Healthcare Provider Factors Affecting Access to Nerve Transfer Surgery to Improve Upper Extremity Function in Individuals With Cervical Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVE: Nerve and tendon transfer surgery has restored upper extremity function in cervical spinal cord injury but is not universally accessible to all eligible individuals. The purpose of this exploratory qualitative study was to understand the healthcare provider factors that are associated with access to nerve transfer surgery for people with spinal cord injury. DESIGN: Semistructured interviews explored healthcare provider knowledge and practices regarding nerve and tendon transfer surgery to improve upper extremity function in cervical spinal cord injury. An inductive, iterative, constant comparative process involving descriptive and interpretive data analyses was used to identify themes, guided by the Consolidated Framework for Implementation Research. RESULTS: Interviews were conducted with healthcare providers ( n = 10 upper extremity surgeons, n = 10 spinal cord injury physiatrists/hospitalists, n = 6 occupational therapists, n = 6 physical therapists). The following nine themes were identified as barriers to accessing care: (1) lack of awareness; (2) lack of sufficient knowledge; (3) lack of buy-in as a priority; (4) lack of collaboration; (5) misperceptions; (6) lack of resources; (7) lack of evidence; (8) lack of ownership among rehabilitation specialists; and (9) hesitancy. CONCLUSIONS: This study identified barriers limiting equitable access to nerve transfer surgery. These barriers highlight the need for a multimodal multidisciplinary approach to address individual-, provider-, and system-level barriers.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".