Measurement properties of self-report physical activity assessment tools in stroke: a protocol for a systematic review
Bibliographic record
Abstract
Introduction Self-report physical activity assessment tools are commonly used for the evaluation of physical activity levels in individuals with stroke. A great variety of these tools have been developed and widely used in recent years, which justify the need to examine their measurement properties and clinical utility. Therefore, the main objectives of this systematic review are to examine the measurement properties and clinical utility of self-report measures of physical activity and discuss the strengths and limitations of the identified tools. Methods and analysis A systematic review of studies that investigated the measurement properties and/or clinical utility of self-report physical activity assessment tools in stroke will be conducted. Electronic searches will be performed in five databases: Medical Literature Analysis and Retrieval System Online (MEDLINE) (PubMed), Excerpta Medica Database (EMBASE), Physiotherapy Evidence Database (PEDro), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS) and Scientific Electronic Library Online (SciELO), followed by hand searches of the reference lists of the included studies. Two independent reviewers will screen all retrieve titles, abstracts, and full texts, according to the inclusion criteria and will also extract the data. A third reviewer will be referred to solve any disagreement. A descriptive summary of the included studies will contain the design, participants, as well as the characteristics, measurement properties, and clinical utility of the self-report tools. The methodological quality of the studies will be evaluated using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist and the clinical utility of the identified tools will be assessed considering predefined criteria. This systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. Discussion This systematic review will provide an extensive review of the measurement properties and clinical utility of self-report physical activity assessment tools used in individuals with stroke, which would benefit clinicians and researchers. Trial registration number PROSPERO CRD42016037146.
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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 | 0.141 | 0.163 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.020 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.008 |
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".