Identifying app components that promote physical activity: a group concept mapping study.

Background: Digital interventions are a promising avenue to promote physical activity in healthy adults. Current practices recommend to include end-users early on in the development process. This study focuses on the wishes and needs of users regarding an a mobile health (mHealth) application that promotes physical activity in healthy adults, and on the differences between participants who do or do not meet the World Health Organization's recommendation of an equivalent of 150 minutes of moderate intensity physical activity. Methods: We used a mixed-method design called Group Concept Mapping. In a first phase, we collected statements completing the prompt "In an app that helps me move more, I would like to see/ do/ learn the following…" during four brainstorming sessions with physically inactive individuals (n = 19). The resulting 90 statements were then sorted and rated by a new group of participants (n = 46). Sorting data was aggregated, and (dis)similarity matrices were created using multidimensional scaling. Hierarchical clustering was applied using Ward's method. Analyses were carried out for the entire group, a subgroup of active participants and a subgroup of inactive participants. Explorative analyses further investigated ratings of the clusters as a function of activity level, gender, age and education. Results: Six clusters of statements were identified, namely 'Ease-of-use and Self-monitoring', 'Technical Aspects and Advertisement', 'Personalised Information and Support', 'Motivational Aspects', 'Goal setting, goal review and rewards', and 'Social Features'. The cluster 'Ease-of-use and Self-monitoring' was rated highest in the overall group and the active subgroup, whereas the cluster 'Technical Aspects and Advertisement' was scored as most relevant in the inactive subgroup. For all groups, the cluster 'Social Features' was scored the lowest. Explorative analysis revealed minor between-group differences. Discussion: The present study identified priorities of users for an mHealth application that promotes physical activity. First, the application should be user-friendly and accessible. Second, the application should provide personalized support and information. Third, users should be able to monitor their behaviour and compare their current activity to their past performance. Fourth, users should be provided autonomy within the app, such as over which and how many notifications they would like to receive, and whether or not they want to engage with social features. These priorities can serve as guiding principles for developing mHealth applications to promote physical activity in the general population.

Association of socioeconomic status and poststroke cognitive function: A systematic review and meta-analysis.

BACKGROUND: Stroke survivors are at high risk of coping with cognitive problems after stroke. In recent decades, the relationship between socioeconomic status (SES) and health-related outcomes has been a topic of considerable interest. Learning more about the potential impact of SES on poststroke cognitive dysfunction is of great importance. OBJECTIVE: The purpose of this systematic review and meta-analysis was to summarize the association between SES and poststroke cognitive function by quantifying the effect sizes of the existing studies. METHOD: We searched studies from PubMed, Ovid, Embase, Cochrane, Scopus, and PsychINFO up to January 30th 2024 and the references of relevant reviews. Studies reporting the risk of poststroke cognitive dysfunction as assessed by categorized SES indicators were included. The Newcastle-Ottawa scale and the Agency for Healthcare Research and Quality were used to evaluate the study quality. Meta-analyses using fixed-effect models or random-effect models based on study heterogeneity were performed to estimate the influence of SES on cognitive function after stroke, followed by subgroup analyses stratified by study characteristics. RESULTS: Thirty-four studies were eligible for this systematic review and meta-analysis. Of which, 19 studies reported poststroke cognitive impairment (PSCI) as the outcome, 13 reported poststroke dementia (PSD), one reported both PSCI and PSD, and one reported vascular cognitive impairment no dementia. The findings showed that individuals with lower SES levels had a higher risk of combined poststroke cognitive dysfunction (odds ratio (OR) = 1.91, 95% confidence interval (CI) = 1.59-2.29), PSCI (OR = 2.09, 95% CI = 1.57-2.78), and PSD (OR = 1.95, 95% CI = 1.48-2.57). Subgroup analyses stratified by SES indicators demonstrated the protective effects of education and occupation against the diagnoses of combined poststroke cognitive dysfunction, PSCI, and PSD. CONCLUSIONS: Stroke survivors belonging to a low SES are at high risk of poststroke cognitive dysfunction. Our findings add evidence for public health strategies to reduce the risk of poststroke cognitive dysfunction by reducing SES inequalities.

