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The success of diagnostic knowledge systems has been proved over the last decades. Nowadays, intelligent systems are embedded in machines within various domains or are used in interaction with a user for solving problems. However, although such systems have been applied very successfully the development of a knowledge system is still a critical issue. Similarly to projects dealing with customized software at a highly innovative level a precise specification often cannot be given in advance. Moreover, necessary requirements of the knowledge system can be defined not until the project has been started or are changing during the development phase. Many success factors depend on the feedback given by users, which can be provided if preliminary demonstrations of the system can be delivered as soon as possible, e.g., for interactive systems validation the duration of the system dialog. This thesis motivates that classical, document-centered approaches cannot be applied in such a setting. We cope with this problem by introducing an agile process model for developing diagnostic knowledge systems, mainly inspired by the ideas of the eXtreme Programming methodology known in software engineering. The main aim of the presented work is to simplify the engineering process for domain specialists formalizing the knowledge themselves. The engineering process is supported at a primary level by the introduction of knowledge containers, that define an organized view of knowledge contained in the system. Consequently, we provide structured procedures as a recommendation for filling these containers. The actual knowledge is acquired and formalized right from start, and the integration to runnable knowledge systems is done continuously in order to allow for an early and concrete feedback. In contrast to related prototyping approaches the validity and maintainability of the collected knowledge is ensured by appropriate test methods and restructuring techniques, respectively. Additionally, we propose learning methods to support the knowledge acquisition process sufficiently. The practical significance of the process model strongly depends on the available tools supporting the application of the process model. We present the system family d3web and especially the system d3web.KnowME as a highly integrated development environment for diagnostic knowledge systems. The process model and its activities, respectively, are evaluated in two real life applications: in a medical and in an environmental project the benefits of the agile development are clearly demonstrated.
Background:
In recent years, there has been an increasing interest in psychosocial workplace risk assessments in Germany. One of the questionnaires commonly employed for this purpose is the Short Questionnaire for Workplace Analysis (KFZA). Originally, the KFZA was developed and validated for office workers. The aim of the present study was to examine the factorial validity of the KFZA when applied to hospital settings. Therefore, we examined the factorial structure of a questionnaire that contained all the original items plus an extension adding 11 questions specific to hospital workplaces and analyzed both, the original version and the extended version.
Methods:
We analyzed questionnaire data of a total of 1731 physicians and nurses obtained over a 10-year period. Listwise exclusion of data sets was applied to account for variations in questionnaire versions and yielded 1163 questionnaires (1095 for the extended version) remaining for factor analysis. To examine the factor structure, we conducted a principal component factor analysis. The number of factors was determined using the Kaiser criterion and scree-plot methods. Factor interpretation was based on orthogonal Varimax rotation as well as oblique rotation.
Results:
The Kaiser criterion revealed a 7-factor solution for the 26 items of the KFZA, accounting for 62.0% of variance. The seven factors were named: “Social Relationships”, “Job Control”, “Opportunities for Participation and Professional Development”, “Quantitative Work Demands”, “Workplace Environment”, “Variability” and “Qualitative Work Demands”. The factor analysis of the 37 items of the extended version yielded a 9-factor solution. The two additional factors were named “Consequences of Strain” and “Emotional Demands”. Cronbach’s α ranged from 0.63 to 0.87 for these scales.
Conclusions:
Overall, the KFZA turned out to be applicable to hospital workers, and its content-related structure was replicated well with some limitations. However, instead of the 11 factors originally proposed for office workers, a 7-factor solution appeared to be more suitable when employed in hospitals. In particular, the items of the KFZA factor “Completeness of Task” might need adaptation for the use in hospitals. Our study contributes to the assessment of the validity of this popular instrument and should stimulate further psychometric testing.