Hibuki therapy combined with other art-therapy methodsin group work with school-age children of different inclusivecategories during the war in Ukraine
Bibliographic record
Abstract
Introduction:The article describes the Hibuki therapy method combined with art therapy techniques to create a set of anti-crisis psychotherapeutic means for group work with school-age children of various inclusive categories.Material and methods: From May to July 2023, a series of social and psychological training sessions using Hibuki therapy together with art therapy was organized.The training sessions were attended by 120 children aged 6 to 17 years having various nosologies and suffering as a result of Russia's armed aggression against Ukraine.The influence on crisis symptoms of the techniques used in the proposed psychological training was evaluated via generalizations of observations and via questionnaires filled in by a parent after the project.Results: The data obtained from observations and questionnaires filled in after the project showed that the majority of children who suffered war-related stresses showed positive changes in their "development zone" due to complex art therapy influences.Namely, their stress reactions were reduced, their confidence was built up, they developed social ties and received certain impulses for personal development.Hibuki therapy can be used as an effective anti-crisis method to overcome traumatic experiences, especially in combination with other art therapy methods, taking into account various social aspects of participants (their age, disability, and migrant status of children).Conclusions: Our study showed the possibility and effectiveness of combining Hibuki therapy method and art therapy methods during group corrective work with school-age children participating in cultural-artistic projects and social practices aimed at mental health restoration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".