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Record W2115378758 · doi:10.1300/j006v24n04_02

Mothers' Perceptions of Their Children's Use of Powered Mobility

2004· article· en· W2115378758 on OpenAlexaff
Lesley Pritchard, Johanna Darrah, Vivien Hollis, Al Cook, Laura May

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2004
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of AlbertaCapital District Health Authority
Fundersnot available
KeywordsReceiptPerceptionPsychologyQualitative researchIndependence (probability theory)Developmental psychologyOccupational therapyPsychiatry

Abstract

fetched live from OpenAlex

Physical therapists and occupational therapists frequently assist parents with the exploration and use of powered wheelchairs for their children with physical disabilities. The purpose of this study was to explore parents' experiences and perceptions of their children's experiences with the receipt and use of powered mobility. Qualitative methods were used to gain insight into the experiences of five mothers of children with physical disabilities who use powered wheelchairs. Information was collected during individual interviews with the mothers. Data analyses revealed five higher-level themes identified across the participants. Results of this study suggest that mothers initially perceive powered mobility as a "last resort" mobility option. The perceived effects of their children's use of powered mobility were significant and included increased personal control, independence, and opportunities to participate in age appropriate, meaningful activities. The mothers perceived that increased independence positively affected others' attitudes toward their children and allowed their children to develop more "legitimate" relationships with their peers.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.315
Teacher spread0.284 · 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 designQualitative
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

Citations81
Published2004
Admission routes1
Has abstractyes

Explore more

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