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Record W4310029387 · doi:10.1016/j.arrct.2022.100249

A Systematic Review of Outcomes Measured Following New Wheelchair and Seating-Prescription Interventions in Adults

2022· review· en· W4310029387 on OpenAlexaboutno aff
Belinda Robertson, Rachel Lane, Natasha A. Lannin, Kate Laver, Christopher M. Barr

Bibliographic record

VenueArchives of Rehabilitation Research and Clinical Translation · 2022
Typereview
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
FundersSouth Australian Research and Development InstituteNational Heart Foundation of Australia
KeywordsPsychological interventionWheelchairMedical prescriptionPhysical medicine and rehabilitationMedicinePsychologyComputer scienceNursingWorld Wide Web

Abstract

fetched live from OpenAlex

Objectives: To determine the outcomes and outcome-measurement tools currently used during the prescription of new wheelchairs and/or seating systems. A systematic review of studies was performed to identify outcome-measurement tools. Data Sources: MEDLINE, CINAHL, EMBASE, and PsycINFO were searched from earliest available to March 2022. Study Selection: Studies were included if they focused on a new wheelchair or seating-system prescription with adults. Data Extraction: Data extraction and quality assessments were conducted by 2 reviewers; disagreements were resolved by consensus. Risk of bias was assessed using the PEDro scale (for randomized controlled trials) and the Newcastle-Ottawa Quality Assessment Scale (for non-randomized studies). Data Synthesis: 48 articles were included which identified 37 standardized outcome-measurement tools. Use of study-specific outcome-measurement tools was common. Wheelchair use, user satisfaction, activity, and participation were the most studied outcome domains. Commonly used standardized assessments included the QUEST 2.0, functional independence measure, WHODAS II, IPPA, and PIADS. Conclusion: Outcome measures to evaluate wheelchair and seating-system prescription vary, and the use of study-specific outcome-measurement tools is high. There is a need to choose consistent outcome measures that are reliable and valid, and deal with this complex area through ensuring carefully constructed study designs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.226
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.408
GPT teacher head0.603
Teacher spread0.195 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2022
Admission routes1
Has abstractyes

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