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UC San Francisco Previously Published Works

Cover page of Managing expansions in medical students' clinical placements caused by curricular transformation: perspectives from four medical schools.

Managing expansions in medical students' clinical placements caused by curricular transformation: perspectives from four medical schools.

(2021)

Many challenges could occur that result in the need to handle an increase in the number of medical student clinical placements, such as curricular transformations or viral pandemics, such as COVID 19. Here, we describe four different institutions' approaches to addressing the impact of curricular transformation on clerkships using an implementation science lens. Specifically, we explore four different approaches to managing the 'bulge' as classes overlap in clerkships Curriculum leaders at four medical schools report on managing the bulge of core clinical placements resulting from reducing the duration of the foundational sciences curriculum and calendar shifts for the respective clerkship curriculum. These changes, which occurred between 2014 and 2018, led to more students being enrolled in core clinical rotations at the same time than occurred previously. Schools provided respective metrics used to evaluate the effectiveness of their bulge management technique. These data typically included number of students affected in each phase of their curricular transformation, performance on standardized examinations, and student and faculty feedback. Not all data were available from all schools, as some schools are still working through their 'bulge' or are affected by COVID-19. There is much to be learned about managing curricular transformations. Working on such endeavors in a learning collaborative such as the AMA Accelerating Change in Medical Education Initiative provided support and insights about how to survive, thrive and identifying lessons learned during curricular transformation.

Cover page of Differences in objectively measured daily physical activity patterns related to depressive symptoms in community dwelling women - mPED trial.

Differences in objectively measured daily physical activity patterns related to depressive symptoms in community dwelling women - mPED trial.

(2021)

Physical activity (PA) is an effective depression treatment. However, knowledge on how variation in day-to-day PA relates to depression in women is lacking. The purposes of this study were to 1) compare overall objectively measured baseline daily steps and duration of moderate to vigorous PA (MVPA) and 2) examine differences in steps and MVPA on days of the week between women aged 25-65 years, who were physically inactive, with high and low depressive symptoms, enrolled in a run-in period of the mobile phone based physical activity education (mPED) trial. The Center for Epidemiological Studies Depression Scale was used to categorize low/high depressive symptom groups. We used linear mixed-effects models to examine the associations between steps and MVPA and depression-status overall and by day of the week, adjusting for selected demographic variables and their interactions with day of the week. 274 women were included in the final analysis, of which 58 had high depressive symptoms. Overall physical activity levels did not differ. However, day of the week modified the associations of depression with MVPA (p = 0.015) and daily steps (p = 0.08). Women with high depression were characterized by reduced activity at the end of the week (Posthoc: Friday: 791 fewer steps, 95% CI: 73-1509, p = 0.03; 8.8 lower MVPA, 95% CI: 2.16-15.5, p = 0.0098) compared to women with low depression, who showed increased activity. Day of the week might be an important target for personalization of physical activity interventions. Future work should evaluate potential causes of daily activity alterations in depression in women.

Cover page of Primary nonadherence to statin medications: Survey of patient perspectives.

Primary nonadherence to statin medications: Survey of patient perspectives.

(2021)

Statin medications reduce cardiovascular events, but many patients never start taking their prescribed statin (primary nonadherence). Limited knowledge exists about the attitudes and beliefs of those with primary nonadherence. In this study, patients with primary nonadherence to statin medications (n = 173) completed a self-administered cross-sectional survey that assessed their attitudes and beliefs related to primary nonadherence and to potential motivators for statin use. Patients were recruited in 2019 from two academic health systems and nationwide internet advertisements. Only 49 of 173 (28.3%) patients with primary nonadherence reported having cardiovascular disease (CVD). Ninety-nine patients (57.2%) never filled their prescription, and 74 (42.8%) filled but never took any statin. Over half failed to initially inform their prescriber they might not take the statin. Patients strongly or somewhat agreed that they desired alternate treatment plans such as diet and/or exercise (n = 134; 77.4%) or natural remedies/dietary supplements (n = 125; 72.3%). Ninety-eight (56.6%) stronglyor somewhat worried about the possibility of statin dependence or addiction. Twenty-seven (15.6%) patients noted that they would not take a statin based solely on CVD risk estimates; 50 (28.9%) selected a CVD risk threshold of >20%; and 23 (13.3%) a threshold of >50% as motivating factors to take statins. Patients with primary nonadherence have attitudes about taking statins based on CVD risk that differ from scientific recommendations, may not tell providers about their hesitation to take statins, and likely prefer alternative initial approaches to cholesterol lowering. Early shared decision-making and assessment of patient attitudes about statins could potentially better align initial approaches for CVD risk reduction.

