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Record W4213053149 · doi:10.1186/s13643-022-01903-w

Psychometric properties of patient-reported outcome measures for dysphagia in head and neck cancer: a systematic review protocol using COSMIN methodology

2022· review· en· W4213053149 on OpenAlexaff
Beatrice Manduchi, Zhiyao Che, Margaret I. Fitch, Jolie Ringash, Doris Howell, Rosemary Martino

Bibliographic record

VenueSystematic Reviews · 2022
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsPromMedicineDysphagiaSwallowingPatient-reported outcomeProtocol (science)Physical therapyOropharyngeal dysphagiaQuality of life (healthcare)Head and neck cancerReliability (semiconductor)InterpretabilityPhysical medicine and rehabilitationCriterion validityPsychometricsConstruct validityClinical psychologyCancerSurgeryAlternative medicinePathologyNursingArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Dysphagia (swallowing difficulty) is one of the most common and debilitating sequelae of head and neck cancer (HNC). Patient-reported outcome measures (PROMs) are a fundamental component of dysphagia outcomes evaluation, as they inform treatment consequences that cannot be captured by objective clinician measures. Many PROMs for dysphagia in HNC are available, but their validity is unclear. As a consequence, the selection of the most appropriate PROM for dysphagia in HNC is complex and often based on the clinician's personal preferences, rather than on valid psychometric properties. This protocol describes a systematic review aiming at (1) identifying PROMs specific to dysphagia symptoms, swallowing functional status, swallowing-related health status, and swallowing-related quality of life in HNC, (2) mapping them to our conceptual framework of dysphagia-related PROs, and (3) appraising their psychometric properties using the Consensus Based Standards for the Selection of Health Measurement Instrument (COSMIN) methodology. METHODS: Six electronic databases will be searched from inception to December 2020 for all primary studies in any language and design detailing PROM development, reliability, validity, feasibility, interpretability, and/or cross-cultural adaptation. Eligibility criteria will target PROMs for patients with HNC (≥ 90% of the study sample) with ≥ 20% of their items pertaining to swallowing. Two independent raters will screen abstract and full texts and a third rater will resolve discrepancies. Data will be extracted on study, sample and PROM characteristics, and results of psychometric testing. PROMs will be mapped to our conceptual framework. The methodological quality of included PROMs and their psychometric properties will be appraised using the COSMIN risk of bias checklist and evidence will be summarized using a modified Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. DISCUSSION: This systematic review will provide a summary of existing dysphagia-related PROMs for people with HNC and a comprehensive account of their psychometric properties. We will provide recommendations on PROMs selection which will aid healthcare professionals to the most appropriate PROM based on its validity, reliability, feasibility, interpretability and suitability for clinical and research settings. Further recommendations will be made on areas of measurement property requiring further testing. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration ID: CRD42021237877.

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)0.112
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.984
Threshold uncertainty score0.594

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1120.115
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0160.015
Bibliometrics0.0170.015
Science and technology studies0.0040.004
Scholarly communication0.0060.006
Open science0.0050.005
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0460.006

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 head0.622
GPT teacher head0.580
Teacher spread0.042 · 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.

Study designSystematic review
DomainMethods
GenreProtocol

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

Citations11
Published2022
Admission routes1
Has abstractyes

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