OBJECTIVE: To validate the Malay version of the DASS-21 (Malay-DASS-21) among male outpatient clinic attendees in Johor.
METHODS: A validation study with a random sample of 402 male respondents attending the outpatient clinic of a major public outpatient clinic in Johor Bahru and Segamat was carried out from January to March 2016. Construct validity of the Malay-DASS-21 was examined using Exploratory Factor Analysis (KMO = 0.947; Bartlett's test of sphericity is significant, p<0.001) through Principal Component Analysis and orthogonal (varimax) rotation with Kaiser Normalization to confirm the psychometric properties of the Malay-DASS- 21 and the internal consistency reliability using Cronbach's alpha.
RESULTS: Construct validity of the Malay-DASS-21 based on eigenvalues and factor loadings to confirm the three factor structure (depression, anxiety, and stress) was acceptable. The internal consistency reliability of the factor construct was very impressive with Cronbach's alpha values in the range of 0.837 to 0.863.
CONCLUSIONS: The present study showed that the Malay- DASS-21 has acceptable psychometric construct and high internal consistency reliability to measure self-perceived depression, anxiety and stress over the past week in male outpatient clinic attendees in Johor. Further studies are necessary to revalidate the Malay-DASS-21 across different populations and cultures, and using confirmatory factor analyses.
METHOD: This study proposes a combination of decision tree and logistic regression techniques to model crash severity (injury vs. noninjury), because the combined approach allows the specification of nonlinearities and interactions in addition to main effects. Both a scobit model and a random parameters logit model, respectively accounting for an imbalance response variable and unobserved heterogeneities, are tested and compared. The study data set contains a total of 5 years of crash data (2008-2012) on selected mountainous highways in Malaysia. To enrich the data quality, an extensive field survey was conducted to collect detailed information on horizontal alignment, longitudinal grades, cross-section elements, and roadside features. In addition, weather condition data from the meteorology department were merged using the time stamp and proximity measures in AutoCAD-Geolocation.
RESULTS: The random parameters logit model is found to outperform both the standard logit and scobit models, suggesting the importance of accounting for unobserved heterogeneity in crash severity models. Results suggest that proportion of segment lengths with simple curves, presence of horizontal curves along steep gradients, highway segments with unsealed shoulders, and highway segments with cliffs along both sides are positively associated with injury-producing crashes along rural mountainous highways. Interestingly, crashes during rainy conditions are associated with crashes that are less likely to involve injury. It is also found that the likelihood of injury-producing crashes decreases for rear-end collisions but increases for head-on collisions and crashes involving heavy vehicles. A higher order interaction suggests that single-vehicle crashes involving light and medium-sized vehicles are less severe along straight sections compared to road sections with horizontal curves. One the other hand, crash severity is higher when heavy vehicles are involved in crashes as single vehicles traveling along straight segments of rural mountainous highways.
CONCLUSION: In addition to unobserved heterogeneity, it is important to account for higher order interactions to have a better understanding of factors that influence crash severity. A proper understanding of these factors will help develop targeted countermeasures to improve road safety along rural mountainous highways.