Importance Attributed to Cardiovascular and Pulmonary Competencies by Public Sector Physical Therapists in Kuwait: A Population-based Exploratory Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Indications for cardiovascular and pulmonary (CVP) physical therapy competencies are changing with the epidemic of non-communicable diseases in Kuwait, particularly lifestyle-related conditions. The degree to which the country's physical therapists (PTs) perceive the importance of CVP competencies (assessment/evaluation and clinical and laboratory investigation interpretation) in professional practice is relevant. Our study objectives were to (1) explore the importance attributed to specific CVP competencies by PTs to professional practice in Kuwait and (2) establish whether these are related to practitioner traits, for example, age, sex, practice setting and specialty. METHOD: The study design was exploratory with a stratified random sample. Questionnaires (n = 221) were distributed to PTs practicing in the facilities of the Ministry of Health, the primary employer of PTs in Kuwait. Questions included participants' demographics and perceived importance of specific CVP competencies (Likert rating scale 1-not important to 5-highly important). RESULTS: Response rate was 87% (n = 193). Participant mean age was 36(±9) years, 63% were women and 48% were Kuwaiti. Ratings of moderately important or higher were 84% for cardiac assessment/intervention skills, 78.8% for cardiac clinical/laboratory investigations interpretation, 77.2% for pulmonary assessment/intervention skills and 73.6% for pulmonary clinical/laboratory investigations interpretation. PTs in the musculoskeletal area attributed less importance to the competencies than those in other specialties. CONCLUSIONS: Participants perceived CVP competencies as generally relevant to practice. However, greater importance was attributed to these competencies in relation to management of CVP conditions (e.g. those that address lifestyle-related conditions) rather than across practice areas. Research is needed to elucidate whether this finding reflects the profession's commitment to holistic care, the prevalence of lifestyle-related risk factors and conditions irrespective of a patient's primary complaint presenting to the PT, best evidence-based, non-pharmacologic practice to address these or some combination. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".