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Exploring student motivation to learn is a research area that has rapidly expanded over the past decade, especially as the COVID-19 pandemic continues to influence education. In the field of anatomy, most research about motivation to learn targets medical and other health professional students, but little is known about factors that drive students enrolled in science degrees. The aims of this mixed-methods study were to determine: (1) what motivates undergraduate university science students to learn anatomy, and whether motivation differs between cohorts (second- and third-year) and gender; and (2) the impact of COVID-19 on motivation to learn. Students (n = 171) completed a survey (the Science Motivation Questionnaire II [SMQII] and questions about learning experiences during the pandemic) and a subset (n = 12) participated in focus groups/interviews. Quantitative data were analyzed using a combination of parametric and non-parametric statistics, and a general inductive approach was applied to qualitative data. Grade, intrinsic, and career factors were consistently identified as the key components of motivation. No statistically significant differences were found for motivation components between level of study or gender. Students reported that the COVID-19 pandemic negatively impacted motivational components, but it had also fast-tracked the development of online learning, with both positive and negative connotations. Students value traditional in-person lectures but support a blended approach of traditional and online teaching methods for learning anatomy. Educators should utilize these findings when considering how to teach and support science students in ways that embrace motivational components to foster success in those studying anatomy.

Abstract Over the past five decades, a large number of wild animals have been individually identified by various observation systems and/or temporary tracking methods, providing unparalleled insights into their lives over both time and space. However, so far there is no comprehensive record of uniquely individually identified animals nor where their data and metadata are stored, for example photos, physiological and genetic samples, disease screens, information on social relationships. Databases currently do not offer unique identifiers for living, individual wild animals, similar to the permanent ID labelling for deceased museum specimens. To address this problem, we introduce two new concepts: (1) a globally unique animal ID (UAID) available to define uniquely and individually identified animals archived in any database, including metadata archived at the time of publication; and (2) the digital ‘home’ for UAIDs, the Movebank Life History Museum (MoMu), storing and linking metadata, media, communications and other files associated with animals individually identified in the wild. MoMu will ensure that metadata are available for future generations, allowing permanent linkages to information in other databases. MoMu allows researchers to collect and store photos, behavioural records, genome data and/or resightings of UAIDed animals, encompassing information not easily included in structured datasets supported by existing databases. Metadata is uploaded through the Animal Tracker app, the MoMu website, by email from registered users or through an Application Programming Interface (API) from any database. Initially, records can be stored in a temporary folder similar to a field drawer, as naturalists routinely do. Later, researchers and specialists can curate these materials for individual animals, manage the secure sharing of sensitive information and, where appropriate, publish individual life histories with DOIs. The storage of such synthesized lifetime stories of wild animals under a UAID (unique identifier or ‘animal passport’) will support basic science, conservation efforts and public participation.

Objective: The goal of this study was to assess students' responses to a potentially triggering passage from literature using differing trigger warnings. Participants and Method: 123 undergraduates read a passage which contained depictions of physical and sexual assault. Students were randomly assigned to differing trigger warning conditions prior to reading the passage that anticipated either neutral, positive, or negative emotional reactions. Measures of PTSD symptoms and distress were taken on Day 1, Day 2, and Day 14. Results: Distress to the triggering passage did not vary as a function of either trauma history or trigger warning type. Those with higher PTSD scores to start did not experience more distress over time. Discussion: The data suggest that instructors can assign challenging passages with the expectation that those with related traumas will not be disproportionately affected. In addition, the type of warning is not likely to impact on student emotional responses.

We tested 10 data-based strategies to better identify student homelessness in Camden City School District, which has a student body from minoritized backgrounds. We operationalized strategies through a research-practice partnership, following the federal homelessness definition. Data span 5 years (2014-15 through 2018-19), including integrated education, municipal, and health records. Nine strategies indicated significant unidentified student homelessness (min: 15; max: 5,008; p-values < 0.001). Consistent with homelessness, six strategies produced groups with lower attendance (p-values < 0.01) and seven with increased school mobility (p-values < 0.05). Homelessness was 34% greater in the most conservative interpretation, though counts could be as much as 454% greater. Student homelessness is more prevalent than recognized, data-based strategies can guide proactive outreach, and cross-system partnerships are warranted.

