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Record W4210488274 · doi:10.2196/preprints.16534

Influence of Cognitive Functioning on Powered Mobility Device Use: Protocol for a Systematic Review (Preprint)

2019· review· en· W4210488274 on OpenAlexaboutno aff
Alice Pellichero, Lisa K. Kenyon, Krista L. Best, É. Sorita, Marie‐Ève Lamontagne, Marie Denise Lavoie, François Routhier

Bibliographic record

Venuenot available
Typereview
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLPsycINFOCognitive skillCognitionMEDLINEInternational Classification of Functioning, Disability and HealthProtocol (science)Clinical psychologyPsychologyApplied psychologyMedicinePsychological interventionPsychiatryPhysical therapyAlternative medicineRehabilitation

Abstract

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BACKGROUND Power mobility devices (PMD) are critical to achieving independent mobility and social participation for many individuals who have trouble walking. Provision of PMDs is complex, with cognitive functioning expressed by clinicians as a major concern. Even if PMD use can be predicted by the level of cognitive functioning, outcome tools used to assess readiness do not consider how cognitive functioning may affect PMD use. OBJECTIVE The specific aims of this review are to identify existing assessments used to assess cognitive functioning and PMD use, classify cognitive functions that are identified within existing assessments related to PMD use, and explore the relationships between cognitive functioning (ie, executive functions and attention) and PMD use. METHODS A systematic review will be conducted using the electronic databases MEDLINE (Ovid), CINAHL, Embase, PsycINFO (Ovid), and Web of Science based on the concepts of PMD performance and capacity, and cognitive functioning. To be included, studies must have: a sample of PMD users (inclusive of age and diagnoses), an assessment of cognitive functioning, and an assessment of PMD capacity or performance. The International Classification of Functioning, Disability and Health will be used to classify cognitive functions. Study quality will be assessed using the Mixed Methods Appraisal Tool. Qualitative and quantitative studies will be analyzed in a complementary manner depending on their designs; a result-based convergent synthesis design will be applied. RESULTS This proposed systematic review protocol has been registered in PROSPERO (CRD42019118957). It was funded by the Quebec Rehabilitation Research Network and approved on February 2019. CONCLUSIONS Results will inform the development of a PMD driving program that aims to enhance cognition. The results of this study will enhance understanding of the influence of cognitive functioning on PMD use and will support the clinical practice in choosing appropriate evaluative tools. CLINICALTRIAL PROSPERO CRD42019118957; https://www.crd.york.ac.uk/PROSPERO/display_record.php? RecordID=118957 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/16534

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.074
metaresearch head score (Gemma)0.108
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 score0.099
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.108
Meta-epidemiology (narrow)0.0060.006
Meta-epidemiology (broad)0.0220.020
Bibliometrics0.0140.013
Science and technology studies0.0040.004
Scholarly communication0.0090.009
Open science0.0040.005
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0990.009

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 head0.291
GPT teacher head0.560
Teacher spread0.269 · 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

Labeled directly by 2 models reading the full record.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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