Practice Settings Research Articles

Wound management provided by advanced practice nurses: a scoping review.

The objective of the review was to map the similarities and differences in the wound care practices of nurse practitioners, clinical nurse specialists, and advanced practice registered nurses, globally. Advanced practice nurses have graduate education and advanced scope of practice. Adding advanced wound care training to their skill set provides an opportunity for advanced practice nurses to provide wound care. This review considered for inclusion studies of advanced practice nurses globally who are registered nurses with graduate-level education and advanced training (certification/education) in wound care in any setting. The review was conducted using JBI methodology for scoping reviews. The databases searched included MEDLINE, CINAHL, ProQuest Nursing and Allied Health, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Scopus, and ProQuest Dissertations and Theses. To reflect changes in the advanced practice nursing scope of practice, searches were limited to articles published from 2011 onward. Articles in languages other than English were translated. Two reviewers independently reviewed titles and abstracts; relevant sources were retrieved in full and screened for eligibility against the inclusion criteria. An additional independent reviewer resolved any disagreements. Data were extracted using a data extraction tool. Extracted data included similarities and differences in wound care practice (type of wound, practice setting, treatments). There were 2504 abstracts screened, and 158 articles were screened at full text. Seven articles were included in this review: 3 sources from the United States, 2 from Australia, and 1 each from Canada and The Netherlands. All 7 sources focused on nurse practitioners. Wound care education varied from certification in wound ostomy to a master's education in wounds. The practice setting varied; there were 2 primary care clinics, 2 community clinics, a wound care center; a suburban hospital, and a study that included tertiary, community, and residential care. Treatments varied, but the sources specific to pressure injuries discussed assessments, cleansing, dressings, topical products, and offloading surfaces/equipment. One source examined the impact of hiring nurse practitioners as wound care consultants. Sources that discussed treatments for various wounds described comprehensive assessments, diagnostic investigations, referrals, wound management, and medications prescribed. This review outlined the characteristics of advanced practice nurses providing wound care and their practice settings, types of wounds, and treatments provided. Many articles on advanced practice nurses with advanced wound care expertise lack a description of the graduate-level education and/or the specifics regarding wound care certification. This prevents comparison of advanced practice nurses with each other and with other providers regarding the impact that advanced practice nurses have on the health care system in relation to wound care, including cost, access to services, and patient satisfaction.

One-misrecorded Poisson INAR(1) model via two random operators with application to crime and economics data

In this paper, we propose a first-order non-negative integer-valued autoregressive (INAR(1)) model with one-misrecorded Poisson (OMP) marginal via a combination of the generalized binomial thinning and mixture Pegram operators for zero-inflated and one deflated count time series. The suggested model is suitable for multimodal, equi- and over-dispersed data modeling. It contains two particular cases: the mixture of Pegram and thinning of a first-order integer-valued autoregressive (MPT(1)) with Poisson and one-misrecorded Poisson. The distribution of the innovation term is derived as a mixture of degenerate distributions at 0 and 1, and two Poisson distributions with certain parameters. Regression and several statistical properties of the proposed model are discussed. We investigate the distribution of the runs (the lengths of zeros and ones). The parameters of the model are estimated using the maximum-likelihood, modified Yule–Walker, and modified conditional least squares methods. The estimation of the parameters, their behavior, and their performance are presented through a simulation study. Two practical data sets on the monthly cases of criminal records and weekly sales are applied to check the proposed process’s performance against other relevant INAR(1) models, showing its capabilities in the challenging case of over-dispersed count data. Furthermore, the proposed model discusses data forecasting.

An Adaptive Black-Box Defense Against Trojan Attacks (TrojDef).

Trojan backdoor is a poisoning attack against neural network (NN) classifiers in which adversaries try to exploit the (highly desirable) model reuse property to implant Trojans into model parameters for backdoor breaches through a poisoned training process. To misclassify an input to a target class, the attacker activates the backdoor by augmenting the input with a predefined trigger that is only known to her/him. Most of the proposed defenses against Trojan attacks assume a white-box setup, in which the defender either has access to the inner state of NN or is able to run backpropagation through it. In this work, we propose a more practical black-box defense, dubbed TrojDef. In a black-box setup, the defender can only run forward-pass of the NN. TrojDef is motivated by the Trojan poisoned training, in which the model is trained on both benign and Trojan inputs. TrojDef tries to identify and filter out Trojan inputs (i.e., inputs augmented with the Trojan trigger) by monitoring the changes in the prediction confidence when the input is repeatedly perturbed by random noise. We derive a function based on the prediction outputs which is called the prediction confidence bound to decide whether the input example is Trojan or not. The intuition is that Trojan inputs are more stable as the misclassification only depends on the trigger, while benign inputs will suffer when augmented with noise due to the perturbation of the classification features. Through mathematical analysis, we show that if the attacker is perfect in injecting the backdoor, the Trojan infected model will be trained to learn the appropriate prediction confidence bound, which is used to distinguish Trojan and benign inputs under arbitrary perturbations. However, because the attacker might not be perfect in injecting the backdoor, we introduce a nonlinear transform to the prediction confidence bound to improve the detection accuracy in practical settings. Extensive empirical evaluations show that TrojDef significantly outperforms the-state-of-the-art defenses and is highly stable under different settings, even when the classifier architecture, the training process, or the hyperparameters change.

