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Abortion stigma is a phenomenon in many regions and cultures. Those receiving training in clinical abortion care should understand abortion stigma both as a theoretical concept and as a lived experience for the abortion-care workforce. Indeed, one of the most challenging aspects of abortion care is managing and negotiating the stigma that often comes with it. In this chapter we define abortion stigma, and discuss its impact on people who seek abortion and on those who care for them. We introduce key concepts in stigma dynamics, in particular the ways in which stigma and silence create vicious cycles that affect psychosocial well-being, abortion complications, and law and policy. We consider the ways in which training settings bring unique stigma-related challenges for both trainer and trainee, including learner dilemmas about seeking abortion training, disclosing abortion training, and interacting with other healthcare providers who may be opposed to abortion. We conclude by reviewing strategies for managing stigma and developing resilience to its consequences, including values clarification trainings and the Provider's Share Workshop.
Background: Despite significant morbidity and mortality, estimates of the burden of healthcare-associated viral respiratory infections (HA-VRI) for noninfluenza infections are limited. Of the studies assessing the burden of respiratory syncytial virus (RSV), cases are typically classified as healthcare associated if a positive test result occurred after the first 3 days following admission, which may miss healthcare exposures prior to admission. Utilizing an expanded definition of healthcare-associated RSV, we assessed the estimates of disease prevalence. Methods: This study included laboratory-confirmed cases of RSV in adult and pediatric patients admitted to acute-care hospitals in a catchment area of 8 counties in Tennessee identified between October 1, 2016, and April 30, 2019. Surveillance information was abstracted from hospital and state laboratory databases, hospital infection control databases, reportable condition databases, and electronic health records as a part of the Influenza Hospitalization Surveillance Network by the Emerging Infections Program. Cases were defined as healthcare-associated RSV if laboratory confirmation of infection occurred (1) on or after hospital day 4 (ie, “traditional definition”) or (2) between hospital day 0 and 3 in patients transferred from a chronic care facility or with a recent discharge from another acute-care facility in the 7 days preceding the current index admission (ie, “enhanced definition”). The proportion of laboratory-confirmed RSV designated as HA-VRI using both the traditional definition as well as with the added enhanced definition were compared. Results: We identified 900 cases of RSV in hospitalized patients over the study period. Using the traditional definition for HA-VRI, only 41 (4.6%) were deemed healthcare associated. Adding the cases identified using the enhanced definition, an additional 12 cases (1.3%) were noted in patients transferred from a chronic care facility for the current acute-care admission and 17 cases (1.9%) were noted in patients with a prior acute-care admission in the preceding 7 days. Using our expanded definition, the total proportion of healthcare-associated RSV in this cohort was 69 (7.7%) of 900 compared to 13.1% of cases for influenza (Figure 1). Although the burden of HA-VRI due to RSV was less than that of influenza, when stratified by age, the rate increased to 11.7% for those aged 50–64 years and to 10.1% for those aged ≥65 years (Figure 2). Conclusions: RSV infections are often not included in estimates of HA-VRI, but the proportion of cases that are healthcare associated are substantial. Typical surveillance methods likely underestimate the burden of disease related to RSV, especially for those aged ≥50 years.
Background: Healthcare-associated transmission of influenza leads to significant morbidity, mortality, and cost. Most studies classify healthcare-associated viral respiratory infections (HA-VRI) as those with a positive test result after the first 3 days following admission, which does not account for healthcare exposures prior to admission. Utilizing an expanded definition of healthcare-associated influenza, we aimed to improve the estimates of disease prevalence on a population level. Methods: This study included laboratory-confirmed cases of influenza in adult and pediatric patients admitted to any acute-care hospital in a catchment area of 8 counties Tennessee identified between October 1, 2012, and April 30, 2019. Surveillance information was abstracted from hospital and state laboratory databases, hospital infection control practitioner databases, reportable condition databases, and electronic health records as a part of the Influenza Hospitalization Surveillance Network (FluSurv-NET) by the Centers for Disease Control and Prevention (CDC) Emerging Infections Program (EIP). Cases were defined as healthcare-associated influenza laboratory confirmation of infection occurred (1) on or after hospital day 4 (“traditional definition”), or (2) between hospital days 0 and 3 in patients transferred from a chronic care facility or with a recent discharge from another acute-care facility in the 7 days preceding the current index admission (ie, enhanced definition). The proportion of laboratory-confirmed influenza designated as HA-VRI using both the traditional definition as well as with the added enhanced definition were compared. Data were imported into Stata software for analysis. Results: We identified 5,904 cases of laboratory-confirmed influenza in hospitalized patients over the study period. Using the traditional definition for HA-VRI, only 147 (2.5%, seasonal range 1.3%–3.4%) were deemed healthcare associated (Figure 1). Adding the cases identified using the enhanced definition, an additional 317 (5.4%, range 2.3%–6.7%) cases were noted in patients transferred from a chronic care facility for the current acute-care admission and 336 cases (5.7%; range, 4.1%–7.4%) were noted in patients with a prior acute-care facility admission in the preceding 7 days. Using our expanded definition, the total proportion of healthcare-associated influenza in this cohort was 772 of 5,904 (13.1%; range, 10.6%–14.8%). Conclusion: HA-VRI due to influenza is an underrecognized infection in hospitalized patients. Limiting surveillance assessment of this important outcome to just those patients with a positive influenza test after hospital day 3 captured only 19% of possible healthcare-associated influenza infections across 7 influenza seasons. These results suggest that the traditionally used definitions of healthcare-associated influenza underestimate the true burden of cases.
