A survey of Israeli physical therapists regarding reactive balance training
Bibliographic record
Abstract
BACKGROUND: 'Reactive balance training' (RBT) was developed to improve balance reactions to unexpected losses of balance. Although this training method is effective, its practical usage in the field of physical-therapy in Israel and world-wide is still unclear. AIMS: This study aimed to evaluate the extent of RBT use in physical-therapy clinics in Israel, to identify the significant barriers to/facilitators for implementing RBT in clinical practice among physical therapists, and to determine which aspects of RBT most interest physical therapists in Israel. METHODS: Physical therapists in Israel completed a survey using a questionnaire regarding their knowledge and use of RBT in their clinical practices. We compared the specific use of RBT among users; non-users; and open-to-use physical therapists. The odds ratios of the facilitators and barriers were calculated using univariate and multivariate logistic regression models. RESULTS: Four-hundred and two physical therapists responded to a yes/no question regarding their use of RBT. Three-quarters (75.4%) of physical therapists reported using RBT in their practices. The most prevalent barrier cited was insufficient space for setting up equipment and most prevalent facilitator was having a colleague who uses RBT. Most of the respondents wanted to learn more about RBT, and most of the non-users wanted to expand their knowledge and mastery of RBT principles. CONCLUSIONS: There are misconceptions and insufficient knowledge about RBT among physical therapists in Israel, indicating that they may falsely believe that RBT requires large and expensive equipment, suggesting they categorize RBT as external perturbation training only. Reliable information may help to improve general knowledge regarding RBT, and to facilitate the more widespread implementation of RBT as an effective fall-prevention intervention method.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".