To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Anxiety disorders are the most frequently diagnosed psychiatric conditions in children and adolescents. Cognitive behavioural therapy (CBT) is a well-established and effective treatment for anxiety and related disorders across the lifespan. Expectations of psychotherapy have been demonstrated to affect outcomes, yet there is sparse existing literature on adolescent patient and parent perspectives of CBT prior to engagement with treatment.
This study aimed to qualitatively explore the expectations and perceptions of CBT for anxiety and related disorders among adolescent patients and parents.
Fourteen adolescent patients and 16 parents participated in semi-structured individual interviews or focus groups consisting of 2–3 participants. Interview transcripts were analysed using inductive analysis.
Three themes were identified: worries about CBT, expectations and knowledge of the CBT process, and the role of parents and families. Overall, we found that adolescents and parents had generally positive views of CBT. The outset of CBT saw adolescents and parents express concern about stigma as well as the ambiguity of CBT. Parents continued to express a lack of understanding of what CBT entailed during their child’s treatment course.
These results suggest that both adolescents and parents would benefit from early discussion and reinforcement of expectations for CBT treatment. Further research efforts are warranted and should be directed towards determining appropriate expectations for parental involvement in a child’s CBT course and effective communication of treatment expectations to both adolescents and parents.
Recent global events demonstrate that analytical frameworks to aid professionals in healthcare ethics must consider the pervasive role of social structures in the emergence of bioethical issues. To address this, the authors propose a new sociologically informed approach to healthcare ethics that they term “social bioethics.” Their approach is animated by the interpretive social sciences to highlight how social structures operate vis-à-vis the everyday practices and moral reasoning of individuals, a phenomenon known as social discourse. As an exemplar, the authors use social bioethics to reframe common ethical issues in psychiatric services and discuss potential implications. Lastly, the authors discuss how social bioethics illuminates the ways healthcare ethics consultants in both policy and clinical decision-making participate in and shape broader social, political, and economic systems, which then cyclically informs the design and delivery of healthcare.
Aspect-based sentiment analysis (ABSA) provides an opportunity to systematically generate user's opinions of specific aspects to enrich the idea creation process in the early stage of product/service design process. Yet, the current ABSA task has two major limitations. First, existing research mostly focusing on the subsets of ABSA task, e.g. aspect-sentiment extraction, extract aspect, opinion, and sentiment in a unified model is still an open problem. Second, the implicit opinion and sentiment are ignored in the current ABSA task. This article tackles these gaps by (1) creating a new annotated dataset comprised of five types of labels, including aspect, category, opinion, sentiment, and implicit indicator (ACOSI) and (2) developing a unified model which could extract all five types of labels simultaneously in a generative manner. Numerical experiments conducted on the manually labeled dataset originally scraped from three major e-Commerce retail stores for apparel and footwear products indicate the performance, scalability, and potentials of the framework developed. Several directions are provided for future exploration in the area of automated aspect-based sentiment analysis for user-centered design.
OBJECTIVES/GOALS: The characterization of the zebrafish as an animal model for Cockayne Syndrome may guide us towards role of Transcription-Coupled Nucleotide Excision Repair (TC-NER) defects in sensorineural hearing loss. METHODS/STUDY POPULATION: To examine our model, we have developed a zebrafish line with a 9+1 base-pair deletion in the ercc6 gene using TALENs. Mutation has since been confirmed by PCR and subsequent restriction digest with StuI. A series of assays evaluating hair cell morphology, structure and function, as well as ribbon synapse structure, will be used to analyze potential differences between the ercc6 mutant zebrafish line a their wild-type siblings. Additionally, electron microscopy will be used to assess differences in hair cell ultrastructure between the ercc6 mutant zebrafish line a their wild-type siblings. Finally, UVC exposure assays will be used to determine the role TC-NER plays in our novel zebrafish model, and evaluate its potential implications in sensorineural hearing loss. RESULTS/ANTICIPATED RESULTS: We anticipate that biallelic loss of function mutations in the zebrafish ercc6 gene will result in abnormalities in hair cell structure, mechanotransduction, or cell number. Additionally, we anticipate that hair cell ultrastructure and ribbon synapse structure will be impacted by loss of ercc6 expression. DISCUSSION/SIGNIFICANCE: Hearing loss mechanisms associated with defects in TC-NER are yet to be described. We believe our model will provide the tools for a faster and efficient way to carry out Cockayne Syndrome studies while laying the groundwork for the association between TC-NER and hearing loss.
