Background. Multitasking is a rapidly evolving construct and we are in dire need of a sound tool for measuring multitasking behaviors and abilities across socio-cultural contexts. To this end, this study has put forward a cultural adaptation (through back translation) of an already developed (Kushniryk, 2008) measure i.e., Communication Specific Multitasking Measurement Instrument.
Objective. This study is intended to translate, adapt, and validate a multitasking measure i.e., Communication Specific Multitasking Measurement Instrument (CSMMI; Kushniryk, 2008) in the context of collectivist culture in Pakistan.
Design. The study was composed of two parts. The first part was completed in two phases. Phase I employed back and forward translation methods to translate the multitasking measure into an indigenous language. Phase II provided empirical validity of the translated and adapted instrument (CSMMI) using exploratory factor analysis (EFA) on data collected from a sample of 230 married individuals. The second part of the study was designed to establish construct validity of the translated instrument using confirmatory factor analysis (CFA) on a larger data set of married individuals.
Results. EFA using a varimax rotation on all 19 items of CSMMI showed that the instrument is a three-dimensional measure. CFA confirmed that the translated and adapted instrument is also a three-dimensional measure on the larger data set. Analysis of the intraclass correlation and alpha coefficient provided sound evidence for validity and reliability of the measure (CSMMI).
Conclusion. The findings of this study indicate that the translated and adapted multitasking measure (CSMMI) is reliable and valid when applied to the culturally collectivist population of Pakistan. This also pertains to any other populations where the translation is adequately applicable.
Keywords: Multitasking measure/ empirical validity/ construct validity/ perceived multitasking ability/ adaptation/ validation
Background. Spearman’s law of diminishing returns (SLODR) states that intercorrelations between scores on tests of intellectual abilities were higher when the data set was comprised of subjects with lower intellectual abilities and vice versa. After almost a hundred years of research, this trend has only been detected on average.
Objective. To determine whether the very different results were obtained due to variations in scaling and the selection of subjects.
Design. We used three methods for SLODR detection based on moderated factor analysis (MFCA) to test real data and three sets of simulated data. Of the latter group, the first one simulated a real SLODR effect. The second one simulated the case of a different density of tasks of varying difficulty; it did not have a real SLODR effect. The third one simulated a skewed selection of respondents with different abilities and also did not have a real SLODR effect. We selected the simulation parameters so that the correlation matrix of the simulated data was similar to the matrix created from the real data, and all distributions had similar skewness parameters (about -0.3).
Results. The results of MFCA are contradictory and we cannot clearly distinguish by this method the dataset with real SLODR from datasets with similar correlation structure and skewness, but without a real SLODR effect. Theresults allow us to conclude that when effects like SLODR are very subtle and can be identified only with a large sample, then features of the psychometric scale become very important, because small variations of scale metrics may lead either to masking of real SLODR or to false identification of SLODR.
Keywords: intelligence; Spearman’s law of diminishing returns; mathematical modeling; structural modelling; structure of intelligence