Daily Negative Affect and Reaction Time Inconsistency in Emerging Adults: Ecological Momentary Assessment Study
Bibliographic record
Abstract
Abstract Background Anxiety and mood disorders, characterized by elevated negative affect (NA) and cognitive impairments, are highly prevalent among college students. Within-person (WP) NA variability, which captures moment-to-moment fluctuations in NA, provides unique insights into emotional processes that are not reflected in mean NA levels. Cognitive variability, particularly reaction time (RT) inconsistency, is increasingly recognized as a sensitive marker of cognitive health and functional integrity. Although prior research links NA to cognitive variability, the short-term dynamics of these associations in naturalistic settings remain understudied. College students provide an ideal population for examining these dynamics using ecological momentary assessment (EMA). Objective This study investigated the association between WP NA and RT inconsistency, hypothesizing that higher WP fluctuations in NA would predict increased RT inconsistency. We also examined the moderating roles of practice effects and covariates, including neuroticism, insomnia, and sex. Methods Using EMA, 99 university students completed morning and evening assessments over 14 days, including a cognitive task measuring RT inconsistency (standard deviation in trial-level RT) and self-reported NA. Multilevel modeling was used to assess WP fluctuations in NA and their impact on RT inconsistency, accounting for time (session number), between-person differences in NA, and covariates such as sleep problems, neuroticism, age, sex, and use of a touch device. Results WP fluctuations in NA significantly predicted increased RT inconsistency (exp(β)=1.022, 95% CI 1.008‐1.037; P =.007), supporting the hypothesis that NA variability disrupts cognitive performance. Male students exhibited lower RT inconsistency than female students, with a small effect size (exp(β)=0.824, 95% CI 0.694‐0.977; P =.049). Finally, EMA sessions were inversely associated with RT inconsistency, with a stronger effect up to session 3 (exp(β)=0.930, 95% CI 0.879‐0.985; P =.03) than after session 3 (exp(β)=0.986, 95% CI=0.979‐0.992; P <.001), indicating practice effects. Conclusions Momentary fluctuations in NA influence cognitive variability, particularly in the early stages of repeated cognitive tasks, underscoring the role of emotional processes in cognitive performance. Practice effects and individual differences, such as sex and insomnia, influence these associations. These findings highlight the use of EMA for understanding cognitive-affective processes and suggest potential intervention targets, such as addressing NA, to improve cognitive functioning in emotionally vulnerable populations like college students.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".