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Record W2995561482 · doi:10.1310/sci19-00002

Implementation Evaluation of an Online Peer-Mentor Training Program for Individuals With Spinal Cord Injury

2019· article· en· W2995561482 on OpenAlexaffabout
Marie‐Ève Lamontagne, Krista L. Best, Teren Clarke, Frédéric Dumont, Luc Noreau

Bibliographic record

VenueTopics in Spinal Cord Injury Rehabilitation · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsSpinal Cord Injury AlbertaCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleCentre for Interdisciplinary Research in RehabilitationUniversité Laval
Fundersnot available
KeywordsContext (archaeology)MedicineProcess (computing)Medical educationSpinal cord injuryImplementation researchPsychological interventionNursingApplied psychologyPsychology

Abstract

fetched live from OpenAlex

Background: Community-based spinal cord injury (SCI) associations play a critical role in successful community integration of individuals having experienced an SCI, with knowledge translation being increasingly important for the process. The implementation of a new online peer-mentor training program was perceived as being useful in improving and standardizing training practices for peer mentors across Canada. It was also seen as an opportunity to explore the context, process, and influence of a formal implementation process in SCI community-based associations that are corporate members of SCI Canada with a view to informing future implementation efforts. Objectives: The objectives of this study were to (a) explore the context in which the implementation process will be conducted, (b) identify barriers and facilitators that influence the implementation process, and (c) measure the influence of the implementation process on service delivery. Methods: A sequential cross-sectional design was used with SCI Canada provincial member associations. SCI Canada's purpose is to support collaboration among provincial corporate members. SCI Canada enlisted the participation of several employees from the provincial associations to assess the implementation context using the Evidence-Based Practice Attitude Scale and the Organizational Readiness to Change Assessmen t and to identify barriers to and facilitators of the implementation of an evidence-based practice through an open-ended questionnaire based on the Consolidated Framework for Implementation Research. A pre-post design was used to evaluate the influence of the implementation process on peer-mentors using the Determinants of Implementation Behavior Questionnaire. Results: Participants reported an overall positive attitude toward evidence-based practice and a positive perception of the organizational readiness to change. The relevance of the practice chosen was a facilitator because peer support is central to the mission of SCI Canada and this type of practice is in line with the organization' culture and values. Equally important, but as an obstacle, is the scarcity of existing resources within the association in general and specifically resources devoted to the implementation of the program. Finally, the implementation process seems to influence half of the implementation determinant types on potential peer mentors. Conclusion: Community-based organizations, such as the provincial association members of SCI Canada, show positive context for the implementation of evidence-based practices. However, successful implementation of online peer-mentor training will require specific consideration of financial and human resources.

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)0.009
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.083
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.487
GPT teacher head0.676
Teacher spread0.189 · 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.

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".

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Citations10
Published2019
Admission routes2
Has abstractyes

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