Measuring impostor phenomenon among health sciences librarians
Barr-Walker, Jill; Bass, Michelle B.; Werner, Debra A.; Kellermeyer, Liz (2018), Measuring impostor phenomenon among health sciences librarians, v5, UC San Francisco Dash, Dataset, https://doi.org/10.7272/Q600008N
This dataset contains Appendices A-J corresponding to the article "Measuring impostor phenomenon among health sciences librarians".
Objective: Impostor phenomenon, also known as impostor syndrome, is the inability to internalize accomplishments while experiencing the fear of being exposed as a fraud. Previous work has examined impostor phenomenon among academic college and research librarians, but health sciences librarians, who are often asked to be experts in medical subject areas with minimal training or education in these areas, have not yet been studied. The aim of this study was to measure impostor phenomenon among health sciences librarians.
Methods: A survey of 2,125 eligible Medical Library Association (MLA) members was taken from October to December 2017. The online survey featuring the Harvey Impostor Phenomenon scale, a validated measure of impostor phenomenon, was administered, and one-way analysis of variance (ANOVA) was used to examine relationships between impostor phenomenon scores and demographic variables.
Results: A total of 703 participants completed the survey (33% response rate), and 14.5% of participants scored ≥42 on the Harvey scale, indicating possible impostor feelings. Gender, race, and library setting showed no associations, but having an educational background in the health sciences was associated with lower impostor scores. Age and years of experience were inversely correlated with impostor phenomenon, with younger and newer librarians demonstrating higher scores.
Conclusions: One out of seven health sciences librarians in this study experienced impostor phenomenon, similar to previous findings for academic librarians. Librarians, managers, and MLA can work to recognize and address this issue by raising awareness, using early prevention methods, and supporting librarians who are younger and/or new to the profession.
Readme file contains instructions for interpreting the data.
Appendix A contains the survey instrument.
Appendix B contains a codebook that corresponds to the variable names listed in Appendix 3.
Appendix C contains all raw quantitative data, plus several new variable categories created by the authors for analysis (these are detailed in Appendix 2).
Appendix D-J contain tabular representations of results (descriptions included therein).