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Record W3012636779 · doi:10.1186/s12955-020-01327-x

Cross-cultural adaptation and validation of the Canadian Haemophilia Outcomes-Kids’ Life Assessment Tool (CHO-KLAT) in Côte d’Ivoire (the Ivory Coast)

2020· article· en· W3012636779 on OpenAlexaffabout
Catherine Lambert, N’Dogomo Meité, Ibrahima Sanogo, Sébastien Lobet, Cédric Hermans, Séverine Henrard, Victor S. Blanchette, Nancy L. Young

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2020
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsHospital for Sick ChildrenLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsHaemophiliaDebriefingQuality of life (healthcare)Cognitive interviewMedicineCronbach's alphaPopulationCross-culturalGerontologyPsychologyFamily medicinePsychometricsPediatricsCognitionClinical psychologyPsychiatryNursingSociologyMedical educationEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Introduction Health-related quality of life evaluation is recognized as an important outcome in the assessment of boys with haemophilia. In fact, reliable health-related quality of life data are even more critical in developing countries to advocate for government agencies to develop national haemophilia care programmes. However, validated tools are not yet available in sub-Saharan African countries. Aims The purpose of this study was to complete the cultural adaptation and validation of the Canadian Haemophilia Outcomes-Kids’ Life Assessment Tool version2.0 (CHO-KLAT2.0) in Côte d’Ivoire. Methods The process included four steps: a linguistic adaptation, cognitive debriefing interviews with children and their parents, a validity assessment with the Pediatric Quality of Life Inventory (PedsQL) as a comparator, and a test-retest reliability assessment. Results The initial Ivoirian version of the CHO-KLAT2.0 was developed through a linguistic adaptation performed in close collaboration with members of the local medical team and haemophilia community. Cognitive debriefings were completed with five boys and their parents, with the final Ivoirian version of the CHO-KLAT2.0 developed in September 2017. The validation process included 37 boys with haemophilia (mean age: 11.4 years; 34 with severe and three with moderate forms of haemophilia, all treated on demand) and their parents. Among the child-reported population (n = 20), we observed a mean CHO-KLAT2.0 score of 51.3 ± 9.2; there was a moderate correlation between the CHO-KLAT2.0 and PedsQL scores (r = 0.581; p = 0.007) and an inverse correlation of the CHO-KLAT2.0 and PedsQL scores with the global rating of the degree to which the boys were bothered by their haemophilia. The mean parent proxy CHO-KLAT2.0 score (n = 17) was 53.5 ± 9.8. Among the parents, we found no significant correlation between the Ivoirian CHO-KLAT2.0 and PedsQL scores or between the parent-reported scores and the parent global ratings of bother. The test-retest intraclass correlation coefficient was 0.879 (95% CI: 0.673; 0.954) for the child-reported questionnaires and 0.880 (95% CI: 0.694; 0.955) for the proxy-reported questionnaires. Conclusions A cross-culturally adapted and validated version of the CHO-KLAT2.0 for Côte d’Ivoire is now available that enables baseline values to be obtained and intervention outcomes (namely, prophylaxis) to be measured in Ivoirian boys with haemophilia.

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)0.018
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.798

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.002
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 head0.185
GPT teacher head0.445
Teacher spread0.260 · 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 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".

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Citations7
Published2020
Admission routes2
Has abstractyes

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