The cost of believing emotions are uncontrollable: Youths’ beliefs about emotion predict emotion regulation and depressive symptoms.
Bibliographic record
Abstract
As humans, we have a unique capacity to reflect on our experiences, including emotions. Over time, we develop beliefs about the nature of emotions, and these beliefs are consequential, guiding how we respond to emotions and how we feel as a consequence. One fundamental belief concerns the controllability of emotions: Believing emotions are uncontrollable (entity beliefs) should reduce the likelihood of trying to control emotional experiences using effective regulation strategies like reappraisal; this, in turn, could negatively affect core indices of psychological health, including depressive symptoms. This model holds particular relevance during youth, when emotion-related beliefs first develop and stabilize and when maladaptive beliefs could contribute to emerging risk for depression. In the present investigation, a pilot diary study (N = 223, aged 21-60) demonstrated that entity beliefs were associated with using reappraisal less in everyday life, even when controlling for possible confounds (i.e., self-efficacy, pessimism, stress exposure, stress reactivity). Then, two studies examined whether entity beliefs and associated impairments in reappraisal may set youths on a maladaptive trajectory: In a cross-sectional study (N = 136, aged 14-18), youths with stronger entity beliefs experienced greater depressive symptoms, and this link was mediated by lower reappraisal. This pattern was replicated and extended in a longitudinal study (N = 227, aged 10-18), wherein youth- and parent-reported depressive symptoms were assessed 18 months after assessing beliefs. These results suggest that entity beliefs about emotion constitute a risk factor for depression that acts via reappraisal, adding to the growing literature on emotion beliefs and their consequences for self-regulation and health. (PsycINFO Database Record
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".