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Record W7019064891

Ervaren problemen van kinderen en adolescenten met cerebrale parese

2016· dissertation· nl· W7019064891 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2016
Typedissertation
Languagenl
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyRehabilitationAcquired brain injury
DOInot available

Abstract

fetched live from OpenAlex

Inleiding: Er is weinig bekend over ervaren problemen van kinderen en adolescenten met cerebrale parese (CP) vanuit hun eigen perspectief. Huidig onderzoek heeft als hoofddoel om de zelf ervaren problemen van kinderen en adolescenten met CP te inventariseren. Een secundair doel betreft het toetsen van verschillen in ervaren problemen tussen leeftijdsgroepen, GMFCS niveau en wel of geen CP. \nMethoden: Totaal werden 246 participanten met CP (M leeftijd: 11.1, SD: 5.8) uit de Pediatric Rehabilitation Research in the Netherlands (PERRIN) in dit onderzoek opgenomen. Om de ervaren problemen te meten werd gebruik gemaakt van de Canadian Occupational Performance Measure (COPM). Om de ernst van CP te meten werd gebruik gemaakt van de Gross Motor Function Classification System (GMFCS). De COPM data werd ingedeeld naar de International Classification of Functioning, Disability and Health (ICF). Verschillen werden getoetst met de Pearson Chi-Kwadraat toets. \nResultaten: De ervaren problemen van kinderen en adolescenten met CP bleken kwalitatief verschillend. Er werd een significant verschil gevonden in ervaren problemen tussen leeftijdsgroepen (X 2 (51, N = 611) = 242, p < .05), GMFCS niveau (X 2 (68, N = 608) = 127, p < .05) en wel of geen CP (X 2 (133, N = 763) = 880, p < .05). \nConclusie: De meeste problemen worden, over alle leeftijden, genoemd binnen het component activiteiten en participatie. Daarnaast blijken de verschillen in ervaren problemen tussen leeftijdsgroepen, GMFCS niveau en wel of geen CP significant. Voor de praktijk is het relevant om naast standaardvragenlijsten de COPM te gebruiken.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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