In two minds about screening: an investigation of cervical cancer prevention among Irish women

Cervical cancer is the second most common female cancer worldwide. Cervical screening programmes can reduce the incidence of cervical cancer by up to 80 percent if the invited women participate. Previous Irish research has associated screening attendance with subjective norms, anticipated regret, higher socio-economic status and education. Greater perceived screening barriers and lacking knowledge were associated with avoidance. These findings support a variety of expectancy-value theories of behaviour. They also suggest that expectancy-value theories could benefit from the inclusion of affective predictors of behaviour, like anticipated regret. In 2008 the Republic of Ireland introduced the National Cervical Screening Programme (NCSP). This research seeks to identify the predictors of participation in the NCSP. A systematic review of reviews showed that predictors of screening participation clustered into environmental and psychological influences. There is a gap in the evidence synthesis of associations with personal characteristics and health beliefs. Thematic analysis of focus group interviews confirmed the validity of many screening predictors identified by the systematic review and expectancy-value theories. A survey of these predictors suggested that reduced screening barriers might encourage first-time participation, while regular attendance requires greater endorsement of screening benefits and stronger subjective norm and intention. Positive attitude, rather than knowledge, appeared to be crucial for strong intention, so the final study piloted an experiment comparing the utility of positive attitude in strengthening intention to the utility of information provision. Despite lacking significant differences between conditions, content analysis of participant comments suggested that a full trial would be worthwhile, given purposive sampling and improved sample retention. These findings agree with previous Irish research on the importance of screening intention, although its association with attitude appeared to be stronger in the present research. The findings further indicate that future screening promotion should consider interventions based on patients’ experiences of screening.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.