Coping with Impostor Feelings: Evidence Based Recommendations from a Mixed Methods Study
Bibliographic record
Abstract
Abstract Objective – The negative effects of impostor phenomenon, also called impostor syndrome, include burnout and decreased job satisfaction and have led to an increased interest in addressing this issue in libraries in recent years. While previous research has shown that many librarians experience impostor phenomenon, the experience of coping with these feelings has not been widely studied. The aim of our study was to understand how health sciences librarians cope with impostor phenomenon in the workplace. Methods – We conducted a census of 2125 Medical Library Association members between October and December 2017. An online survey featuring the Harvey Impostor Phenomenon scale and open-ended questions about coping strategies to address impostor phenomenon at work was administered to all eligible participants. We used thematic analysis to explore strategies for addressing impostor phenomenon and one-way analysis of variance (ANOVA) to examine relationships between impostor phenomenon scores and coping strategies. Results – Among 703 survey respondents, 460 participants completed the qualitative portion of the survey (65%). We found that external coping strategies that drew on the help of another person or resource, such as education, support from colleagues, and mentorship, were associated with lower impostor scores and more often rated by participants as effective, while internal strategies like reflection, mindfulness, and recording praise were associated with less effectiveness and a greater likelihood of impostor feelings. Most respondents reported their strategies to be effective, and the use of any strategy appeared to be more effective than not using one at all. Conclusions – This study provides evidence based recommendations for librarians, library leaders, and professional organizations to raise awareness about impostor phenomenon and support our colleagues experiencing these feelings. We attempt to situate our recommendations within the context of potential barriers, such as white supremacy culture, the resilience narrative, and the lack of open communication in library organizations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.327 | 0.493 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".