(Un)expected exception: validating acquiescent response style factor in the Czech Republic

ABSTRACT

This study explores the acquiescent response style (ARS) among respondents in the Czech Republic. To analyse ARS, confirmatory factor analysis (CFA) was employed and the response style (RS) was modelled as a latent variable. The RS factor in the CFA model must be validated by its relationship to education and age, i.e. proxies of cognitive ability. The two studies presented in this article use large amount of data as all available balanced batteries of items were analysed. In Study 1, the RS factor showed no correlation with age/education in most of the models. Study 2 employed additional measures of cognitive ability and education and confirmed the overall absence of the relationship. Author concludes that the modelled RS factor then cannot be considered the ARS and deduces that the most likely explanation of the identified systematic error variance is the respondents’ carelessness manifested by automatically choosing the extreme agreement, or choosing the first presented answer as a result of memory effect.     

Young people,social workers and social work education: the role of digital skills

ABSTRACT

This paper addresses a key issue in the development of youth-focused social work: the role of digital skills in the relationship between young people and social workers who work with these native digital users. To this end, we analysed data from the International Digital Economy and Society Index 2019 and Eurostat. Information from the sixth European Working Conditions Survey and a survey conducted by the Social Care Institute for Excellence and the British Association of Social Workers supported the empirical analysis. The main findings reveal a gap between the level of digital skills required in the labour market and the actual level of digital skills in both young people and social workers, despite efforts by both groups to improve their skills. Initiatives to foster digital skills are therefore recommended to bridge this digital divide. Lastly, it was concluded that both groups could act as mutual drivers of digital transformation.     

Portmanteau tests for linearity of stationary time series

This article considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns.     

Evaluation of Multicriteria Decision Analysis Algorithms in Food Safety: A Case Study on Emerging Zoonoses Prioritization

Decision making in food safety is a complex process that involves several criteria of different nature like the expected reduction in the number of illnesses, the potential economic or health-related cost, or even the environmental impact of a given policy or intervention. Several multicriteria decision analysis (MCDA) algorithms are currently used, mostly individually, in food safety to rank different options in a multifactorial environment. However, the selection of the MCDA algorithm is a decision problem on its own because different methods calculate different rankings. The aim of this study was to compare the impact of different uncertainty sources on the rankings of MCDA problems in the context of food safety. For that purpose, a previously published data set on emerging zoonoses in the Netherlands was used to compare different MCDA algorithms: MMOORA, TOPSIS, VIKOR, WASPAS, and ELECTRE III. The rankings were calculated with and without considering uncertainty (using fuzzy sets), to assess the importance of this factor. The rankings obtained differed between algorithms, emphasizing that the selection of the MCDA method had a relevant impact in the rankings. Furthermore, considering uncertainty in the ranking had a high influence on the results. Both factors were more relevant than the weights associated with each criterion in this case study. A hierarchical clustering method was suggested to aggregate results obtained by the different algorithms. This complementary step seems to be a promising way to decrease extreme difference among algorithms and could provide a strong added value in the decision-making process.     

Work overload and intimidation: The moderating role of resilience

Work overload is a critical but understudied stressor at work, particularly for boundary-spanning positions. Recent studies have highlighted the need for more research on the identification of different predictors of the use of intimidation, a type of assertive impression management tactic. Relying on Lazarus's transactional theory, this study hypothesized and investigated a mediated moderation model that includes resilience, work overload, and its outcomes.This paper contributes to the organizational literature by examining the use of intimidation by salespeople as a reaction to stressful circumstances and the association between this tactic and salespeople's performance. The information provided by 248 employee–supervisor dyads confirmed the proposed model. Work overload has a positive association with intimidation, and the direct effect of work overload on intimidation depends on the level of an employee's resilience. Finally, the use of intimidation has a negative association with supervisor-rated performance.     

Revisiting the Role of Impulsivity and Compulsivity in Problematic Sexual Behaviors

Impulsivity and compulsivity are transdiagnostic features associated with clinically relevant aspects of psychiatric disorders, including addictions. However, little research has investigated how impulsivity and compulsivity relate to hypersexuality and problematic pornography use. Thus, the aims of the present study were to investigate (a) self-reported impulsivity and compulsivity with respect to hypersexuality and problematic pornography use and (b) the similarities and possible differences between hypersexuality and problematic pornography use in these domains. Utilizing structural equation modeling (SEM) in a large community sample (N = 13,778 participants; female = 4,151, 30.1%), results indicated that impulsivity (β = .28, β = .26) and compulsivity (β = .23, β = .14) were weakly related to problematic pornography use among men and women, respectively. Impulsivity had a stronger relationship (β = .41, β = .42) with hypersexuality than did compulsivity (β = .21, β = .16) among men and women, respectively. Consequently, impulsivity and compulsivity may not contribute as substantially to problematic pornography use as some scholars have proposed. On the other hand, impulsivity might have a more prominent role in hypersexuality than in problematic pornography use. Future research should examine further social and situational factors associated with problematic pornography use.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.