Decentering From Emotions in Daily Life: Dynamic Associations With Affect, Symptoms, and Well-Being
Bibliographic record
Abstract
Decentering is thought to be protective against a range of psychological symptoms, but little is known about the outcomes of decentering as a momentary state in daily life. We used ecological momentary assessment (42 reports across one week) to examine the temporal ordering of the associations of decentering with affect, dysphoria, participant-specific idiographic symptoms, and wellbeing. We also hypothesized that greater decentering predicts less inertia (persistence) of each variable, and weakens the association of affect with dysphoria, idiographic symptoms, and wellbeing. Results in 345 community participants indicated that decentering and these variables were mutually reinforcing over time, and that greater decentering was associated with less inertia of negative affect and dysphoria. Decentering generally predicted reduced impact of positive and negative affect on dysphoria symptoms, but results were mixed when predicting idiographic symptoms or wellbeing. Clinical implications and refinements for theory on decentering are discussed.
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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 | 0.000 |
| 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".