Development and validation of metrics for a new RAPN training model.

Robot-assisted partial nephrectomy (RAPN) is a complex and index procedure that urologists need to learn how to perform safely. No validated performance metrics specifically developed for a RAPN training model (TM) exist. A Core Metrics Group specifically adapted human RAPN metrics to be used in a newly developed RAPN TM, explicitly defining phases, steps, errors, and critical errors. A modified Delphi meeting concurred on the face and content validation of the new metrics. One hundred percent consensus was achieved by the Delphi panel on 8 Phases, 32 Steps, 136 Errors and 64 Critical Errors. Two trained assessors evaluated recorded video performances of novice and expert RAPN surgeons executing an emulated RAPN in the newly developed TM. There were no differences in procedure Steps completed by the two groups. Experienced RAPN surgeons made 34% fewer Total Errors than the Novice group. Performance score for both groups was divided at the median score using Total Error scores, into HiError and LoError subgroups. The LowErrs Expert RAPN surgeons group made 118% fewer Total Errors than the Novice HiErrs group. Furthermore, the LowErrs Expert RAPN surgeons made 77% fewer Total Errors than the HiErrs Expert RAPN surgeons. These results established construct and discriminative validity of the metrics. The authors described a novel RAPN TM and its associated performance metrics with evidence supporting their face, content, construct, and discriminative validation. This report and evidence support the implementation of a simulation-based proficiency-based progression (PBP) training program for RAPN.

CT Perfusion Map Synthesis from CTP Dynamic Images Using a Learned LSTM Generative Adversarial Network for Acute Ischemic Stroke Assessment.

Computed tomography perfusion (CTP) is a dynamic 4-dimensional imaging technique (3-dimensional volumes captured over approximately 1 min) in which cerebral blood flow is quantified by tracking the passage of a bolus of intravenous contrast with serial imaging of the brain. To diagnose and assess acute ischemic stroke, the standard method relies on summarizing acquired CTPs over the time axis to create maps that show different hemodynamic parameters, such as the timing of the bolus arrival and passage (Tmax and MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV). However, producing accurate CTP maps requires the selection of an arterial input function (AIF), i.e. a time-concentration curve in one of the large feeding arteries of the brain, which is a highly error-prone procedure. Moreover, during approximately one minute of CT scanning, the brain is exposed to ionizing radiation that can alter tissue composition, and create free radicals that increase the risk of cancer. This paper proposes a novel end-to-end deep neural network that synthesizes CTP images to generate CTP maps using a learned LSTM Generative Adversarial Network (LSTM-GAN). Our proposed method can improve the precision and generalizability of CTP map extraction by eliminating the error-prone and expert-dependent AIF selection step. Further, our LSTM-GAN does not require the entire CTP time series and can produce CTP maps with a reduced number of time points. By reducing the scanning sequence from about 40 to 9 time points, the proposed method has the potential to minimize scanning time thereby reducing patient exposure to CT radiation. Our evaluations using the ISLES 2018 challenge dataset consisting of 63 patients showed that our model can generate CTP maps by using only 9 snapshots, without AIF selection, with an accuracy of 84.37 % .

Predictability and Variation in Language Are Differentially Affected by Learning and Production.

General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory-the component of short-term memory used for temporary storage and manipulation of information. In this study, we consider the relationship between working memory and regularization of linguistic variation. Regularization is a well-documented process whereby languages become less variable (on some dimension) over time. This process has been argued to be driven by the behavior of individual language users, but the specific mechanism is not agreed upon. Here, we use an artificial language learning experiment to investigate whether limitations in working memory during either language learning or language production drive regularization behavior. We find that taxing working memory during production results in the loss of all types of variation, but the process by which random variation becomes more predictable is better explained by learning biases. A computational model offers a potential explanation for the production effect using a simple self-priming mechanism.

