Relationship Between Valence and Arousal for Subjective Experience in a Real-life Setting for Supportive Housing Residents: Results From an Ecological Momentary Assessment Study
Bibliographic record
Abstract
BACKGROUND: The circumplex model of affect posits that valence and arousal are the principal dimensions of affect. The center of the 2D space represents a neutral state of valence and a medium state of arousal. The role of valence and arousal in human emotion has been studied extensively. However, no consistent relationship between valence and arousal has been established. Most of the prior studies investigating the relationship have been conducted in relatively controlled laboratory settings. OBJECTIVE: Ecological momentary assessment (EMA) of affect from participants residing in permanent supportive housing was used to study the relationship between valence and arousal in real-life settings. The goal of this study was to explore the relationship between valence and arousal in a person's natural environment. METHODS: Participants were recruited from housing agencies in Fort Worth, Texas, United States. All participants had a history of chronic homelessness and reported at least one mental health condition. A subset of participants completed daily (morning) EMAs of emotions and other behaviors. The sample comprised 78 women and 77 men, and the average age was 52 (SD 8) years. From the circumplex model of affect, the EMA included 9 questions related to the participant's current emotional state (happy, frustrated, sad, worried, restless, excited, calm, bored, and sluggish). The responses were used to calculate 2 composite scores for valence and arousal. RESULTS: Statistical models uniformly showed a dominant linear relation between valence and arousal and a significant difference in the slopes among races. None of the other effects were statistically significant. Compared with previous studies, the effects were quite robust. CONCLUSIONS: Our findings may provide a window to the fundamental structure of affect. We found a strong positive linear relationship between valence and arousal at the nomothetic level, which may provide insight into a universal structure of affect. However, the study needs to be replicated for different populations to determine whether our findings can be generalized beyond the population studied here.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".