The Effect of Mobile Phone Short Messages System on Physical Activity and Anthropometric Measures among Postmenopausal Women
Bibliographic record
Abstract
The main objective of this study was to evaluate the impact of mobile phone short messages system on physical activity and anthropometric measures among postmenopausal women in Iran. This was a randomized controlled trial in which 100 postmenopausal women with body mass index (BMI) ≥25were recruited randomly in Ahvaz, Iran. Weight, height, waist circumference, hip circumference, waist-hip ratio and physical activity were measured at the beginning and four months after intervention. Intervention was including; 49 short messages with the content of motivating the subjects to enhance their daily physical activity that sent for participants every other day. The control group received the routine care. The descriptive, independent t-test, paired t-test and chi-square test were utilized for statistical purposes. At the end of the study, weight reduced significantly in the control group compared to the intervention group (p=0.004) and physical activity level was reduced in both groups after four months; however the reduction was more evident in the control group. There was not any significant difference between two groups regarding weight, BMI, waist circumference, hip circumference, waisthip ratio and physical activity. Further studies with aim of compare mobile short messages with other educational methods are recommended.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".