Determination of the minimal clinically important difference on the Australian Therapy Outcome Measures for Occupational Therapy (AusTOMs – OT)
Bibliographic record
Abstract
PURPOSE: Outcome measures must be responsive to change (able to show statistically significant change) and must also produce information on the degree of change that is clinically significant, or the minimal clinically important difference (MCID). This research sought to establish the MCID for four domains of the Australian Therapy Outcome Measures for Occupational Therapy (AusTOMs-OT). METHODS: Using a criterion approach, 30 international clinicians were surveyed about their perceptions of the MCID for AusTOMs-OT. Second, using a distribution-based approach, the MCID was calculated as half of the standard deviation (SD) of the AusTOMs-OT raw scores for a sample of 787 clients. RESULTS: Just over half the clinicians surveyed indicated that a one-point change represented the MCID for AusTOMs-OT for three domains, and 0.5-point change showed MCID for the final domain. The data analysed for the distribution-based calculation indicated that the half SD ranged from 0.51 to 0.61. CONCLUSION: Using both criterion and distribution-based approaches, this research empirically demonstrated that a change on the four domains of the AusTOMs-OT of between 0.51 and 1 point shows MCID. Considering these findings, and for ease of clinical interpretation, it is recommended that a one-point shift be adopted as the MCID across all domains. IMPLICATIONS FOR REHABILITATION: The AusTOMs-OT have been previously shown to be valid and reliable outcome measures for use with all client groups across all settings including rehabilitation. So that rehabilitation professionals can interpret outcomes data from AusTOMs-OT, information must be available on the degree of change that is clinically significant (also referred to as the minimal clinically important difference or MCID). Using empirical calculations as well as clinician opinion, it is recommended that a one-point shift be used as the minimal clinically important difference for the AusTOMs-OT.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".