Feasibility and reliability of an online version of the beat alignment test in neurotypical adults and people with stroke
Bibliographic record
Abstract
BACKGROUND: Rhythm-based rehabilitation interventions are gaining attention and measuring their effects is critical. With more clinical care and research being conducted online, it is important to determine the feasibility of measuring rhythm abilities online. However, some tools used to measure rhythm abilities, in particular the beat alignment test (BAT), have not been validated for online delivery. This study aims to determine the feasibility, reliability, and learning effects for online delivery of the BAT in adults with and without stroke. METHODS: Neurotypical adults and adults with chronic stroke completed the BAT online three times, with testing sessions separated by 2 to 4 days. The BAT includes a perception task (identifying whether tones overlayed on music matched the beat of the music) and a production task (tapping to the beat of music). Feasibility was evaluated with completion rates, technical challenges and resolutions, participant experience via exit questionnaire, and test duration. Reliability was measured using inter-class correlations and standard error of measurement, and learning effects were determined using a repeated-measures ANOVA. RESULTS: Thirty-nine neurotypical adults and 23 adults with stroke participated in this study. More a priori feasibility criteria for the online BAT were met with neurotypical adults than people with stroke. Most components of the online BAT were considered reliable based on an ICC = 0.60 cut-off, except for perception in the neurotypical group, and production asynchrony in the stroke group. There was notable variability in performance, but no learning effects in either group. CONCLUSIONS: Online administration of the BAT is more feasible for neurotypical adults than people with stroke. Challenges with online administration for people with stroke may be partly related to the delivery platform. The BAT is a reliable tool with no learning effects and therefore is a promising way to assess for rhythm abilities online with careful consideration of user interface for people with stroke.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".