Phone messages affect the detection of approaching pedestrians in healthy young and older adults immersed in a virtual community environment
Bibliographic record
Abstract
BACKGROUND: Mobile phones are increasingly associated with accidents while walking. Little is known, however, about the impact of phone messaging on the actual perception of other pedestrians. This study aimed to investigate the extent to which the detection of approaching pedestrians is affected by the sensory modality (text or audio) of phone messages in young vs. older adults. METHODS: Eighteen healthy young (24 ± 2.9 years) and 15 older adults (68 ± 4.2 years) performed a phone message deciphering task, an obstacle detection task, and a dual-task condition combining both tasks. Participants were tested while seated and viewing a virtual subway station (VE) in a helmet mounted display. As they were passively moved within the VE one of three virtual pedestrians randomly approached them from the center (0°), right (+40°) or left (+40°). When present, phone message conditions were delivered at obstacle movement onset and presented either as (1) text messages on the screen of a virtual phone or (2) audio messages delivered through earphones. Participants were instructed to press a joystick button as soon as they detected the approaching virtual pedestrian and to report the message content at the end of the trials. RESULTS: Young and older participants showed delayed obstacle detection times with vs. without text messages. Older adults further showed reduced accuracy of message report for texts compared to audio messages. In both groups, audio messages yielded no difference in obstacle detection time or accuracy of message report compared to the no message condition. CONCLUSIONS: Findings indicate that text messages prolong the detection of approaching pedestrians, suggesting that they compromise safe ambulation in community environments. Older adults, who show larger deteriorations on the obstacle detection and message deciphering tasks, may be at even greater risk of collision. Audio messages could be a safer alternative for on-the-go communication.
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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 | 0.001 | 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".