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Record W2015133244 · doi:10.2340/16501977-1922

Adaptive devices in young people with upper limb reduction deficiencies: Use and satisfaction

2015· article· en· W2015133244 on OpenAlexaboutno aff
Ecaterina Vasluian, Iris van Wijk, Pieter U. Dijkstra, Heleen A. Reinders‐Messelink, Corry K. van der Sluis

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2015
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
Fundersnot available
KeywordsReduction (mathematics)ProsthesisPhysical medicine and rehabilitationAmputationPhysical therapyPatient satisfactionPsychologyMedicineNursingSurgeryMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate use of, satisfaction with, and social adjustment with adaptive devices compared with prostheses in young people with upper limb reduction deficiencies. METHODS: Cross-sectional study of 218 young people with upper limb reduction deficiencies (age range 2-20 years) and their parents. A questionnaire was used to evaluate participants' characteristics, difficulties encountered, and preferred solutions for activities, use satisfaction, and social adjustment with adaptive devices vs prostheses. The Quebec User Evaluation of Satisfaction with assistive Technology and a subscale of Trinity Amputation and Prosthesis Experience Scales were used. RESULTS: Of 218 participants, 58% were boys, 87% had transversal upper limb reduction deficiencies, 76% with past/present use of adaptive devices and 37% with past/present use of prostheses. Young people (> 50%) had difficulties in performing activities. Of 360 adaptive devices, 43% were used for self-care (using cutlery), 28% for mobility (riding a bicycle) and 5% for leisure activities. Prostheses were used for self-care (4%), mobility (9%), communication (3%), recreation and leisure (6%) and work/employment (4%). The preferred solution for difficult activities was using unaffected and affected arms/hands and other body parts (> 60%), adaptive devices (< 48%) and prostheses (< 9%). Satisfaction and social adjustment with adaptive devices were greater than with prostheses (p < 0.05). CONCLUSION: Young people with upper limb reduction deficiencies are satisfied and socially well-adjusted with adaptive devices. Adaptive devices are good alternatives to prostheses.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2015
Admission routes1
Has abstractyes

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