The Oxford Happiness Questionnaire: Transformation from an Ordinal to an Interval Measure Using Rasch Analysis

The scientific study of happiness requires accurate measurement of the construct that satisfies assumptions of parametric statistics and thus allows both researchers and clinicians to make reliable and valid comparisons with the relevant data sources. The 29-item Oxford Happiness Questionnaire (OHQ) is a widely-used scale for assessment of personal happiness. While its psychometric properties are acknowledged to be acceptable, it presents scores on an ordinal scale and may thus not discriminate precisely between individual happiness levels. The current study aimed to improve precision and item functioning of the OHQ by applying Rasch analysis to a sample of 281 participants. To correct disordered thresholds items were rescored in a uniform fashion. Four items displayed poor relationships with the latent trait of happiness and were removed. Best fit to the unidimensional Rasch model was achieved after locally dependent items were combined into subtests and adjusted for personal differences. Using the ordinal-to-interval conversion tables published here, ordinal OHQ scores can now be transformed to interval level data and thus subjected to parametric statistical analysis without violating fundamental assumptions. The precision of the instrument can be improved significantly by these minor modifications without the need to modify the original response format.     

Cultural roots of Russian sophiology

Conclusion The development of Russian culture predetermined three propensities which form the intellectual framework of Russian national philosophy—historicism, mysticism and aestheticism. The most significant conceptions of Russian philosophy, united by the idea and image of Sophia, are defined by this framework. There is no contradiction in Russian philosophy between rational and mystical modes of thought because they are complementary in this tradition. It is, however, necessary to redefine the conception of rationality. I would like to finish with Solovyov's words: “The idea of a nation is not what it thinks of itself in time, but what God thinks of it in eternity”. I am very grateful to Dr. Graeme Marshall for his support and help.     

The European University at St. Petersburg: a case study in sociology of post-Soviet knowledge

The article presents results of an ongoing study of centers of intellectual innovations in post-Soviet Russia. Using the European University at St. Petersburg as the main object of their analysis, the authors demonstrate how new models of academic careers, which became available in the 1980s and 1990s, were eventually institutionalized as new models of knowledge production and educational practices. Supported by American foundations, this private university had to invent a new institutional structure and to position itself within the field of higher education, still mostly dominated by the state.     

Aggressive behavior,related conduct problems,and variation in genes affecting dopamine turnover

A number of dopamine‐related genes have been implicated in the etiology of violent behavior and conduct problems. Of these genes, the ones that code for the enzymes that influence the turnover of dopamine (DA) have received the most attention. In this study, we investigated 12 genetic polymorphisms in four genes involved with DA functioning (COMT, MAOA and MAOB, and DβH) in 179 incarcerated male Russian adolescents and two groups of matched controls: boys without criminal records referred to by their teachers as (a) “troubled‐behavior‐free” boys, n=182; and (b) “troubled‐behavior” boys, n=60. The participants were classified as (1) being incarcerated or not, (2) having the DSM‐IV diagnosis of conduct disorder (CD) or not, and (3) having committed violent or nonviolent crimes (for the incarcerated individuals only). The findings indicate that, although no single genetic variant in any of the four genes differentiated individuals in the investigated groups, various linear combinations (i.e., haplotypes) and nonlinear combinations (i.e., interactions between variants within and across genes) of genetic variants resulted in informative and robust classifications for two of the three groupings. These combinations of genetic variants differentiated individuals in incarceration vs. nonincarcerated and CD vs. no‐CD groups; no informative combinations were established consistently for the grouping by crime within the incarcerated individuals. This study underscores the importance of considering multiple rather than single markers within candidate genes and their additive and interactive combinations, both with themselves and with nongenetic indicators, while attempting to understand the genetic background of such complex behaviors as serious conduct problems. Aggr. Behav. 36:158–176, 2010. © 2010 Wiley‐Liss, Inc.     

Automated classification and scoring of smooth pursuit eye movements in the presence of fixations and saccades

Ternary eye movement classification, which separates fixations, saccades, and smooth pursuit from the raw eye positional data, is extremely challenging. This article develops new and modifies existing eye-tracking algorithms for the purpose of conducting meaningful ternary classification. To this end, a set of qualitative and quantitative behavior scores is introduced to facilitate the assessment of classification performance and to provide means for automated threshold selection. Experimental evaluation of the proposed methods is conducted using eye movement records obtained from 11 subjects at 1000 Hz in response to a step-ramp stimulus eliciting fixations, saccades, and smooth pursuits. Results indicate that a simple hybrid method that incorporates velocity and dispersion thresholding allows producing robust classification performance. It is concluded that behavior scores are able to aid automated threshold selection for the algorithms capable of successful classification.     

