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Record W2327692390 · doi:10.7224/1537-2073.2014-053

Participation as an Outcome in Multiple Sclerosis Falls-Prevention Research

2014· article· en· W2327692390 on OpenAlexaff
Marcia Finlayson, Elizabeth Peterson, Patricia Noritake Matsuda

Bibliographic record

VenueInternational Journal of MS Care · 2014
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineIntervention (counseling)Psychological interventionOutcome (game theory)Suicide preventionPoison controlGerontologyNursingEnvironmental health

Abstract

fetched live from OpenAlex

Selecting the outcomes for an intervention trial is a key decision that influences many other aspects of the study design. One of the major tasks during the 3-day inaugural meeting of the International MS Falls Prevention Research Network was to identify the key outcomes for the falls-prevention intervention that was being designed by the Network members for testing across their multiple sites. Through a nominal group process, meeting participants described how engagement in important, meaningful everyday activities, beyond traditional basic and instrumental activities of daily living, should be a long-term outcome of a successful falls-prevention intervention for people with MS. Post-meeting work, which involved literature reviews and comparisons of definitions of major constructs identified during the meeting discussions, led to the consensus recommendation of including participation as a long-term outcome in MS falls-prevention interventions. Participation reflects involvement in a life situation. This article explains the rationale for this recommendation and presents four measures that have the potential for use in tracking long-term participation outcomes in MS falls-prevention research.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.173
GPT teacher head0.441
Teacher spread0.268 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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