Facilitators and barriers to using neurological outcome measures in developed and developing countries
Bibliographic record
Abstract
OBJECTIVE: To identify and compare factors influencing the use of standardized outcome measures by neurological physical therapists working in representative developed (Canada) and developing (India) countries. METHODS: A self-administered web-based questionnaire on facilitators and barriers to using neurological outcome measures was sent by email to neurological physical therapists in Canada and India. Frequencies of responses to each question were computed. Differences between countries were assessed using two-proportion z test. RESULTS: Of 317 respondents, the use of standardized outcome measures was higher for Indian (96.7%) compared with Canadian physical therapists (89.2%). Among the most highly reported facilitators, three were common for both countries (known validity and reliability, outcome measures learned in professional training, and recommended in clinical practice guidelines). Three highly reported barriers were also common for India and Canada (lack of time, relying on judgement for clinical decisions, and unavailability of the assessment tools). Nevertheless, there were differences in the percentages of barriers and facilitators between countries. CONCLUSION: Understanding the factors influencing the uptake of outcome measures among neurological physical therapists working in a developed (Canada) and a developing country (India) can help identify whether strategies should or should not be modified to facilitate knowledge translation in different geographical, professional, or social contexts.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".