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The nurse mentor is important in the personal and professional development of undergraduate nurses, ensuring that nursing students are competent and well prepared for practice at the point of registration. The importance of a rigorous evidence base for mentors and fellow nurse educators to use to inform education and practice should not be overlooked. This article seeks to expand this knowledge base and acquire research data that is relevant, topical and in line with the latest thinking to support best practice in nurse mentorship and nursing student education.

Thirteen student nurses from the Mental Health and Learning Disability branches (Project 2000) of the School of Care Sciences at the University of Glamorgan volunteered to participate in a research study as research assistants. Participation of this kind represents a novel, practical way of learning about research. Following training and data collection within the research study we evaluated the student's experience of training and participation. Within the survey both quantitative and qualitative data were collected using a self-report questionnaire. Thirteen questionnaires were distributed and twelve completed questionnaires were returned to the School of Care Sciences. The overall results were extremely encouraging with regards to using this approach to increase research awareness. An evaluation of the student's experiences as a researcher confirmed that this was a successful strategy to learning, in particular increasing knowledge of the research process, ethical considerations and skills in interviewing. Involvement also increases the student's awareness of the topic area being studied. Limitations to the study were that this was a small sample.

Large scale surveys have conventionally been analysed using a statistical package. This saves considerable time and permits many more analyses to be undertaken than with more traditional methods. It does, however, have certain drawbacks. First, it does not help with the problem of data management. SPSS and Epfino, for example, have some facilities for data entry restrictions and cross-checking. They are excellent for the static purpose for which they are designed, but rather crude in comparison with those provided by a dedicated database tool. Second, it requires considerable experience to achieve maximum benefit. Third, it does not help at all in the major undertaking of data exploration. The authors have analysed a large scale survey using a statistical package and a database in collaboration. Their experience is reported here.