Shyness Associations With Approach/Avoidance Behaviors in Emerging Adulthood: The Moderating Role of Emotional Intelligence Differs for Women and Men
Bibliographic record
Abstract
Previous research has shown that shyness is a risk factor for poor socio-emotional outcomes, although not all shy adults develop these problematic behaviors. Emotional intelligence (EI) may be one explanatory factor that helps facilitate adaptive social behaviors and buffers against developing internalizing behaviors in some shy individuals. Accordingly, this study investigated whether EI moderated the relation between shyness and social approach (i.e., sociability) and avoidance (i.e., internalizing behaviors) behaviors in emerging adulthood. Participants were 523 young adults (M = 18.65 years, SD = 0.90, 19.3% male) who completed online questionnaires related to shyness, EI, sociability, and internalizing behaviors. We found that the EI subfactor Others' Emotion Appraisal (OEA) moderated a negative relation between shyness and sociability. Specifically, shy women with higher OEA reported higher levels of sociability than those with lower levels of OEA. Notably, this effect was not observed in men. As well, contrary to our expectation, EI had no moderating effect on the relation between shyness and internalizing behaviors. Findings indicate that the ability to perceive others' emotions may help shy women navigate social situations more effectively. Moreover, they challenge the idea that EI uniformly moderates the effects of shyness, instead highlighting the different pathways through which specific emotional competencies interact with personality and sex.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".