A systematic literature review of alcohol education programmes in middle and high school settings (2000-2014)

Purpose Social marketing benchmark criteria were used to understand the extent to which single-substance alcohol education programmes targeting adolescents in middle and high school settings sought to change behaviour, utilised theory, included audience research and applied the market segmentation process. The paper aims to discuss these issues. Design/methodology/approach A systematic literature review retrieved a total of 1,495 identified articles; 565 duplicates were removed. The remaining 930 articles were then screened. Articles detailing formative research or programmes targeting multiple substances, parents, families and/or communities, as well as elementary schools and universities were excluded. A total of 31 articles, encompassing 16 qualifying programmes, were selected for detailed evaluation. Findings The majority of alcohol education programmes were developed on the basis of theory and achieved short- and medium-term behavioural effects. Importantly, most programmes were universal and did not apply the full market segmentation process. Limited audience research in the form of student involvement in programme design was identified. Research limitations/implications This systematic literature review focused on single-substance alcohol education programmes targeted at middle and high school student populations, retrieving studies back to the year 2000. Originality/value The results of this systematic literature review indicate that application of the social marketing benchmark criteria of market segmentation and audience research may represent an avenue for further extending alcohol education programme effectiveness in middle and high school settings.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.