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Involuntary admissions to psychiatric hospitals are on the rise. If patients at elevated risk of involuntary admission could be identified, prevention may be possible. Our aim was to develop and validate a prediction model for involuntary admission of patients receiving care within a psychiatric service system using machine learning trained on routine clinical data from electronic health records (EHRs).
Methods
EHR data from all adult patients who had been in contact with the Psychiatric Services of the Central Denmark Region between 2013 and 2021 were retrieved. We derived 694 patient predictors (covering e.g. diagnoses, medication, and coercive measures) and 1134 predictors from free text using term frequency-inverse document frequency and sentence transformers. At every voluntary inpatient discharge (prediction time), without an involuntary admission in the 2 years prior, we predicted involuntary admission 180 days ahead. XGBoost and elastic net models were trained on 85% of the dataset. The models with the highest area under the receiver operating characteristic curve (AUROC) were tested on the remaining 15% of the data.
Results
The model was trained on 50 634 voluntary inpatient discharges among 17 968 patients. The cohort comprised of 1672 voluntary inpatient discharges followed by an involuntary admission. The best XGBoost and elastic net model from the training phase obtained an AUROC of 0.84 and 0.83, respectively, in the test phase.
Conclusion
A machine learning model using routine clinical EHR data can accurately predict involuntary admission. If implemented as a clinical decision support tool, this model may guide interventions aimed at reducing the risk of involuntary admission.
The dynamics and nonlinear wave forcing of a flexible floating structure are investigated experimentally and numerically. The floater was designed to match sub-harmonic rigid-body natural frequencies of typical floating wind turbine substructures, with the addition of a flexible bending mode. Experiments were carried out for three sea states with phase-shifted input signals to allow harmonic separation of the measured response. We find for the weakest sea states that sub-harmonic rigid-body motion is driven by even-harmonic difference frequency forcing, and by linear forcing for the strongest sea state. The flexible mode was tested in a soft, linearly forced layout, and a stiff layout, forced by second-, third- and fourth-harmonic frequency content, for increasing severity of the sea state. Further insight is gained by analysis of the amplitude scaling of the resonant response. A new simplified approach is proposed and compared with the recent method of Orszaghova et al. (J. Fluid Mech., vol. 929, 2021, A32). We find that resonant surge and pitch motions are dominated by even-harmonic potential-flow forcing and that odd-harmonic response is mainly potential-flow driven in surge and mainly drag driven in pitch. The measured responses are reproduced numerically with second-order forcing and quadratic drag loads, using a recent and computationally efficient calculation method, extended here for the heave, pitch and flexible motions. We are able to reproduce the response statistics and power spectra for the measurements, including the subharmonic pitch and heave modes and the flexible mode. Deeper analysis reveals that inaccuracies in the even-harmonic forcing content can be compensated by the odd-harmonic loads.
To identify and describe patterns and challenges in communication in sudden-onset major incidents.
Methods:
Systematic scoping review according to Joanna Briggs Institute and PRISMA-ScR guidelines. Data sources included Cochrane Library, EMBASE, PubMed/MEDLINE, Scopus, SweMed+, Web of Science, and Google Scholar. Non-indexed literature was searched as well. The included literature went through data extraction and quality appraisal as per pre-registered protocol.
Results:
The scoping review comprised 32 papers from different sources. Communication breakdown was reported in 25 (78.1%) of the included papers. Inter-authority communication challenges were reported in 18 (56.3%) of the papers. System overload and incompatibility was described in 9 papers (28.1%). Study design was clearly described in 30 papers (93.8%).
Conclusions:
The pattern in major incident communication is reflected by frequent breakdowns with potential and actual consequences for patient survival and outcome. The challenges in communication are predominantly inter-authority communication, system overload and incompatibility, and insufficient pre-incident planning and guidelines.
Natural language processing (NLP) methods hold promise for improving clinical prediction by utilising information otherwise hidden in the clinical notes of electronic health records. However, clinical practice – as well as the systems and databases in which clinical notes are recorded and stored – change over time. As a consequence, the content of clinical notes may also change over time, which could degrade the performance of prediction models. Despite its importance, the stability of clinical notes over time has rarely been tested.
Methods:
The lexical stability of clinical notes from the Psychiatric Services of the Central Denmark Region in the period from January 1, 2011, to November 22, 2021 (a total of 14,811,551 clinical notes describing 129,570 patients) was assessed by quantifying sentence length, readability, syntactic complexity and clinical content. Changepoint detection models were used to estimate potential changes in these metrics.
