Evaluating measures of malevolent creativity

Creativity is defined as the generation of something of a novel, valuable, and adaptive nature which must occur by discovering a new possibility of the entity and then bringing it into being (Martin & Wilson, 2017). This study will concentrate on Malevolent creativity (MC) a relatively new field within creativity research which is defined as creativity with the intention to do harm (Cropley et al., 2008). The aim of this study is to discuss and consider the most robust options of measurement to aid future MC research. This aim was developed from a prominent criticism of the MC field, a lack of congruent measurements. The theories and scales behind all the current methods being used do have their merits, however the notion of the field of MC growing without consistent dimensions and measures of MC is one that should not be entertained. 105 participants completed four common MC measures: Malevolent Creativity Behaviour Scale, Kapoor Intention Scale, Malevolent Creativity Task, and two Divergent Thinking Tasks (one specifically asking for negative responses and one not specifying a valence for the responses), alongside a face validity measure. The study had three main conclusions stemming from three hypotheses. The first indicated that there are mixed results within face validity of the current measures of MC, for example, while the Malevolent Creativity Behaviour Scale rated highest in malevolence it scored but low in creativity, and the Divergent Thinking Task with neutral wording scored highest in creativity but low on malevolence. This raises the question of why the measures of MC do not score high in categories malevolence as well creativity and if the measures can be compared if they do not seem to measure the same subjects according to participants. The second result suggested that when looking at correlations between MC results using all five measures, while there was a lot of significant results, there were some insignificant results primarily with the self-report measures of MC again indicating a lack of consistency between the current measures of MC and how well they can be compared when the same participant’s MC scores did not correlate across all of the measures. Lastly, results showed that negative/neutral wording of divergent thinking tasks did have a significant effect on the results produced by the measure, as it was found that while there were more negative responses given to the task asking specifically for negative responses, but the negatively worded task also had less responses overall. These all indicate that there needs to be much more analysis of the measures of MC as they currently are and how to modify them to encapsulate MC to the best of their ability. To do this, it is suggested to utilise two models of MC (the AMORAL model and the Malevolent Innovation Model) to aide a better measure being made by including more of the different key components of the models in the measures themselves