The semi-automatic classification of an open-ended question on panel survey motivation and its application in attrition analysis.

In this study, we demonstrate how supervised learning can extract interpretable survey motivation measurements from a large number of responses to an open-ended question. We manually coded a subsample of 5,000 responses to an open-ended question on survey motivation from the GESIS Panel (25,000 responses in total); we utilized supervised machine learning to classify the remaining responses. We can demonstrate that the responses on survey motivation in the GESIS Panel are particularly well suited for automated classification, since they are mostly one-dimensional.

Attitudes towards refugees: Introducing a short three-dimensional scale.

Many researchers subscribe to the three-component conceptualization of attitudes, the idea that attitudes have cognitive, affective, and behavioural (intentional) components. Yet, these components are rarely considered simultaneously in scales, especially those measuring attitudes towards refugees. Moreover, it is debated how these components relate to one another.

Patient satisfaction with care in office-based oncology practices.

Introduction: The purpose of patient surveys is to measure the quality of health care from the patient's point of view. They are recommended as a way to detect the strengths and weaknesses of patient care and to locate areas of potential improvement.

Methods: In the autumn of 2006, patients undergoing care in subspecialty oncology practices across Germany were given a questionnaire to be answered in writing.