Certification examinations for massage therapists: A psychometric analysis
Bibliographic record
Abstract
OBJECTIVE: To describe the components of the Alberta Registered Massage Therapists Society (ARMTS) examination and their psychometric properties. METHODS: All 3 components of the ARMTS examination (knowledge, clinical judgement, and clinical skills) were administered to 112 candidates. The examination consisted of 2 written components (140 multiple-choice questions on basic science knowledge and 60 multiple-choice questions on clinical judgment) and a clinical competency assessment of the following practical skills with standardized patients: (1) taking a case history, (2) assessing physical condition, and (3) treating the condition. All components of the examination were criterion-referenced with the methods of minimum performance level (MPL). RESULTS: The internal consistency reliability coefficients (Cronbach alpha) ranged from 0.60 to 0.88 for all test components. The descriptive statistics, performance levels, and reliability estimates indicate that the examination is functioning well. Concurrent, criterion-related validity evidence was provided by correlations between the examination components that ranged from r = 0.24 (P <.05) to r = 0.78 (P <.01). Factor analysis produced 3 factors: information processing, clinical treatment, and follow-up management. CONCLUSIONS: The results provide evidence of adequate-to-good internal consistency reliability and content validity. Empirical validity evidence based on concurrent, criterion-related measures is provided by the correlational analysis. The significant correlations indicate that although performance is related across the examination, the various components do assess unique and independent domains. This is further supported by the results of the factor analysis that provide evidence for discriminant validity of the measures (ie, they discriminate between domains of measurement such as information processing, treatment, and basic knowledge). Taken together, these results indicate that the ARMTS examination has evidence for both reliability and validity.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".