Attitudes and Beliefs of Physical Therapists in Saudi Arabia Regarding Direct Access and Scope of Practice
Bibliographic record
Abstract
Purpose: This study aimed to understand better what practicing physical therapists know and believe about direct access (DA) and scope of practice (SOP) for physical therapy in Saudi Arabia (SA). Methods: A pilot study was first performed to ensure the clarity of the questions. Then, a cross-sectional survey was sent through emails, and social media platforms included three main sections: demographics, opinions, and beliefs questions. Results: A total of 150 respondents met the inclusion criteria. About 55.3% of the participants reported never or rarely using an SOP document as a reference for knowing their practice. Moreover, nearly 48% learned about the SOP through an informal discussion. Only 24.7% of the participants correctly identified which practice setting DA is permitted. Most participants felt confident or strongly confident of their abilities to assess (67.3%) and treat (72%) patients without physicians’ referral. Around 84% of the participants agreed or strongly agreed that DA should be expanded to include all healthcare settings. Conclusion: We found that physical therapists are confident about their ability to treat and assess patients without physicians’ referrals. There is uncertainty about where DA is permitted in SA.
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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".