Mattering Versus Self-Esteem in University Students: Associations With Regulatory Focus, Social Feedback, and Psychological Distress
Bibliographic record
Abstract
Although research has established that feelings of not mattering are associated with distress, the factors and processes that contribute to these associations have not received much consideration. The current study was conducted to address three themes. First, mattering was evaluated from a motivational perspective by examining mattering and regulatory focus. Second, the uniqueness of low mattering in predicting distress was investigated when considered along with other predictors (i.e., self-esteem and regulatory focus). Finally, a negative inferential style involving perceptions of negative social feedback was tested as a cognitive mediator of the link between mattering and distress. Mattering was correlated moderately with a promotion self-regulation focus. Regression analyses showed that mattering was also linked uniquely with distress beyond the variance predicted by self-esteem and regulatory focus. In addition, the association between low mattering and distress was mediated by negative social feedback. Our findings highlight the need for further investigation of mattering as a unique contributor to distress and the factors associated with mattering.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".