Home-based involvement refers to caregivers' active efforts to create learning opportunities for their children at home and in the community. Across child development, home-based involvement is a positive influence on children's social-emotional and academic functioning. Findings have suggested that home-based involvement tends to decline during elementary and middle school, but the extent to which home-based involvement changes over time during the transition to early elementary school is less clear. Dyadic adjustment is the quality of the relationship between two partners. Grounded in family systems theory, the spillover hypothesis suggests that dyadic adjustment is an important influence on home-based involvement. However, there is limited research on the extent to which dyadic adjustment predicts home-based involvement. The present study used latent growth curve analysis to examine the trajectory of home-based involvement during the transition to early elementary school, as well as the extent to which dyadic adjustment predicts home-based involvement during this transition. Participants were 157 primary caregivers of children in kindergarten through second grade. Results suggest that home-based involvement has a negative, linear trajectory between kindergarten and second grade, and that dyadic adjustment predicts higher levels of home-based involvement at kindergarten, first grade, and second grade. Implications of study findings for research and practice are discussed, with a focus on preventive interventions that aim to promote dyadic adjustment and home-based involvement during the transition to early elementary school.

Summary: Cultivated meat has the potential to revolutionize food production, but its progress is hindered by fundamental shortcomings of mammalian cells with respect to industrial-scale bioprocesses. Here, we discuss the essential role of cell line engineering in overcoming these limitations, highlighting the balance between the benefits of enhanced cellular traits and the associated regulatory and consumer acceptance challenges. We believe that careful selection of cell engineering strategies, including both genetic and non-genetic modifications, can address this trade-off and is essential to advancing the field.

Australia has a rich history of utilising linked administrative data for health and human services research. The Population Health Research Network (PHRN), established in 2009, has developed national population-based data linkage capability and infrastructure. Australia-wide, specialist data linkage units have successfully linked their core population health data for over a decade, and within the network over 200 data collections are routinely linked. Data collections are typically classified as either routinely linked or linked on a project-by-project, ad hoc basis. Over time, linkage of data collections that were originally considered ad hoc, for example some longitudinal cohorts and clinical registries, has become ‘routine’. This paper reports on findings of a study that evaluated the volume and proportion of data linkage requests that have been facilitated through the PHRN over the past 5 years that include ad hoc linkage. The paper also reports on the type of data collections that have been linked on an ad hoc basis and details the type of research projects and fields of research currently supported via ad hoc linkage. Quantifying and characterising the type and most sought-after data collections for ad hoc linkage and the breadth of research being undertaken informs future planning and resource allocation for expanding the Australian national linkage capability. This paper explores the integration of ad hoc data linkage within the evolving landscape of expanded master linkage files and national linked data assets, responding to a growing range of data sources and research that could benefit from population-based data linkage.

Objective In the rapidly evolving landscape of digital health, data sharing using primary health care records has gained prominence. Linking primary care data with other administrative health datasets has the potential to provide a whole-of-life perspective on the patient journey and improve health outcomes. This study aimed to gain insight into Australian General Practitioners' (GPs) perspectives on the use of general practice health records for research and data linkage. Approach The study employed a mixed-methods approach. We conducted semi-structured interviews with GPs who had little experience of data sharing, focusing on understanding the challenges and opportunities that increased data sharing poses. We also conducted a three-round modified Delphi study with GPs with experience of and interest in research and data sharing to refine recommendations for data sharing using general practice data. Results In this paper we describe the findings from both arms of the study and compare their recommendations to contribute to a nuanced understanding of general practitioners’ views on data linkage and sharing in general practice. Conclusions and Implications Bridging the knowledge gap between novices and expert practitioners, the findings will inform policies, practices, and initiatives to address the ethical, legal and social implications of data sharing in general practice settings in Australia.

Objective Research has found general but conditional support for health data being used for public benefit. The term “social licence” describes which uses of health data the public supports and under what conditions. Here, we aim to compare two approaches to understanding community attitudes towards health data use, and how social licence may differ, between Canadian and Australian populations. Approach Factors that affect community support for health data use include the specific population, the type(s) of data, and the engagement approach used. In Canada, facilitated dialogues were held to explore whether (i) there were uses of health data that diverse members of the public all supported and (ii) there was consensus on essential requirements for health data social licence. In Australia, national surveys and citizens’ juries were conducted to better understand (i) attitudes towards private sector data use and (ii) the ethical, legal and social implications of using general practice data in research. Results Despite the different approaches taken, many conditions for social licence were similar across Canadian and Australian participants. Both groups agreed on conditions for health data social licence related to equity, governance, privacy and transparency. However, there was a stark contrast between levels of support for private sector data use, personal control and consent. Conclusion This comparative exercise contributes valuable insights into the ongoing dialogue surrounding community attitudes towards health data use. Continued research monitoring health data social licence across populations is imperative for public trust while gaining full benefits from health data use in research.

