Supplementary Materials<i>Emotional Regulation and Subjective Well-Being in Adolescents: A Systematic Review</i>
Bibliographic record
Abstract
Introduction: Emotional regulation and its relationship with subjective well-being are relevant phenomena to study, especially during adolescence, a critical period marked by significant changes in mental health and social development. These antecedents underscore the importance of studying how emotional regulation can act as a protective factor for adolescents' subjective well-being. Objetive: The purpose of this systematic review was to investigate the impact of emotional regulation on adolescents' subjective well-being. Design/Methodology/Approach: The search was conducted following the PRISMA methodology in the Web of Science, Scopus, PubMed, and Scielo databases from January 2018 to December 2023, and the methodological quality was also assessed using the Newcastle-Ottawa Scale (NOS). Results: A total of 16 studies met the inclusion criteria, highlighting that adaptive emotional regulation strategies, particularly cognitive reappraisal and acceptance, are consistently associated with higher levels of life satisfaction, happiness, and self-esteem. Moreover, these strategies act as protective factors against depression, anxiety, and emotional distress. Studies employing longitudinal designs suggest that emotional regulation fosters resilience and improves adolescents' long-term well-being. Conversely, maladaptive strategies such as rumination and suppression were linked to lower subjective well-being and increased psychological distress. Conclusions: The findings underscore the critical role of emotional regulation in fostering adolescent well-being. Specifically, interventions that promote cognitive reappraisal and acceptance may enhance psychological resilience and overall life satisfaction. Future research should explore the long-term effects of emotional regulation training and its integration into educational and clinical settings to support adolescent mental health.
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 | 0.009 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.273 | 0.010 |
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".