Computer related musculoskeletal ill-health among upper-secondary school pupils 2005
Bibliographic record
Abstract
The data collection was performed in high schools in the counties of Stockholm, Södermanland, Uppsala and Västmanland during the autumn of 2005. The study consisted of two parts: 1. Questionnaires for the students. 2. Ergonomic evaluation of the schools computer workplaces and a short interview with the person responsible for the computers at the school. An information letter was sent to the school leaders where the setup and implementation of the study were explained. After that the school leaders were contacted by telephone and asked if their school wished to participate in the study. If they chose to take part, they were asked to send a record of all students in the second grade to Working Life Institute (Arbetslivsinstitutet). From these lists a selection of classes was made. Then a new contact with the school leader was made, where the leader was asked to inform the teachers concerned by the study. In addition, each teacher got a letter with information about the study. The students got information about the study from their teachers and from the first page in the questionnaire. The ambition was to have a researcher from the Working Life Institute present at the school when the students answered the questionnaire. The completed questionnaires were gathered by the teachers or the researcher and brought to the Working Life Institute where they were de-identified. After that the questionnaires were sent to the company "Tabell och Form AB" for scanning and a primary data preparation. Ergonomists from the Working Life Institute visited all selected schools to perform an ergonomic evaluation, according to a structured checklist, of the student's computer workplaces and to do a short interview with the person responsible for the computers at the school. The aim of the study was to describe range of computer usage in school and in spear time and the prevalence of difficulties, especially in the locomotive organs, among high school students. The aim was also to examine if there is a connection between computer time and physical difficulties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.149 |
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; both teacher heads agree on what is shown here.
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".