Results:
We find lexical stability of the clinical notes over time, with minor deviations during the COVID-19 pandemic. Out of 2988 data points, 17 possible changepoints (corresponding to 0.6%) were detected. The majority of these were related to the discontinuation of a specific note type.
Conclusion:
We find lexical and syntactic stability of clinical notes from psychiatric services over time, which bodes well for the use of NLP for predictive modelling in clinical psychiatry.
The surface of the Greenland Ice Sheet is darkening, which accelerates its surface melt. The role of glacier ice algae in reducing surface albedo is widely recognised but not well quantified and the feedbacks between the algae and the weathering crust remain poorly understood. In this letter, we summarise recent advances in the study of the biological darkening of the Greenland Ice Sheet and highlight three key research priorities that are required to better understand and forecast algal-driven melt: (i) identifying the controls on glacier ice algal growth and mortality, (ii) quantifying the spatio-temporal variability in glacier ice algal biomass and processes involved in cell redistribution and (iii) determining the albedo feedbacks between algal biomass and weathering crust characteristics. Addressing these key research priorities will allow us to better understand the supraglacial ice-algal system and to develop an integrated model incorporating the algal and physical controls on ice surface albedo.
The transient pressure field around a moderately thick airfoil is studied as it undergoes ramp-type pitching motions at high Reynolds numbers and low Mach numbers. A unique set of laboratory experiments were performed in a high-pressure wind tunnel to investigate dynamic stall at chord Reynolds numbers in the range of $0.5\times 10^6\leq Re _c\leq 5.5\times 10^6$ in the absence of compressibility effects. In addition to variations of mean angle and amplitude, pitching manoeuvres at reduced frequencies in the range of $0.01\leq k\leq 0.40$ were studied by means of surface-pressure measurements. Independently of the parameter variations, all test cases exhibit a nearly identical stall behaviour characterized by a gradual trailing-edge stall, in which the dynamic stall vortex forms approximately at mid-chord. The location of the pitching window with respect to the Reynolds-number-dependent static stall angle is found to define the temporal development of the stall process. The time until stall onset is characterized by a power law, where a small excess of the static stall angle results in a drastically prolonged stall delay. The reduced frequency exhibits a decrease in impact on the stall development in the case of angle-limited pitching manoeuvres. Beyond a critical reduced frequency, both load magnitudes and vortex evolution become reduced frequency independent and instead depend on the geometry of the motion and the convective time scale, respectively. Overall, the characteristics of vortex evolution induced by dynamic stall show remarkable similarities to the framework of optimal vortex formation reported in Gharib et al. (J. Fluid Mech., vol. 360, 1998, pp. 121–140). The data from this study are publicly available at https://doi.org/10.34770/b3vq-sw14.
The quality of life and lifespan are greatly reduced among individuals with mental illness. To improve prognosis, the nascent field of precision psychiatry aims to provide personalised predictions for the course of illness and response to treatment. Unfortunately, the results of precision psychiatry studies are rarely externally validated, almost never implemented in clinical practice, and tend to focus on a few selected outcomes. To overcome these challenges, we have established the PSYchiatric Clinical Outcome Prediction (PSYCOP) cohort, which will form the basis for extensive studies in the upcoming years.
Methods:
PSYCOP is a retrospective cohort study that includes all patients with at least one contact with the psychiatric services of the Central Denmark Region in the period from January 1, 2011, to October 28, 2020 (n = 119 291). All data from the electronic health records (EHR) are included, spanning diagnoses, information on treatments, clinical notes, discharge summaries, laboratory tests, etc. Based on these data, machine learning methods will be used to make prediction models for a range of clinical outcomes, such as diagnostic shifts, treatment response, medical comorbidity, and premature mortality, with an explicit focus on clinical feasibility and implementation.
Discussions:
We expect that studies based on the PSYCOP cohort will advance the field of precision psychiatry through the use of state-of-the-art machine learning methods on a large and representative data set. Implementation of prediction models in clinical psychiatry will likely improve treatment and, hopefully, increase the quality of life and lifespan of those with mental illness.