Angle Robustness Unmanned Aerial Vehicle Navigation in GNSS-Denied Scenarios

Due to the inability to receive signals from the Global Navigation Satellite System (GNSS) in extreme conditions, achieving accurate and robust navigation for Unmanned Aerial Vehicles (UAVs) is a challenging task. Recently emerged, vision-based navigation has been a promising and feasible alternative to GNSS-based navigation. However, existing vision-based techniques are inadequate in addressing flight deviation caused by environmental disturbances and inaccurate position predictions in practical settings. In this paper, we present a novel angle robustness navigation paradigm to deal with flight deviation in point-to-point navigation tasks. Additionally, we propose a model that includes the Adaptive Feature Enhance Module, Cross-knowledge Attention-guided Module and Robust Task-oriented Head Module to accurately predict direction angles for high-precision navigation. To evaluate the vision-based navigation methods, we collect a new dataset termed as UAV_AR368. Furthermore, we design the Simulation Flight Testing Instrument (SFTI) using Google Earth to simulate different flight environments, thereby reducing the expenses associated with real flight testing. Experiment results demonstrate that the proposed model outperforms the state-of-the-art by achieving improvements of 26.0% and 45.6% in the success rate of arrival under ideal and disturbed circumstances, respectively.

Domain-Hallucinated Updating for Multi-Domain Face Anti-spoofing

Multi-Domain Face Anti-Spoofing (MD-FAS) is a practical setting that aims to update models on new domains using only novel data while ensuring that the knowledge acquired from previous domains is not forgotten. Prior methods utilize the responses from models to represent the previous domain knowledge or map the different domains into separated feature spaces to prevent forgetting. However, due to domain gaps, the responses of new data are not as accurate as those of previous data. Also, without the supervision of previous data, separated feature spaces might be destroyed by new domains while updating, leading to catastrophic forgetting. Inspired by the challenges posed by the lack of previous data, we solve this issue from a new standpoint that generates hallucinated previous data for updating FAS model. To this end, we propose a novel Domain-Hallucinated Updating (DHU) framework to facilitate the hallucination of data. Specifically, Domain Information Explorer learns representative domain information of the previous domains. Then, Domain Information Hallucination module transfers the new domain data to pseudo-previous domain ones. Moreover, Hallucinated Features Joint Learning module is proposed to asymmetrically align the new and pseudo-previous data for real samples via dual levels to learn more generalized features, promoting the results on all domains. Our experimental results and visualizations demonstrate that the proposed method outperforms state-of-the-art competitors in terms of effectiveness.

Improving Open Set Recognition via Visual Prompts Distilled from Common-Sense Knowledge

Open Set Recognition (OSR) poses significant challenges in distinguishing known from unknown classes. In OSR, the overconfidence problem has become a persistent obstacle, where visual recognition models often misclassify unknown objects as known objects with high confidence. This issue stems from the fact that visual recognition models often lack the integration of common-sense knowledge, a feature that is naturally present in language-based models but lacking in visual recognition systems. In this paper, we propose a novel approach to enhance OSR performance by distilling common-sense knowledge into visual prompts. Utilizing text prompts that embody common-sense knowledge about known classes, the proposed visual prompt is learned by extracting semantic common-sense features and aligning them with image features from visual recognition models. The unique aspect of this work is the training of individual visual prompts for each class to encapsulate this common-sense knowledge. Our methodology is model-agnostic, capable of enhancing OSR across various visual recognition models, and computationally light as it focuses solely on training the visual prompts. This research introduces a method for addressing OSR, aiming at a more systematic integration of visual recognition systems with common-sense knowledge. The obtained results indicate an enhancement in recognition accuracy, suggesting the applicability of this approach in practical settings.

