Quality of life as a criterion for children’s adaptation to schooling
Bibliographic record
Abstract
Introduction. In modern conditions, the quality of life (QoL) is regarded as one of the main and reliable tools for health state research. Most questionnaires for the quality of life assessment have been developed for children with various diseases, and studies of the quality of life in somatically healthy children are few. The study of the processes of a child’s adaptation to learning in primary school mainly has a psychological and pedagogical focus. There are virtually no scientific papers covering the course of a child’s adaptation to learning in the first grade. Objective. To assess the adaptation of children to learning in the first grade using QoL indices. Materials and methods. The study was conducted from the fall of 2022 to the spring of 2023. To assess the QoL, the Russian-language version of the international instrument was chosen — the general questionnaire — Pediatric Quality of Life Inventory — PedsQL 4.0. The Kern–Jerasik test was used to assess the school maturity. A total of 454 questionnaires in 7–8 years of children going in for the school of the Moscow region were analyzed. Results. When assessing the Kern–Jerasik test for readiness for school, it was found that only a quarter of the children was found to be completely ready for school, the same number of younger schoolchildren had risks at the beginning of the study, and most of the children fell into the “maturing” group with good potential for development. At the end of the school year, a repeat examination of children was conducted. More than 50% were assessed as “mature”, 35% fell into the “maturing” group with a favourable prognosis and 13% of children remained in the risk group at the end of the school year. When assessing the QoL at the beginning of the school year, children from the risk group were noted to have worse scores compared to other groups in physical, social, and school functioning. Assessment of QoLin children in this group at the end of the school year showed the scores on all scales to remain significantly lower than those of children from other groups. When assessing the course of QoL during the school year, both in children at risk and in mature children, the index significantly decreased in all aspects of functioning, primarily due to the emotional aspect. Conclusion. New data on the QoL in primary school children was obtained. The demonstrated capabilities of the PedsQL 4.0 questionnaire and the Kern–Jerasik Test, when used together, can provide material for creating a more complete picture of the life of children entering school and predicting their adaptation based on changes in QoL indice during the first year of the study.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".