Documenting the Content of Physical Therapy for Children With Acquired Brain Injury: Development and Validation of the Motor Learning Strategy Rating Instrument
Bibliographic record
Abstract
BACKGROUND: A goal of physical therapy interventions for children and youth with acquired brain injury (ABI) is the learning and relearning of motor skills. Therapists can apply theoretically derived and evidence-based motor learning strategies (MLSs) to structure the presentation of a task and organize the environment in ways that may promote effective, transfer-oriented practice. However, little is known about how MLSs are used in physical therapy interventions for children with ABI. OBJECTIVE: The purpose of this study was to develop and validate an observer-rated Motor Learning Strategy Rating Instrument (MLSRI) quantifying the application of MLSs in physical therapy interventions for children with ABI. DESIGN: A multi-stage, iterative, item generation and reduction approach was used. METHODS: An initial list of MLS items was generated through literature review. Seven experts participated in face validation to confirm item comprehensiveness. In a content validation process, 12 physical therapists with pediatric ABI experience responded to a questionnaire evaluating feasibility and importance of items. Six physical therapy sessions with clients with ABI were videotaped at a children's rehabilitation center. The 12 physical therapists participated in a session where they: (1) rated session videos to test the MLSRI and (2) provided verbal feedback. RESULTS: Revisions were made sequentially to the MLSRI based on these processes. LIMITATIONS: The MLSRI was scored during videotape observation rather than being given a live rating, which may be onerous in certain settings and may influence therapist or child behavior. CONCLUSIONS: Further reliability investigations will determine whether the 33-item MLSRI is of help in documenting strategy use during intervention, as an evaluation tool in research, and as a knowledge transfer resource in clinical practice.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".