The Effect of Audiovisual Education on Physical Activity Tendencies in Secondary School Children
Bibliographic record
Abstract
The aim of this study was to investigate the effect of audiovisual education method on the physical activity tendencies of 13-year-old secondary school students. A total of 66 healthy and voluntary male students who were aged 13 years in secondary school participated in this study. The participants were randomly divided into three groups: an educational group (EG; n: 22; height: 146.51±9.01 cm; weight: 37.73±12.20 kg), educational group with parents (EGP; n: 23; height: 146.97±7.19 cm; weight: 42.04±11.39 kg) and a control group (CG; n: 21; height: 141.53±8.27 cm; weight: 39.62±11.72 kg). EG and EGP completed their audiovisual education program in 2 days of the intervention week. Total energy expenditure (TEE), physical activity level (MET), STEP, physical activity duration, lying-down duration and sleep duration values were taken with SenseWear Armband in 6 consecutive days during 24 hours. These values of the study group were taken before (pre-test) and after (post-test) the intervention week. The variances between the groups were determined by one-way ANOVA, and multiple comparisons were used to determine possible differences. The level of significance was used at 0.05. After the audiovisual education programs, a significant increase were observed in the TEE, STEP and MET values of the groups. According to the CG, the TEE and MET values were significantly higher in favor of EGP, and in STEP was also significantly higher in favor of EG and EGP. The audiovisual education programs may contribute to increase physical activity levels by affecting the children’s intrinsic motivations. Also, the family played an effective role in physical activity trends, and therefore, increased the inner motivation of the child, and caused the negative behaviors to be positively changed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".