Introduction
The relationship between speed of information processing and intelligence has been established in the large body of research. Two comprehensive meta-analyses report the correlations of -0.24 (Sheppard & Vernon, 2008) and -0.50 (Deary et al., 2001) which means that smarter participants tend to respond faster in the tasks with the response time in simple and choice tasks. Arthur Jensen suggested that higher speed of information processing maintains more efficient information processing and therefore contributes to the individual differences in cognitive ability (Jensen, 1982, 1993, 2006). Further research revealed that intelligence is stronger associated with response time in complex tasks and with the responses in slowest experimental conditions (Larson & Alderton, 1990, Coyle, 2003). The studies of intra-individual variability of response time demonstrated close relationship between intelligence and the parameters of the random walk model of decision making (Shmidek et al., 2007). In current study we aimed to extend the evidence on the relationship between intelligence and speed of information processing in adolescents from Russia and Kyrgyzstan.
Sample and Methods
The sample included 105 participants from Russia and 207 participants from Kyrgyzstan (mean age 12.8 years, SD=2.2 years, 137 were male, 175 were female). The individual differences in intelligence were assessed using Raven’s Standard Progressive Matrices (Raven & Court, 1998). The speed of information processing was measured using Simple Reaction Time (SRT) and Choice ReactionTime (CRT) tests from Cambridge Neuropsychological Test Automated Battery (CANTAB, Neuropsychological Test Automated Battery (CANTABeclipse) manual, 2006). SRT and CRT tests implement Jensen’s paradigm of measuring reaction time (Jensen, 1987). A participant holds the index finger at the fixation point on the touchscreen. When the stimulus appears on the screen (one position in SRT and five alternative positions in CRT), the participant has to touch it as quick as possible. For the analyses we used reaction time, movement time, and the accuracy of response. The logarithmic transformation was applied to response times to achieve normal distribution.
Results
Intelligence demonstrated considerable improvement with age (r=0.280, p=0.000) as well as RT in CRT (r=-0.251, p=0.000) and accuracy in SRT (r=0.134, p=0.018). On average, Russian adolescents achieved 7.14 points over Kyrgyz adolescents (F[1,237]=26.571, p=0.000). No cross-cultural differences were revealed in RT performance. The relationships between Raven’s total score and measures of RT performance were statistically non-significant. The biggest correlations were with CRT reaction time (r=-0.109, p=0.093) and SRT reaction time (r=-0.114, p=0.078). However, the separate analysis showed statistically significant correlations between Raven’s score and CRT reaction time (r=-0.168, p=0.040) and SRT reaction time (r=-0.182, p=0.026) in Kyrgyz, but not in Russian adolescents.
Conclusion
We aimed to study the relationship between speed of information processing in adolescents from Russia and Kyrgyzstan. The associations were small in Kyrgyz adolescents and non-detectable in Russian adolescents. The level of detected associations was lower than in previous research (Sheppard & Vernon, 2008, Deary et al., 2001). This can be accounted for the developmental changes in cognition that endure through adolescence (Jensen, 2006). In further study we plan to consider intra-individual variability of response time and to address the question of genetic and environmental sources of the relationship between intelligence and speed of information processing.
The research was supported by the grant from the Department of Humanities and Social Sciences of the Russian Foundation for Basic Research №17-36-01135.