The timing and duration of the coldest period in the last glacial stage, often referred to as the last glacial maximum (LGM), has been observed to vary spatially and temporally. In Australia, this period is characterised by colder, and in some places more arid, climates than today. We applied Monte-Carlo change point analysis to all available continuous proxy records covering this period, primarily pollen records, from across Australia (n = 37) to assess this change. We find a significant change point occurred (within uncertainty) at 28.6 ± 2.8 ka in 25 records. We interpret this change as a shift to cooler climates, associated with a widespread decline in biological productivity. An additional change point occurred at 17.7 ± 2.2 ka in 24 records. We interpret this change as a shift towards warmer climates, associated with increased biological productivity. We broadly characterise the period between 28.6 (± 2.8) – 17.7 (± 2.2) ka as an extended period of maximum cooling, with low productivity vegetation that may have occurred as a combined response to reduced temperatures, lower moisture availability and atmospheric CO2. These results have implications for how the spatial and temporal coherence of climate change, in this case during the LGM, can be best interrogated and interpreted.
Early in the coronavirus disease 2019 (COVID-19) pandemic, the CDC recommended collection of a lower respiratory tract (LRT) specimen for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing in addition to the routinely recommended upper respiratory tract (URT) testing in mechanically ventilated patients. Significant operational challenges were noted at our institution using this approach. In this report, we describe our experience with routine collection of paired URT and LRT sample testing. Our results revealed a high concordance between the 2 sources, and that all children tested for SARS-CoV-2 were appropriately diagnosed with URT testing alone. There was no added benefit to LRT testing. Based on these findings, our institutional approach was therefore adjusted to sample the URT alone for most patients, with LRT sampling reserved for patients with ongoing clinical suspicion for SARS-CoV-2 after a negative URT test.
Previous results have been mixed regarding the role of the apolipoprotein E e4 (APOE e4) allele in later-life depression: some studies note that carriers experience greater symptoms and increased risk while others find no such association. However, there are few prospective, population-based studies of the APOE e4-depression association and fewer that examine depressive symptom trajectory and depression risk longitudinally. We examined the association between APOE e4 allele status and longitudinal change in depressive symptoms and depression risk in later-life, over a 12-year follow-up period.
We used data from 690 participants of the Lothian Birth Cohort 1936 who took part in the Scottish Mental Survey 1947 (aged 11) and were followed-up in later-life over five waves from 2004 to 2019 (aged 70–82). We used APOE e4 allele status to predict longitudinal change in depressive symptom scores and risk of depression (defined by a symptom score threshold or use of depression-related medication). Models were adjusted for sex, childhood cognitive ability, childhood social class, education, adult social class, smoking status and functional limitations at baseline.
Depressive symptom scores increased with age. Once adjusted for covariates, APOE e4 allele status did not significantly predict symptom score trajectories or depression risk. Greater functional limitations at baseline significantly predicted poorer symptom score trajectories and increased depression risk (defined by medications). APOE e4 allele status did not significantly moderate the contribution of sex, education or functional limitations.
There was no evidence that APOE e4 carriers experience an increased risk for later-life depression.
