Polymorphisms in the oxytocin receptor gene, OXTR_rs53576, have been linked to differences in maternal sensitivity and depressive symptoms. Although some studies suggest the A allele confers risk for mood disorders, individuals homozygous for the G allele may exhibit greater sensitivity to both positive and negative social experiences, including in the mother-infant dyad. Given the bi-directional nature of mother-infant influences on maternal mood, we tested the association between both mothers' and infants' OXTR_rs53576 genotype and maternal depression, as assessed through a self-report inventory. Although Beck Depression Inventory (BDI-II) scores were significantly higher for GG in comparison to AG/AA mothers, and for mothers of GG in comparison to AG/AA infants, an ANCOVA revealed that after sociodemographic risk factors had been controlled, infants', but not mothers', OXTR genotype predicted maternal depression scores, with no significant interaction between the two. The effect of infant OXTR on maternal depression was not explained by maternal reports of difficult infant temperament. We propose that GG infants have an enhanced capacity for processing both positive and negative socially meaningful contextual information, first amplifying and then differentially perpetuating negative affectivity in mothers who exhibit depressive characteristics. K E Y W O R D Sinfant temperament, mood disorders, oxytocin receptor gene, postpartum depression | 497 ASHERIN Et Al.

In this article, we review the potential for adverse impacts on the clinician following a medical error or poor clinical outcome. Second victim syndrome, its symptoms, risk factors, natural history, and possible outcomes are described. We also discuss the important role of organizational leadership and culture and highlight possible programmatic interventions designed to support clinicians following an adverse event.

Accurate postpartum depression screening measures are needed to identify mothers with depressive symptoms both in the postpartum period and beyond. Because it had not been tested beyond the immediate postpartum period, the reliability and validity of the Postpartum Depression Screening Scale (PDSS) and its sensitivity, specificity, and predictive value for diagnoses of major depressive disorder (MDD) were assessed in a diverse community sample of 238 mothers of 4- to 15-month-old infants. Mothers (N = 238; M age = 30.2, SD = 5.3) attended a lab session and completed the PDSS, the Beck Depression Inventory-II (BDI-II), and a structured clinical interview (SCID) to diagnose MDD. The reliability, validity, specificity, sensitivity, and predictive value of the PDSS to identify maternal depression were assessed. Confirmatory factor analysis supported the construct validity of five but not seven content subscales. The PDSS total and subscale scores demonstrated acceptable to high reliability (α = 0.68-0.95). Discriminant function analysis showed the scale correctly provided diagnostic classification at a rate higher than chance alone. Sensitivity and specificity for major depressive disorder (MDD) diagnosis were good and comparable to those of the BDI-II. Even in mothers who were somewhat more diverse and had older infants than those in the original normative study, the PDSS appears to be a psychometrically sound screener for identifying depressed mothers in the 15 months after childbirth.

Face preferences for speakers of infant-directed and adult-directed speech (IDS and ADS) were investigated in 4- to 13.5-month-old infants of depressed and non-depressed mothers. Following 1-min of exposure to an ID or AD speaker (order counterbalanced), infants had an immediate paired-comparison test with a still, silent image of the familiarized versus a novel face. In the test phase, ID face preference ratios were significantly lower in infants of depressed than non-depressed mothers. Infants' ID face preference ratios, but not AD face preference ratios, correlated with their percentile scores on the cognitive () scale of the Bayley Scales of Infant & Toddler Development (3 Edition; BSID III), assessed concurrently. Regression analyses revealed that infant ID face preferences significantly predicted infant percentiles even after demographic risk factors and maternal depression had been controlled. Infants may use IDS to select social partners who are likely to support and facilitate cognitive development.