Unraveling Temporal Dynamics of Multidimensional Statistical Learning in Implicit and Explicit Systems: An X-Way Hypothesis.

Statistical learning enables humans to involuntarily process and utilize different kinds of patterns from the environment. However, the cognitive mechanisms underlying the simultaneous acquisition of multiple regularities from different perceptual modalities remain unclear. A novel multidimensional serial reaction time task was developed to test 40 participants' ability to learn simple first-order and complex second-order relations between uni-modal visual and cross-modal audio-visual stimuli. Using the difference in reaction times between sequenced and random stimuli as the index of domain-general statistical learning, a significant difference and dissociation of learning occurred between the initial and final learning phases. Furthermore, we used a negative and positive occurrence-frequency-and-reaction-time correlation to indicate implicit and explicit learning, respectively, and found that learning simple uni-modal patterns involved an implicit-to-explicit segue, while acquiring complex cross-modal patterns required an explicit-to-implicit segue, resulting in a X-shape crossing of regularity learning. Thus, we propose an X-way hypothesis to elucidate the dynamic interplay between the implicit and explicit systems at two distinct stages when acquiring various regularities in a multidimensional probability space.

Learning with our peers: peer-led versus instructor-led debriefing for simulated crises, a randomized controlled trial.

BACKGROUND: Although peer-assisted learning is known to be effective for reciprocal learning in medical education, it has been understudied in simulation. We aimed to assess the effectiveness of peer-led compared to instructor-led debriefing for non-technical skill development in simulated crisis scenarios. METHODS: Sixty-one undergraduate medical students were randomized into the control group (instructor-led debriefing) or an intervention group (peer debriefer or peer debriefee group). After the pre-test simulation, the participants underwent two more simulation scenarios, each followed by a debriefing session. After the second debriefing session, the participants underwent an immediate post-test simulation on the same day and a retention post-test simulation two months later. Non-technical skills for the pre-test, immediate post-test, and retention tests were assessed by two blinded raters using the Ottawa Global Rating Scale (OGRS). RESULTS: The participants' non-technical skill performance significantly improved in all groups from the pre-test to the immediate post-test, with changes in the OGRS scores of 15.0 (95% CI [11.4, 18.7]) in the instructor-led group, 15.3 (11.5, 19.0) in the peer-debriefer group, and 17.6 (13.9, 21.4) in the peer-debriefee group. No significant differences in performance were found, after adjusting for the year of medical school training, among debriefing modalities (P = 0.147) or between the immediate post-test and retention test (P = 0.358). CONCLUSIONS: Peer-led debriefing was as effective as instructor-led debriefing at improving undergraduate medical students' non-technical skill performance in simulated crisis situations. Peer debriefers also improved their simulated clinical skills. The peer debriefing model is a feasible alternative to the traditional, costlier instructor model.

Adopting, implementing and assimilating coproduced health and social care innovations involving structurally vulnerable populations: findings from a longitudinal, multiple case study design in Canada, Scotland and Sweden.

