Attitudes and Beliefs Toward Non‐Specific Neck Pain Among Physiotherapists in Jordan: A Cross‐Sectional Study
Bibliographic record
Abstract
BACKGROUND: Physiotherapists' attitudes and beliefs play a crucial role in the management and treatment outcomes of non-specific neck pain (NSNP). OBJECTIVE: To investigate the attitudes and beliefs of physiotherapists in Jordan towards NSNP, and to identify factors influencing these attitudes and beliefs. METHODS: A Cross-sectional survey of registered physiotherapists working in Jordan was conducted. A structured questionnaire was used to assess the attitudes and beliefs of physiotherapists towards NSNP. Descriptive and inferential statistics were used. RESULTS: A total of 301 PTs completed the survey, 155 females (51.56%). Most respondents held bachelor's degrees, with an average of 9.5 ± 6.6 experience years. The total score for PABS-PT (Z = 11.4, p < 0.001) and its BM (Z = +11.9, p < 0.001) and PS (Z = 3.6, p < 0. 001) subscales were significantly positive. The score of the biomedical subscale was more significantly positive than psychosocial subscale. The treatment orientation was positively correlated with education level, and negatively with age and experience. The most reported treatments were manual therapy followed by general exercises and electrical modalities. No significant relationship was observed between treatment orientation and treatment selection. CONCLUSION: This study created the initial profile for pain attitudes and beliefs in Jordan. Physiotherapists hold positive attitudes and beliefs towards the NSNP treatment orientations with a superiority of the BM approach. Engaging educational sectors and stakeholders in the current situation of PTs' attitudes and beliefs is important.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".