This study examined associations between multiple dietary supplement (DS) categories and medical conditions diagnosed by health professionals.
Volunteers completed an online questionnaire on DS use and demographic/lifestyle factors. Medical diagnoses were obtained from a comprehensive military electronic medical surveillance system and grouped into twenty-four clinically diagnosed medical conditions (CDMC).
A stratified random sample of US service members (SM) from all military services (n 26 680).
After adjustment for demographic/lifestyle factors (logistic regression), higher risk was found for 92 % (22/24) of CDMC among individual vitamins/minerals users, 58 % (14/24) of CDMC among herbal users, 50 % (12/24) of CDMC among any DS users and 46 % (11/24) of CDMC among multivitamins/multiminerals (MVM) users. Among protein/amino acid (AA) users, risk was lower in 25 % (6/24) of CDMC. For combination products, risk was higher in 13 % (3/24) of CDMC and lower in 8 % (2/24). The greater the number of CDMC, the higher the prevalence of DS use in most DS categories except proteins/AA where prevalence decreased.
Users in many DS categories had a greater number of CDMC, but protein/AA users had fewer CDMC; results for combination products were mixed. These data indicate those with certain CDMC were also users in some DS categories, especially individual vitamins/minerals, herbals and MVM. Data are consistent with the perception that use of DS enhances health, especially in those with CDMC. Protein/AA and combination product users were more likely to be younger, more physically active men, factors that likely reduced CDMC.
Religious belief is a topic of longstanding interest to psychological science, but the psychology of religious disbelief is a relative newcomer. One prominently discussed model is analytic atheism, wherein cognitive reflection, as measured with the Cognitive Reflection Test, overrides religious intuitions and instruction. Consistent with this model, performance-based measures of cognitive reflection predict religious disbelief in WEIRD (Western, Educated, Industrialized, Rich, & Democratic) samples. However, the generality of analytic atheism remains unknown. Drawing on a large global sample (N = 3461) from 13 religiously, demographically, and culturally diverse societies, we find that analytic atheism as usually assessed is in fact quite fickle cross-culturally, appearing robustly only in aggregate analyses and in three individual countries. The results provide additional evidence for culture’s effects on core beliefs.
The authors present the results of a drone-based airborne LiDAR survey of the fifth century AD Tsukuriyama mounded tomb group in Okayama Prefecture, Japan, revealing the relationship between tomb building and the surrounding landscape during Japan's period of ancient state formation.
Although exposure therapy (ET) is an effective treatment for anxiety disorders and obsessive-compulsive disorder, many clinicians report not utilizing it. The present study targeted common utilization barriers by evaluating an intensive ET training experience in a relatively inexperienced sample of pre-professionals. Thirty-two individuals at the undergraduate or college graduate level without formal clinical experience participated as camp counsellors in a 5day exposure-based therapeutic summer camp for youth with anxiety disorders and/or obsessive-compulsive disorder. Participants were trained in ET through a progressive cascading model and answered questionnaires before and after camp. Repeated measure MANOVA revealed significantly increased feelings of self-efficacy conducting exposures, and significantly decreased feelings of disgust sensitivity and contamination-related disgust from pre-camp to post-camp. A subset of individuals providing data 1 month after the camp maintained a significant gain in ET self-efficacy. Regression analyses revealed that contamination-related disgust, but not disgust sensitivity, significantly predicted post-camp ET self-efficacy. These findings suggest that individuals early into their post-secondary education can learn ET, and the progressive cascading model holds promise in its utility across experience levels and warrants further investigation. Disgust may also play a role in feelings of competency conducting ET. Implications on dissemination and implementation efforts are also discussed.
Key learning aims
(1) How can training of CBT techniques such as exposure occur prior to graduate education?
(2) Can self-efficacy in conducting exposures meaningfully increase in an experiential training of pre-professionals?
(3) How does an individual’s tolerance of disgust impact feelings of competence conducting exposures?