“I don't want to be near you,unless…”: The interactive effect of unethical behavior and performance onto relationship conflict and workplace ostracism

Examined through the lens of moral psychology, we investigate when and why employees’ unethical behaviors may be tolerated versus rejected. Specifically, we examine the interactive effect of employees’ unethical behaviors and job performance onto relationship conflict, and whether such conflict eventuates in workplace ostracism. Although employees’ unethical behaviors typically go against moral norms, high job performance may provide a motivated reason to ignore moral violations. In this regard, we predict that job performance will mitigate the relationship between employee unethical behavior and workplace ostracism, as mediated by relationship conflict. Study 1, a multisource field study, tests and provides support for Hypotheses 1 and 2. Study 2, also a multisource field study, provides support for our fully specified model. Study 3, a time‐lagged field study, provides support for our theoretical model while controlling for employees’ negative affectivity and ethical environment. Theoretical and practical implications are discussed.     

Effects of loading modes on densification efficiency of spark plasma sintering: sample study of zirconium carbide consolidation

Theoretical studies on the densification kinetics of the new spark plasma sinter-forging (SPS-forging) consolidation technique and of the regular SPS have been carried out based on the continuum theory of sintering. Both modelling and verifying experimental results indicate that the loading modes play important roles in the densification efficiency of SPS of porous ZrC specimens. Compared to regular SPS, SPS-forging is shown to be able to enhance the densification more significantly during later sintering stages. The derived analytical constitutive equations are utilised to evaluate the high-temperature creep parameters of ZrC under SPS conditions. SPS-forging and regular SPS setups are combined to form a new SPS hybrid loading mode with the purpose of reducing shape irregularity in the SPS-forged specimens. Loading control is imposed to secure the geometry as well as the densification of ZrC specimens during hybrid SPS process.     

Measurement invariance of the Phubbing Scale across 20 countries

Mobile phone addiction is a robust phenomenon observed throughout the world. The social aspect of mobile phone use is crucial; therefore, phubbing is a part of the mobile phone addiction phenomenon. Phubbing is defined as ignoring an interlocutor by glancing at one's mobile phone during a face-to-face conversation. The main aim of this study was to investigate how the Phubbing Scale (containing 10 items) might vary across countries, and between genders. Data were collected in 20 countries: Belarus, Brazil, China, Croatia, Ecuador, India, Israel, Italy, Netherlands, Pakistan, Poland, Portugal, Serbia, Slovakia, Slovenia, Spain, Turkey, UK, Ukraine and USA. The mean age across the sample (N = 7696, 65.8% women, 34.2% men) was 25.32 years (SD = 9.50). The cross-cultural invariance of the scale was investigated using multigroup confirmatory factor analyses (MGCFA) as well as the invariance analyses. Additionally, data from each country were assessed individually via confirmatory factor analyses (CFAs). We obtained two factors, based on only eight of the items: (a) communication disturbances and (b) phone obsession. The 8 items Phubbing Scale.     

A novel evaluation of two related and two independent algorithms for eye movement classification during reading

Nystr?m and Holmqvist have published a method for the classification of eye movements during reading (ONH) (Nyström & Holmqvist, 2010). When we applied this algorithm to our data, the results were not satisfactory, so we modified the algorithm (now the MNH) to better classify our data. The changes included: (1) reducing the amount of signal filtering, (2) excluding a new type of noise, (3) removing several adaptive thresholds and replacing them with fixed thresholds, (4) changing the way that the start and end of each saccade was determined, (5) employing a new algorithm for detecting PSOs, and (6) allowing a fixation period to either begin or end with noise. A new method for the evaluation of classification algorithms is presented. It was designed to provide comprehensive feedback to an algorithm developer, in a time-efficient manner, about the types and numbers of classification errors that an algorithm produces. This evaluation was conducted by three expert raters independently, across 20 randomly chosen recordings, each classified by both algorithms. The MNH made many fewer errors in determining when saccades start and end, and it also detected some fixations and saccades that the ONH did not. The MNH fails to detect very small saccades. We also evaluated two additional algorithms: the EyeLink Parser and a more current, machine-learning-based algorithm. The EyeLink Parser tended to find more saccades that ended too early than did the other methods, and we found numerous problems with the output of the machine-learning-based algorithm.     

Using machine learning to detect events in eye-tracking data

Event detection is a challenging stage in eye movement data analysis. A major drawback of current event detection methods is that parameters have to be adjusted based on eye movement data quality. Here we show that a fully automated classification of raw gaze samples as belonging to fixations, saccades, or other oculomotor events can be achieved using a machine-learning approach. Any already manually or algorithmically detected events can be used to train a classifier to produce similar classification of other data without the need for a user to set parameters. In this study, we explore the application of random forest machine-learning technique for the detection of fixations, saccades, and post-saccadic oscillations (PSOs). In an effort to show practical utility of the proposed method to the applications that employ eye movement classification algorithms, we provide an example where the method is employed in an eye movement-driven biometric application. We conclude that machine-learning techniques lead to superior detection compared to current state-of-the-art event detection algorithms and can reach the performance of manual coding.