Workers’ Perspectives on Vocational Rehabilitation Services
Bibliographic record
Abstract
The purpose of the present study was to consider the vocational rehabilitation (VR) process from the perspective of VR consumers. To better understand the experiences of workers who were injured on the job and participated in VR rehabilitation services, 27 semistructured interviews were completed; 24 were completed face-to-face and 3 were completed over the phone. The present data suggested five primary themes, including expectations, communication, human factors, psychological factors , and reemployment considerations as the most important areas from the workers’ perspectives. Using these themes, recommendations for VR consultant (VRC) practice may be developed. These recommendations include the demonstration of sincere empathy for the consumer and clear communication that allows the client to feel a part of their VR plan/process. It is also recommended that VRCs evaluate and monitor client expectations, openly address barriers, and provide mental health support whenever requested or required. Finally, additional support during the job development process is recommended. In particular, clients desired ample support and communication during the processes of job assessment, job search, and job placement. Finally, clients desired and valued the use of accommodated employment in situations where accommodations would improve their employment outcomes.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".