BACKGROUND: Innovations in coproduction are shaping public service reform in diverse contexts around the world. Although many innovations are local, others have expanded and evolved over time. We know very little, however, about the process of implementation and evolution of coproduction. The purpose of this study was to explore the adoption, implementation and assimilation of three approaches to the coproduction of public services with structurally vulnerable groups. METHODS: We conducted a 4 year longitudinal multiple case study (2019-2023) of three coproduced public service innovations involving vulnerable populations: ESTHER in Jönköping Region, Sweden involving people with multiple complex needs (Case 1); Making Recovery Real in Dundee, Scotland with people who have serious mental illness (Case 2); and Learning Centres in Manitoba, Canada (Case 3), also involving people with serious mental illness. Data sources included 14 interviews with strategic decision-makers and a document analysis to understand the history and contextual factors relating to each case. Three frameworks informed the case study protocol, semi-structured interview guides, data extraction, deductive coding and analysis: the Consolidated Framework for Implementation Research, the Diffusion of Innovation model and Lozeau's Compatibility Gaps to understand assimilation. RESULTS: The adoption of coproduction involving structurally vulnerable populations was a notable evolution of existing improvement efforts in Cases 1 and 3, while impetus by an external change agency, existing collaborative efforts among community organizations, and the opportunity to inform a new municipal mental health policy sparked adoption in Case 2. In all cases, coproduced innovation centred around a central philosophy that valued lived experience on an equal basis with professional knowledge in coproduction processes. This philosophical orientation offered flexibility and adaptability to local contexts, thereby facilitating implementation when compared with more defined programming. According to the informants, efforts to avoid co-optation risks were successful, resulting in the assimilation of new mindsets and coproduction processes, with examples of how this had led to transformative change. CONCLUSIONS: In exploring innovations in coproduction with structurally vulnerable groups, our findings suggest several additional considerations when applying existing theoretical frameworks. These include the philosophical nature of the innovation, the need to study the evolution of the innovation itself as it emerges over time, greater attention to partnered processes as disruptors to existing power structures and an emphasis on driving transformational change in organizational cultures.

Teaching Medical Students Rapid Ultrasound for shock and hypotension (RUSH): learning outcomes and clinical performance in a proof-of-concept study.

BACKGROUND: Point-of-care ultrasound (POCUS) is a critical diagnostic tool in various medical settings, yet its instruction in medical education is inconsistent. The Rapid Ultrasound for Shock and Hypotension (RUSH) protocol is a comprehensive diagnostic tool, but its complexity poses challenges for teaching and learning. This study evaluates the effectiveness of a single-day training in RUSH for medical students by assessing their performance in clinical scenarios. METHODS: In this prospective single-center observational proof-of-concept study, 16 medical students from Saarland University Medical Center underwent a single-day training in RUSH, followed by evaluations in clinical settings and on a high-fidelity simulator. Performance was assessed using a standardized scoring tool and time to complete the RUSH exam. Knowledge gain was measured with pre- and post-training written exams, and diagnostic performance was evaluated with an objective structured clinical examination (OSCE). RESULTS: Students demonstrated high performance in RUSH exam views across patients (median performance: 85-87%) and improved scanning times, although not statistically significant. They performed better on simulators than on live patients. Written exam scores significantly improved post-training, suggesting a gain in theoretical knowledge. However, more than a third of students could not complete the RUSH exam within five minutes on live patients. CONCLUSIONS: Single-day RUSH training improved medical students' theoretical knowledge and simulator performance but translating these skills to clinical settings proved challenging. The findings suggest that while short-term training can be beneficial, it may not suffice for clinical proficiency. This study underscores the need for structured and possibly longitudinal training programs to ensure skill retention and clinical applicability.

Personalised learning in higher education for health sciences: a scoping review protocol.

BACKGROUND: Personalised learning, an educational approach that tailors teaching and learning to individual needs and preferences, has gained attention in recent years, particularly in higher education. Advances in educational technology have facilitated the implementation of personalised learning in various contexts. Despite its potential benefits, the literature on personalised learning in health sciences higher education remains scattered and heterogeneous. This scoping review aims to identify and map the current literature on personalised learning in health sciences higher education and its definition, implementation strategies, benefits, and limitations. METHODS: A comprehensive search of electronic databases, PubMed, Scopus, Google Scholar, Educational Research Complete, and Journal Storage (JSTOR), will be conducted to identify relevant articles. The search will be limited to articles published in the English language between 2000 and 2023. The search strategy will be designed and adapted for each database using a combination of keywords and subject headings related to personalised learning and health sciences higher education. Eligibility criteria will be applied to screen and select articles. Data extraction and quality assessment will be performed, and thematic synthesis will be used to analyse the extracted data. DISCUSSION: The results of the scoping review will present a comprehensive and coherent overview of the literature on personalised learning in health sciences higher education. Key themes and topics related to personalised learning, its definitions, models, implementation strategies, benefits, and limitations, will be identified. The geographical and temporal distribution of research on personalised learning in health sciences higher education will also be described. This scoping review will provide a structured synthesis of the available evidence on personalised learning in health sciences higher education, highlighting potential gaps and areas for future research. The findings will contribute to ongoing scholarly and policy debates on personalised learning in higher education, informing the development of best practices, guidelines, and future research agendas.

