Personality, interview performance, and the mediating role of impression management
Bibliographic record
Abstract
The present study investigated the association between personality and job interview performance, as mediated by applicant use of impression management (IM) behaviours. We focused primarily on the novel role of Honesty‐Humility, with a secondary focus on Extraversion and an exploratory examination of other HEXACO personality traits. The sample consisted of 212 management students participating in high fidelity mock interviews with 70 experienced interviewers. Findings indicated that, across both self‐ and peer reports of personality, (low) Honesty‐Humility, (high) Extraversion, and (low) Emotionality predict IM use. In addition, mediation analyses indicated that individuals high in Extraversion and low on Emotionality may perform better in the interview through their use of IM. On the other hand, while Honesty‐Humility indirectly impacted interview performance through several paths, the overall effect was null, such that individuals low in Honesty‐Humility did not perform better in the interview. This is because they used both forms of IM that led to success, and those that detracted from success, thereby cancelling each other out. This study informs our knowledge of personality and interview performance, such that differences in the IM behaviours an individual chooses have implications for whether individuals with certain traits are successful. Practitioner points Impression management behaviours have an important impact on how applicants are evaluated by interviewers. Individuals who engage in IM may not be those who are necessarily better at the job once hired. They are predominantly high in Extraversion and low in Honesty‐Humility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".