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The National Academies of Science stresses the importance of research mentoring. We assessed the internal consistency and application of a novel 33 item mentor evaluation survey and explored differences across subgroups. The survey was administered annually to mentees. The response rate was 17.8% for a sample of 710 respondents. The survey exhibited strong internal validity with Cronbach Alpha > 0.89 for each subscale. Overall scores across the three domains were high. Basic Science trainees scored their mentor significantly lower than those in Translational or Clinical Science across domains (0.11-0.25 points). Underrepresented Racial Ethnic Groups (UREG) trainee scores were significantly lower in academic guidance and personal communication. Women had lower scores in 4 out of 5 domains. The survey is a modified instrument to assess mentee experience, although further validation against mentee outcomes is needed.
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Background: Multimorbidity research has focused on the prevalence and consequences of multimorbidity in older populations. Less is known about the accumulation of chronic conditions earlier in the life course. Methods: We identified patterns of longitudinal multimorbidity accumulation using 30 years of data from in-person exams, annual follow-ups, and adjudicated end-points among 4,945 participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Chronic conditions included arthritis, asthma, atrial fibrillation, cancer, end stage renal disease, chronic obstructive pulmonary disease, coronary heart disease, diabetes, heart failure, hyperlipidemia, hypertension, and stroke. Trajectory patterns were identified using latent class growth curve models. Results: Mean age (SD) at baseline (1985-6) was 24.9 (3.6), 55% were female, and 51% were Black. The median follow-up was 30 years (interquartile range 25-30). We identified six trajectory classes characterized by when conditions began to accumulate and the rapidity of accumulation: (1) early-fifties, slow, (2) mid-forties, fast, (3) mid-thirties, fast, (4) late-twenties, slow, (5) mid-twenties, slow, and (6) mid-twenties, fast. Compared with participants in the early-fifties, slow trajectory class, participants in mid-twenties, fast were more likely to be female, Black, and currently smoking and had a higher baseline mean waist circumference (83.6 vs. 75.6 cm) and BMI (27.0 vs. 23.4 kg/m2) and lower baseline physical activity (414.1 vs. 442.4 exercise units). Conclusions: A life course approach that recognizes the heterogeneity in patterns of accumulation of chronic conditions from early adulthood into middle age could be helpful for identifying high risk subgroups and developing approaches to delay multimorbidity progression.
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BACKGROUND: Central nervous system (CNS) medication use is common among older adults, yet the impact of hospitalizations on use remains unclear. This study details CNS medication use, discontinuations, and user profiles during hospitalization periods. METHODS: Retrospective cohort study using electronic health records on patients ≥65 years, from three hospitals (2018-2020), and prescribed a CNS medication around hospitalization (90 days prior to 90 days after). Latent class transitions analysis (LCTA) examined profiles of CNS medication class users across four time points (90 days prior, admission, discharge, 90 days after hospitalization). RESULTS: Among 4666 patients (mean age 74.3 ± 9.3 years; 63% female; 70% White; mean length of stay 4.6 ± 5.6 days (median 3.0 [2.0, 6.0]), the most commonly prescribed CNS medications were antidepressants (56%) and opioids (49%). Overall, 74% (n = 3446) of patients were persistent users of a CNS medication across all four time points; 7% (n = 388) had discontinuations during hospitalization, but of these, 64% (216/388) had new starts or restarts within 90 days after hospitalization. LCTA identified three profile groups: (1) low CNS medication users, 54%-60% of patients; (2) mental health medication users, 30%-36%; and (3) acute/chronic pain medication users, 9%-10%. Probability of staying in same group across the four time points was high (0.88-1.00). Transitioning to the low CNS medication use group was highest from admission to discharge (probability of 9% for pain medication users, 5% for mental health medication users). Female gender increased (OR 2.4, 95% CI 1.3-4.3), while chronic kidney disease lowered (OR 0.5, 0.2-0.9) the odds of transitioning to the low CNS medication use profile between admission and discharge. CONCLUSIONS: CNS medication use stays consistent around hospitalization, with discontinuation more likely between admission and discharge, especially among pain medication users. Further research on patient outcomes is needed to understand the benefits and harms of hospital deprescribing, particularly for medications requiring gradual tapering.