Space as a scaffold for rotational generalisation of abstract concepts.

Learning invariances allows us to generalise. In the visual modality, invariant representations allow us to recognise objects despite translations or rotations in physical space. However, how we learn the invariances that allow us to generalise abstract patterns of sensory data ('concepts') is a longstanding puzzle. Here, we study how humans generalise relational patterns in stimulation sequences that are defined by either transitions on a nonspatial two-dimensional feature manifold, or by transitions in physical space. We measure rotational generalisation, i.e., the ability to recognise concepts even when their corresponding transition vectors are rotated. We find that humans naturally generalise to rotated exemplars when stimuli are defined in physical space, but not when they are defined as positions on a nonspatial feature manifold. However, if participants are first pre-trained to map auditory or visual features to spatial locations, then rotational generalisation becomes possible even in nonspatial domains. These results imply that space acts as a scaffold for learning more abstract conceptual invariances.

How children generalize novel nouns: An eye-tracking analysis of their generalization strategies.

Recent research has shown that comparisons of multiple learning stimuli which are associated with the same novel noun favor taxonomic generalization of this noun. These findings contrast with single-stimulus learning in which children follow so-called lexical biases. However, little is known about the underlying search strategies. The present experiment provides an eye-tracking analysis of search strategies during novel word learning in a comparison design. We manipulated both the conceptual distance between the two learning items, i.e., children saw examples which were associated with a noun (e.g., the two learning items were either two bracelets in a "close" comparison condition or a bracelet and a watch in a "far" comparison condition), and the conceptual distance between the learning items and the taxonomically related items in the generalization options (e.g., the taxonomic generalization answer; a pendant, a near generalization item; versus a bow tie, a distant generalization item). We tested 5-, 6- and 8-year-old children's taxonomic (versus perceptual and thematic) generalization of novel names for objects. The search patterns showed that participants first focused on the learning items and then compared them with each of the possible choices. They also spent less time comparing the various options with one another; this search profile remained stable across age groups. Data also revealed that early comparisons, (i.e., reflecting alignment strategies) predicted generalization performance. We discuss four search strategies as well as the effect of age and conceptual distance on these strategies.

Enhancing capability for continuous organisational improvement and learning in healthcare organisations: a systematic review of the literature 2013-2022.

BACKGROUND: Healthcare organisations strive to meet their current and future challenges and need to increase their capacity for continuous organisational improvement and learning (COIL). A key aspect of this capacity is the development of COIL capability among employees. OBJECTIVE: This systematic review aims to explore common attributes of interventions that contribute to the development of COIL capability in healthcare organisations and to explore possible facilitating and hindering factors. METHODS: A comprehensive search was conducted in Scopus, MEDLINE and Business Source Complete for primary research studies in English or Swedish, in peer-reviewed journals, focusing on organisational improvements and learning in healthcare organisations. Studies were included if they were published between 2013 and 23 November 2022, reported outcomes on COIL capability, included organisations or groups, and were conducted in high-income countries. The included articles were analysed to identify themes related to successful interventions and factors influencing COIL capability. RESULTS: Thirty-six articles were included, with two studies reporting unsuccessful attempts at increasing COIL capability. The studies were conducted in nine different countries, encompassing diverse units, with the timeframes varying from 15 weeks to 8 years, and they employed quantitative (n=10), qualitative (n=11) and mixed methods (n=15). Analysis of the included articles identified four themes for both attributes of interventions and the factors that facilitated or hindered successful interventions: (1) engaged managers with a strategic approach, (2) external training and guidance to develop internal knowledge, skills and confidence, (3) process and structure to achieve improvements and learning and (4) individuals and teams with autonomy, accountability, and safety. CONCLUSION: This review provides insights into the intervention attributes that are associated with increasing COIL capability in healthcare organisations as well as factors that can have hindering or facilitating effects. Strategic management, external support, structured processes and empowered teams emerged as key elements for enhancing COIL capability.

