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Record W2582439330 · doi:10.1136/bmj.j14

Inter-rater agreement in evaluation of disability: systematic review of reproducibility studies

2017· review· en· W2582439330 on OpenAlexaff
Jürgen Barth, W. E. L. de Boer, Jason W. Busse, Jan L. Hoving, Sarah Kedzia, Rachel Couban, Katrin Fischer, David Yoh von Allmen, Jerry Spanjer, Regina Kunz

Bibliographic record

VenueBMJ · 2017
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsycINFOInter-rater reliabilityObservational studyInclusion (mineral)NormativeResearch designMEDLINEPsychologyDescriptive statisticsSystematic reviewMedicineApplied psychologyRating scaleMedical educationFamily medicineSocial psychologyStatisticsPathologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To explore agreement among healthcare professionals assessing eligibility for work disability benefits. DESIGN: Systematic review and narrative synthesis of reproducibility studies. DATA SOURCES: Medline, Embase, and PsycINFO searched up to 16 March 2016, without language restrictions, and review of bibliographies of included studies. ELIGIBILITY CRITERIA: Observational studies investigating reproducibility among healthcare professionals performing disability evaluations using a global rating of working capacity and reporting inter-rater reliability by a statistical measure or descriptively. Studies could be conducted in insurance settings, where decisions on ability to work include normative judgments based on legal considerations, or in research settings, where decisions on ability to work disregard normative considerations. : Teams of paired reviewers identified eligible studies, appraised their methodological quality and generalisability, and abstracted results with pretested forms. As heterogeneity of research designs and findings impeded a quantitative analysis, a descriptive synthesis stratified by setting (insurance or research) was performed. RESULTS: From 4562 references, 101 full text articles were reviewed. Of these, 16 studies conducted in an insurance setting and seven in a research setting, performed in 12 countries, met the inclusion criteria. Studies in the insurance setting were conducted with medical experts assessing claimants who were actual disability claimants or played by actors, hypothetical cases, or short written scenarios. Conditions were mental (n=6, 38%), musculoskeletal (n=4, 25%), or mixed (n=6, 38%). Applicability of findings from studies conducted in an insurance setting to real life evaluations ranged from generalisable (n=7, 44%) and probably generalisable (n=3, 19%) to probably not generalisable (n=6, 37%). Median inter-rater reliability among experts was 0.45 (range intraclass correlation coefficient 0.86 to κ-0.10). Inter-rater reliability was poor in six studies (37%) and excellent in only two (13%). This contrasts with studies conducted in the research setting, where the median inter-rater reliability was 0.76 (range 0.91-0.53), and 71% (5/7) studies achieved excellent inter-rater reliability. Reliability between assessing professionals was higher when the evaluation was guided by a standardised instrument (23 studies, P=0.006). No such association was detected for subjective or chronic health conditions or the studies' generalisability to real world evaluation of disability (P=0.46, 0.45, and 0.65, respectively). CONCLUSIONS: Despite their common use and far reaching consequences for workers claiming disabling injury or illness, research on the reliability of medical evaluations of disability for work is limited and indicates high variation in judgments among assessing professionals. Standardising the evaluation process could improve reliability. Development and testing of instruments and structured approaches to improve reliability in evaluation of disability are urgently needed.

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

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: Reproducibility · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement 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)0.046
metaresearch head score (Gemma)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.158
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0460.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
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 head0.301
GPT teacher head0.537
Teacher spread0.236 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainReproducibility · Methods
GenreReview

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

Citations94
Published2017
Admission routes1
Has abstractyes

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