The Effect of Texting on Balance and Temporospatial Aspects of Gait
Bibliographic record
Abstract
The purpose of this study was to determine effects of texting on standing balance and the temporospatial aspects ofgait. It was hypothesized that texting would decrease stride velocity and increase deviation from midline while walking, as well asincrease centre of pressure (CoP) excursions while standing. Fifteen participants (eleven males and four females, 21.12±1.25 yearsof age) performed two standing balance tasks and two walking tasks. A repeated measures experimental design was used. Thestanding task consisted of standing as still as possible on a force plate for 20 seconds, which was then repeated while theparticipant texted a standard text message (48 characters). The second task consisted of walking along a six metre straight linewhile being filmed posteriorly along the line of progression, and perpendicular to direction of motion. This task was completed againwhile texting a similar predetermined message (48 characters). Balance performance was quantified by the percentage of total timewithin a 5 mm radius of each participant’s centre of pressure (CoP). Gait quality was quantified using the average step length, stridevelocity, and mediolateral standard deviation from midline averaged from both feet. The percentage of time spent within 5 mm of theaverage CoP was significantly (p<0.05) less while texting compared to the non-texting control condition. Additionally, themediolateral standard deviation from the midline while walking increased significantly (p<0.05) in the texting condition. Average steplength and average stride velocity decreased significantly (p<0.05) while texting compared to the control condition. Standing balanceand temporospatial aspects of walking are significantly degraded by texting. These results are valuable due to the growingprevalence of mobile technology. These results suggest that texting and walking could be detrimental to pedestrian safety and canhelp inform decisions regarding infrastructure to minimize potential dangers associated with distracted walkers.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".