Foundational and Clinical Science Integration in a Team-Based Learning Module Modeling Care of a Patient With Dyslipidemia.

Introduction: Foundational and clinical science integration, a long-standing goal of undergraduate medical education, benefits learners by promoting retention of critical knowledge and skills as well as their transfer to the clinical setting. We implemented a team-based learning (TBL) module in which foundational knowledge and skills from the disciplines of biochemistry, nutrition, and genetics were leveraged in a simulated patient encounter for diagnosis and management of a patient with dyslipidemia. Methods: The TBL was deployed in a first-year medical student cardiovascular system course with 125 students over three academic years. Following individual and team readiness assurance tests (iRAT and tRAT, respectively), teams participated in an initial application exercise requiring consideration of clinical and laboratory data and other risk factors to engage the patient in a shared decision-making process. Using dietary and family history narratives in subsequent application exercises, teams completed recommendations for an individualized diet plan and an assessment of potential disease inheritance patterns to formulate appropriate patient care management strategies. Results: Student engagement with prelearning materials and session team activities was high as judged by RAT performance and application exercise outcomes: iRAT question performance ranged from 89% to 99% for individual items, and tRAT performance was routinely 100%. Learners reported that the exercises were impactful and believed the learned foundational knowledge and skills were transferable to future patient care. Discussion: The dyslipidemia TBL module provides an illustration for early clinical learners of how foundational knowledge and skills can be operationalized and transferred for optimal patient care.

Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students.

ChatGPT (OpenAI), a cutting-edge natural language processing model, holds immense promise for revolutionizing medical education. With its remarkable performance in language-related tasks, ChatGPT offers personalized and efficient learning experiences for medical students and doctors. Through training, it enhances clinical reasoning and decision-making skills, leading to improved case analysis and diagnosis. The model facilitates simulated dialogues, intelligent tutoring, and automated question-answering, enabling the practical application of medical knowledge. However, integrating ChatGPT into medical education raises ethical and legal concerns. Safeguarding patient data and adhering to data protection regulations are critical. Transparent communication with students, physicians, and patients is essential to ensure their understanding of the technology's purpose and implications, as well as the potential risks and benefits. Maintaining a balance between personalized learning and face-to-face interactions is crucial to avoid hindering critical thinking and communication skills. Despite challenges, ChatGPT offers transformative opportunities. Integrating it with problem-based learning, team-based learning, and case-based learning methodologies can further enhance medical education. With proper regulation and supervision, ChatGPT can contribute to a well-rounded learning environment, nurturing skilled and knowledgeable medical professionals ready to tackle health care challenges. By emphasizing ethical considerations and human-centric approaches, ChatGPT's potential can be fully harnessed in medical education, benefiting both students and patients alike.

Orthogonal extended infomax algorithm.

Objective.The extended infomax algorithm for independent component analysis (ICA) can separate sub- and super-Gaussian signals but converges slowly as it uses stochastic gradient optimization. In this paper, an improved extended infomax algorithm is presented that converges much faster.Approach.Accelerated convergence is achieved by replacing the natural gradient learning rule of extended infomax by a fully-multiplicative orthogonal-group based update scheme of the ICA unmixing matrix, leading to an orthogonal extended infomax algorithm (OgExtInf). The computational performance of OgExtInf was compared with original extended infomax and with two fast ICA algorithms: the popular FastICA and Picard, a preconditioned limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm belonging to the family of quasi-Newton methods.Main results.OgExtInf converges much faster than original extended infomax. For small-size electroencephalogram (EEG) data segments, as used for example in online EEG processing, OgExtInf is also faster than FastICA and Picard.Significance.OgExtInf may be useful for fast and reliable ICA, e.g. in online systems for epileptic spike and seizure detection or brain-computer interfaces.

