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Record W4212915643 · doi:10.1017/cjn.2019.167

P.067 Quality of my life: perceptions of boys with Duchenne muscular dystrophy and their parents

2019· article· en· W4212915643 on OpenAlexvenueaboutno aff
G Bhullar, MR Miller, C. Campbell, Yuan We, B El-Aloul

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2019
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)Duchenne muscular dystrophyMedicinePhysical therapyHealth related quality of lifePediatricsDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Background: To attain the most comprehensive view of the quality of life (QoL) of a child with Duchenne Muscular Dystrophy (DMD), the completion of a pediatric QoL measure by the child and his/her parent and the assessment of QoL and health-related quality of life (HRQoL) as separate constructs is crucial. Previous QoL research has not assessed HRQoL as a separate construct. By using the Quality of My Life (QoML) questionnaire, our objective was to describe QoL and HRQoL in boys with DMD based on child-and parent-reports. Methods: Parent and child dyads identified via the Canadian Neuromuscular Disease Registry received QoML questionnaires (2013-2016). Children and parent-proxy each completed the QoL and HRQoL Visual Analog Scales. Responses were marked on a 10-cm line, with higher scores (max=10) reflecting higher QoL and HRQoL. Descriptive statistics were computed for child- and parent-reports of QoL and HRQoL at three time-points. Results: Mean( SD ) QoL and HRQoL scores for child- and parent-reports were: 1) Baseline ( n =20 dyads), 8.32( 1.72 ) vs. 6.73( 2.23 ) and 7.63( 2.51 ) vs. 6.73( 2.19 ); 2)18-months ( n =10 dyads, n =9 dyads), 7.83( 2.05 ) vs 7.66( 1.66 ) and 7.62( 2.41 ) vs 7.41( 2.16 ); 3) 36-months ( n =15 dyads) 7.38( 2.00 ) vs. 6.99( 1.77 ) and 7.19( 2.70 ) vs. 6.76( 2.26 ). Conclusions: Boys with DMD report higher QoL and HRQoL compared to their parents.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.299
Teacher spread0.263 · 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 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

Citations3
Published2019
Admission routes2
Has abstractyes

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