Objective: Prominent theories of Neuroticism emphasize its potential link to threator punishment-sensitivity processes. Even in the absence of external threats, though, Neuroticism may predispose people to a sort of "mental noise," or cognitive instabil ity, that creates problems for ongoing efforts after control. If this is the case, cogni tive views of Neuroticism might be needed to complement the primarily emotion-related views that currently exist. Method: In a four study program of research (total N = 541), momentary forms of monitoring and control were assessed using variants of a continuous tracking task. Results: As hypothesized, the dimension of Neuroticism was consistently linked to performance deficits, regardless of whether aversive sounds were present or not (Studies 1-3), and the relevant deficits also predicted daily levels of negative affect (Study 4). Conclusions:The results support the idea that momentary self-regulation is noisier in the context of higher levels of Neuroticism. K E Y W O R D S control, mental noise, monitoring, Neuroticism, self-regulation 1222 | KLEIN aNd ROBINSON

Introduction Online social networking data (SN) is a contextually and temporally rich data stream that has shown promise in the prediction of suicidal thought and behavior. Despite the clear advantages of this digital medium, predictive modeling of acute suicidal ideation (SI) currently remains underdeveloped. SN data, in conjunction with robust machine learning algorithms, may offer a promising way forward. Methods We applied an ensemble machine learning model on a previously published dataset of adolescents on Instagram with a prior history of lifetime SI ( N = 52) to predict SI within the past month. Using predictors that capture language use and activity within this SN, we evaluated the performance of our out-of-sample, cross-validated model against previous efforts and leveraged a model explainer to further probe relative predictor importance and subject-level phenomenology. Results Linguistic and SN data predicted acute SI with an accuracy of 0.702 (sensitivity = 0.769, specificity = 0.654, AUC = 0.775). Model introspection showed a higher proportion of SN-derived predictors with substantial impact on prediction compared with linguistic predictors from structured interviews. Further analysis of subject-specific predictor importance uncovered potentially informative trends for future acute SI risk prediction. Conclusion Application of ensemble learning methodologies to SN data for the prediction of acute SI may mitigate the complexities and modeling challenges of SI that exist within these time scales. Future work is needed on larger, more heterogeneous populations to fine-tune digital biomarkers and more robustly test external validity.

Following biological and comparative perspectives, it was posited that acute stressors would activate more primitive modes of action control favoring gross motor actions (e.g., fight or flight) over behavioral precision. Influences of this type should result in more rapid changes in movement velocity subsequent to emotionally upsetting stimulation. In investigating processes of this type, participants in three experiments (total N = 457) were asked to track a moving visual target as smoothly as possible. The introduction of brief, aversive noise blasts was found to destabilize such efforts. In particular, time-locked analyses revealed the presence of an emotion-related increase in tremor that began quickly and persisted for nearly 2 s. In addition, the persistence component was elevated in the context of higher levels of neuroticism (Experiment 2) and emotional reactivity (Experiment 3). The results speak to questions about the emotion-action interface using a method suited to affective chronometry.

According to psychological flexibility theory, fully experiencing one's emotions, even when they involve negative reactions, can enhance psychological well-being. In pursuit of this possibility, procedures capable of disentangling reaction intensities from reaction durations, in response to affective images, were developed and variations of this paradigm were applied in understanding variations in happiness and adaptive behavior. Consistent with psychological flexibility theory, three studies showed that more intense emotional reactions, irrespective of valence, were associated with higher levels of wellbeing. Two additional studies showed that happy individuals, relative to less happy individuals, exhibited more functional approach/avoidance behavior in behavior-focused tasks. Together, the results are consistent with the idea that adaptive emotion generation systems are those that flexibly adapt emotion output to concurrent emotion-related stimulation. The program of research adds to our understanding of the relationship between emotion reactivity and well-being while highlighting specific processes through which emotion and well-being interact.

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