Sequences of Moment-to-Moment Emotion Dynamics during Mother-Adolescent Conflicts and Prospective Associations with Internalizing Problems
Bibliographic record
Abstract
How emotions unfold during interactions between mothers and adolescents can shape psychosocial adjustment in the long term. We examined moment-to-moment emotion dynamics in mother-adolescent conflicts and their concurrent and longitudinal associations with depressive and anxious symptoms. At Time 1 (2018), dyads were recorded during a 4-minute conflict discussion, and their emotional expressions were coded. At Time 1 and Time 2 (2019), participants reported internalizing problems. Time 1 data included 198 parent-adolescent dyads while Time 2 data included 177 parents and 176 adolescents. We used grid sequence analysis, a data-driven method in which common multi-step sequences of dyadic emotions can be identified, to examine different interaction patterns between mother-adolescent dyads. We used structural equation modeling to test the associations between these patterns and internalizing symptoms. We found two sequence patterns. Mother and adolescent anxious symptoms were not related to interaction sequences; however, the pattern of mutual high positive emotion up-regulation was related to adolescent depressive symptoms concurrently and negatively, and the pattern of mothers’ regulation of adolescents’ externalizing negative emotion was related to maternal depressive symptoms concurrently and negatively. Thus, internalizing problems are associated with the momentary interaction patterns during mother-adolescent conflicts.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".