Pre- and post-supervision quantitative data will be entered onto SPSS. Following EDA and error checking procedures, descriptive analyses will be produced on expectations and delivery. Factor analysis will be used to reduce the number of scores from this questionnaire, and these will then be subjected to repeated measures ANOVA to identify those dimensions on which supervision exceeded or disappointed the expectations of supervisees. Exploratory analyses of the relationship between difference scores and other demographic data on supervisees will take place to identify significant relationships and to aid the development of explanations for any findings. Repeated measures ANOVA will also be used to analyse the data resulting from use of the APDQ, GHQ-12, and MBI. Variables will be combined in a single multi-way analysis of variance in order to reduce the experimentwise error rate. Appropriate post hoc corrections for multiple comparisons will be applied.

Pre and post-supervision qualitative data will be entered onto qualitative data analysis software (NUD*IST). Simple content analysis will be used to identify themes in the detailed material on expectations and performance. Where possible, some of this qualitative data may be categorised or rated, then exported to SPSS for quantitative testing and further analysis.

MCSS data will be entered onto SPSS and compared with norms previously obtained in large-scale studies of face-to-face supervision. Exploratory analyses of the relationship between difference scores and other demographic data on supervisees will take place to identify significant relationships and to aid the development of explanations for any findings.

Archived email supervision records will also be entered onto qualitative data analysis software for analysis.

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online-supervision.net research team
20 July 2003