ABSTRACT IMPACT: Despite its importance in systemic diseases such as diabetes, the eye is notably difficult to examine for non-specialists; this study introduces a fully automated approach for eye disease screening, coupling a deep learning algorithm with a robotically-aligned optical coherence tomography system to improve eye care in non-ophthalmology settings. OBJECTIVES/GOALS: This study aims to develop and test a deep learning (DL) method to classify images acquired from a robotically-aligned optical coherence tomography (OCT) system as normal vs. abnormal. The long-term goal of our study is to integrate artificial intelligence and robotic eye imaging to fully automate eye disease screening in diverse clinical settings. METHODS/STUDY POPULATION: Between August and October 2020, patients seen at the Duke Eye Center and healthy volunteers (age ≥18) were imaged with a custom, robotically-aligned OCT (RAOCT) system following routine eye exam. Using transfer learning, we adapted a preexisting convolutional neural network to train a DL algorithm to classify OCT images as normal vs. abnormal. The model was trained and validated on two publicly available OCT datasets and two of our own RAOCT volumes. For external testing, the top-performing model based on validation was applied to a representative averaged B-scan from each of the remaining RAOCT volumes. The model’s performance was evaluated against a reference standard of clinical diagnoses by retina specialists. Saliency maps were created to visualize the areas contributing most to the model predictions. RESULTS/ANTICIPATED RESULTS: The training and validation datasets included 87,697 OCT images, of which 59,743 were abnormal. The top-performing DL model had a training accuracy of 96% and a validation accuracy of 99%. For external testing, 43 eyes of 27 subjects were imaged with the robotically-aligned OCT system. Compared to clinical diagnoses, the model correctly labeled 18 out of 22 normal averaged B-scans and 18 out of 21 abnormal averaged B-scans. Overall, in the testing set, the model had an AUC for the detection of pathology of 0.92, an accuracy of 84%, a sensitivity of 86%, and a specificity of 82%. For the correctly predicted scans, saliency maps identified the areas contributing most to the DL algorithm’s predictions, which matched the regions of greatest clinical importance. DISCUSSION/SIGNIFICANCE OF FINDINGS: This is the first study to develop and apply a DL model to images acquired from a self-aligning OCT system, demonstrating the potential of integrating DL and robotic eye imaging to automate eye disease screening. We are working to translate this technology for use in emergency departments and primary care, where it will have the greatest impact.
This two-part article examines the global public health (GPH) information system deficits emerging in the coronavirus disease 2019 (COVID-19) pandemic. It surveys past, missed opportunities for public health (PH) information system and operational improvements, examines current megatrend changes to information management, and describes a new multi-disciplinary model for population-based management (PBM) supported by a GPH Database applicable to pandemics and GPH crises.
Head impact exposure (HIE) in youth football is a public health concern. The objective of this study was to determine if one season of HIE in youth football was related to cognitive changes.
Over 200 participants (ages 9–13) wore instrumented helmets for practices and games to measure the amount of HIE sustained over one season. Pre- and post-season neuropsychological tests were completed. Test score changes were calculated adjusting for practice effects and regression to the mean and used as the dependent variables. Regression models were calculated with HIE variables predicting neuropsychological test score changes.
For the full sample, a small effect was found with season average rotational values predicting changes in list-learning such that HIE was related to negative score change: standardized beta (β) = -.147, t(205) = -2.12, and p = .035. When analyzed by age clusters (9–10, 11–13) and adding participant weight to models, the R2 values increased. Splitting groups by weight (median split), found heavier members of the 9–10 cohort with significantly greater change than lighter members. Additionaly, significantly more participants had clinically meaningful negative changes: X2 = 10.343, p = .001.
These findings suggest that in the 9–10 age cluster, the average seasonal level of HIE had inverse, negative relationships with cognitive change over one season that was not found in the older group. The mediation effects of age and weight have not been explored previously and appear to contribute to the effects of HIE on cognition in youth football players.
This study examined the relationship between patient performance on multiple memory measures and regional brain volumes using an FDA-cleared quantitative volumetric analysis program – Neuroreader™.
Ninety-two patients diagnosed with mild cognitive impairment (MCI) by a clinical neuropsychologist completed cognitive evaluations and underwent MR Neuroreader™ within 1 year of testing. Select brain regions were correlated with three widely used memory tests. Regression analyses were conducted to determine if using more than one memory measures would better predict hippocampal z-scores and to explore the added value of recognition memory to prediction models.
Memory performances were most strongly correlated with hippocampal volumes than other brain regions. After controlling for encoding/Immediate Recall standard scores, statistically significant correlations emerged between Delayed Recall and hippocampal volumes (rs ranging from .348 to .490). Regression analysis revealed that evaluating memory performance across multiple memory measures is a better predictor of hippocampal volume than individual memory performances. Recognition memory did not add further predictive utility to regression analyses.