Objectives This paper describes a Population Health Research Network project establishing the NMLK as a national linkage system utilising an enduring linkage between national and jurisdictional linkage spines. It used keys from existing enduring linkages within each participating jurisdictional Data Linkage Unit (DLU). The process is demonstrated with reference to an enduring map between AIHW Health Linkage Spine (HLS) and Centre for Health Record Linkage (CHeReL) MLK. Approach The NMLK has jurisdictional sections. The NSW section was established in four steps. • CHeReL provided data from its regularly updated MLK for the NMLK project authorised by existing project ethics approval. • AIHW linked NSW MLK subset to HLS and the de-identified linkage map and report were sent to CHeReL for review. • CHeReL reviewed the results, particularly the additional duplicates identified through the linkage process. The agreed links form the AIHW-NSW section of NMLK quarantined for a year. • The annual update, scheduled for later in 2024, will focus only on linking the new and unlinked individuals in both datasets. Results The NSW cohort was supplied with almost 50 million records, comprising over 14 million unique person ids. Of these, 12 million were matched with reasonable confidence to HLS, or 84.4% of the total (or around 97% if we exclude NSW records with missing personal information and around 140,000 individuals out of scope of HLS.) Conclusion Establishment of the NMLK enabled effective production of high-quality enduring linkage maps used across multiple cross-jurisdictional projects while minimising the privacy risks.

Background Metadata plays a crucial role in the health research infrastructure ecosystem. Despite the abundance of metadata for data collections in Australia, there is no simple way for researchers to search for standardised metadata about linked and linkable data collections across sectors or jurisdictions, making it an arduous and time-intensive task. Methods The project comprised three phases: an initial scoping exercise to understand the current state of metadata and best practice; a national consultation involving researchers data linkage staff and data custodians to develop a high-fidelity prototype; and a final build and implementation phase. The platform underwent several prototyping and testing cycles to refine the digital experience. Results Key expert interviews confirmed that there is a wealth of metadata available in Australia, but it is difficult for researchers to access and evaluate. Consultations with researchers identified opportunities to standardise metadata and provide a centralised platform to enhance the discoverability of linkable data collections for research. High value platform features included searching, browsing and filtering capabilities, variable list metadata, standardised formats, sample data, and frequently asked questions. The final design and functionality reflected user consultations and data custodian input on feasibility and resulted in the standardisation of metadata for linked data collections across sectors and jurisdictions. Conclusion The Population Health Research Network developed and implemented a metadata platform to enable researchers to assess and evaluate the suitability of data collections for data linkage projects more readily. Improved metadata accessibility will save time and enhance the quality of linked data applications.

Background Australia possesses valuable population health data, yet its potential for advancing medical product development remains largely untapped. Transformative growth in the use of linked data in clinical trials will support Australia’s therapeutic development sector to be more responsive in the development of new therapeutics and the monitoring and surveillance of their safety and effectiveness. Methods We conducted interviews with clinical trialists and data linkage experts to understand the current state and awareness of linked data within the clinical trials sector, identify existing pain points in the linkage process, and explore opportunities for improving visibility and access for the clinical trials sector. Researchers represented all stages of the medical product development pipeline and had a diverse range of experience with linked data. Results Interviews revealed numerous barriers hindering the clinical trials sector from effectively using linked data, limiting its impact. Barriers included a lack of awareness, the complexity of the application and approval process, and lengthy delays in accessing data. Participants readily recognised several ways that linkage of real-world data could be applied to their work in clinical trials, with pre-recruitment data, measurements of primary and secondary endpoints, and health economic analysis being the most consistently noted use cases. Conclusion To optimise the use of linked data to support clinical trials and medical product development in Australia, increased awareness among the therapeutic development sector regarding available real-world data and its potential is needed urgently. Lowering the barriers to accessing linked data will enhance health services and patient outcomes across Australia.

