Design and psychometric evaluation of sociocultural scale predicting the incidence of road traffic crashes in drivers.
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Summary
This study addresses the lack of indigenous instruments for measuring Sociocultural Factors (SCFs) that predict Road Traffic Crashes (RTCs) among Iranian drivers. While human factors contribute significantly to RTCs, particularly in Low- and Middle-Income Countries, existing scales often fail to account for local sociocultural contexts or modern driving behaviors. The researchers aimed to design and psychometrically evaluate a valid and reliable scale to identify high-risk drivers and support injury prevention efforts. The study employed an exploratory sequential mixed-methods design conducted in three phases from December 2019 to June 2021. Phase 1 involved a systematic literature review across international and national databases to generate initial items. Phase 2 consisted of semi-structured interviews with 25 specialists in road traffic, psychology, and sociology, and 50 experienced drivers with a history of accidents. These phases yielded an initial pool of 110 items, which were reduced to 89 through expert review. Phase 3 focused on psychometric evaluation. Face and content validity were assessed by drivers and a panel of 10 experts. Construct validity was tested using Principal Component Analysis (PCA) on 300 drivers and Confirmatory Factor Analysis (CFA) on 200 drivers. Discriminant validity was evaluated by comparing scores between accident-involved and accident-free drivers. Reliability was measured using internal consistency indices and test-retest stability. The final scale comprised 27 items organized into seven factors: Inadequate adherence to traffic laws, Risk-taking, Beliefs and norms, Driver performance, Irritability and anger, Adherence to traffic laws, and External locus of control. These factors explained 55.56% of the total variance. The scale demonstrated strong content validity with a Scale Content Validity Index of 0.92. CFA results indicated satisfactory model fit, with indices such as CFI (0.96), IFI (0.96), and RMSEA (0.052) meeting acceptable thresholds. Discriminant analysis revealed significant differences (P < 0.001) between accident-involved and accident-free drivers across all dimensions and the composite scale. Reliability metrics were robust, with Cronbach’s alpha at 0.82, Theta at 0.96, Omega at 3.07, and an Intraclass Correlation Coefficient of 0.80. The study concludes that the developed sociocultural scale is a valid and reliable instrument for assessing factors predicting RTCs in Iranian drivers. By capturing specific sociocultural determinants, the scale can assist health managers and policymakers in identifying at-risk populations and designing targeted interventions to reduce traffic injuries. The findings highlight the importance of indigenous measurement tools in addressing public health threats within specific cultural contexts.
Key finding
The developed 27-item sociocultural scale demonstrated strong psychometric properties and significantly distinguished between accident-involved and accident-free drivers.
Methodology
mixed_methods
Sample size: 530
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via author_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | canonical_url | — | — | 11 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- dbq psychometrics
- incidence prevalence
- induced exposure
- causation analyses
- naturalistic crash near crash
- cultural cross national
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: crash risk outcomes
- Methodological Resource: validation psychometrics, dataset resource