This study provides support for use of MR Neuroreader™ hippocampal volumes as a clinically informative biomarker associated with memory performance, which is a critical diagnostic feature of MCI phenotype.
Disasters can damage the essential public health infrastructure and social protection systems required for vulnerable populations. This contributes to indirect mortality and morbidity as high as 70–90%, primarily due to an exacerbation of life-threatening conditions and chronic diseases. Despite this, the traditional focus of public health systems has been on communicable diseases. To address this challenge, disaster and health planners require access to repeatable and measurable methods to rank and prioritize the needs of people with life-threatening and chronic diseases before, during, and after a disaster.
Propose a repeatable and measurable method for ranking and prioritizing the needs of people with life-threatening and chronic diseases before, during, and after a disaster.
The research began with identifying the risk disasters pose to people with life-threatening and chronic diseases. The data gathered was then used to develop indicators and explore the use of DisasterAWARE™ (All-hazard Warnings, Analysis, and Risk Evaluation) to rank and prioritize the needs before, during, and after a disaster.
This research found people at greatest risk are those with underlying cardiovascular and respiratory diseases, unstable diabetes, renal diseases, and those undergoing cancer treatment. A sustainable method to help address this problem is to expand the use of DisasterAWARE™ (All-hazard Warnings, Analysis, and Risk Evaluation) to rank and prioritize needs at national and sub-national levels.
DisasterAWARE™ has been successfully applied to the assessment and prioritization of disaster risk and humanitarian assistance needs in Southeast Asia (ASEAN, Viet Nam), Central America (Guatemala, El Salvador, Honduras, Nicaragua), South America (Peru), and the Caribbean (Jamaica, Dominican Republic). Using the indicators developed through this research, this proven methodology can be seamlessly and easily translated to rank and prioritize the needs of people with life-threatening and chronic diseases before, during, and after a disaster.
Water exposures in healthcare settings and during healthcare delivery can place patients at risk for infection with water-related organisms and can potentially lead to outbreaks. We aimed to describe Centers for Disease Control and Prevention (CDC) consultations involving water-related organisms leading to healthcare-associated infections (HAIs).
Retrospective observational study.
We reviewed internal CDC records from January 1, 2014, through December 31, 2017, using water-related terms and organisms, excluding Legionella, to identify consultations that involved potential or confirmed transmission of water-related organisms in healthcare. We determined plausible exposure pathways and routes of transmission when possible.
Of 620 consultations during the study period, we identified 134 consultations (21.6%), with 1,380 patients, that involved the investigation of potential water-related HAIs or infection control lapses with the potential for water-related HAIs. Nontuberculous mycobacteria were involved in the greatest number of investigations (n = 40, 29.9%). Most frequently, investigations involved medical products (n = 48, 35.8%), and most of these products were medical devices (n = 40, 83.3%). We identified a variety of plausible water-exposure pathways, including medication preparation near water splash zones and water contamination at the manufacturing sites of medications and medical devices.
Water-related investigations represent a substantial proportion of CDC HAI consultations and likely represent only a fraction of all water-related HAI investigations and outbreaks occurring in US healthcare facilities. Water-related HAI investigations should consider all potential pathways of water exposure. Finally, healthcare facilities should develop and implement water management programs to limit the growth and spread of water-related organisms.
Pure and Nb-doped zirconium germanate materials of composition K2-xZr1-xNbxGe3O9.H2O where x = 0, 0.1, 0.2 and 0.25 with the structure of the mineral umbite have been successfully synthesised. The parent material displays negligible ion exchange of K+ for Cs+ but the doped materials shows much improved exchange. Synchrotron X-ray diffraction shows substantial peak splitting which varies with increasing niobium content. Preliminary Rietveld refinements suggest a two phase model with a caesium and potassium rich doped umbite phase.
Hyperbolic polariton modes are highly appealing for a broad range of applications in nanophotonics, including surfaced enhanced sensing, sub-diffractional imaging, and reconfigurable metasurfaces. Here we show that attenuated total reflectance (ATR) micro-spectroscopy using standard spectroscopic tools can launch hyperbolic polaritons in a Kretschmann–Raether configuration. We measure multiple hyperbolic and dielectric modes within the naturally hyperbolic material hexagonal boron nitride as a function of different isotopic enrichments and flake thickness. This overcomes the technical challenges of measurement approaches based on nanostructuring, or scattering scanning near-field optical microscopy. Ultimately, our ATR approach allows us to compare the optical properties of small-scale materials prepared by different techniques systematically.
