Search

Training and development programs are increasingly delivered online with numerous studies reporting no differences in learning outcomes between online and traditional learning. However, there are no established standardized methods to evaluate the effectiveness of online learning. This review aims to map the state of research around health-related education to determine what elearning evaluation methods are being used, the strengths or deficiencies of these methods, and which are appropriate for measuring the effectiveness of online education. Databases searched were PubMed, ProQuest, Education Resources Information Centre, Cumulative Index to Nursing and Allied Health Literature, Scopus, PsychInfo, and Medline. Studies were included if they were published between 2011 and 2021, reported health-related online education and included an evaluation component. Thirty studies were obtained from numerous countries with varied methodologies and designs. Participants ranged from undergraduate students to medical professionals. Evaluation methods included student participation, students' reaction to the training program, self-efficacy, knowledge assessment, long-term performance, and the Kirkpatrick Evaluation Framework. The review identified that course evaluations, such as measuring student satisfaction scores alone, are insufficient when used to quantify learning effectiveness for online education. This was particularly important as studies are reporting these single metrics as positive effects of training interventions without justification. Suggestions within the reviewed papers were to adopt and implement an appropriate validated method within the course curriculum to evaluate learning outcomes.

The motion of ions in supercapacitor electrodes produces internal stresses that cause viscoelastic strains. In addition, stresses may be due to external forces applied to structural supercapacitors, which are multifunctional materials that simultaneously store energy and carry structural loads. There are currently no thermodynamics-based models for the coupled electro-chemo-viscoelastic response of electrodes. Here, the same thermodynamics model is used for both the viscoelastic response and the electrochemical response. This mathematical equivalence is a reference from which to study coupling between the viscoelastic and electrochemical responses. The model has two inputs (stress or strain and electric potential or specific charge) and two outputs (strain or stress and specific charge or electric potential). The coupling is studied by adding three constants in the free energy. The convexity of the free energy and the stability of the free response limit the magnitude of the coupling. The unit response matrix is derived, and results are given for the time and frequency domains. The effect of an applied potential on stress is shown to be much more significant than the converse effect. The model compares well to an experiment consisting of a cyclic electric current applied during stress relaxation. [ABSTRACT FROM AUTHOR]

Currently, no treatments available for Parkinson's disease (PD) can slow PD progression. At the early stage of the disease, only a subset of individuals with PD progress quickly, while the majority have a slowly progressive form of the disease. In developing treatments that aim to slow PD progression, clinical trials aim to include individuals who are likely to progress faster, such that a treatment effect, if one exists, can be identified easier and earlier. The aim of the present study was to identify baseline predictors of clinical progression in early PD. We analyzed 12-month data acquired from the PASADENA trial Part 1 (NCT03100149, n = 76 participants who were allocated to the placebo arm and did not start symptomatic therapy) and the Parkinson's Progression Markers Initiative (PPMI) study (n = 139 demographically and clinically matched participants). By using ridge regression models including clinical characteristics, imaging, and non-imaging biomarkers, we found that Hoehn and Yahr stage and dopamine transporter single-photon emission computed tomography specific binding ratios (Dat-SPECT SBR) in putamen ipsilateral to the side of motor symptom onset predicted PD progression at the early stage of the disease. Further studies are needed to confirm the validity of these predictors to identify with high accuracy individuals with early PD with a faster progression phenotype.