This SHEA white paper identifies knowledge gaps and challenges in healthcare epidemiology research related to coronavirus disease 2019 (COVID-19) with a focus on core principles of healthcare epidemiology. These gaps, revealed during the worst phases of the COVID-19 pandemic, are described in 10 sections: epidemiology, outbreak investigation, surveillance, isolation precaution practices, personal protective equipment (PPE), environmental contamination and disinfection, drug and supply shortages, antimicrobial stewardship, healthcare personnel (HCP) occupational safety, and return to work policies. Each section highlights three critical healthcare epidemiology research questions with detailed description provided in supplementary materials. This research agenda calls for translational studies from laboratory-based basic science research to well-designed, large-scale studies and health outcomes research. Research gaps and challenges related to nursing homes and social disparities are included. Collaborations across various disciplines, expertise and across diverse geographic locations will be critical.
The COVID-19 pandemic prompted the development and implementation of hundreds of clinical trials across the USA. The Trial Innovation Network (TIN), funded by the National Center for Advancing Translational Sciences, was an established clinical research network that pivoted to respond to the pandemic.
The TIN’s three Trial Innovation Centers, Recruitment Innovation Center, and 66 Clinical and Translational Science Award Hub institutions, collaborated to adapt to the pandemic’s rapidly changing landscape, playing central roles in the planning and execution of pivotal studies addressing COVID-19. Our objective was to summarize the results of these collaborations and lessons learned.
The TIN provided 29 COVID-related consults between March 2020 and December 2020, including 6 trial participation expressions of interest and 8 community engagement studios from the Recruitment Innovation Center. Key lessons learned from these experiences include the benefits of leveraging an established infrastructure, innovations surrounding remote research activities, data harmonization and central safety reviews, and early community engagement and involvement.
Our experience highlighted the benefits and challenges of a multi-institutional approach to clinical research during a pandemic.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
The Common Metrics Initiative aims to develop and field metrics to improve research processes within the national Clinical and Translational Science Award (CTSA) Consortium. A Median Accrual Ratio (MAR) common metric was developed to assess the results of efforts to increase subject accrual into a set of clinical trials within the expected time period. A pilot test of the MAR was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. Post-pilot interviews were conducted with 9 CTSA Principal Investigators (PIs) and 23 pilot team members. Over three-quarters (78%) of respondents reported that the MAR could be useful for performance improvement, but also described limitations or concerns. The most commonly cited barrier to MAR use for performance improvement was difficulty in interpreting the single value that is produced. Most respondents were interested in using the MAR to assess recruitment at an individual trial level. Majority of respondents (63%) had mixed opinions about aggregating metric results across the CTSA Consortium for comparison or benchmarking. Collecting data about additional contextual factors, and comparing accrual between subgroups, were cited as potentially helping address concerns about aggregation. Significant challenges remain in ensuring that the MAR can be sufficiently useful for collaborative process improvement. We offer recommendations to potentially improve metric usefulness.
Failure to accrue participants into clinical trials incurs economic costs, wastes resources, jeopardizes answering research questions meaningfully, and delays translating research discoveries into improved health. This paper reports the results of a pilot test of the Median Accrual Ratio (MAR) metric developed as a part of the Common Metrics Initiative of the NIH’s National Center for Advancing Translational Science (NCATS) Clinical and Translational Science Award (CTSA) Consortium. Using the metric is intended to enhance the ability of the CTSA Consortium and its “hubs” to increase subject accrual into trials within expected timeframes. The pilot test was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. We describe the pilot test methods, and results regarding feasibility of collecting metric data and the quality of data that was collected. Participating hubs welcomed the opportunity to assess accrual efforts, but experienced challenges in collecting accrual metric data due to insufficient infrastructure and inconsistent implementation of electronic data systems and lack of uniform data definitions. Also, the metric could not be constructed for all trial designs, particularly those using competitive enrollment strategies. We offer recommendations to address the identified challenges to facilitate progress to broad accrual metric data collection and use.
Clinical trial participation among US Hispanics remains low, despite a significant effort by research institutions nationwide. ResearchMatch, a national online platform, has matched 113,372 individuals interested in participating in research with studies conducted by 8778 researchers. To increase accessibility to Spanish speakers, we translated the ResearchMatch platform into Spanish by implementing tenets of health literacy and respecting linguistic and cultural diversity across the US Hispanic population. We describe this multiphase process, preliminary results, and lessons learned.
Translation of the ResearchMatch site consisted of several activities including: (1) improving the English language site’s reading level, removing jargon, and using plain language; (2) obtaining a professional Spanish translation of the site and incorporating iterative revisions by a panel of bilingual community members from diverse Hispanic backgrounds; (3) technical development and launch; and (4) initial promotion.
