Mindfulness-based stress reduction (MBSR) in oncology: a Canadian example.
Bibliographic record
Abstract
Įvadas. Įsisamoninimu pagrįsto streso valdymo (angl. Mindfulness Based Stress Reduction, MBSR) programa yra sėkmingai taikoma pacientams, turintiems fizinių, psichosomatinių ir psichikos sutrikimų. Lietuvoje ši praktika yra pakankamai nauja ir iki šiol šia tema publikuotas tik vienas mokslinis straipsnis. Skirtingai nuo Lietuvoje pradedančios vystytis MBSR praktikos, taikytos išemine širdies liga sergantiems pacientams, dauguma pirmaujančių pasaulio šalių mokslininkų tyrėjų taiko šią metodiką vėžiu sergantiems pacientams. Darbo tikslas. Pateikti Kanados smokslininkų gerąją patirtį taikant MBSR metodiką ir vykdant MBSR efektyvumo mokslinius tyrimus. Metodai. Apžvelgiami duomenų bazėje PsycINFO paskelbti naujausi MBSR tyrimai Kanadoje iki 2013 m. kovo mėn. Rezultatai. Per pastaruosius dešimt metų mokslinių publikacijų susijusių su dėmesingu įsisamoninimu (angl. mindfulness) kiekis sparčiai augo: ISI Web of Science duomenų bazėje 2001 m. buvo 30 publikacijų, 2007 m. – 170, o 2010 m. buvo apie 397 publikacijas. Kanada yra viena aktyviausių šalių prisidedančių prie MBSR programos vystymo įvairiose mokslinių tyrimų srityse ir populiacijoje. [...]. Research has shown that Mindfulness Based Stress Reduction (MBSR) can be successfully applied in patients suffering from physical, psychosomatic, psychiatric disorders. In Lithuania this practice is still in the development phase. A good practice example could be taken from Canada MBSR studies. Trending research article on MBSR in oncology, published in a Canadian setting, was obtained for review using the PsycINFo database. Key trending research articles on MBSR within oncology in Canada demonstrates that MBSR programs are effective in decreasing depressive and stress symptoms, decreasing cortisol levels, cytokine production, blood pressure, improving mood, sleep and quality of life and increasing physical activity. [...].
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".