Assessing seatbelt use among pregnant drivers in Australia: Correct seatbelt positioning, discomfort, knowledge and information sources
Bibliographic record
Abstract
• Correct seatbelt use during pregnancy is critical for ensuring maternal and fetal safety. • An online survey evaluated seatbelt use among 1,491 pregnant vehicle drivers in Australia. • Nearly all participants wore seatbelts (99.1%), but only 41.4% used correct seatbelt positioning. • Discomfort increased with pregnancy, but was not associated with correct seatbelt positioning. • Receiving information on seatbelt use significantly improved correct positioning. Background : Correct seatbelt use during pregnancy is critical for ensuring maternal and fetal safety during a motor vehicle crash. This study aimed to investigate seatbelt use among pregnant vehicle drivers in Australia, focusing on correct seatbelt positioning and the potential influence of comfort and the receipt of seatbelt information. Method: An online survey was completed by 1,491 participants (M = 33.2 years, SD = 4.1, Range = 18.0 – 50.0 years). Results: While nearly all participants (99.1%) reported ‘always’ wearing their seatbelt while driving a vehicle, only 41.4% met the correct seatbelt positioning criteria, defined as positioning the lap belt under the belly and low over the upper thighs and the shoulder belt between the breasts. Despite increased discomfort with seatbelt use as pregnancy advanced, discomfort was not significantly associated with correct seatbelt positioning. Additionally, while most participants had not received information about seatbelt use during pregnancy (87.7%), those who did had better knowledge (96.2% vs. 90.5%, χ2(1) = 7.16, p < 0.05), and were more likely to meet all three criteria for correct seatbelt positioning during pregnancy (56.8% vs. 39.3%, χ2(1) = 20.26, p < 0.001), than participants who had not received information (90.5%). However, receiving information did not necessarily increase confidence in correct seatbelt use, as participants who had received information were actually less likely to be confident in their ability to use the seatbelt correctly (3.3% vs. 6.6%, χ2(2) = 8.24, p < 0.05). Conclusions : These findings highlight a significant gap in correct seatbelt positioning among pregnant occupants and the scope for substantial improvement in correct positioning by providing specific information on seatbelt use during pregnancy. Practical applications: To improve correct seatbelt use among pregnant individuals, public health messaging should be enhanced, and obstetrician-gynaecologists, nurses and other healthcare professionals should provide clear guidance on correct seatbelt positioning throughout the pregnancy. Future research should focus on developing effective educational strategies, assessing vehicle design improvements for comfort and safety, and exploring other factors influencing correct seatbelt use during pregnancy.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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 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".