The Spanish language version was launched in August 2018, after 11 months of development. Community input improved the initial translation, and early registration and use by researchers demonstrate the utility of Spanish ResearchMatch in engaging Hispanics. Over 12,500 volunteers in ResearchMatch self-identify as Hispanic (8.5%). From August 2018 to March 2020, 162 volunteers registered through the Spanish language version of ResearchMatch, and over 500 new and existing volunteers have registered a preference to receive messages about studies in Spanish.
By applying the principles of health literacy and cultural competence, we developed a Spanish language translation of ResearchMatch. Our multiphase approach to translation included key principles of community engagement that should prove informative to other multilingual web-based platforms.
Growing evidence suggests that emotion socialization may be disrupted by maternal depression. However, little is known about emotion-related parenting by mothers with bipolar disorder or whether affective modeling in early childhood is linked to young adults’ recollections of emotion socialization practices. The current study investigates emotion socialization by mothers with histories of major depression, bipolar disorder, or no mood disorder. Affective modeling was coded from parent–child interactions in early childhood and maternal responses to negative emotions were recollected by young adult offspring (n = 131, 59.5% female, M age = 22.16, SD = 2.58). Multilevel models revealed that maternal bipolar disorder was associated with more neglecting, punishing, and magnifying responses to children's emotions, whereas maternal major depression was associated with more magnifying responses; links between maternal diagnosis and magnifying responses were robust to covariates. Young adult recollections of maternal responses to emotion were predicted by affective modeling in early childhood, providing preliminary validity evidence for the Emotions as a Child Scale. Findings provide novel evidence that major depression and bipolar disorder are associated with altered emotion socialization and that maternal affective modeling in early childhood prospectively predicts young adults’ recollections of emotion socialization in families with and without mood disorder.
We have examined gyral folding in a total of more than 500 subjects with first episode schizophrenia, subjects at high risk who do and do not become ill, people with learning disabilities (LD) with and without schizophrenia, and LD with schizotypal or autistic features, as well as appropriate healthy controls.
The gyrification index (GI), the ratio of the inner and outer cortical surface contours, was hand-traced bilaterally on every second 1.88-mm image slice throughout the brain in about 100 scans. We then developed an Automated-GI (A-GI) approach to determine cortical folding in pre-frontal lobes, and have applied this to the other scans.
Gyrification index values were significantly increased in the right temporal lobe of the schizophrenic patients. Right prefrontal lobe GI values were significantly increased in high risk individuals who subsequently developed schizophrenia (especially in BA 9 and 10). A-GI reduces the analysis time, improves repeatability, has low susceptibility to scanner noise and variability. Using A-GI we have replicated hand-traced results and also found a similar pattern of increased ‘gyrification’ in LD with schizophrenia or schizotypy but not LD alone or with autistic features.
Differences in fronto-temporal GI might reflect trait disconnectivity predictive of schizophrenia across a range of IQ levels. GI is however poorly understood and influenced by age, sex and volume measures. Further examination of sulco-gyral patterns is required to clarify this. A-GI could be usefully applied to MRI data sets of the brain in health and disease to address these issues.
Many institutions are attempting to implement patient-reported outcome (PRO) measures. Because PROs often change clinical workflows significantly for patients and providers, implementation choices can have major impact. While various implementation guides exist, a stepwise list of decision points covering the full implementation process and drawing explicitly on a sociotechnical conceptual framework does not exist.
To facilitate real-world implementation of PROs in electronic health records (EHRs) for use in clinical practice, members of the EHR Access to Seamless Integration of Patient-Reported Outcomes Measurement Information System (PROMIS) Consortium developed structured PRO implementation planning tools. Each institution pilot tested the tools. Joint meetings led to the identification of critical sociotechnical success factors.
Three tools were developed and tested: (1) a PRO Planning Guide summarizes the empirical knowledge and guidance about PRO implementation in routine clinical care; (2) a Decision Log allows decision tracking; and (3) an Implementation Plan Template simplifies creation of a sharable implementation plan. Seven lessons learned during implementation underscore the iterative nature of planning and the importance of the clinician champion, as well as the need to understand aims, manage implementation barriers, minimize disruption, provide ample discussion time, and continuously engage key stakeholders.
Highly structured planning tools, informed by a sociotechnical perspective, enabled the construction of clear, clinic-specific plans. By developing and testing three reusable tools (freely available for immediate use), our project addressed the need for consolidated guidance and created new materials for PRO implementation planning. We identified seven important lessons that, while common to technology implementation, are especially critical in PRO implementation.