A Primal-Dual Algorithm for Hybrid Federated Learning

Very few methods for hybrid federated learning, where clients only hold subsets of both features and samples, exist. Yet, this scenario is very important in practical settings. We provide a fast, robust algorithm for hybrid federated learning that hinges on Fenchel Duality. We prove the convergence of the algorithm to the same solution as if the model was trained centrally in a variety of practical regimes. Furthermore, we provide experimental results that demonstrate the performance improvements of the algorithm over a commonly used method in federated learning, FedAvg, and an existing hybrid FL algorithm, HyFEM. We also provide privacy considerations and necessary steps to protect client data.

Abstract 2565: Vitamin D deficiency and outcomes in prostate cancer patients: A real-world database

Abstract Introduction: Vitamin D is essential for many bodily functions, including bone health and the prevention of osteoporosis and rickets. In recent years, the importance of vitamin D metabolism in immune system regulation and cancer prevention has been studied with increased focus. With the advent of cancer immunotherapies this has become more important. Multiple recent publications document that vitamin D deficiency is prevalent in cancer patients. This has also been observed specifically in prostate cancer patients, with a high percentage of these deficient patients being of African- American ancestry. It has been theorized that high levels of vitamin D deficiency among African American prostate cancer patients could contribute to worse cancer outcomes and increased health disparities. However, routine vitamin D testing has not been commonly performed in the oncologic community. We hypothesized that deficient levels of vitamin D could lead to inferior prostate cancer outcomes in men with a wide range of ethnic and socio-economic backgrounds. In this project we recorded vitamin D levels in prostate cancer patients at a large community oncology group and evaluated them by stage, pathologic data, survival, race/ethnicity, and other clinical features. Methods: This study is a retrospective, observational study of the data from the electronic medical records of patients with prostate cancer who received vitamin D level testing at Florida Cancer Specialists & Research Institute from 2008- 2023, throughout the state of Florida. All data used in this study will constitute secondary data, it will have been collected originally for clinical use in the general oncology practice setting. No date parameters or patient limits will be applied to this study, and all eligible patients are included. Results: 451 patients with prostate cancer had determination of vitamin D levels, out of a total of 27,772 prostate cancer patients in the database. 38% of the prostate cancer patients analyzed had low 25-OH vitamin D levels (<32 ng/ml). Patients with low vitamin D levels had an average Gleason score of 7.46. Patients with low vitamin D levels who died had an average survival of 144 months. Patients with low vitamin D levels who presented with localized disease had a 35% chance of eventually developing castrate-resistant disease. 45% of the low vitamin D group developed metastatic disease during their course of treatment. Further comparisons of vitamin D levels with pathologic data, survival/longevity, race/ethnicity, and clinical course will be evaluated and presented. Citation Format: Lowell L. Hart, James Reeves, Stacey Garofalo, William Amick. Vitamin D deficiency and outcomes in prostate cancer patients: A real-world database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2565.

Multiple arbitrarily inflated Poisson regression analysis

In this paper, a new flexible count regression analysis is proposed. For this purpose, a new modification of the Poisson distribution is introduced which generalizes the Poisson, zero-inflated Poisson, zero-one inflated Poisson, and zero-one-two inflated Poisson distributions. Some distributional properties are discussed for the proposed distribution. The Fisher scoring and EM algorithms are derived to attain the maximum likelihood estimates of the unknown parameters. An expected Fisher information matrix is provided to construct an approximate confidence interval for the parameters. Using the modified Poisson distribution, an arbitrary multiply inflated counting regression model is proposed. The performance of the maximum likelihood methodology is investigated with a simulation study for the distribution and count regression model. Finally, two practical data sets are analyzed and the superiority of the proposed model is demonstrated among others.

A scoping review of pre-employment transition services for transition aged youth with disabilities

BACKGROUND: The Workforce Innovation and Opportunity Act (2014) requires state vocational rehabilitation agencies to dedicate 15% of their budget to providing pre-employment transition services (Pre-ETS) to transition aged youth (TAY) with disabilities. OBJECTIVE: The purpose of this study was to summarize the peer-reviewed, empirical literature focused on Pre-ETS for TAY with disabilities. METHOD: An initial search was completed on October 24th, 2023. A second search was conducted on January 1, 2024 to determine whether any additional publications that met inclusion criteria were published. We used scoping review methods to review, summarize, and identify gaps within the existing literature about Pre-ETS for TAY with disabilities. We identified study characteristics and main areas of foci for each study. RESULTS: A total of 26 peer-reviewed articles published in the United States between 2017–2023 focused on Pre-ETS for TAY with disabilities. Articles focused on (a) participants’ perceptions of Pre-ETS, (b) program and TAY outcomes, and (c) policy analyses. CONCLUSION: Our findings suggest that Pre-ETS are a promising set of practices to increase the postschool outcomes of TAY with disabilities. Implications for practice, research, and policy are discussed.

