The effects of the Interactive Metronome® as an intervention tool on decreasing levels of aggression and improving life satisfaction with mild traumatic brain injury and post- traumatic stress disorder clients: a pilot study of protocols
Bibliographic record
Abstract
The purpose of this study was to validate the protocols created for the Interactive Metronome® (IM®) and TRX® Suspension Training (TRX®) system for use with clients diagnosed with mild Traumatic Brain Injury (mTBI) and Post-Traumatic Stress Disorder (PTSD). Protocols were established matching IM® routines in conjunction with TRX® exercise routines. These were then validated on two healthy male and two healthy female participants. The data collected was collected using the IM® Long Form and Short Form Assessments, the Nine Hole Peg Test, the Canadian Occupational Performance Model and a version of the Overt Aggression Scale. Percentages of change were then compared between instruments and individuals for positive efforts gained, along with additional statistical analyses conducted. Data analysis indicated the use of the IM® in conjunction with the physical challenge of the TRX® provide a positive change maintaining or lowering aggression levels and increasing life satisfaction. The IM® protocols created, paired with the TRX®, were effective instruments used for creating a change in healthy participants. Occupational therapists will be able to benefit from the information collected and use it towards bettering the lives of those with mild TBI and PTSD. Future research with this intervention should anticipate favorable outcomes with mild TBI and PTSD cases.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".