Scoping review of the person-centered literature in adult physical rehabilitation
Bibliographic record
Abstract
Purpose To describe the amount, range, and key characteristics (e.g., publication years, methods, topics) of the person-centered rehabilitation literature in adults with physical impairments.Method Following the published scoping review protocol, papers were identified through: three major databases, snowball searches and expert consultation. Two independent reviewers have identified English-language papers on adult person-centered rehabilitation according to six pre-defined inclusion categories – theoretical, quantitative and qualitive research papers are included; and then have extracted their key characteristics (e.g., aims, methods, participants). Descriptive statistics, regression and content analyses were used to synthesize the results.Results Of 5912 deduplicated records initially screened, 170 papers were included: 136 empirical, including 13 systematic reviews. Empirical papers had data from 15264 clients and 4098 providers, in total. Yearly publications grew significantly from 2009 to 2018 (r2 = 0.71; b = 1.98: p < 0.01). Publications were unevenly distributed by countries (e.g., United States’ publications per population was 44 times lower than New Zealand’s). Most papers focused in more than one profession, setting-type or health conditions. Finally, many empirical papers (n = 67) studied implementation of person-centered rehabilitation approaches, including its effect.Conclusion This scoping review synthesizes key characteristics and publication trends in the person-centered rehabilitation literature on adults with physical impairments, a growing but unchartered territory thus far. This large and diverse body of literature can ground further person-centered rehabilitation practices and research, including toward building a transdisciplinary, trans-service model of person-centered rehabilitation.Implications for rehabilitationThe person-centered rehabilitation literature on adults with physical impairments, especially the empirical one, has been growing significantly over time, despite inequitably distributed per countries.Rehabilitation stakeholders, including practitioners, have a growing amount of literature in which they can rely for the operationalization and implementation of person-centered rehabilitation approaches into routine practice.Based on our work, person-centered rehabilitation emerges as a practice requirement that cuts across professional and other rehabilitation silos.
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 | 0.069 | 0.235 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.052 | 0.050 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| 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".