and out of school and performed moderate exercises (p < 0.05). CONCLUSIONS: In conclusion parental support to PA was significantly associated with students' being physically active both within and outside schools.

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 score0.285
Threshold uncertainty score0.455

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)0.0000.000

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 head0.024
GPT teacher head0.308
Teacher spread0.284 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicChildren's Physical and Motor DevelopmentFrench-language works237,207