Cover page of Novel RT-ddPCR assays for simultaneous quantification of multiple noncoding and coding regions of SARS-CoV-2 RNA.

Novel RT-ddPCR assays for simultaneous quantification of multiple noncoding and coding regions of SARS-CoV-2 RNA.

(2021)

A hallmark of coronavirus transcription is the generation of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and an array of subgenomic mRNAs (sgRNAs) encompassing sequences arising from discontinuous transcription. Existing PCR-based diagnostic assays for SAR-CoV-2 are qualitative or semi-quantitative and do not provide the resolution needed to assess the complex transcription dynamics of SARS-CoV-2 over the course of infection. We developed and validated a novel panel of sensitive, quantitative RT-ddPCR assays designed to target regions spanning the genome of SARS-CoV-2. Our assays target untranslated regions (5', 3') as well as different coding regions, including non-structural genes that are only found in full length (genomic) RNA and structural genes that are found in genomic as well as different subgenomic RNAs. Application of these assays to clinically relevant samples will enhance our understanding of SARS-CoV-2 gene expression and may also inform the development of improved diagnostic tools and therapeutics.

Accuracy of Primary Care Medical Home Designation in a Specialty Mental Health Clinic.

(2021)

To assess whether primary care medical homes (PCMHs) are accurately identified for patients receiving care in a specialty mental health clinic within an integrated public delivery system. This study reviewed the electronic records of patients in a large urban mental health clinic. The study defined 'matching PCMH' if the same primary care clinic was listed in both the mental health and medical electronic records. This study designated all others as 'PCMH unknown.' This study assessed whether demographic factors predicted PCMH status using chi-square tests. Among 229 patients (66% male; mean age 49; 36% White, 30% Black, and 17% Asian), 72% had a matching PCMH. Sex, age, race, psychiatric diagnosis, and psychotropic medication use were not associated with matching PCMH. To improve care coordination and health outcomes for people with severe mental illness, greater efforts are needed to ensure the accurate designation of PCMHs in all mental health patient electronic records.

Cover page of A model of nurses' intention to care of patients with COVID-19: Mediating roles of job satisfaction and organisational commitment.

A model of nurses' intention to care of patients with COVID-19: Mediating roles of job satisfaction and organisational commitment.

(2021)

Aim and objectives

This study aims to test the hypothesis that job satisfaction and organisational commitment might play a mediating roles between workload, quality of supervision, extra-role behaviour, pay satisfaction and intention to care of patients with COVID-19.

Background

Given the high incidence of coronavirus and shortage of nurses in Iranian hospitals, learning about nurses' intention to care for patients with COVID-19 is important.

Design

In this cross-sectional study, 648 Iranian nurses were surveyed during March 2020. The online questionnaire consisted of two parts. The mediating role was explored for the following: job satisfaction and commitment in the association of workload, quality of supervisor, extra-role behaviours, and pay satisfaction with the intention to care. The study adhered to STROBE checklist for cross-sectional studies.

Results

The results of this study show that job satisfaction and organisational commitment mediated the relationship of nurses' workload, quality of supervisor, extra-role behaviours, and pay satisfaction with the intention to care for patients with COVID-19.

Conclusion

The results of the study indicate the importance of job satisfaction and organisational commitment as mechanisms that help to understand the association of nurses' workload, quality of supervisor, extra-role behaviours and pay satisfaction with the intention to care during the COVID-19 pandemic.

Relevance to clinical practice

Hospital managers need to attend to the role of nurses' job satisfaction and other organisational factors to ensure that they can cope with the challenges of the COVID-19 pandemic.

Cover page of Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

(2021)

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case-control classification. An L0 -norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi-study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.

Cover page of Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study.

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study.

(2021)

Background

COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks.

Methods

We developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase chain reaction (PCR) surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing, and universal mask wearing.

Results

The proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6 to 51.6%, which translated to the basic reproduction number (R0) estimates of 2.9-6.2. With moderate community incidence (~ 30 confirmed cases/1,000,000 people/day), the estimated probabilities of averting an outbreak in a low-risk (R0 = 1.5), moderate-risk (R0 = 2.9), and high-risk (R0 = 6.2) shelter were respectively 0.35, 0.13, and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27, and 0.08 for universal masking; and 0.74, 0.42, and 0.19 for these strategies in combination. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community.

Conclusions

In high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom screening, frequent PCR testing, and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk.