Publication Productivity in Central Asia and Countries of the Former Soviet Union

Introduction. Despite the significant number of research institutions and rich scientific heritage, published research from Central Asia (Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan) is traditionally underrepresented in international scientific literature. The goal of this paper was to analyze publication patterns in Central Asian countries, and to explore the factors that contributed to the publication productivity in Kazakhstan. Methods. Publication  productivity was evaluated using data generated by the SCImago Journal & Country Rank over the period of 1996-2014 for all of the 15 former Soviet Union Republics for all subject categories. Country specific data, including total population, gross domestic product (GDP) per capita, research and development (R&D) expenditure (% of GDP), number of reserchers (per million people), was abstracted from World Bank data. ANOVA and ANCOVA analyses compared the mean number of publications among Central Asian countries. Separate analyses was done for publication patterns in the health sciences. Multiple comparisons were performed using Tukey method Results. The analysis of publication productivity showed significant discrepancies in the number of published documents among the Central Asian countries. Kazakhstan demonstrated a significant increase in the number of published documents in the period of 1996-2014, mainly in the areas of natural and multidisciplinary sciences. Our analyses also showed that the number of publications are siginicantly associated with GDP and population size. Conclusions. We identified large gaps in publication productivity among the Central Asian countries. The association between publication rate with GDP and population size indicates there is a need to adjust for these factors when planning research policy

Publication Productivity in Central Asia and Countries of the Former Soviet Union

Introduction. Despite the significant number of research institutions and rich scientific heritage, published research from Central Asia (Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan) is traditionally underrepresented in international scientific literature. The goal of this paper was to analyze publication patterns in Central Asian countries, and to explore the factors that contributed to the publication productivity in Kazakhstan. Methods. Publication  productivity was evaluated using data generated by the SCImago Journal & Country Rank over the period of 1996-2014 for all of the 15 former Soviet Union Republics for all subject categories. Country specific data, including total population, gross domestic product (GDP) per capita, research and development (R&D) expenditure (% of GDP), number of reserchers (per million people), was abstracted from World Bank data. ANOVA and ANCOVA analyses compared the mean number of publications among Central Asian countries. Separate analyses was done for publication patterns in the health sciences. Multiple comparisons were performed using Tukey method Results. The analysis of publication productivity showed significant discrepancies in the number of published documents among the Central Asian countries. Kazakhstan demonstrated a significant increase in the number of published documents in the period of 1996-2014, mainly in the areas of natural and multidisciplinary sciences. Our analyses also showed that the number of publications are siginicantly associated with GDP and population size. Conclusions. We identified large gaps in publication productivity among the Central Asian countries. The association between publication rate with GDP and population size indicates there is a need to adjust for these factors when planning research policy

Visual Behavior Differences in Drivers Across The Lifespan: A Digital Billboard Simulator Study

Driver distraction is implicated in a significant portion of motor vehicle collisions; evidence has suggested that billboards can contribute to such distraction, but many knowledge gaps remain. The purpose of this study was to evaluate the effects of various types of billboards (static, 250-foot digital transition, 500-foot digital transition, and a control [no billboard] condition) and age group (teen, middle, and older) on visual behavior through the use of a driving simulator. To address gaps in the existing literature, the effects of age group and billboard type on the following visual attention variables were considered: percent of time participants looked at billboards, average glance length, number of glances, and glance pattern activity. Significant main effects of age group were found, suggesting that teen drivers exhibited significantly different visual behavior as compared to drivers in the other age groups. An Age Group x Billboard Type interaction for one outcome provided some evidence that percent of time spent looking at billboards significantly increased as billboard transition time increased for drivers, except for older adults, who spent more time looking at static billboards. This study helps lay the groundwork for future studies that may consider how young drivers’ differential scanning patterns impact driving safety

Distracted Driving in Teens With and Without Attention-Deficit/Hyperactivity Disorder

OBJECTIVE: This study is among the first to examine the effect of talking on a cell phone or text messaging while driving in teens with and without Attention Deficit/Hyperactivity Disorder (ADHD). METHOD: Teens (average age 17 years) with a diagnosis of ADHD (N=16) were matched with typically developing controls (N=18). All participants operated a driving simulator while (1) conversing on a cell phone, (2) text messaging, and (3) with no distraction during a baseline condition. Six indicators of driving performance were recorded: (a) time to complete the drive; (b) lane deviations; (c) variability in lane position (i.e., Root Mean Square [RMS]); (d) reaction time; (e) motor vehicle collisions; and, (f) speed fluctuation. RESULTS: Significantly greater variation in lane position occurred in the texting task compared to no task and the cell phone task. While texting, in particular, teens with ADHD took significantly less time to complete the scenario. No significant main effects of group were found. CONCLUSIONS: Generally, those with ADHD did not differ in regard to driving performance, when compared to controls, with the exception of one outcome: time to complete scenario. These findings suggest that distracted driving impairs driving performance of teen drivers, regardless of ADHD status. Texting while driving had the greatest negative impact on driving performance, particularly with regard to variability in lane position (i.e., RMS). This study sheds light on key issues regarding injury prevention, with the intent of providing pediatric care providers with the knowledge to inform teen drivers of risks associated with distracted driving which will ultimately result in reduced rates of motor vehicle crashes and concomitant injuries

Impact of Distracted Driving on Safety and Traffic Flow

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16 to 25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted