Quantitative Assessment Research Articles

Enhancing students’ authentic mathematical problem-solving skills and confidence through error analysis of GPT-4 solutions

Authentic mathematical problems connect mathematics to real-life scenarios, making mathematics learning more meaningful. However, students often find it challenging to comprehend the complexity and extensive textual descriptions of authentic mathematical problems, resulting in a lack of mathematical confidence. This study aims to investigate whether error analysis learning activity of GPT-4 solutions can enhance the skill of fifth-grade students to solve authentic mathematical problems and foster their mathematical confidence. A quasi-experimental design was employed, involving 59 fifth-grade students from a primary school in northern Taiwan. The experimental group engaged in error analysis learning activity of GPT-4 solutions, while the control group received traditional instruction, with both groups using the same teaching materials. Quantitative assessments were conducted through tests on solving authentic mathematical problems and a mathematical confidence scale, complemented by qualitative data collected via semi-structured interviews. The results revealed that the experimental group showed significant improvement in solving authentic mathematical problems, both in pre- and post-test comparisons within the group and in post-test comparisons between groups. Furthermore, the low-achieving students in the experimental group showed a significant improvement in solving authentic mathematical problems compared to the control group. Additionally, the mathematical confidence of both high- and low-achieving students in the experimental group was significantly higher than that of the control group. This study confirms the effectiveness of GPT-4 in mathematics education, offering new teaching strategies and research directions for educators and researchers.

Quantitative Risk Assessment of Wellbore Collapse of Inclined Wells in Formations with Anisotropic Rock Strengths

Quantitative Risk Assessment of Wellbore Collapse of Inclined Wells in Formations with Anisotropic Rock Strengths

Reducing stigma and improving access to care for people with mental health conditions in the community: protocol for a multi-site feasibility intervention study (Indigo-Local)

Abstract Background Stigma and discrimination towards people with mental health conditions by their communities are common worldwide. This can result in a range of negative outcomes for affected persons, including poor access to health care. However, evidence is still patchy from low- and middle-income countries (LMICs) on affordable, community-based interventions to reduce mental health-related stigma and to improve access to mental health care. Methods This study aims to conduct a feasibility (proof-of-principle) pilot study that involves developing, implementing and evaluating a community-based, multi-component, awareness-raising intervention (titled Indigo-Local), designed to reduce stigma and discrimination and to increase referrals of people with mental health conditions for assessment and treatment. It is being piloted in seven sites in five LMICs—China, Ethiopia, India, Nepal and Tunisia—and includes several key components: a stakeholder group workshop; a stepped training programme (using a ‘Training of Trainers’ approach) of community health workers (or similar cadres of workers) and service users that includes repeated supervision and booster sessions; community engagement activities; and a media campaign. Social contact and service user involvement are instrumental to all components. The intervention is being evaluated through a mixed-methods pre-post study design that involves quantitative assessment of stigma outcomes measuring knowledge, attitudes and (discriminatory) behaviour; quantitative evaluation of mental health service utilization rates (optional, where feasible in sites); qualitative exploration of the potential effectiveness and impact of the Indigo-Local intervention; a process evaluation; implementation evaluation; and an evaluation of implementation costs. Discussion The output of this study will be a contextually adapted, evidence-based intervention to reduce mental health-related stigma in local communities in five LMICs to achieve improved access to healthcare. We will have replicable models of how to involve people with lived experience as an integral part of the intervention and will produce knowledge of how intervention content and implementation strategies vary across settings. The intervention and its delivery will be refined to be feasible and ready for larger-scale implementation and evaluation. This study thereby has the potential to make an important contribution to the evidence base on what works to reduce mental health-related stigma and discrimination and improve access to health care.

Engaging Adolescents: Innovative ESL Teaching Strategies for Teen Learners

This study investigated the effectiveness of innovative ESL teaching strategies tailored specifically for teenage learners, focusing on the integration of digital tools and culturally relevant materials. Participants aged 13 to 19 were subjected to a mixed-methods approach, combining quantitative assessments of language skills and qualitative feedback through interviews and focus groups. Results indicated significant improvements in both test scores and student engagement, highlighting the crucial role of adapting educational strategies to the developmental needs and interests of teenagers. The research confirms that interactive and relevant teaching approaches can profoundly enhance learning outcomes in ESL contexts.

