Use of Outcome Measures in Physiotherapy Practice in Ireland from 1998 to 2003 and Comparison to Canadian Trends
Bibliographic record
Abstract
PURPOSE: The purposes of this study were to examine changes in the use of standardized outcome measures by practising physiotherapists in Ireland and to compare those trends to the results of a similar survey conducted previously in Canada. METHOD: A survey methodology was employed. The review of practice occurred at two points in time. Senior clinical physiotherapists working with older people participated. Questions were asked about the use of standardized outcome measures, the nature and pattern of their use, and the level of confidence the respondents had in using such measures. RESULTS: The results chart the changes in practice over a 5-year period. Although there was an increase in the use of standardized outcome measures, the respondents acknowledged barriers to their systematic use in routine practice (e.g., lack of time, resources/administrative support). There was a lack of professional consensus on what instruments to use in general, as well as which to use for particular client groups. Concern was expressed that none of the available instruments met their clients' needs. Where possible and appropriate, comparison was made between the data from the 2003 Irish study and a survey of Canadian physiotherapists conducted in 1998. CONCLUSION: This review of practice illustrates that changes that have occurred in Ireland in the use of standardized outcome measures are similar to those that have occurred in Canada, but barriers remain to their complete integration into clinical practice and clinical decision making.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".