Between Body and Soul: The Role of Need Satisfaction and Physiological Reactivity in the Recall of Anxious Memories on Subjective Emotional Experience
Bibliographic record
Abstract
The current study examined the experiential components of anxiety-related memories, that is, what is experienced during the event of the memory, and how these experiences can shape subjective emotional responses. A total of 76 participants were asked to recall a personal memory of an event that elicited fear or anxiety. Two key experiential components were evaluated: the level of need satisfaction associated with the memory and the physiological reactivity upon memory recall, as indexed by heart rate. Additionally, networked memories were assessed, referring to other memories associated with the anxiety-related memory, along with the need satisfaction component of each. Results highlighted the role of networked memories and the interaction between need satisfaction and physiological reactivity in predicting self-reported subjective experience. Specifically, participants who exhibited a low increase in heart rate during the recall of their anxiety-related memory found that need satisfaction in networked memories predicted self-reported anxiety and negative emotions. However, this relationship was not observed in participants who experienced a high increase in heart rate. These findings suggest that high physiological arousal linked to a memory may limit access to other memory-related cognitions, thereby influencing the formation of subjective emotional experiences.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".