Social capital plays a key role in college and career success, and research indicates that a dearth of on-campus connections contributes to challenges first-generation college students face in effectively navigating the college environment. This study investigates a novel intervention that focuses on the development of skills and attitudes to empower first-generation college students to cultivate social capital and on-campus connections during the transition to college. A mixed methods, explanatory design was used to evaluate impacts and processes of the intervention among first-generation college students (n = 164) in the context of an ethnically diverse, urban, public university in the Northeast. Results indicated that students who participated in the intervention demonstrated improved attitudes and behaviors around seeking support in college, closer relationships with instructors, and higher GPAs at the end of their first year in college. These results suggest the potential benefits of a relatively scalable approach to supporting the needs of first-generation college students.

A growing body of research has documented the phenomenon of climate change anxiety (CCA), defined broadly as negative cognitive, emotional, and behavioral responses associated with concerns about climate change. A recently validated scale of CCA indicated two subscales: cognitive emotional impairment and functional impairment (Clayton & Karazsia, 2020). However, there are few empirical studies on CCA to date and little evidence regarding whether CCA is associated with psychiatric symptoms, including symptoms of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD), and whether engaging in individual and collective action to address climate change could buffer such relationships. This mixed methods study draws on data collected from a sample of emerging adult students (ages 18–35) in the United States ( N = 284) to address these gaps. Results indicated that both CCA subscales were significantly associated with GAD symptoms, while only the Functional Impairment subscale was associated with higher MDD symptoms. Moreover, engaging in collective action, but not individual action, significantly attenuated the association between CCA cognitive emotional impairment and MDD symptoms. Responses to open-ended questions asking about participants’ worries and actions related to climate change indicated the severity of their worries and, for some, a perception of the insignificance of their actions relative to the enormity of climate change. These results further the field’s understanding of CCA, both in general and specifically among emerging adults, and suggest the importance of creating opportunities for collective action to build sense of agency in addressing climate change.

In the past decade, brief bursts of fast oscillations in the ripple range have been identified in the scalp EEG as a promising non-invasive biomarker for epilepsy. However, investigation and clinical application of this biomarker have been limited because standard approaches to identify these brief, low amplitude events are difficult, time consuming, and subjective. Recent studies have demonstrated that ripples co-occurring with epileptiform discharges (‘spike ripple events’) are easier to detect than ripples alone and have greater pathological significance. Here, we used objective techniques to quantify spike ripples and test whether this biomarker predicts seizure risk in childhood epilepsy. We evaluated spike ripples in scalp EEG recordings from a prospective cohort of children with a self-limited epilepsy syndrome, benign epilepsy with centrotemporal spikes, and healthy control children. We compared the rate of spike ripples between children with epilepsy and healthy controls, and between children with epilepsy during periods of active disease (active, within 1 year of seizure) and after a period of sustained seizure-freedom (seizure-free, >1 year without seizure), using semi-automated and automated detection techniques. Spike ripple rate was higher in subjects with active epilepsy compared to healthy controls (P = 0.0018) or subjects with epilepsy who were seizure-free ON or OFF medication (P = 0.0018). Among epilepsy subjects with spike ripples, each month seizure-free decreased the odds of a spike ripple by a factor of 0.66 [95% confidence interval (0.47, 0.91), P = 0.021]. Comparing the diagnostic accuracy of the presence of at least one spike ripple versus a classic spike event to identify group, we found comparable sensitivity and negative predictive value, but greater specificity and positive predictive value of spike ripples compared to spikes (P = 0.016 and P = 0.006, respectively). We found qualitatively consistent results using a fully automated spike ripple detector, including comparison with an automated spike detector. We conclude that scalp spike ripple events identify disease and track with seizure risk in this epilepsy population, using both semi-automated and fully automated detection methods, and that this biomarker outperforms analysis of spikes alone in categorizing seizure risk. These data provide evidence that spike ripples are a specific non-invasive biomarker for seizure risk in benign epilepsy with centrotemporal spikes and support future work to evaluate the utility of this biomarker to guide medication trials and tapers in these children and predict seizure risk in other at-risk populations.

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