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Record W6977060941 · doi:10.6084/m9.figshare.5254498

Développement et validation de la version canadienne-française de l’échelle de Satisfaction des Adolescents de la gestion de la Douleur postopératoire – Scoliose idiopathique (SAD-S)

2017· article· en· W6977060941 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typearticle
Languageen
FieldMedicine
TopicParvovirus B19 Infection Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScoliosisDelphi methodScale (ratio)Idiopathic scoliosisPsychometricsHealth professionalsOrdinal dataPatient satisfaction

Abstract

fetched live from OpenAlex

<b>Background</b>: Spinal fusion for scoliosis generates moderate to severe pain intensity. There are currently no instruments available to measure adolescents’ satisfaction regarding post-spinal fusion pain management. <b>Aims</b>: To develop and validate a scale on satisfaction of adolescents regarding pain management following spinal fusion for scoliosis. <b>Methods</b>: A methodological design was used to develop and validate the French-Canadian scale “Satisfaction des Adolescents de la gestion de la Douleur postopératoire – Scoliose idiopathique (SAD-S)”. A modified Delphi method, with seven healthcare professionals and 10 adolescents, was used to establish content validity of the SAD-S. A pre-test of the scale was conducted with 10 adolescents post-spinal fusion. The final version of the scale was validated through a pilot study with 98 adolescents following their surgery. <b>Results</b>: The SAD-S scale includes a total of 13 items. Principal component analysis yielded a two-factor structure (2 subscales): 1) Pain management education and 2) Education regarding medication. These two factors explained 47,8% of the total variance for satisfaction. A Cronbach’s alpha of 0,84 was obtained for internal consistency. <b>Conclusion</b>: Validation of the SAD-S scale showed that it has good psychometric properties with this population. Further validation is required with a larger sample to pursue its validation.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.343
Teacher spread0.310 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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