The motivation of our study is to provide forecasters and users complementary guidance and tools to identify and predict atmospheric conditions that could lead to life-threatening flash floods. Using hourly and sub-hourly rainfall datasets, proximity radiosondes, ERA5 reanalysis of extreme rainfall events in the UK during 2000–2020, and case studies in 2021, we observe a three-layered atmospheric structure, consisting of Moist Absolute Unstable Layers (MAULs) embedded in a conditional unstable layer sandwiched between a stable upper layer and a near-stable low layer. Based on our analysis, we propose a conceptual model to describe the atmospheric properties of a ‘rainfall extreme’ environment, with a particular focus on the thermodynamics associated with sub-hourly rainfall production processes. We then set this model within a wider framework to describe the precursor synoptic and mesoscale environments necessary for sub-hourly rainfall extremes in the mid-latitudes. We show that evolution of the Omega block and Rex Vortex couplet provides the optimal environmental conditions for sub-hourly rainfall extremes. These results provide the potential to develop a ‘4-stage’ warning system to assist in the identification and forecasting of life threatening short-duration extreme rainfall intensities and flash floods.

Abstract Background This study investigated the role of emotion regulation in relation to the links between fear of missing out (i.e., FOMO) and two components of problematic internet use: problematic social media use and doomscrolling. Methods Participants (N = 603, M age = 30.41, SD age = 7.64; 49.1% male-identifying) completed measures of fear of missing out, intrapersonal and interpersonal emotion regulation, and problematic social media use, and doomscrolling. A parallel mediation model was tested to examine the nature of the associations between fear of missing out, intrapersonal, and interpersonal emotion regulation, in accounting for variance in the outcome measures. Results Analyses revealed that the effect of fear of missing out on problematic social media use was fully mediated by both intrapersonal and interpersonal emotion regulation. In contrast, the effect on doomscrolling was fully mediated by intrapersonal emotion regulation only. Conclusions Findings clarify the role of emotion regulation in explaining the relationship between fear of missing out and two types of problematic internet use, indicating a need to consider individual differences in emotion regulation in an evolving social media landscape.

BackgroundStratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.MethodsWe present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.FindingsWe found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.InterpretationSemantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.FundingNIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

Problematic pornography use is a growing area of interest necessitating a deeper understanding of its contributing factors. Loneliness and emotion regulation difficulties have been advanced as factors that may exacerbate or perpetuate PPU, however, to date, researchers typically consider these factors in isolation. In addition, the evolving landscape of problematic pornography is further shaped by the emergence of pornography content creators. This study explores the relationships between loneliness, emotion regulation difficulties and problematic pornography use and individuals’ interactions with pornography content creators. Specifically, we examine whether emotion regulation difficulties mediate the relationship between loneliness and PPU and whether this mediation is contingent on interactions with content creators. A total of 213 adults (Mage = 35.57 years, SD = 16.90; 77.50 % men) participants completed an online questionnaire assessing PPU, emotion regulation difficulties and loneliness. Results revealed loneliness is associated with increased PPU and emotion regulation difficulties. Emotion regulation difficulties, in turn, relate to PPU. Though interaction with pornographic content creators was associated with reduced PPU, interacting with content creators did not moderate the effect of emotion regulation on the relationship between loneliness and PPU. Our findings support the hypothesised model, suggesting that emotion regulation difficulties mediate the relationship between loneliness and PPU. The identified mediating role of emotion regulation difficulties provides a foundation for further investigations into the underlying mechanisms connecting emotional well-being and problematic pornography use, offering potential directions for future research.

Abstract Operational Meteorologists (OMs) in the Met Office have a perception that elevated convection is not well represented in kilometre‐scale models, which are generally associated with an improved representation of convection. Here, we consider why there may be a problem with representing elevated convection and consider how OMs judge the model to be poor so often. Three OMs have subjectively scored and classified observed elevated convection cases over the UK from 2017 to 2020. Continental plumes (warm, moist, air coming from the near continent or Africa) account for 73% of the cases. The most frequent errors are associated with (i) location, (ii) organisation, (iii) timing and (iv) intensity of the convection. Thus, OMs perceive that the biggest problem with predicting elevated convection is constraining the location of the convective events. The location errors are particularly prevalent for events coming to the UK from the near continent. The location errors are most frequently identified for flow regimes coming from the near continent in weakly forced synoptic conditions. The identification of this problem enables the specific targeting of research into continental plumes (for UK elevated convection) but also raises questions around the role of lateral boundary conditions in the forecasts of elevated convection.