Stonnington, Cynthia M.

Objectives This study identified the prevalence of second victim experience (SVE) in a multidisciplinary sample of healthcare learners and explored personal experiences of trauma and desired forms of support following traumatic patient care events or situations. Method We used the validated SVE Support Tool-Revised and the Physician Well-Being Index (PWBI) to query healthcare learners at a large academic health system across the institution's medical, graduate medical education, and health sciences schools. The survey was open to all healthcare learners from April 8th, 2022 to May 30th, 2022. Here, we report on an analysis of respondents’ fixed responses describing the prevalence and characteristics of SVE. Results Of 2298 potential respondents, 206 answered at least one question (9.0% response rate). Of the 206 respondents, 205 answered questions inquiring if they had been a part of a stressful or traumatic patient care event or situation and 54.1% (111/205) answered in the affirmative. Of this group, 49.5% (51/103) reported feeling like a second victim (SV). The average PWBI of the exposed group was significantly higher (worse well-being) than the nonexposed group (3.4 vs 2.6, P = .0009). The most common forms of desired support for those exposed to a traumatic event and felt like an SV was conversation with peers 95.3% (41/43), family 81.4% (35/43), and a supervisor or manager 67.4% (29/43). Conclusion Findings suggest that many healthcare learners experience SVE and would benefit from connection to desired support strategies. Strategies to mitigate the impact of SVE on professional self-efficacy should be considered by education administrators. We present strategies from the literature and our institution that may be replicated for early identification and support of learners with SVE.

AbstractINTRODUCTIONWe previously demonstrated that single‐domain amnestic mild cognitive impairment (SDAm‐MCI) detected through longitudinal neuropsychological testing in our research cohort is less severe than in clinically incident symptomatic individuals. This study aims to replicate and expand this work using a National Alzheimer's Coordinating Center dataset.METHODSParticipants were classified into two groups: those enrolled with normal cognition (Normal Enrollees) and those enrolled with SDAm‐MCI (Amnestic Enrollees). Groups were compared at the time of diagnosis and on rates of cognitive decline post‐diagnosis.RESULTSAt SDAm‐MCI diagnosis, Normal Enrollees were 17% to 39% less impaired on memory tasks, after which the slope of change over time steepened compared to their pre‐symptomatic change and was steeper than in Amnestic Enrollees.DISCUSSIONIncident MCI detected through longitudinal neuropsychological testing is initially milder but may progress more steeply than in clinically established MCI. Sensitive assessment of cognitive decline is essential for capturing early changes that are more likely to be amenable to therapeutic treatment.Highlights Longitudinal cognitive evaluation detects symptomatic Alzheimer's disease earlier than mental status exams. At the time of diagnosis, converters were less impaired compared to initially symptomatic patients. Converters’ cognition declined more steeply than initially symptomatic patients. Sensitive cognitive tests are essential to capture early changes, given new disease‐modifying therapies.

Abstract Objective Our objectives were to examine cross‐sectional correlations of headache disability with measures of resilience, anxiety, and depression, and to determine if resilience modified the association between headache severity/frequency and disability. Background Resilience is associated with quality of life and functioning among patients with chronic conditions. We investigated whether resilience strongly mitigates headache‐related disability as measured by the Migraine Disability Assessment (MIDAS). Methods We prospectively recruited 160 patients with primary headache disorders seen in a tertiary headache medicine program between February 20, 2018 and August 2, 2019. Each participant completed the MIDAS, Conner Davidson Resilience Scale (CDRS‐25), Patient Health Questionnaire‐9 (PHQ‐9), Generalized Anxiety Disorder‐7 (GAD‐7), and WHO‐5 Well‐Being Index. Results The CDRS‐25 score was negatively correlated with the total MIDAS ( r = −0.21, p = 0.009), GAD‐7 ( r = −0.56, p < 0.001), and PHQ‐9 scores ( r = −0.34, p < 0.001). Well‐being inversely correlated with disability ( r = −0.37, p < 0.001). Increases in anxiety and depression increased the odds of disability. A 1 point increase in the CDRS‐25 score decreased the odds of being severely disabled by 4% (OR = 0.96, 95% CI: 0.94 to 0.99, p = 0.001). However, the CDRS‐25 score did not significantly moderate the association between headache days and disability. Conclusion Traits associated with resilience decreased the odds of severe disability from headaches, whereas anxiety, depression, and headache frequency were strongly associated with higher disability from headache.

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.

Abstract Background: Despite widespread efforts to create wellness programming in medical schools, there is a paucity of literature examining students’ perception of wellness and perceptions of these programs. With the inaugural class at the Arizona campus of Mayo Clinic Alix School of Medicine (MCASOM-AZ), an opportunity arose to establish an empirically evaluated wellness curriculum that most inclusively and effectively enables medical students to flourish for years to come. The initial wellness offerings included mental health, academic success, and disability services, curriculum-embedded seminars, wellness committee driven programming, and student-proposed wellness activities. We aimed to improve the relevance and impact of medical school wellness curricula by soliciting in-depth and longitudinal perspectives of medical students themselves. As MCASOM-AZ opened in 2017, the student body at the time of study consisted of first- and second-year medical students. Methods: Employing a mixed methods analysis of qualitative and longitudinal quantitative data,first- and second-year students at a MCASOM-AZ were invited to respond to an anonymous, online year-long survey (baseline, six months and 12 months) during the 2018-2019 academic year and participate in a structured, in-depth and in-person, peer-to-peer interview about their conceptions of wellness and the MCASOM-AZ wellness curriculum and resources. Qualitative data was coded for themes using thematic analysis strategies by independent raters. Results: Nearly half of eligible students completed the baseline survey,1/3 completed all 3 time-points, and 1/5 participated in an in-depth interview. Participant age, gender, and year of school were representative of the larger student body. Although individual conceptions varied, Wellness was consistently highly valued. Family, Academic Performance, and Friends emerged as most important to well-being across time-points. Academic work arose as the largest barrier to wellness. Analysis of qualitative data revealed five themes. Despite individual differences in approaches to wellness, wellbeing was interrelated to the learning environment; mandatory wellness efforts that didn’t address the medical culture met with skepticism.Conclusions: Interview responses provided understanding and context by which to interpret questionnaire responses. Academics was critical to students’ identity and wellness, while also the largest barrier. Suggested curricular improvements include restructuring academic work, seamlessly integrating wellness within coursework, and offering optional individualized approaches.

Although recent studies have explored the potential of multidomain brain health programs, there is a dearth of literature on operationalizing this research to create a clinical treatment program specifically for subjective cognitive decline (SCD). Patients seen by geriatricians in primary care and by behavioral neurology services at our institution presenting with SCD were recruited via a patient-appropriate flyer. After all participants had a 1-h brain health consultation with a neuropsychologist and were provided with program materials, they were randomized to attend a 10-week intervention designed to support program implementation (N = 10) or the control group of implementing the program on their own (N = 11). The program included (1) a calendar-based executive and memory support system for compensatory training and (2) training in healthy lifestyle. There were no significant differences between groups for any outcomes. Participants across both groups showed significant improvements with moderate effect sizes in compensatory strategy use, anxiety symptoms, and daily functioning, which were sustained through 6-month follow-up. They also increased physical activity by the end of the intervention period but did not sustain this through 6-month follow-up. Our pilot study demonstrates preliminary feasibility of a cognitive compensatory and lifestyle-based brain health program. Additional research is recommended to further develop two potentially scalable implementation strategies—coaching and self-implementation after brief consultation.