Embedding organisational development in educational institutions into a community network
Bibliographic record
Abstract
Background According to the Ottawa charter (1986), health promotion has to be facilitated in settings. For the age group of 3- to 10-year-olds, not only educational institutions as the primary non-familial settings should be addressed, but also communities must establish health promoting structures. Therefore, the Prevention Network Ortenaukreis (PNO) has developed a district-wide strategy to promote the physical and mental health of children following a two-track implementation: (1) establishing integrated health promotion networks of professionals from the health, educational and youth welfare system; (2) providing organisational development for educational institutions (kindergarten & primary schools) to become health promoting institutions. Methods The complex implementation is accompanied by quantitative and qualitative evaluation components, e. g. interviews with network agents, a mixed-methods community needs assessment on health promotion etc. In kindergartens a waiting list control group design is carried out with pre, post and follow up evaluation to assess the outcomes of the organisational development process. Results The analysis of the community needs assessment (n = 440) on health promotion shows existing and desired future cooperation of professionals from different systems and highlights aspects of health promotion that need to be addressed in the near future. The first analysis from the organisational development in kindergarten shows significant positive effects in the competence development of early childhood teachers (n = 76) over time and in comparison to the control group. The pre-post analysis of the children’s data in the treatment group (n = 132) also shows significant differences in terms of well-being, resilience and social inclusion. Conclusions First analysis show that the interlinked setting development on community and organisational level show promising results for the measures that have been implemented in the last two years. Key messages: A combination of community and educational setting development helps to implement health promotion in the living environment of children and also ensures sustainability on a structural level. Implementing health promotion in the community setting should be based on a systematic, infrastructural strategy and include relevant professionals who influence the living situation of children.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".