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Record W4223579791 · doi:10.1186/s12877-022-02993-w

An international Delphi consensus process to determine a common data element and core outcome set for frailty: FOCUS (The Frailty Outcomes Consensus Project)

2022· article· en· W4223579791 on OpenAlexaff
Jeanette Prorok, Paula Williamson, Beverley Shea, Darryl Rolfson, Leocadio Rodríguez‐Mañas, Matteo Cesari, Perry Kim, John Muscedere

Bibliographic record

VenueBMC Geriatrics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsQueen's UniversityUniversity of AlbertaKingston Health Sciences CentreUniversity of Ottawa
Fundersnot available
KeywordsDelphi methodMedicineSet (abstract data type)Ranking (information retrieval)DelphiData collectionProcess (computing)Computer scienceArtificial intelligenceStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Despite increased recognition of frailty and its importance, high quality evidence to guide decision-making is lacking. There has been variation in reported data elements and outcomes which makes it challenging to interpret results across studies as well as to generalize research findings. The creation of a frailty core set, consisting of a minimum set of data elements and outcomes to be measured in all frailty studies, would allow for findings from research and translational studies to be collectively analyzed to better inform care and decision-making. To achieve this, the Frailty Outcomes Consensus Project was developed to reach consensus from the international frailty community on a set of common data elements and core outcomes for frailty. METHODS: An international steering committee developed the methodology and the consensus process to be followed. The committee formulated the initial list of data elements and outcomes. Participants from across the world were invited to take part in the Delphi consensus process. The Delphi consisted of three rounds. Following review of data after three rounds, a final ranking round of data elements and outcomes was conducted. A required retention rate of 80% between rounds was set a priori. RESULTS: One hundred and eighty-four panelists from 25 different countries participated in the first round of the Delphi consensus process. This included researchers, clinicians, administrators, older adults, and caregivers. The retention rate between rounds was achieved. Data elements and outcomes forming primary and secondary core sets were identified, within the domains of participant characteristics, physical performance, physical function, physical health, cognition and mental health, socioenvironmental circumstances, frailty measures, and other. CONCLUSION: It is anticipated that implementation and uptake of the frailty core set will enable studies to be collectively analyzed to better inform care for persons living with frailty and ultimately improve their outcomes. Future work will focus on identification of measurement tools to be used in the application of the frailty core set.

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 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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.509
GPT teacher head0.544
Teacher spread0.035 · 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 teacher head, 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".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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