Bibliographic record
Abstract
Introduction: The critical role of emotion regulation (ER) for emotional and social well-being has now been well-established. Recently, there have been calls in the literature for a better understanding of the interpersonal context of ER. This study used an intensive longitudinal design to (i) describe the frequency with which interpersonal ER strategies are used; (ii) assess the association of interpersonal ER strategies with positive and negative emotions, and (iii) assess the roles of friends and parents in ER efforts. Methods: A sample of 139 emerging adults was recruited. Participants recorded their emotions, use of 12 interpersonal ER strategies, and use of respective support sources three times a day over the course of a week using their mobile device. The moderating roles of neuroticism and extraversion were also examined. Multilevel modeling was used to assess the within- and between-person variability in positive and negative emotions. Results: Positive strategies, and specifically those that communicated acceptance of the individual, were not only used most frequently, but were also associated with higher and lower levels of positive and negative emotions, respectively. When source of support was considered, acceptance strategies were associated with positive and negative emotions when used by friends as well as parents. Positive engagement strategies (i.e., those that involve attempts to engage in the individual’s situation or emotion) were associated with emotions when used by friends, but there was no significant association when parents used these same strategies. Neuroticism was found to moderate the relationship between acceptance and negative emotions. Conclusions: This study is one of the first of its kind to explore interpersonal ER on a day-to-day basis and provides insights into the strategies being used to manage emotions, as well as the respective roles of friends and parents. Future intensive longitudinal research is warranted that considers lagged effects and additional within- and between-person factors associated with positive and negative emotions in order to further understand the dynamic process of ER as it unfolds in social relationships.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".