Clinical Utility and Usability of the Digital Box and Block Test: Mixed Methods Study
Bibliographic record
Abstract
Background: The Box and Block Test (BBT) is a clinical tool used to measure hand dexterity, which is often used for tracking disease progression or the effectiveness of therapy, particularly benefiting older adults and those with neurological conditions. Digitizing the measurement of hand function may enhance the quality of data collection. We have developed and validated a prototype that digitizes this test, known as the digital BBT (dBBT), which automatically measures time and determines and displays the test result. Objective: This study aimed to investigate the clinical utility and usability of the newly developed dBBT and to collect suggestions for future improvements. Methods: A total of 4 occupational therapists participated in our study. To evaluate the clinical utility, we compared the dBBT to the BBT across dimensions such as acceptance, portability, energy and effort, time, and costs. We observed therapists using the dBBT as a dexterity measurement tool and conducted a quantitative usability questionnaire using the System Usability Scale (SUS), along with a focus group. Evaluative, structured, and qualitative content analysis was used for the qualitative data, whereas quantitative analysis was applied to questionnaire data. The qualitative and quantitative data were merged and analyzed using a convergent mixed methods approach. Results: Overall, the results of the evaluative content analysis suggested that the dBBT had a better clinical utility than the original BBT, with ratings of all collected participant statements for the dBBT being 45% (45/99) equal to, 48% (48/99) better than, and 6% (6/99) lesser than the BBT. Particularly in the subcategories "acceptance," "time required for evaluation," and "purchase costs," the dBBT was rated as being better than the original BBT. The dBBT achieved a mean SUS score of 83 (95% CI 76-96). Additionally, several suggested changes to the system were identified. Conclusions: The study demonstrated an overall positive evaluation of the clinical utility and usability of the dBBT. Valuable insights were gathered for future system iterations. These pioneering results highlight the potential of digitizing hand dexterity assessments.
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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 | 0.081 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".