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Record W4412400666 · doi:10.1186/s41687-025-00920-2

Principles of good practice for concept definition in the context of translation and linguistic validation of clinical outcome assessments (COAs)

2025· article· en· W4412400666 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Patient-Reported Outcomes · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEquivalence (formal languages)Process (computing)Adaptation (eye)Context (archaeology)Meaning (existential)Conceptual frameworkComputer scienceKnowledge managementPsychologyLinguisticsManagement scienceSociologyEngineeringSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Translation teams conducting translation and cultural adaptation find it paramount to properly describe concepts of items within clinical outcome assessments (COAs). To minimize potential threats to linguistic/conceptual equivalence, these teams must understand the concepts a COA intends to measure. This research provides recommendations for the process of developing concept definitions in general, as well as specific recommendations on who should be involved in the process and what a concept definition document should contain. METHODS: The Concept Definition Working Group of the International Society for Quality of Life Research (ISOQOL) Translation and Cultural Adaptation Special Interest Group (TCA-SIG) carried out a literature review and a survey of 20 professionals working in the area of translation and linguistic validation of COAs. The Working Group based recommendations on a combination of survey results and consensus building via online meetings. RESULTS: Translation teams should develop concept definitions during the preparation phase of the translation process, assuming they do not already exist, and include COA developers and project managers with experience in linguistic validation and conceptual analysis of COAs. The Working Group recommends that concept definitions consist of information related to the therapeutic area being studied, information related to the COA development process, definitions of concepts and domains, as well as elaboration of colloquialisms and acceptable/unacceptable translation alternatives. We recommend centralized distribution of concept definitions. CONCLUSIONS: Concept definitions guide stakeholders and ensure all parties align on the intended meaning of items being translated. While experts have made recommendations for best practices around translation and linguistic validation methodology, they have not clearly delineated the process of defining concepts. The Concept Definition Working Group of the ISOQOL TCA-SIG has therefore developed a set of recommendations for the process of defining concepts. With these recommendations the Working Group intends to standardize the development of concept definitions with the goal of enhancing conceptual equivalence across translations to support data pooling and provide confidence that clinical trial data are comparable, interpretable, and can be relied upon in evaluating clinical benefit of treatments.

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.

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)0.061
metaresearch head score (Gemma)0.149
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0610.149
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.787
GPT teacher head0.612
Teacher spread0.175 · 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