The impact of nutrition information on public health is partly determined by the population's level of nutrition literacy (NL), which involves functional NL (such as knowledge of dietary guidelines) and critical NL (such as the ability to distinguish between evidence-based nutrition information and alternative facts). The aim of this cross-sectional study was to describe aspects of functional and critical NL and predictors of NL scores among university students and employees. We recruited at different university campuses, 414 students and 112 employees, of which 80 % were females and 69 % were in the ages of 18–30 years. In total, 82 % reported knowledge about where to find information on nutrition issues, and 70 % were familiar with Norwegian dietary guidelines. Being female, having higher age, being highly physically active and studying or working within health sciences were significant predictors of higher levels of functional nutrition knowledge. Significantly more women than men found it difficult to judge if media information on nutritional issues could be trusted (69 v. 54 %) and found it hard to distinguish between scientific and non-scientific information about diet (60 v. 42 %). Our findings indicate that for a sample of university students and employees, affiliation with health sciences, being female, having a higher age and being physically active were associated with higher functional NL. Women did, however, seem to have lower levels of some aspects of critical NL, e.g. how to critically judge nutrition information. A more thorough assessment of NL in university students and employees should therefore be conducted.
Prototyping is essential for fuzzy front-end product development. The prototyping process answers questions about critical assumptions and supports design decisions, but it is often unstructured and context-dependent. Previously, we showed how to guide novice designers in early development stages with prototyping milestones. Here, we studied the prototyping success perceived by novice design teams. This was done in two steps: (1) teams were asked to assign each prototype to a milestone, a specific purpose, a fidelity level, and a human-centered design lens, and then evaluate the success using a predefined set of criteria. (2) Teams were interviewed about the success of the prototyping process, this time using self-chosen criteria. Results related to (1) show that teams perceived prototyping activities with respect to desirability and problem validation significantly less successful than prototyping activities towards feasibility and solution validation. Results related to (2) show that teams mostly chose success criteria related to how well prototypes supported communication, decision making, learning, and tangibility. This insight may be used to give priorities to further improvement of methods and guidance in these areas.
In this paper, we conceptualize, analyze, and assemble a prototype adaptive surface system capable of morphing its geometric configuration using an array of linear actuators to impose omnidirectional movement of objects that lie on the surface. The principal focus and contribution of this paper is the derivation of feedback control protocols–for regulating the actuators’ length in order to accomplish the object conveyance task–that scale with the number of actuators and the nonlinear kinematic constraints of the morphing surface. Simulations and experimental results demonstrate the advantages of distributed manipulation over static-shaped feeders.
Prototyping is an essential activity in product development, but novice designers lack awareness and purpose when they prototype. To foster prototyping mindsets in novice designers, we introduce a prototyping support tool that structures prototyping activities. This paper outlines the Prototyping Planner's development, evolution, and evaluation by 125 novice designers. The majority of novice designers’ experienced that the Prototyping Planner helped them create purposeful prototypes and evaluate results from prototyping.
The design of government portfolios – that is, the distribution of competencies among government ministries and office holders – has been largely ignored in the study of executive and coalition politics. This article argues that portfolio design is a substantively and theoretically relevant phenomenon that has major implications for the study of institutional design and coalition politics. The authors use comparative data on portfolio design reforms in nine Western European countries since the 1970s to demonstrate how the design of government portfolios changes over time. Specifically, they show that portfolios are changed frequently (on average about once a year) and that such shifts are more likely after changes in the prime ministership or the party composition of the government. These findings suggest a political logic behind these reforms based on the preferences and power of political parties and politicians. They have major implications for the study of institutional design and coalition politics.
A wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.
Methods
Forty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.
Results
Cognitive data significantly classified patients from controls (accuracies = 60–69%; p values = 0.0001–0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.
Conclusions
In this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.
Citizen science has been proposed as one way of engaging local stakeholders in landscape stewardship. In this chapter we analyse the success and challenges of three citizen science schemes that stand out from the majority, because they involve natural resource users directly in monitoring attributes central to their livelihoods (Greenland and Finland) or because of the role of digital technology in facilitating the citizen science activities (Faroe Islands). We describe and explain the activities and outcomes for each of the three schemes, and we present a cross-cutting analysis of the benefits and challenges of such approaches for engaging local stakeholders in landscape stewardship. Our findings suggest that citizen science approaches that involve community members not only in data collection but also in the design of the monitoring and in the interpretation and use of the results for decision-making can be an effective way of facilitating landscape stewardship approaches in the ’real-world’. We suggest that landscape stewardship should include the involvement of citizens in actual monitoring of what is going on. The tools for citizen science, both digital and analogue, however need further development, refinement, and testing to incorporate integration of local and traditional knowledge into national monitoring systems.