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Background: Most youth with type 1 diabetes (T1D) do not meet current ADA recommendations for A1C, thus, it is important to identify at diagnosis, those at-risk for later suboptimal glycemic control (A1C ≥9.5%) and complications. Methods: The Risk Index for Poor Glycemic Control (RI-PGC) was administered to 266 parents during children’s (ages <1-19 years) routine new onset T1D visit. The RI-PGC provides a single score (range = 0-9, higher scores = higher risk) based on psychosocial factors (e.g., insurance, child mood, parent stress/anxiety) to classify risk as “Low,” “Moderate,” or “High” in the 1-4 years after diagnosis. Demographic data and DKA occurrence at diagnosis were also collected. Results: Of 266 children with new onset T1D (Mage 9.98 ± 4.42 years; 52% male; 68% Caucasian), 18.8% and 28.6% were Moderate and High Risk, respectively. DKA at onset (n=157; 59%) was significantly correlated with risk score (r=0.888, p<0.001). Children in DKA at onset were more than twice as likely to score high on RI-PGC (p=0.009; Table). Conclusions: We use the RI-PGC in a prevention program to identify risk of future suboptimal glycemic control. These results are consistent with the only other study (Schwartz et al., 2014) to examine risk-most children were Low Risk and more children were High Risk than Moderate Risk. Presence of DKA at onset may be another predictor of future suboptimal glycemic control, DKA episodes, and complications. Risk Classification at T1D New Onset for Later ComplicationsRI-PGC Risk Category (n; %)LowModerateHighDKA at Onset75 (54%)26 (52%)56 (74%)No DKA at Onset65 (46%)24 (48%)20 (26%) Disclosure S. Majidi: None. J.M. Vogeli: None. K.A. Driscoll: None.

The shocking statistic that the United States (US) loses one physician per day to suicide equates to 300-400 doctors dying each yearthe equivalent of an entire medical school class. 1 Among physicians, long-term exhaustion and chronic occupational stress often result in burnout, which in turn can lead to adverse consequences to patients, themselves, and their families. This occupational hazard has implications for the entire healthcare system and society. One approach to addressing physician burnout is to offer a formal curriculum that emphasizes strategies for well-being. Over the last few years, physician burnout and healthcare provider well-being have been recognized as issues that transcend specialty and have the ability to negatively impact personal and professional lives. Leading healthcare organizations have defined physician burnout as a public health crisis. 2 Physicians and healthcare workers were in crisis prior to the global pandemic of COVID-19, but now more than ever, physicians, trainees, and healthcare workers are under enormous amounts of stress as they deal with nearly constant change and chronic uncertainty. Well-being initiatives, programming, and access to support for all medical professionals are of paramount importance. Medicine is a career choice that impacts the entire course of one's life. Physicians are gifted with the knowledge and skills to help people in the most critical and vulnerable moments of their lives. However, the impact of continually witnessing death, dying, and suffering can overstress even the most stoic individuals. Therefore, we must educate our physicians on compassion fatigue, mitigate its effect on healthcare workers, and train physicians to recognize burnout in themselves and colleagues. Over the past 20 years, a great deal has been written about physician burnout, with a growing interest in best practices to prevent burnout among medical students and residents. A 2004 meta-analysis of studies on resident burnout concluded that burnout levels were high among residents, but that more robust research on the topic was needed. 3 Shana felt et al, 4 who conducted longitudinal (2011, 2014, 2017) surveys of US physicians that focused on burnout and work-life integration,

Objective: To examine demographic and mental health diagnostic characteristics for individuals with type 1 diabetes (T1D) and current mental health diagnoses. Methods: The medical records of 397 individuals ages 10-25 with T1D (mean age = 15.3±3.1 years, mean T1D duration = 6.0±4.5 years) who were screened during routine T1D clinic visits for depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9) were reviewed for current DSM-5 diagnoses, demographic information, and T1D management data. Results: Of those screened, 29% had a mental health diagnosis; 56% had 1 diagnosis, 26% had 2, and 18% had 3+. The most common diagnoses were depression (16% of total screened), anxiety (15%), and attention-deficit/hyperactivity disorder (10%). Other diagnoses included mood, learning, and eating disorders. Those with a mental health diagnosis were slightly older and they had higher PHQ-9 scores and higher HbA1c (Table). Sex, race, insulin regimen, continuous glucose monitor use, T1D duration, and insurance were not significantly different. Conclusions: Mental health diagnoses are common in adolescents and young adults with T1D. Those with mental health conditions may experience greater difficulties in T1D management, contributing to higher HbA1c. There is a need to develop tailored interventions to improve T1D management when specific mental health conditions are present. Differences in Characteristics between T1D youth with and without a Mental Health Diagnosis.Mental Health Diagnosis (n=116)No Mental Health Diagnosis (n=281)p-valueAge (years)15.8±2.915.0±3.20.023PHQ-9 Score7.5±6.43.8±4.3<0.001A1C9.88±2.59.17±2.10.004 Disclosure K.R. Stanek: None. S. Majidi: None. E.M. Youngkin: None. J.M. Vogeli: None. K.A. Driscoll: None.