Classroom management remains one of the greatest challenges for teachers. In this study, with 52 general and special education teachers, we examined the effectiveness of a screencast-delivered professional development program focused on classroom management practices in the first 3 days of school. Results suggest that after participating in the program, teachers report a positive change to the start of their school year across 12 different areas. Further, teachers’ classroom management self-efficacy increased significantly after completing the program, and there was a significant correlation (r = .41) between increases in classroom management self-efficacy and rate of implementation of new practices. Implications for practitioners and future directions for research are included.
Electroconvulsive therapy (ECT) is an effective NICE-approved treatment for severe depression, treatment-resistant mania and catatonia; the Royal College of Psychiatrists’ (RCPsych) guidelines also support its use fourth line for treatment-resistant schizophrenia.
Evaluate the use of ECT at Broadmoor High Secure psychiatric hospital, focusing on the indications for its prescription and patients’ capacity to consent.
Analyse case records of all patients who received ECT, and of all patients referred for Second Opinion Appointed Doctor (SOAD) certified ECT treatment under Section 58 of the Mental Health Act 1983 (MHA) due to incapacity, between 01.09.11 and 30.07.15.
All patients lacked capacity to consent to treatment during this time. Thirty-three referrals were made to the SOAD service for 15 patients, and of these 30 resulted in certification (T6) of which 10 were not subsequently used. Improvements in mental state and agreement to take clozapine were common reasons for T6s either not being certified or used. Urgent treatment under Section 62 of the MHA was employed 7 times for 4 patients during this period. Of the referrals to the SOAD service, 25 were for treatment-resistant schizophrenia, 5 for mania, 3 for catatonia and none for depression.
Those patients requiring ECT within this population tended to be the most unwell and all lacked the capacity to consent to it. The majority (76%) of patients receiving ECT at Broadmoor do so outside of NICE (but within RCPsych) guidelines. ECT may be an effective strategy for promoting compliance with clozapine.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
To identify risk factors of patients placed in airborne infection isolation (AII) for possible pulmonary tuberculosis (TB) to better predict TB diagnosis and allow more judicious use of AII.
Case-control, retrospective study at a single tertiary-care academic medical center. The study included all adult patients admitted from October 1, 2014, through October 31, 2017, who were placed in AII for possible pulmonary TB. Cases were defined as those ultimately diagnosed with pulmonary TB. Controls were defined as those not diagnosed with pulmonary TB. Those with TB diagnosed prior to admission were excluded. In total, 662 admissions (558 patients) were included.
Overall, 15 cases of pulmonary TB were identified (2.7%); of these, 2 were people living with human immunodeficiency virus (HIV; PLWH). Statistical analysis was limited by low case number. Those diagnosed with pulmonary TB were more likely to have been born outside the United States (53% vs 13%; P < .001) and to have had prior positive TB testing, regardless of prior treatment (50% vs 19%; P = .015). A multivariate analysis using non–US birth and prior positive TB testing predicted an 18.2% probability of pulmonary TB diagnosis when present, compared with 1.0% if both factors were not present.
The low number of pulmonary TB cases indicated AII overuse, especially in PLWH, and more judicious use of AII is warranted. High-risk groups, including those born outside the United States and those with prior positive TB testing, should be considered for AII in the appropriate clinical setting.
Shared patient–clinician decision-making is central to choosing between medical treatments. Decision support tools can have an important role to play in these decisions. We developed a decision support tool for deciding between nonsurgical treatment and surgical total knee replacement for patients with severe knee osteoarthritis. The tool aims to provide likely outcomes of alternative treatments based on predictive models using patient-specific characteristics. To make those models relevant to patients with knee osteoarthritis and their clinicians, we involved patients, family members, patient advocates, clinicians, and researchers as stakeholders in creating the models.
Stakeholders were recruited through local arthritis research, advocacy, and clinical organizations. After being provided with brief methodological education sessions, stakeholder views were solicited through quarterly patient or clinician stakeholder panel meetings and incorporated into all aspects of the project.
Participating in each aspect of the research from determining the outcomes of interest to providing input on the design of the user interface displaying outcome predications, 86% (12/14) of stakeholders remained engaged throughout the project. Stakeholder engagement ensured that the prediction models that form the basis of the Knee Osteoarthritis Mathematical Equipoise Tool and its user interface were relevant for patient–clinician shared decision-making.
Methodological research has the opportunity to benefit from stakeholder engagement by ensuring that the perspectives of those most impacted by the results are involved in study design and conduct. While additional planning and investments in maintaining stakeholder knowledge and trust may be needed, they are offset by the valuable insights gained.