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Record W4398251068 · doi:10.1136/bmjebm-2023-112681

Guidelines for the development and validation of patient-reported outcome measures: a scoping review

2024· review· en· W4398251068 on OpenAlex
Andrés Jung, Dimitris Challoumas, Larissa Pagels, Susan Armijo‐Olivo, Tobias Braun, Kerstin Luedtke

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

VenueBMJ evidence-based medicine · 2024
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPromPsycINFOCLARITYGuidelineMEDLINEScopusMedicineData extractionComputer scienceMedical physicsPathology

Abstract

fetched live from OpenAlex

Objective The objectives of this scoping review were to provide an overview of existing guidelines for the development and validation of patient-reported outcome measures (PROMs), review them for comprehensiveness and clarity and provide recommendations for their use based on the goals of the instrument developers. Design Scoping review. Methods A literature search was performed in PubMed, Scopus, PsycInfo and Google Scholar up to 2 June 2023 to identify guidelines for the development and validation of PROMs. Screening of records and reports as well as data extraction were performed by two reviewers. To assess the comprehensiveness of the included guidelines, a mapping synthesis was performed and steps to develop and validate a measurement instrument outlined in the included guidelines were mapped to an a priori framework including 20 steps, which was based on the guideline by de Vet et al . Results A total of 40 guidelines were included. Statistical advice (at least partially) was provided in 98% of the guidelines (39/40) and 88% (35/40) of the guidelines included examples for steps required to develop and validate PROMs. However, 78% (31/40) of the guidelines were not comprehensive and two essential steps in PROM development (‘consideration and elaboration of the measurement model’ and ‘responsiveness’) were not included in 80% and 72% of the guidelines, respectively. Three guidelines included all 20 steps and six included almost all steps (≥90% of steps) for developing and validating a PROM. Discussion Most guidelines on PROM development and validation do not appear to be comprehensive, and some crucial steps are missing in most guidelines. Nevertheless, for some purposes of PROMs, many guidelines provide helpful advice and support. Conclusion At least 15 guidelines may be recommended, including three comprehensive guidelines that can be recommended for the development and validation of PROMs for most purposes (eg, to discriminate between subjects with a particular condition and subjects without that condition, to evaluate the effects of treatments (between a pre and post time-points) or to evaluate a status quo).

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.005
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.000
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 head0.539
GPT teacher head0.525
Teacher spread0.014 · 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