The use of mindfulness-based stress reduction (MBSR) for lung cancer patients: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Mindfulness-based stress reduction (MBSR) intervention has been extensively applied in cancer patients for relieving symptom burden and its effectiveness has also been demonstrated. However, the effectiveness of MBSR on psychological and physical functions in lung cancer patients has not yet been determined. The aim of the present systematic review and meta-analysis seeks to determine the role of MBSR in lung cancer patients. METHODS: A systematic search of PubMed, EMBASE, Cochrane Library, and China National Knowledgement Infrastructure (CNKI) will be carried out from their inception until to December 30, 2020. Studies investigating the comparative effects between MBSR and control groups on psychological and physical outcomes will be documented. Data concerning studies, patient characteristics, and outcomes will be extracted. Methodological quality of each eligible randomized controlled trial (RCT) will be assessed individually by two investigators independently using criteria recommended in the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0. Meanwhile, Newcastle-Ottawa Quality Assessment Scale (NOS) will be used to assess methodological quality of non-randomized studies. All statistical analyses will be performed with RevMan and STATA softwares. DISCUSSION: The role of MBSR in lung cancer patients has not yet been demonstrated. This systematic review and meta-analysis will further determine the effectiveness of MBSR on psychological and physical outcomes and QoL among lung cancer patients, which will provide golden references for developing psychological interventions in order to improve patient care and designing future studies to bridge the gap between research findings and clinical practice. TRIAL REGISTRATION: We registered the protocol of this systematic review and meta-analysis in Open Science Framework (OSF) platform with a registration DOI of 10.17605/OSF.IO/MWVBQ (available from: https://osf.io/mwvbq).
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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 | 0.054 | 0.071 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.005 |
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".