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The criminal narrative experience (CNE) framework posits that criminals’ personal experiences of offending can be differentiated into distinct narrative themes. This study aims to examine whether CNE themes of sexual offenders (SO) was related to particular cognitive distortions (criminal thinking). Additionally, given previously identified psychological differences between child SO and SO that target adults, the study also compared CNE and criminal thinking styles between these SO groups.

Twenty-six adult male offenders convicted for sexual crimes completed a survey composed of the Psychological Inventory of Criminal Thinking Styles (Version 4) and a Criminal Narrative Experience Questionnaire which identified two narrative themes of sexual offending (The Intrepid Professional-Adventurer, IPA; and The Dejected Revenger Victim, DRV).

Analyses failed to identify significant relationships between CNE themes and most of the criminal thinking styles. However, offenders reporting the DRV narrative displayed greater fears about the prospect of changing. Additionally, child SO displayed the IPA narrative more than SO that targeted adults.

The CNE framework can assist practitioners who are working towards a goal of desistance, as the experience of crime from the perspective of the offender is understood through their narrative roles and emotional experience. Identifying an individual’s strongest CNE theme could aid practitioners in identifying and planning interventions which challenge the distorted thinking.

This study is the first to examine the relationship between CNE and cognitive distortions that enable (re)offending.

The Triarchic Psychopathy Measure (Tri-PM) was developed in 2010 as an alternative approach to the assessment of psychopathy. The measure aims to capture psychopathic traits on a 3-factor model, which encompass the characteristics established in previous measures, as well as those evidenced within practise. Though support for the tool in academic research is growing, less is known about the scale’s utility within crime forensic settings. Thus, this study aims to explore the relationship between the Tri-PM psychopathy constructs and criminal cognition within a forensic sample.

Seventy-three adult male offenders, convicted for acquisitive or sexual crimes, from a Category B prison within the Northwest of England completed questionnaires measuring their criminal backgrounds, psychopathy traits (Tri-PM; Patrick, 2010) and criminal thinking styles (Psychology Inventory of Criminal Thinking Styles; Walters, 2001).

The Tri-PM measurement proved to be a successful predictor of most criminal thinking styles. Moreover, the meanness construct was the strongest predictor of proactive thinking styles, whereas the disinhibition construct was the strongest predictor of reactive thinking styles, and the boldness construct was negatively associated with reactive thinking. Comparisons among offender groups also indicated that acquisitive offenders reported higher scores of psychopathy and criminal thinking.

This study offers valuable insight into the proposed relationship between psychopathy and criminal thinking, using a recent addition to the repertoire of psychopathy measurements, the Tri-PM. This study also offers practical implications for those offering treatment within forensic settings, with significant relationships identified between the highly scoring psychopathy constructs and various criminal thinking styles.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.