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Record W4400878829 · doi:10.1371/journal.pone.0307418

A PROGRESS-driven approach to cognitive outcomes after traumatic brain injury: A study protocol for advancing equity, diversity, and inclusion through knowledge synthesis and mobilization

2024· article· en· W4400878829 on OpenAlexafffundabout
Thaisa Tylinski Sant’Ana, Sara Hanafy, Esme Fuller‐Thomson, Michelle M. McDonald, Angela Colantonio, Daìthì Cee, Gráinne McGettrick, Brian Lawlor, Tatyana Mollayeva

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsOntario Brain InstitutePublic Health OntarioToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsHealth equityEquity (law)Inclusion (mineral)PsychologyPublic relationsMedicinePolitical sciencePublic healthSocial psychologyNursing

Abstract

fetched live from OpenAlex

Evidence syntheses for advancing equitable traumatic brain injury (TBI) research, policy, and practice presents formidable challenges. Research and clinical frameworks are currently not specific to equity, diversity, and inclusion considerations, despite evidence that persons with TBI live in societies in which power imbalances and systems of social dominance may privilege some people and marginalize others. The present protocol outlines a strategy for a research program, supported by the Canadian Institutes of Health Research, that explores the integration of PROGRESS-Plus parameters in research with the goal of advancing open-science databases and tools to improve our understanding of equity in cognitive and brain health outcomes in TBI. PROGRESS-Plus is a framework outlining social, economic, and cultural parameters that may influence health opportunities and outcomes (e.g., place of residence, race, occupation, gender, etc.). A multistep research program is proposed to support three objectives: (1) organizing existing data on TBI-induced changes in cognition and brain health into a template to facilitate future research, including research using machine learning techniques; (2) updating published evidence with a more rigorous approach to the consideration of PROGRESS-Plus parameters; and (3) mobilizing knowledge on the current state of evidence that is relevant, equitable, and accessible. This program facilitates partnerships with knowledge users across clinical, research, academic, and community sectors to address the three research objectives through a unifying workflow of exchange, synthesis, and knowledge mobilization. We anticipate that this global collaboration between topic experts and community leaders in equity in brain health will add significant value to the field of TBI by promoting equity-transformative advancements in knowledge synthesis, policy, and practice.

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)0.266
metaresearch head score (Gemma)0.193
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.266
Threshold uncertainty score0.905

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2660.193
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0100.008
Science and technology studies0.0090.008
Scholarly communication0.0090.010
Open science0.0070.011
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0490.015

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 head0.231
GPT teacher head0.446
Teacher spread0.214 · 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 designNot applicable
Domainnot available
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

Citations6
Published2024
Admission routes3
Has abstractyes

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