Risk for internalizing symptom development in young children: Roles of child parasympathetic reactivity and maternal depression and anxiety exposure in early life.

Intergenerational transmission of internalizing disorders (anxiety and depression) is well documented, but the responsible pathways are underspecified. One possible mechanism is via programming of the child's parasympathetic nervous system (PNS). For example, maternal depression and anxiety, via multiple pathways, may heighten child PNS reactivity, which has been linked to increased risk for internalizing disorders. Heightened PNS reactivity also may sensitize a child to their environment, increasing the vulnerability to developing psychopathology when exposed to stressors, such as maternal psychopathology. In a prospective longitudinal study of mother-child dyads (N = 446), we examined relations among maternal depression and anxiety symptoms when children were infants and aged 3 and 5 years, child respiratory sinus arrythmia (RSA) reactivity (measure of PNS reactivity) at 3 years, and child internalizing symptoms at age 5 years. Consistent with an adaptive calibration perspective, analyses tested the roles of child RSA reactivity as both a mediator and a moderator of associations between maternal and child symptoms. Greater child RSA reactivity in response to a fearful video predicted higher internalizing symptoms among children exposed to higher levels of maternal depression or anxiety symptoms at age 5 years (moderation effects). Child RSA reactivity did not mediate relations between maternal depression or anxiety symptoms in infancy and child internalizing symptoms at age 5 years. The results suggest that heightened PNS reactivity may represent a biological vulnerability to stressful environments early in life: When coupled with maternal depression or anxiety exposure, child PNS reactivity may promote the development of internalizing psychopathology in early childhood.

Trauma exposure and mental health outcomes among Central American and Mexican children held in immigration detention at the United States-Mexico border.

We explored the associations between early-life adversity and migration-related stress on the mental health of Central American and Mexican migrating children held in United States immigration detention facilities. Migrating children have high rates of trauma exposure prior to and during migration. Early-life adversity increases risk for developing mental health disorders. Forced separation of migrating children from their parents at the United States-Mexico border potentially exacerbates this risk. We sought to determine whether exposure to trauma prior to immigration and specific features of immigration detention were associated with posttraumatic stress symptomatology. We interviewed parents of 84 migrating children (ages 1-17) after families were released from immigration detention facilities to assess children's migration- and detention-related experiences. A modified version of the University of California Los Angeles Posttraumatic Stress Disorder (PTSD) Reaction Index was administered to assess children's PTSD symptoms and document trauma exposure. A total of 97.4% of children experienced at least one premigration traumatic event. PTSD symptom severity was most strongly predicted by premigration trauma and duration of parent-child separation. This study contributes to a growing empirical literature documenting that early-life adversity increases risk of developing mental health disorders, particularly following additional stress exposure, and that remaining with parents during immigration detention may help mitigate children's stress response.

The Role of Large Language Models in Medical Education: Applications and Implications.

Large language models (LLMs) such as ChatGPT have sparked extensive discourse within the medical education community, spurring both excitement and apprehension. Written from the perspective of medical students, this editorial offers insights gleaned through immersive interactions with ChatGPT, contextualized by ongoing research into the imminent role of LLMs in health care. Three distinct positive use cases for ChatGPT were identified: facilitating differential diagnosis brainstorming, providing interactive practice cases, and aiding in multiple-choice question review. These use cases can effectively help students learn foundational medical knowledge during the preclinical curriculum while reinforcing the learning of core Entrustable Professional Activities. Simultaneously, we highlight key limitations of LLMs in medical education, including their insufficient ability to teach the integration of contextual and external information, comprehend sensory and nonverbal cues, cultivate rapport and interpersonal interaction, and align with overarching medical education and patient care goals. Through interacting with LLMs to augment learning during medical school, students can gain an understanding of their strengths and weaknesses. This understanding will be pivotal as we navigate a health care landscape increasingly intertwined with LLMs and artificial intelligence.