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Record W7084122625 · doi:10.6084/m9.figshare.28548229

Barriers and facilitators to implementing peer mentorship programs for individuals with spinal cord injury into rehabilitation hospitals: a multiple case study

2025· article· en· W7084122625 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldComputer Science
TopicWireless Sensor Networks for Data Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipFacilitatorRehabilitationSpinal cord injuryFocus groupPeer supportPeer group

Abstract

fetched live from OpenAlex

To identify and compare barriers and facilitators to implementing a spinal cord injury (SCI) peer mentorship program at two rehabilitation hospitals. 24 participants from the two rehabilitation hospitals participated − 10 were from China and 14 were from Canada. Semi-structured interviews and focus groups were used to collect data. A cross-case analysis based on the Consolidated Framework for Implementation Research was conducted. At an individual level, four common facilitators for both hospitals were: engaging patients with SCI, engaging health professionals, high-level leaders providing financial and instrumental support, and increasing health professionals’ motivation to implement the program. Two common barriers were health professionals’ low capability and opportunity to implement the program. At an organizational level, one common facilitator was a team culture characterized by openness to innovation and a strong commitment to prioritizing patients’ needs. For the Canadian hospital, their partnership and connections with a community-based SCI organization and collaborative work infrastructure were facilitators. For the Chinese hospital, team separation within the local work infrastructure was a barrier. Multiple barriers and facilitators to implementing SCI peer mentorship programs were identified in two culturally distinct contexts. Assessing organizational needs and identifying available resources are key pre-implementation processes for rehabilitation hospitals to implement SCI peer mentorship programs. The in- and out-patient rehabilitation period is an ideal time to establish peer mentorship relationships for individuals with spinal cord injury.Implementation of peer mentorship programs in rehabilitation hospitals relies on interprofessional collaboration between high-level leaders, health professionals, and spinal cord injury mentors who can take on different roles in the implementation process.Identifying available resources, such as partnerships with community-based spinal cord injury organization and human resources to lead the efforts, will facilitate the imitation of the implementation process. The in- and out-patient rehabilitation period is an ideal time to establish peer mentorship relationships for individuals with spinal cord injury. Implementation of peer mentorship programs in rehabilitation hospitals relies on interprofessional collaboration between high-level leaders, health professionals, and spinal cord injury mentors who can take on different roles in the implementation process. Identifying available resources, such as partnerships with community-based spinal cord injury organization and human resources to lead the efforts, will facilitate the imitation of the implementation process.

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)0.012
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.002
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.324
Teacher spread0.302 · 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 designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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