Traditional ambulatory rhythm monitoring in children can have limitations, including cumbersome leads and limited monitoring duration. The ZioTM patch ambulatory monitor is a small, adhesive, single-channel rhythm monitor that can be worn up to 2 weeks. In this study, we present a retrospective cross-sectional analysis of the ZioTM monitor’s impact in clinical practice. Patients aged 0–18 years were included in the study. A total of 373 studies were reviewed in 332 patients. In all, 28.4% had structural heart disease, and 16.9% had a prior surgical, catheterisation, or electrophysiology procedure. The most common indication for monitoring was tachypalpitations (41%); 93.5% of these patients had their symptoms captured during the study window. The median duration of monitoring was 5 days. Overall, 5.1% of ZioTM monitoring identified arrhythmias requiring new intervention or increased medical management; 4.0% identified arrhythmias requiring increased clinical surveillance. The remainder had either normal-variant rhythm or minor rhythm findings requiring no change in management. For patients with tachypalpitations and no structural heart disease, 13.2% had pathological arrhythmias, but 72.9% had normal-variant rhythm during symptoms, allowing discharge from cardiology care. Notably, for patients with findings requiring intervention or increased surveillance, 56% had findings first identified beyond 24 hours, and only 62% were patient-triggered findings. Seven studies (1.9%) were associated with complications or patient intolerance. The ZioTM is a well-tolerated device that may improve what traditional Holter and event monitoring would detect in paediatric cardiology patients. This study shows a positive clinical impact on the management of patients within a paediatric cardiology practice.
We examine the role of status quo bias in the ballot wording of social issues that affect the rights of minority groups. We test the salience of this framing bias by conducting an experiment that randomly assigns different ballot wordings for five policies across survey respondents. We find that status quo bias changes the percent of individuals who vote for the ballot measure by 5–8 percentage points with the least informed individuals being the most affected by status quo bias.
Molecular assays are often implemented by weed scientists for detection of
herbicide-resistant individuals; however, the utility of these assays can be
limited if multiple mechanisms of evolved resistance exist. Waterhemp
resistant to protoporphyrinogen oxidase (PPO)– inhibiting herbicides is
conferred by a target-site mutation in PPX2L (a gene coding
for PPO), resulting in the loss of a glycine at position 210 (ΔG210). This
ΔG210 mutation of PPX2L is the only known mechanism
responsible for PPO-inhibitor resistance (PPO-R) in waterhemp from five
states (Illinois, Indiana, Iowa, Kansas, and Missouri); however, a limited
number of populations have been tested, especially in Illinois. To verify
the ubiquity of the ΔG210 in PPO-R waterhemp populations in Illinois, a
previously published allele-specific PCR (asPCR) was used for the detection
of the ΔG210 mutation to associate this mutation with phenotypic resistance
in 94 Illinois waterhemp populations. The ΔG210 mutation was detected in all
populations displaying phenotypic resistance to lactofen (220 g ai
ha−1), indicating the deletion is likely the only mechanism of
resistance. With evidence that the ΔG210 mutation dominates PPO-R waterhemp
biotypes, molecular detection techniques have considerable utility.
Unfortunately, the previously published asPCR is time consuming, very
sensitive to PCR conditions, and requires additional steps to eliminate the
possibility of false negatives. To overcome these limitations, a streamlined
molecular method using the TaqMan® technique was developed, utilizing
allele-specific, fluorescent probes for high-throughput, robust
discrimination of each allele (resistant and susceptible) at the 210th amino
acid position of PPX2L.
Pure and Nb-doped zirconium germanate materials of composition K2-xZr1-xNbxGe3O9.H2O where x = 0, 0.1, 0.2 and 0.3 with the structure of the natural mineral umbite have been prepared in high yield using hydrothermal synthesis methods. The parent material displays virtually no ion exchange of the K+ for Cs+ but the doped materials show rapidly enhanced exchange with replacement of ca. 70% of the K+ by Cs+ for the 30% doped material. Rietveld analysis of the powder X-ray diffraction data is consistent with no change in the unit cell parameters or K+ bonding prior to the exchange, hence we propose the improved property is due to the creation of cation defect sites within the pores of the material that facilities greater cation mobility and leads to exchange.