Effectiveness of child-oriented mindfulness therapy on pain of the children with rheumatism
Bibliographic record
Abstract
Background: many researches have shown physiological and chronic diseases such as rheumatism can damage the children’s psychological, relationships, social and emotional processes. Could mindfulness therapy be effective to reduce if this damages? Aims: Therefore, the present study was conducted aiming to investigate the effectiveness of child-oriented mindfulness on pain of the children with rheumatism. Method: It was a quasi-experimental study with pretest, posttest, control group and two-month follow-up period. The research population included the children with rheumatism in the city of Isfahan in the autumn of 2018. 30 children with rheumatism were selected through non-random convenient sampling and randomly replaced into experimental and control groups. Then the experimental group received ten sixty-minute sessions of child-oriented mindfulness interventions (Burdic, 2017) during three months. The applied questionnaire included McGill Pain Questionnaire (Melzack, 1997). The data from the study were analyzed through repeated measurement ANOVA. Results: The results of the study showed that mindfulness therapy has significantly influenced pain of the children with rheumatism (p<0/001). Moreover, the results showed that this therapy was able to significantly maintain its effect in time (p<0/001). The degree of statistical effect of mindfulness therapy on mindfulness on pain was 90% respectively in the children with rheumatism. Conclusions: According to the findings of the present study it can be concluded that mindfulness therapy employing techniques such as thoughts, emotions and mindful behavior can be applied as an efficient therapy to decrease pain of the children with rheumatism.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".