How Different Are Threshold and Other Specified Feeding and Eating Disorders? Comparing Severity and Treatment Outcome

Background: Other Specified Feeding and Eating Disorders (OSFED) are characterized by less frequent symptoms or symptoms that do not meet full criteria for another eating disorder. Despite its high prevalence, limited research has examined differences in severity and treatment outcome among patients with OSFED compared to threshold EDs [Anorexia Nervosa (AN), Bulimia Nervosa (BN), and Binge Eating Disorder (BED)]. The purpose of the current study was to examine differences in clinical presentation and treatment outcome between a heterogenous group of patients with OSFED or threshold EDs. Method: Patients with threshold EDs (AN = 42, BN = 50, BED = 14) or OSFED (n = 66) presenting for eating disorder treatment completed self-report questionnaires at intake and discharge to assess eating disorder symptoms, depression symptoms, impairment, and self-esteem. Results: At intake, OSFED patients showed lower eating concerns compared to patients with BN, but similar levels compared to AN and BED. The OSFED group showed higher restraint symptoms compared to BED, and similar restraint to AN and BN. Global symptoms as well as shape and weight concerns were similar between OSFED and threshold ED groups. There were no differences between diagnostic groups in self-esteem, depression scores, or symptom change from intake to discharge. Discussion: Our findings suggest that individuals with OSFED showed largely similar ED psychopathology and similar decreases in symptoms across treatment as individuals diagnosed with threshold EDs. Taken together, findings challenge the idea that OSFED is less severe and more resistant to treatment than threshold EDs

The National Teaching Repository − Sharing effective interventions: Learning from each other so that we can continue to enhance and improve what we do

The National Teaching Repository (NTR) is a widely recognised Open Educational Resource (OER) that has made a significant impact on the global higher education community. Recently, the UNESCO Secretariat invited the NTR team to present reports on the repository’s reach and impact (Wooff and Irving-Bell, 2022), which has prompted this article. In it, we provide an overview of the NTR’s origins, values, and vision, and we also extend an invitation for you to join us in this exciting initiative

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Innovative placement allocation model for pre-registration student nurses

Student nurses need a variety of high quality practice placements to prepare them for qualification yet, in reality, this can be difficult to achieve. A practice placement allocation model has enabled one university and its partner healthcare organisations to shift from a traditional, process-led system to a robust, proactive, student-focused approach. The model is based on partnership concepts including advance planning of student placements and clear lines of communication. It has resulted in 100% of first-year students taking part in a new fundamentals of care placement and received positive feedback from students and mentors