Strategies for Preparing Future Public Health Leaders: Learning from Trailblazing Women in Health Education

Many female health education pioneers made seminal contributions to public health and social justice, yet these examples are not well documented in textbooks or integrated into public health curricula as pedagogical learning opportunities. Providing biographies and lessons learned from the past leaders within undergraduate health education curricula can help develop students’ skills as future leaders and address gender inequities in the field. Gender inequities in higher education as well as many public health practice settings result in lower salaries, slower career advancement opportunities, fewer supervisory positions, increased work-life conflicts, and heavier workloads. Developing women’s competencies in leadership and professionalism early in their careers is critical to meeting public health challenges such as COVID-19. We present four female health education trailblazers from different historical eras and various workforce sectors who exemplify leadership attributes (i.e., courage/risk taking, vision, advocacy, mentorship) and can be highlighted as a part of future health education curriculum. Innovative methods and approaches are provided for integrating these leadership lessons into undergraduate public health courses, in alignment with the HESPA II 2020 competencies. Learning from the past to inform the future is critical to inspiring and shaping the careers of emerging health educators.

Evaluation of a remote hybrid staffing model for investigational drug service pharmacists.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. This project compared the time to complete investigational prescription drug order verification by investigational drug service (IDS) pharmacists in an onsite vs offsite (hybrid) staffing model, evaluating the impact of remote work on verification time. Parenteral IDS drug orders from August 2019 through June 2022 were analyzed. Electronic medical records were timestamped for each order, first verification, second verification, and medication administration. The project was divided into four 6-month time periods to allow for 2 independent comparisons of onsite vs hybrid staffing models. A survey was given retrospectively to IDS pharmacists for the last hybrid timeframe to assess work satisfaction and burnout. A total of 4,398 orders were evaluated. The time from order entry to first verification was 14 minutes (n = 1,248) during the first onsite time period compared to 13 minutes (n = 1,042) during the first hybrid period (P = 0.003). The time for order verification was similar between the second onsite and hybrid periods (12 minutes [n = 1,041] vs 10 minutes [n= 1,067], respectively; P < 0.0001). The staff satisfaction survey for the hybrid model showed high levels of job satisfaction and no self-reported burnout. The remote hybrid staffing model did not result in a meaningful change in the time from order placement to medication administration within the IDS pharmacy. Hybrid staffing also resulted in greater job satisfaction among IDS pharmacists. This study highlights the benefits of implementing remote work practices in the pharmacy practice setting.

Multidisciplinary First-Line Healthcare Leaders' Roles and Experiences During the COVID-19 Pandemic in Ontario Canada.

Throughout the COVID-19 pandemic, first-line healthcare leaders across the healthcare system played crucial roles leading, motivating, and supporting staff. This study aims to describe multidisciplinary first-line healthcare leaders' experiences during the COVID-19 pandemic in Ontario, Canada using transformational and crisis leadership theory. A descriptive two-phase (quantitative & qualitative) design was conducted in the spring of 2021. Phase 1 employed an online survey sent via email to first-line leaders from various sectors who were members of healthcare professional associations in Ontario. Participants included nurse managers, professional practice leaders (e.g., occupational and physiotherapists), advanced practice nurses, and clinical educators. In Phase 2, a subset (n = 19) of the Phase 1 participants were interviewed to gain a deeper understanding of these leaders' experiences including role impact and support available. Semistructured individual interviews were conducted and recorded via Zoom©. Inductive and deductive analysis approaches identified key themes. This paper reports the qualitative findings from Phase 2. Leaders' behaviors were representative of the key dimensions of transformational and complexity leadership theories. Recommendations for leading during a crisis included: engaging in self-care activities to manage the personal impact of the crisis; teamwork and collaborative leadership; and support from fellow first-line leaders and senior leaders. Findings can inform healthcare leadership education programs designed to manage future crises for both academic and practice settings. Descriptions of first-line healthcare leaders' roles and experiences during multiple waves of the COVID-19 pandemic validated their important contributions within various health sectors.

