Quality of mobility measures among individuals with acquired brain injury: an umbrella review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: While several mobility measures exist, there is large variability across measures in how mobility is conceptualized, the source of information and the measurement properties making it challenging to select relevant mobility measures for individuals with acquired brain injury (ABI). Therefore, the objective was to conduct a comprehensive synthesis of existing evidence on the measurement properties, the interpretability and the feasibility of mobility measures from various sources of information (patients, clinicians, technology) using an umbrella review of published systematic reviews among individuals with ABI. METHODS: Ovid MEDLINE, CINHAL, Cochrane Library and EMBASE electronic databases were searched from 2000 to March 2020. Two independent reviewers appraised the methodological quality of the systematic reviews using the Joanna Briggs Institute critical appraisal checklist. Measurement properties and quality of evidence were applied according to COnsensus-based Standards for the Selection of Health Measurement Instrument (COSMIN) guidelines. Mobility measures were categorized using international standards with the international classification of functioning, disability and health (ICF). RESULTS: Thirty-five systematic reviews were included covering 147 mobility measures, of which 85% were mapped to the ICF Activity and Participation component. Results showed an acceptable overall "sufficient" rating for reliability, construct validity and responsiveness for 132 (90%), 127 (86%) and 76 (52%) of the measures, respectively; however, among these measures, ≤ 25% of the methods for evaluating these properties were rated as 'high' quality of evidence. Also, there was limited information that supports measure feasibility and scoring interpretability. CONCLUSIONS: Future systematic reviews should report measures' content validity to support the use of the measure in clinical care and research. More evaluations of the minimal important difference and floor and ceiling effects are needed to help guide clinical interpretation. REGISTRATION INFORMATION: International Prospective Register of Systematic Reviews (PROSPERO); ID: CRD42018100068.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.097 | 0.342 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.034 | 0.024 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".