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Record W2015980438 · doi:10.2147/jhl.s58649

Model for bridging the translational "valleys of death" in spinal cord injury research

2014· article· en· W2015980438 on OpenAlexafffund
Joon‐Young Park, B Barrable, Nancy P. Thorogood, Vanessa K. Noonan, J. S. Tomkinson, Kenneth Stephenson, John Barclay, Katharina Kovacs Burns

Bibliographic record

VenueJournal of Healthcare Leadership · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersHealth CanadaRick Hansen FoundationRick Hansen Institute
KeywordsBridging (networking)Spinal cord injurySpinal cordMedicineNeurosciencePsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract: To improve health care outcomes with cost-effective treatments and prevention initiatives, basic health research must be translated into clinical application and studied during implementation, a process commonly referred to as translational research. It is estimated that only 14% of health-related scientific discoveries enter into medical practice and that it takes an average of 17 years for them to do so. The transition from basic research to clinical knowledge and from clinical knowledge to practice or implementation is so fraught with obstacles that these transitions are often referred to as “valleys of death”. The Rick Hansen Institute has developed a unique praxis model for translational research in the field of spinal cord injury (SCI). The praxis model involves three components. The first is a coordinated program strategy of cure, care, consumer engagement, and commercialization. The second is a knowledge cycle that consists of four phases, ie, environmental scanning, knowledge generation and synthesis, knowledge validation, and implementation. The third is the provision of relevant resources and infrastructure to overcome obstacles in the “valleys of death”, ie, funding, clinical research operations, informatics, clinical research and best practice implementation, consumer engagement, collaborative networks, and strategic partnerships. This model, which is to be independently evaluated in 2018 to determine its strengths and limitations, has been used to advance treatments for pressure ulcers in SCI. The Rick Hansen Institute has developed an innovative solution to move knowledge into action by bridging the “valleys of death” in the research continuum, with the intention of improving health outcomes for people with SCI and decreasing the financial impact on the health care system. This model may be generalizable to other health conditions and the lessons learned in developing the praxis model may assist other organizations dealing with similar translational research challenges. Keywords: spinal cord injuries, clinical outcomes, translational research, implementation, knowledge mobilization, praxis model

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)0.077
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.046
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.005
Science and technology studies0.0070.018
Scholarly communication0.0170.015
Open science0.0050.014
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0120.003

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 head0.934
GPT teacher head0.725
Teacher spread0.209 · 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 designTheoretical or conceptual
DomainMethods
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

Citations15
Published2014
Admission routes2
Has abstractyes

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