Spotlight on the real-world treatment of CML pts in Germany: a retrospective survey in private oncology practices

Clinical trials in chronic myeloid leukemia (CML) are usually carried out in specialized centers whereas primary care for patients (pts) with CML is mainly provided by local oncology practices. The aim of this study was to assess treatment practices in pts with CML in the setting of private oncology practices in Germany. We collected data of 819 pts with a confirmed diagnosis (dx) of CML in 2013 or later from 43 practices. At dx, 84.2% (n=690) and 9.4% (n=77) of pts were in chronic or accelerated phase, 0.7% (n=6) had a blast crisis. Molecular monitoring was provided by EUTOS certified laboratories in 87.7% of pts. Typical BCR::ABL1 transcripts were detected in 86.6% (n=709). Molecular response was assessed after 2.8, 6.0, 9.4 and 12.9 m (mean) after start of treatment. Of the pts with available data, 11.1% did not achieve early molecular response and at 18 m, 83.7% had at least a major molecular response. 288 (35.2%) of pts switched to 2nd line (2L) treatment after a mean of 21.0 months. Reasons for 2L treatment were side effects in 43.4% and suboptimal response or failure in 31.4% of pts. 106 pts went on to third line (3L) treatment. 36.8 % of pts switched to and 92.8 % of pts still on 3L treatment achieved BCR::ABL1IS ≤1% at 12 m. In conclusion, in Germany pts with CML are routinely monitored by qPCR and good responses are achieved in the majority. Treatment changes are mainly due to adverse events rather than suboptimal responses.

Restaurants without Bins: How Does a Circular Restaurant Operate?

The circular economy is seen as a potential solution to tackle the environmental concerns of the restaurant industry, offering a set of practices to support the industry in achieving more efficient use of resources and becoming more sustainable. However, studies that focus on the circular economy as a theoretical framework in the restaurant context are scarce. Thus, this study aims to increase understanding of how a circular restaurant operates in practice and provide insight into the circular transformation of restaurants. This article adopts a qualitative, multiple case study methodology, assessing six pioneer restaurants fully embracing a circular economy. The results show that a circular restaurant can be defined as a restaurant based on a systemic design that eliminates waste and keeps materials in circulation. A circular restaurant redesigns and reverses the supply chain, designs circular menus, is committed to closed-loop cooking, and reprocesses the remaining waste. In addition, a circular restaurant features a circular approach to interior design and embraces its social capital. The article includes various practical implications for chefs who can lead the transition to a more circular food system by adopting relevant practices.

Operational Security, Safe Quantum, Space Communications and Data Privacy Cyber Security

In recent years the internet has become an important part of daily life for people around the world. 18 On the other hand, as the effectiveness of the internet increases, cybercrimes also increase. Over the last 15 years, cybersecurity has emerged as a way to accelerate the pace of change in cyberspace. Cybersecurity refers to the procedures a country or organization can use to protect its assets and information in cyberspace. Twenty years ago the term "cybersecurity" was little known to the public [1]. Cybersecurity affects not only people but also organizations or governments. In recent years, everything has been going well and it has used many technologies such as cybernetics, cloud computing, smartphones, and Internet of Things technology. Cyber attacks raise concerns about privacy, security, and financial security. Cybersecurity is a set of technologies, processes, and practices designed to prevent attacks, damage, and unauthorized access to networks, computers, operations, and machines. The main purpose of this article is to provide detailed information about types of cybersecurity, why cybersecurity is important, cybersecurity frameworks, cybersecurity tools, and problem points of cybersecurity [2].

‘Within the limits of decency and modesty’: the construction of cis-heteronormativity in New Brunswick school dress code policies

ABSTRACT This study considers the ways school dress code policies in the Atlantic Canadian province of New Brunswick subtly perpetuate heteronormative and cisgendered assumptions regarding acceptable youth cultures. Although past media attention in the province has drawn attention to their indiscriminate enforcement, little is known on how these policies implicate queer and trans youth. Using critical discourse analysis, I collect and analyse data from 113 dress code policies across the region and examine how the language constructs norms about gender and sexuality. My findings reveal many policies using language which largely excludes the stylistic expression of queer and trans students: The texts nullify overall student sexuality and attempt to stabilise gender in ways that make sense to oppressive systems. I argue that my findings have broader appeal to other educational jurisdictions and can be applied to a wider set of discourses and practices around school dress code policies.

