Prediction of Seat Belt Use Among Iranian Automobile Drivers: Application of the Theory of Planned Behavior and the Health Belief Model
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Bibliographic record
Abstract
OBJECTIVE: Seat belt use plays an important role in traffic safety by reducing the severity of injuries and fatality rates during vehicle accidents. The aim of this study was to investigate predictors of self-reported seat belt use in a sample of automobile drivers in Bandar Abbas, Iran. The theory of planed behavior and the health belief model served as the conceptual framework for the study. METHODS: The convenience sample consisted of 284 eligible automobile drivers who frequented 8 petrol stations in different geographical areas of the city. Of the drivers approached to participate in the study, 21 declined to take part in the study and 12 other questionnaires were incomplete. Thus, a total of 251 questionnaires were analyzed (response rate=88.4%). A self-administered questionnaire including demographic characteristics and items arising from the theory of planed behavior and health belief model constructs were used to collect data. Data were analyzed using SPSS 16 (version 16, Chicago, IL, USA). RESULTS: The subjects' mean age was 31.6 years (SD=8.7), mostly male (72.9%), and 53.4 percent of them reported that they used their seat belt "often." Multiple regression analyses revealed that from the theory of planed behavior, attitude, subjective norms, and perceived behavioral control significantly predicted intention to use a seat belt (R2=0.38, F=51.1, p<.001); and subjective norms, perceived behavioral control, and behavioral intention significantly predicted seat belt use (R2=0.43, F=45.7, p<.001). Arising from the health belief model, perceived benefits and perceived barriers significantly predicted seat belt use (R2=0.39, F=26.2, p<.001). CONCLUSION: This study revealed that automobile drivers who perceived more subjective norms, more behavioral control, greater intention to use seat belts as well as more benefits and fewer barriers were more likely to use their seat belts.
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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 | 0.000 | 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 it