Distinct forms of structural plasticity of adult-born interneuron spines in the mouse olfactory bulb induced by different odor learning paradigms.

The morpho-functional properties of neural networks constantly adapt in response to environmental stimuli. The olfactory bulb is particularly prone to constant reshaping of neural networks because of ongoing neurogenesis. It remains unclear whether the complexity of distinct odor-induced learning paradigms and sensory stimulation induces different forms of structural plasticity. In the present study, we automatically reconstructed spines in 3D from confocal images and performed unsupervised clustering based on morphometric features. We show that while sensory deprivation decreased the spine density of adult-born neurons without affecting the morphometric properties of these spines, simple and complex odor learning paradigms triggered distinct forms of structural plasticity. A simple odor learning task affected the morphometric properties of the spines, whereas a complex odor learning task induced changes in spine density. Our work reveals distinct forms of structural plasticity in the olfactory bulb tailored to the complexity of odor-learning paradigms and sensory inputs.

Program coordinators' perspectives on implementing a transition program for newly graduated nurses: a qualitative interview study.

PURPOSE: While transition programs are widely used to facilitate newly graduated nurses transition to healthcare settings, knowledge about preconditions for implementing such programs in the hospital context is scarce. The purpose of this study was to explore program coordinators' perspectives on implementing a transition program for newly graduated nurses. DESIGN/METHODOLOGY/APPROACH: An explorative qualitative study using individual interviews. Total of 11 program coordinators at five acute care hospital administrations in a south-west region in Sweden. Data was subjected to thematic analysis, using NVivo software to promote coding. FINDINGS: The following two themes were identified from the analysis: Create a shared responsibility for introducing newly graduated nurses, and establish legitimacy of the program. The implementation process was found to be a matter of both educational content and anchoring work in the hospital organization. To clarify the what and why of implementing a transition program, where the nurses learning processes are prioritized, was foundational prerequisites for successful implementation. ORIGINALITY/VALUE: This paper illustrates that implementing transition programs in contemporary hospital care context is a valuable but complex process that involves conflicting priorities. A program that is well integrated in the organization, in which responsibilities between different levels and roles in the hospital organization, aims and expectations on the program are clarified, is important to achieve the intentions of effective transition to practice. Joint actions need to be taken by healthcare policymakers, hospitals and ward managers, and educational institutions to support the implementation of transition programs as a long-term strategy for nurses entering hospital care.

The Contribution of Willingness to Communicate to L2 Learners' Depth of Vocabulary Knowledge: An Empirical Study.

The issues of depth vocabulary knowledge and Willingness to Communicate (henceforth, WTC) are among the most important issues in second language learning. The present study set out to empirically look into the contribution of WTC to depth of vocabulary knowledge in L2 learning. To this end, 88 English L2 learners, divided into two groups in terms of their WTC, were given two depth vocabulary tests. The Word Association Test (WAT) was first administered to make a comparison between the depth vocabulary knowledge of the two WTC groups. Then, to triangulate the results, the Word Part Levels Test (WPLT) was administered to check whether the obtained results confirmed those of WAT. Analyzing data through independent t-test and MANOVA indicated that learners with higher levels of WTC had deeper vocabulary knowledge than those with lower levels of WTC on the WAT. Further, the triangulation results evinced that although the two groups did not differ significantly on the form-section and meaning-section of the WPLT, they significantly differed on the use-section of the test. The relevant pedagogical implications of the study are discussed.