Enhanced electrochemical detection of tartrazine in beverages and liquid soap via nickel phosphide-adorned functionalized carbon nanofibers

BackgroundTartrazine (TAT) is a widely used food colorant dye, offering an orange-yellow hue in various products such as foods, cosmetics, and pharmaceuticals. Despite its popularity, TAT is banned in several countries due to its potential health risks, including respiratory issues, migraines, and skin allergies. Moreover, TAT is linked with adverse effects on human physiology, including mutagenicity, biliary cirrhosis, changes in liver and kidney functions, and neurodegeneration at varying doses. Consequently, the detection of this food additive is crucial for safeguarding human health and protecting aquatic organisms. MethodsIn this study, a novel sensor was developed for the detection of TAT, utilizing a composite material made from nickel phosphide decorated with functionalized carbon nanofiber (Ni2P@f-CNF). The Ni2P@f-CNF was synthesized and characterized through several techniques, including X-ray diffraction, X-ray photoelectron spectroscopy, field emission-scanning electron microscopy, and elemental mapping. The composite was then integrated with a glassy carbon electrode to create a sensor. The sensor's performance was evaluated in terms of detection limit, linear range, selectivity, sensitivity, reproducibility, repeatability, and long-term stability. Main FindingsThe developed Ni2P@f-CNF composite sensor displayed a lower detection limit of 0.011 µM and a broad linear range from 0.01 to 1875 µM. Its selectivity and sensitivity were exceptional, primarily due to the catalytic activity of the Ni2P@f-CNF composite towards TAT. The sensor also demonstrated excellent reproducibility, repeatability, and notable long-term stability. Importantly, when applied in real-world scenarios, the sensor successfully detected TAT in soft drink and liquid soap samples, yielding high recovery rates between 97.45 % to 99.37 % and 98.26 % to 99.01 %, respectively, underscoring its potential applicability in practical settings.

Obstetric imaging practice characteristics associated with prenatal detection of critical congenital heart disease in a rural US region over 20years.

To identify clinical practice characteristics associated with the frequency of prenatal critical congenital heart disease (CCHD) detection (i.e., the number of liveborn infants with postnatally confirmed CCHD identified on prenatal sonography) over 20years in a rural setting comprised of 11 primarily low-volume obstetric hospitals and the single tertiary academic hospital to which they refer. This was a retrospective cohort study of all patients in the referral region with an initial prenatal and/or postnatal diagnosis of CCHD from 01/01/2002 to 12/31/2021. The frequency of prenatal CCHD detection at the time of an obstetric ultrasound was reported, as was the change in detection over time. Critical congenital heart disease detection was assessed as a function of cardiac lesion type, practice setting, and practice characteristics. There were 271 cases with a confirmed postnatal CCHD diagnosis, of which 49% were identified prenatally. The majority of community practices each averaged <10 CCHD cases in total over the study period. Prenatal detection at the tertiary academic hospital's obstetric ultrasound unit was 64%, compared to 22% at the combined referring community practices (p<0.001), though CCHD detection improved over time in both settings. Professional accreditation by the American Institute of Ultrasound in Medicine, image interpretation by radiology or Maternal Fetal Medicine, and use of video clips of ventricular outflow tracts were associated with improved prenatal CCHD detection. Our data demonstrate the infrequency of CCHD cases at small-volume, rural hospitals and the substantial variation in prenatal CCHD detection across practice settings. Our methods allowed for the identification of practice characteristics associated with prenatal CCHD detection.

A qualitative investigation into care-leavers' experiences of accessing mental health support.

People who grew up under the care of children's social services are a highly vulnerable group, with 50% of this population meeting the criteria for a mental health problem at any one time. Emerging evidence suggests that there is a disparity between the number of people who require support, and those that receive it, and that they face several barriers to accessing timely and effective mental health support. We have a limited understanding of how to support the mental health of this group as they 'age out' of children's social services, and the transition to independence, which occurs around the age of 18. We aimed to explore how care-leavers understand their experiences of help-seeking from formal mental health services. We used qualitative interviews, and Interpretative Phenomenological Analysis with 9 care-experienced young people aged between 18 and 25 years old. This work was co-produced by a team of care-experienced adults, from the conception of the study to write-up. Qualitative analysis revealed several themes which centred around: (1) taking reluctant steps towards recovery, (2) challenges with being understood and the importance of gaining an understanding of yourself, (3) navigating trust and (4) the legacy of not having your mental health needs met. We identified several important implications for health and social care practice, across primary and secondary health care settings. This work highlights ways to better support this highly vulnerable group in accessing evidence-based mental health support, and how to maintain engagement.