Is attachment related to teenagers’ emotion regulation strategies and alexithymia during the COVID-19 pandemic?
Bibliographic record
Abstract
Literature on adults shows that attachment patterns, especially dismissing and preoccupied ones, are related to maladaptive emotion regulation strategies - e.g. expressive suppression - and greater alexithymia. Both emotion regulation and alexithymia influence teenagers’ psychosocial adjustment, but little is known about their relationships with attachment during adolescence. Therefore, this study investigated the relationships among these three constructs in community adolescents during the COVID-19 pandemic. One-hundred-one \nteenagers (Mage = 14.94, SD = 1.64, 47% boys) were assessed in attachment through the Friends and Family Interview, in cognitive reappraisal and expressive suppression strategies with the Emotion Regulation Questionnaire for Children and Adolescents, and alexithymia through the Toronto Alexithymia Scale–20 items. \nResults show that dismissing and disorganized attachment patterns were related to higher use of the expressive suppression (all p < .046), and attachment security was related and predicted 6% lower alexithymia (p = .012). In conclusion, practitioners could support attachment security to improve teenagers’ ability to identify and describe feelings, while more studies are needed to understand risk pathways connecting attachment to emotion regulation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".