Bibliographic record
Abstract
Purpose: The study aimed to provide inputs that would help to promote Community Physiotherapy as a field of future study and work. While the focus was on undergraduate physiotherapy students’ perceptions, attitudes and beliefs regarding this field of specialisation, the study also attempted to find whether there were variations in attitude depending on which year of the programme the students belonged to.Method: In December 2015, 118 students of a private physiotherapy college in Gujarat, India, took part in a self-administered questionnaire-based survey. Of these, 56 students were in the third year of their course, while the rest were in the final year. Written informed consent was taken from each respondent. Results: While it was a positive finding to note that this cohort viewed physiotherapy as a service profession, majority of the students wished to pursue higher education outside India due to their perceptions about lack of adequate training facilities, salaries and scope for the profession within the country. For the majority, musculoskeletal sciences was the preferred area of specialisation, followed by Community Health. However, there was awareness about the importance of Community Physiotherapy.Conclusion: Among undergraduate physiotherapy students in the study sample, musculoskeletal sciences is the preferred specialisation, followed by Community Physiotherapy. The year of the programme in which they were studying did not significantly affect their attitudes towards Community Physiotherapy.Limitations: The sample size was too small to compare the differing attitudes of participants from different batches of the course. First and second-year students could not be included since the specialisation of Community Physiotherapy is introduced only in the third year.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".