The utilisation of factorial research methods in the exploration of treatment decisions by health and social workers

Self-neglect can be understood as the failure to engage in those activities which a given culture deems necessary to maintain a socially accepted standard of personal and household hygiene and carry out those activities needed to maintain health status. It has been articulated that perceptions of self-neglect may differ among and between professional groups and those who they categorise as self-neglecting. To date, the types of treatment decisions made by health and social practitioners and the factors that influence these decisions over time, is not clearly understood. For best practice to be provided by health and social professionals it is necessary to gain an understanding of how practitioners decide when and what type of treatment or intervention is required. The factorial survey is a research method which combines elements of a standard survey and aspects of an experimental design (Lauder 2002). The current research, utilising factorial survey methods, aims to explore treatment decisions by health and social professionals in Queensland, the U.K. and the U.S.A. The research further aims to develop factorial survey methods by designing and testing progressive factorial survey methods and related statistical analyses. The development of progressive factorial surveys is currently being undertaken by an interdisciplinary group of academics and systems analysts from Australia, USA and UK. This group are improving the method in order to more fully replicate the conditions under which judgements are made, insofar as this is possible, whilst maintaining the existing strengths of the method. The group propose to refine factorial survey methods to capture issues such as social class, uncertainty, the ways in which judgements occur over time and the physical ways in which information comes to practitioners. The research also intends to develop statistical methods to test for main and interaction effects over time