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Record W4394347593 · doi:10.6084/m9.figshare.5255722

Development of Child and Family-Centered Engagement Guidelines for Clinical Administration of the <i>Challenge</i> to Measure Advanced Gross Motor Skills: A Qualitative Study

2017· dataset· en· W4394347593 on OpenAlexaboutno aff
Barbara E. Gibson, Bhavnita Mistry, F. Virginia Wright

Bibliographic record

VenueFigshare · 2017
Typedataset
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
Fundersnot available
KeywordsGross motor skillMeasure (data warehouse)Administration (probate law)PsychologyQualitative researchDevelopmental psychologyMotor skillApplied psychologyPolitical scienceSociologyComputer scienceSocial scienceData miningLaw

Abstract

fetched live from OpenAlex

Aims: This article describes a qualitative study aimed at producing child-centered guidelines for the administration of a measure of children's advanced gross motor skills, the Challenge. The purpose of the guidelines is to promote collaborative interpretation and application of results. Methods: The study was conducted in three Canadian cities and included 31 children with cerebral palsy (GMFCS Level I or II) ages 8 to 18 and one parent/caregiver per child (N = 62 participants). Following Challenge administration, each child and one of their caregivers took part in separate qualitative interviews. Analyses were oriented to exploring understandings of the purposes of testing, impressions of the child's performance, and perceptions of how results might inform activity choices and interventions. Results: Three themes were generated: investments in doing well; I know my child/myself; and caregivers' interpretations of child's performance. Themes were then integrated with principles of child and family-centered care to develop The Challenge Engagement Guidelines directed at reducing test anxiety and enhancing shared decision making. Conclusions: The Guidelines are the first of their kind to integrate child and family-centered principles into the administration protocol of a motor measure. Although developed for the Challenge, the principles have applicability to other rehabilitation measures.

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)0.043
metaresearch head score (Gemma)0.047
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: Dataset · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.012
Scholarly communication0.0040.003
Open science0.0030.006
Research integrity0.0020.003
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 head0.266
GPT teacher head0.490
Teacher spread0.224 · 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
GenreDataset

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
Published2017
Admission routes1
Has abstractyes

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