Background: Currently available treatments for Parkinson's disease (PD) do not slow clinical progression nor target alpha-synuclein, a key protein associated with the disease. Objective: The study objective was to evaluate the efficacy and safety of prasinezumab, a humanized monoclonal antibody that binds aggregated alpha-synuclein, in individuals with early PD. Methods: The PASADENA study is a multicenter, randomized, double-blind, placebo-controlled treatment study. Individuals with early PD, recruited across the US and Europe, received monthly intravenous doses of prasinezumab (1,500 or 4,500 mg) or placebo for a 52-week period (Part 1), followed by a 52-week extension (Part 2) in which all participants received active treatment. Key inclusion criteria were: aged 40-80 years; Hoehn & Yahr (H&Y) Stage I or II; time from diagnosis ≤2 years; having bradykinesia plus one other cardinal sign of PD (e.g., resting tremor, rigidity); DAT-SPECT imaging consistent with PD; and either treatment naïve or on a stable monoamine oxidase B (MAO-B) inhibitor dose. Study design assumptions for sample size and study duration were built using a patient cohort from the Parkinson's Progression Marker Initiative (PPMI). In this report, baseline characteristics are compared between the treatment-naïve and MAO-B inhibitor-treated PASADENA cohorts and between the PASADENA and PPMI populations. Results: Of the 443 patients screened, 316 were enrolled into the PASADENA study between June 2017 and November 2018, with an average age of 59.9 years and 67.4% being male. Mean time from diagnosis at baseline was 10.11 months, with 75.3% in H&Y Stage II. Baseline motor and non-motor symptoms (assessed using Movement Disorder Society-Unified Parkinson's Disease Rating Scale [MDS-UPDRS]) were similar in severity between the MAO-B inhibitor-treated and treatment-naïve PASADENA cohorts (MDS-UPDRS sum of Parts I + II + III [standard deviation (SD)]; 30.21 [11.96], 32.10 [13.20], respectively). The overall PASADENA population (63.6% treatment naïve and 36.4% on MAO-B inhibitor) showed a similar severity in MDS-UPDRS scores (e.g., MDS-UPDRS sum of Parts I + II + III [SD]; 31.41 [12.78], 32.63 [13.04], respectively) to the PPMI cohort (all treatment naïve). Conclusions: The PASADENA study population is suitable to investigate the potential of prasinezumab to slow disease progression in individuals with early PD. Trial Registration: NCT03100149.

Electrical resistivity tomography (ERT), a geophysical imaging method, is commonly used on flood embankments (dykes or levees) to characterize their internal structure and look for defects. These surveys often use a single line of electrodes to enable 2-D imaging through the embankment crest, an approach that enables rapid and efficient surveying compared to 3-D surveys. However, offline variations in topography can introduce artefacts into these 2-D images, by affecting the measured resistivity data. Such topographic effects have only been explored on a site-specific basis. If the topographic effects can be assessed for a distribution of embankment geometries (e.g. slope angle and crest width) and resistivity variations, it would allow for targeted correction procedures and improved survey design. To investigate topographic effects on ERT measurements, we forward-modelled embankments with different trapezoidal cross-sections sat atop a flat foundation layer with contrasting resistivity values. Each was compared to a corresponding flat model with the same vertical resistivity distribution. The modelling workflow was designed to minimize the effect of forward modelling errors on the calculation of topographic effect. We ran 1872 unique embankment forward models, representing 144 geometries, each with 13 different resistivity contrasts. Modelling results show that offline topography affects the tested array types (Wenner–Schlumberger, Dipole–Dipole and Multiple–Gradient) in slightly different ways, but the magnitudes are similar, so all are equally suitable for embankment surveys. Three separate mechanisms are found to cause topographic effects. The dominant mechanism is caused by the offline topography confining the electrical current flow, increasing the measured transfer resistance from the embankment model. The two other mechanisms, previously unidentified, decrease the measured transfer resistances from the embankment model compared to a layered half-space but only affect embankments with specific geometries and resistivity distributions. Overall, we found that for typical embankment geometries and resistivity distributions, the resistivity distribution has a greater control on the magnitude of the topographic effect than the exact embankment geometry: the subsurface resistivity distribution cannot be neglected. 2-D inversions are suitable when both the embankment is more resistive than the foundations and when the embankment's cross-sectional area is greater than 4 m2 m−2 (area scaled to an embankment with a height of 1 m). Topographic corrections, 3-D data acquisition or 3-D forward models are required when these conditions are not met. These are demonstrated using field data from an embankment at Hexham, Northumberland, UK. Improving the accuracy of the resistivity values in ERT models will enable more accurate ground models, better integration of resistivity data with geotechnical data sets, and will improve the translation of resistivity values into geotechnical properties. Such developments will contribute to a better characterized and safer flood defence network. [ABSTRACT FROM AUTHOR]