Conclusion

1. THE 4th INTERNATIONAL CONFERENCE ON BULLYING AND HARASSMENT IN THE WORKPLACE (Bergen, Norway, 2004) Clinical definitions determining the size of bullied workers versus data driven estimation with latent cluster analysis Guy Notelaers1, Jeroen Vermunt,2, Stale Einarsen3 & Hans De Witte1 1: Katholieke Universiteit Leuven, Belgium; 3: Bergen University, Norway; 2:Tilburg Univeristy, Netherlands • Introduction • Research shows that bullying at work is a widespread phenomenem. In some research bullying at work takes the form of a desease... • Scandinavian reserach (Einarsen & Skogstad, 1996; Leymann, 1996): 4% • British studies 10% • - Netherlands (Hubert & van Veldhoven, 2001) 2 tot 3% • - In Belgium prevailence rates are between 10 (Notelaers & De Witte, 2003a; Notelaers & De Witte, 2003b) and 16% (Opdebeeck, et. al, 2002). • These rates differ a lot. That questions how we measure bullying and how we decide who is bullied and who is not. • This is a major problem for organisations who are meeting the EC directive about riskanalysis. Following the control cycle (Cox & Gonzales, 2000) it is vital to make an inventory of the psychosocial risks and to make a link between the risks and its healh consequences in order to • - Eliminate the risk (primary prevention) • - Prevent the risk (secondary secondary) • - ‘Cure’ the victims (tertiary prevention) • Thus it is essential that our categorization methods can capture or discriminate between who is a victim of bullying and who is not. • Measuring bullying at work • Subjective • Until now different definitions were used but nowaday in Europe many use Einarsen & Skogstad ‘s (1996) definition. But many have used different responscategories and different time – reference (e.g. 6 and 12 months) • Objective • By means of questionnaire without referring directly to ‘bullying’. • LIPT (46 items) • NAQ (22 items, 29 items, 32 items, 17 items) and NAQ-r • => different prevailence rates of bullying • Categorizing victims/non-victims • Different decisions to attribute victims and non victims are in fact questioning the dimensionality of bullying concept. Applying the operational definition of one or two acts during the last six months is assuming a one dimensional construct. • But the literature reveals : • - 5 dimensions according the effect they cause (Leymann, 1996) • - 7 dimensions by Knorz&Zapf (1996) • - 5 dimensions by Einarsen & Raknes (1997) • - 2 dimensions by Einarsen & Hoel (2001) • - 4 dimensions in Dick & Rayner’s instrument (2004) • How to categorize victims / non – victims when dimensions are related/ non related? Which dimension? How to weight? How are dimensions related? • For riskanalysis it is a problem to decidewhether someone is bullied or not with a multidimensional concept. • Aim of this research • To inspect wheter bullying, as it has been measured by the NAQ without dichotomizing the responscategories into yes and no, is a multidimensional measurement. And if so to to inspect whether a latent cluster approach (Vermunt&Magidson, 2002) can help to classify respondents in homogenous groups according to their exposure to bullying. Sample 6175 observations stem from two kinds of research :research to inventarise wellbeing (14 studies) and research with focus on mobbing (4 studies) (see the other poster (Notelaers, et. al, 2004). Method Subjective methods ‘Are you being bullied at work?’ (‘never’, ‘sometimes’, ‘often’ and ‘always’) ‘Are you being bullied at work during the last six months?’ (‘never’, ‘sometimes’, ‘often’ and ‘always’ ) ‘Are you being bullied at work the last six months according to our definition’(no, never’, ‘yes, seldom’, ‘yes, sometimes’, ‘yes, weekly’ and ‘yes, daily’) Objective method : Belgian NAQ 17 items Results Six clustermodel for bullying at work Discussion : a phase model for bullying at work? Evaluation of clustermodel • Conclusion • Bulliying measured with the NAQ is a multidimensional construct when the answers to the negative acts are not recoded into ‘yes’ or ‘no’. Nonetheless there is proof for a multidimensional approach, the latent factor solutions are inferior to the latent cluster solutions. • This latent cluster solution is multidimensional by nature. It captures six classes of respondents of which only one is to be considered as a victims cluster. Therefore we conclude that 3% of the population is victim of bullying at work. However there are other cluster who are clearly exposed to bullying but the occurence of bullying is not high enough to cause serious (z<-1) health consequences. These clusters are referred to as latent bullying and workrelated bullying. Three clusters are not really related to bullying. For riskassessment these cluster can be interesting in that two clusters can be dedected where preventive measures can avoid bullied persons to become victims. • Compared to other ways of categorizing respondents into classes i.e. operational criteria it is clear that the latent cluster approach has the most discriminatory power and captures best the self-judgement of respondents (subjective method). • Maybe the latent cluster approach suits a phase model that has been suggested troughout the years (Bjorkvist, Einarsen, Zapf, Leymann). Phase I : no acts • Phase II : at a very low level workrelated acts emerge. Phase III : the level of workrelated acts remains constant but some personal directed acts ermerge at a very low level. Phase IV : intensification (towards now and then and sometimes between now and then and once a month). Phase V : intensification of work related acts (once a month). Phase VI : overall intensification (once a month-week) • contact : guy.notelaers@psy.kuleuven.ac.be References Einarsen, Raknes, Matthiesen & Hellesøy, (1994). The negative acts questionnaire . Mikkelsen, E. Einarsen, S. (2001) Bullying in Danish work-life: Prevalence and Health correlates. European Journal of Work and Organizational Psychology, 10, 4, 393 – 413. Salin, D. (2001) Prevalence and forms of bullying among business professionals: a comparison of two different strategies of measuring bullying. European Journal of Work and Organizational Psychology, 10, 4, 425-411. Vermunt, J.K. Magidson, J. (2002) Latent Class Cluster Analysis. In : Hagenaars, J.&McCutcheon (eds), Applied Latent Class Analysis, Cambridge : Cambridge University Press, 89-106. Vermunt, J.K. Magidson, J. (2003) Latent Gold : Users GuideLatent Gold : Users Guide. Statistical Innovations. Zapf, D. Knorz, C. Kulla, M. (1996) On the Relationship between Mobbing Factors and Job Content, Social Work Environment, and Health Outcomes. European Journal of Work and Organizational Psychology, 5, 2, 215-237. Zapf, D. Einarsen, S. Hoel, H. Vartia, M. (2003) Empirical findings on bullying in the workplace. In: Einarsen, S. Hoel, H. Zapf, D & Cooper, C. (Eds) Bullying and Emotional Abuse in the Workplace. Taylor & Francis, London, 103-124. Gedruckt im Rechenzentrum der Universität Leipzig