Block Building Task Identifies Distinct Groups of Left/Right-hand Choice Patterns After Unilateral Peripheral Nerve Injury
Bibliographic record
Abstract
Numerous methods exist to assess hand and arm function after upper extremity peripheral nerve injury, but peripheral injuries are often unilateral, and few existing methods are designed to capture the unique consequences of unilateral injury. Unilateral impairment of an upper extremity can lead to increased or decreased use of the dominant hand, and either change may be adaptive or maladaptive depending on the individual patient's needs. To identify atypical hand usage (left/right choices), researchers and clinicians need to measure it. However, hand usage is traditionally assessed with self-report surveys, which do not necessarily reflect actual left/right-hand choices. Here, this gap in knowledge is addressed with the Block Building Task (BBT), which provides a rapid, quantitative, inexpensive assessment of left/right-hand choices in an unconstrained environment. In the BBT, participants build abstract shapes with interlocking plastic bricks, with no instructions about hand usage. The primary outcome is the fraction of reaches (i.e., for the initial pickup of each brick) made with each hand. After unilateral peripheral nerve injury, patients fell into three clusters: approximately typical hand use (44%), always use the dominant hand (44%), or never use the dominant hand (13%). Even among patients with an injured dominant hand, atypically elevated use of the dominant hand occurred regularly (36%). Notably, hand usage was not predicted by clinical characteristics, so the BBT provides an objective measurement of left/right-hand choices that are not otherwise predictable from the clinical characteristics of patients with peripheral nerve injury. The BBT protocol will be of interest to researchers or clinicians interested in the assessment of conditions with asymmetric effects on the upper limb.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".