A growing body of research suggests that the functionality of coping strategies may in part depend on the context in which they are executed. Thus far, functionality has mostly been defined through the associations of coping strategies with psychopathology, particularly depression. Whether associations of coping strategies with proxies for happiness such as subjective well-being (SWB) are simply inverse remains to be shown. A total of n = 836 individuals from the U. S. general population participated in an online survey that included a revised version of the Maladaptive and Adaptive Coping Styles Questionnaire (MAX-R) that incorporates context-specific items, the Scale of Positive and Negative Affect (SPANE), the Temporal Satisfaction with Life Scale (TSWLS), the Patient Health Questionnaire (PHQ-9), and the Web Screening Questionnaire (WSQ). The MAX-R was submitted to an exploratory factor analysis. The factor analysis of the MAX-R yielded four subscales: adaptive, maladaptive, avoidance, and expressive suppression coping. Similar strategies in different contexts at times loaded on the same (e.g., maladaptive) or different (e.g., adaptive and avoidance) dimensions. Hierarchical multiple linear regression revealed significant associations of adaptive coping with SPANE (ß = 0.21), TSWLS (ß = 0.03), and PHQ-9 (ß = 0.07), all ps < .001, of maladaptive coping with SPANE (ß = − 0.19), TSWLS (ß = − 0.10), and PHQ-9 (ß = 0.02), all ps < .01, of avoidance with PHQ-9 (ß = 0.01, p < .001), and of expressive suppression with SPANE (ß = − 0.06) and TSWLS (ß = − 0.16), ps < .005. Final models explained 64.6% of variance in SPANE, 41.8% of variance in TSWLS, and 55% of variance in PHQ-9 score. In some instances, the functionality of coping strategies appears to be impacted by contextual factors. When investigating the overall benefit of use versus nonuse of coping strategies, their association with psychopathology measures and with subjective well-being should both be considered.

Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level. Using multichannel whole-head high density functional near-infrared spectroscopy (fNIRS) brain activation measurements, we aimed to predict driving difficulty level, both separate for each WML level and with a combined model. Participants drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. In half of the time, the course led through a construction site with reduced lane width, increasing visuospatial attentional demands. Concurrently, participants performed a modified version of the n-back task with five different WML levels (from 0-back up to 4-back), forcing them to continuously update, memorize, and recall the sequence of the previous ‘n’ speed signs and adjust their speed accordingly. Using multivariate logistic ridge regression, we were able to correctly predict driving difficulty in 75.0% of the signal samples (1.955 Hz sampling rate) across 15 participants in an out-of-sample cross-validation of classifiers trained on fNIRS data separately for each WML level. There was a significant effect of the WML level on the driving difficulty prediction accuracies [range 62.2–87.1%; χ²(4) = 19.9, p < 0.001, Kruskal–Wallis H test] with highest prediction rates at intermediate WML levels. On the contrary, training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46.8%). Activation changes in the bilateral dorsal frontal (putative BA46), bilateral inferior parietal (putative BA39), and left superior parietal (putative BA7) areas were most predictive to increased driving difficulty. These discriminative patterns diminished at higher WML levels indicating that visuospatial attentional demands and WML involve interacting underlying brain processes. The changing pattern of driving difficulty related brain areas across WML levels could indicate potential changes in the multitasking strategy with level of WML demand, in line with the multiple resource theory.

Background: Prevalence estimates for body-focused repetitive behaviors (BFRBs) such as trichotillomania differ greatly across studies owing to several confounding factors (e.g. different criteria). For the present study, we recruited a diverse online sample to provide estimates for nine subtypes of BFRBs and body-focused repetitive disorders (BFRDs).Methods: The final sample comprised 1481 individuals from the general population. Several precautions were taken to recruit a diverse sample and to exclude participants with low reliability. We matched participants on gender, race, education and age range to allow unbiased interpretation.Results: While almost all participants acknowledged at least one BFRB in their lifetime (97.1%), the rate for BFRDs was 24%. Nail biting (11.4%), dermatophagia (8.7%), skin picking (8.2%), and lip-cheek biting (7.9%) were the most frequent BFRDs. Whereas men showed more lifetime BFRBs, the rate of BFRDs was higher in women than in men. Rates of BFRDs were low in older participants, especially after the age of 40. Overall, BFRBs and BFRDs were more prevalent in White than in non-White individuals. Education did not show a strong association with BFRB/BFRDs.Discussion: BFRBs are ubiquitous. More severe forms, BFRDs, manifest in approximately one out of four people. In view of the often-irreversible somatic sequelae (e.g. scars) BFRBs/BFRDs deserve greater diagnostic and therapeutic attention by clinicians working in both psychology/psychiatry and somatic medicine (especially dermatology and dentistry).