MétaCan
Menu
Back to cohort
Record W3156968646 · doi:10.11124/jbisrir-d-19-00273

Psychometric properties of life-space mobility measures in community-dwelling older adults: a systematic review protocol

2021· review· en· W3156968646 on OpenAlexaff
Emily Cino, Marla Beauchamp, Julie Richardson, Muhib Masrur, Ayse Kuspinar

Bibliographic record

VenueJBI Evidence Synthesis · 2021
Typereview
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsQuality of life (healthcare)Space (punctuation)InterpretabilityConstruct validityProtocol (science)Reliability (semiconductor)PsychologyConstruct (python library)GerontologyApplied psychologyPopulationMedicinePsychometricsComputer scienceClinical psychologyAlternative medicineArtificial intelligencePsychotherapist

Abstract

fetched live from OpenAlex

INTRODUCTION: Mobility is one of the most important contributors to healthy aging and is traditionally measured through performance-based tests. Measuring life-space mobility is a holistic way to measure the spaces individuals visited over a period of time versus what they are physically able to do. However, before a measure of life-space mobility can be widely used in research and clinical settings, it must have robust psychometric properties. The objective of this review is to summarize the psychometric properties of existing life-space mobility measures in community-dwelling older adults. INCLUSION CRITERIA: The construct is life-space mobility and the instruments are: The Nursing Home Life Space Diameter, the Life-Space Questionnaire, and the Life-Space Assessment. The population is community-dwelling older adults (age > 65). The outcome of the review includes all psychometric properties (reliability, validity, responsiveness) as well as feasibility and interpretability data. METHODS: Following the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and JBI guidelines, a search strategy will be piloted and then translated to multiple databases. Two independent reviewers will conduct title/abstract screening, full-text screening, data extraction, and assess the methodological quality of the studies. A narrative synthesis will be compiled for all collected data. A meta-analysis will be conducted for each psychometric property if there are enough studies with sufficiently low heterogeneity. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42019121855.

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 imitation

Not 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.

metaresearch head score (Codex)0.081
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.081
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.097
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0170.016
Bibliometrics0.0140.012
Science and technology studies0.0040.005
Scholarly communication0.0070.008
Open science0.0050.005
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0490.006

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.

Opus teacher head0.137
GPT teacher head0.452
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJBI Evidence SynthesisSame topicOlder Adults Driving StudiesFrench-language works237,207