Ice algae are a key component in polar marine food webs and have an active role in large-scale biogeochemical cycles. They remain extremely under-sampled due to the coarse nature of traditional point sampling methods compounded by the general logistical limitations of surveying in polar regions. This study provides a first assessment of hyperspectral imaging as an under-ice remote-sensing method to capture sea-ice algae biomass spatial variability at the ice/water interface. Ice-algal cultures were inoculated in a unique inverted sea-ice simulation tank at increasing concentrations over designated cylinder enclosures and sparsely across the ice/water interface. Hyperspectral images of the sea ice were acquired with a pushbroom sensor attaining 0.9 mm square pixel spatial resolution for three different spectral resolutions (1.7, 3.4, 6.7 nm). Image analysis revealed biomass distribution matching the inoculated chlorophyll a concentrations within each cylinder. While spectral resolutions >6 nm hindered biomass differentiation, 1.7 and 3.4 nm were able to resolve spatial variation in ice algal biomass implying a coherent sensor selection. The inverted ice tank provided a suitable sea-ice analogue platform for testing key parameters of the methodology. The results highlight the potential of hyperspectral imaging to capture sea-ice algal biomass variability at unprecedented scales in a non-invasive way.
Based on findings from the literature on campaign effects on the one hand, and the literature on European Parliament elections on the other, we propose a model of European Parliamentary elections in which the campaign shift the calculus of electoral support, making differences in national political allegiances less important and attitudes about the European project more important by informing voters of and getting them interested in European politics. In effect, we argue that the political campaign leading up to the election makes European Parliament elections less second order. While previous studies have demonstrated that EU issues can matter for voting behavior in European Parliament elections, existing research has drawn on post-election surveys that do not enable us to capture campaign effects. Our contribution is to assess the impact of a campaign by utilizing a rolling cross-sectional survey that enables us to track how voters were affected by the campaign. Our findings show that campaigns do have an effect on European Parliament election outcomes, in that they provide information that enables voters to make decisions based on their attitude on European issues, making voter decision-making more dominated by EU issue voting.
Tectatodinium rugulatum (Hansen, 1977) McMinn, 1988, from the lower Danian of Denmark, is considered conspecific with, and a junior synonym of, the extant thermophilic species Tectatodinium pellitum Wall, 1967. However, the Danian material, based on holotype and topotype specimens, appears to show a degree of morphologic variability not seen in younger material. The accepted stratigraphic range base of Tectatodinium pellitum is now extended to the lower Danian, where this species appears to be a useful biostratigraphic marker in the Danish North Sea basin.
In modern democracies, the representation of voter interests and preferences is primarily the job of political parties and their elected officials. These patterns can, however, change when the issues that are at stake concern the interests of social groups represented by all relevant parties of a political system. In this article we focus on the behavior of female MPs in the parliament of Weimar Germany and, thus, on a parliament where legislative party discipline was very high. On the basis of a dataset containing information on the legislative voting behavior of MPs, we show that gender, even when controlling for a battery of further theoretically derived explanatory factors, had a decisive impact on the MPs' voting behavior on a law proposal to curb the spread of sexually transmitted diseases.
Co-morbid major depression occurs in approximately 10% of people suffering from a chronic medical condition such as cancer. Systematic integrated management that includes both identification and treatment has been advocated. However, we lack information on the cost-effectiveness of this combined approach, as published evaluations have focused solely on the systematic (collaborative care) treatment stage. We therefore aimed to use the best available evidence to estimate the cost-effectiveness of systematic integrated management (both identification and treatment) compared with usual practice, for patients attending specialist cancer clinics.
Method
We conducted a cost-effectiveness analysis using a decision analytic model structured to reflect both the identification and treatment processes. Evidence was taken from reviews of relevant clinical trials and from observational studies, together with data from a large depression screening service. Sensitivity and scenario analyses were undertaken to determine the effects of variations in depression incidence rates, time horizons and patient characteristics.
Results
Systematic integrated depression management generated more costs than usual practice, but also more quality-adjusted life years (QALYs). The incremental cost-effectiveness ratio (ICER) was £11 765 per QALY. This finding was robust to tests of uncertainty and variation in key model parameters.
Conclusions
Systematic integrated management of co-morbid major depression in cancer patients is likely to be cost-effective at widely accepted threshold values and may be a better way of generating QALYs for cancer patients than some existing medical and surgical treatments. It could usefully be applied to other chronic medical conditions.