Artificial Intelligence and Image Analysis-Assisted Diagnosis for Fibrosis Stage of Metabolic Dysfunction-Associated Steatotic Liver Disease Using Ultrasonography: A Pilot Study

Purpose: Elastography increased the diagnostic accuracy of liver fibrosis. However, several challenges persist, including the widespread utilization of equipment, difficulties in measuring certain cases, and the influence of viscosity factors. A rough surface and a blunted hepatic margin have long been acknowledged as valuable characteristics indicative of hepatic fibrosis. The objective of this study was to conduct an image analysis and quantitative assessment of the contour of the sagittal section of the left lobe of the liver. Methods: Between February and October 2020, 486 consecutive outpatients underwent ultrasound examinations at our hospital. A total of 214 images were manually annotated by delineating the liver contour to create annotation images. U-Net was employed for liver segmentation, with the dataset divided into training (n = 128), testing (n = 42), and validation (n = 44) subsets. Additionally, 43 Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) cases with pathology data from between 2015 and 2020 were included. Segmentation was performed using the program developed in the first step. Subsequently, shape analysis was conducted using ImageJ. Results: Liver segmentation exhibited high accuracy, as indicated by Dice loss of 0.044, Intersection over Union of 0.935, and an F score of 0.966. The accuracy of the classification of the liver surface as smooth or rough via ResNet 50 was 84.6%. Image analysis showed MinFeret and Minor correlated with liver fibrosis stage (p = 0.046, 0.036, respectively). Sensitivity, specificity, and AUROC of Minor for ≥F3 were 0.571, 0.862, and 0.722, respectively, and F4 were 1, 0.600, and 0.825, respectively. Conclusion: Deep learning segmentation of the sagittal cross-sectional contour of the left lobe of the liver demonstrated commendable accuracy. The roughness of the liver surface was correctly judged by artificial intelligence. Image analysis showed the thickness of the left lobe inversely correlated with liver fibrosis stage.

Digital Health Platform for Improving the Effect of the Active Health Management of Chronic Diseases in the Community: Mixed Methods Exploratory Study

Background China is vigorously promoting the health management of chronic diseases and exploring digital active health management. However, as most medical information systems in China have been built separately, there is poor sharing of medical information. It is difficult to achieve interconnectivity among community residents’ self-testing information, community health care information, and hospital health information, and digital chronic disease management has not been widely applied in China. Objective This study aimed to build a digital health platform and improve the effectiveness of full-cycle management for community chronic diseases through digital active health management. Methods This was a single-arm pre-post intervention study involving the development and use of a digital health platform (2-year intervention; 2020 to 2022). The digital health platform included the “i Active Health” applet for residents and the active health information system (cardio-cerebrovascular disease risk management system) for medical teams. The digital active health management of chronic diseases involved creating health streets, providing internet-assisted full-cycle active health services for residents, implementing internet-based community management for hypertension and diabetes, and performing real-time quantitative assessment and hierarchical management of residents’ risks of cardio-cerebrovascular disease. After the 2-year intervention, management effectiveness was evaluated. Results We constructed a digital health platform with interconnected health information and implemented a digital active health management model. After the intervention, the 2-way referral between community health care institutions and hospitals increased. Residents’ health literacy rate increased from 30.6% (3062/10,000) in 2020 to 49.9% (4992/10,000) in 2022, with improvements in health knowledge, health behavior, and health skills. Moreover, the risk of cardio-cerebrovascular disease decreased after the intervention. The community hypertension and diabetes standardized management rates increased from 59.6% (2124/3566) and 55.8% (670/1200) in 2020 to 75.0% (3212/4285) and 69.4% (1686/2430) in 2022, respectively. The control rates of blood pressure in patients with hypertension and blood sugar in patients with diabetes increased from 51.7% (1081/2091) and 42.0% (373/888) in 2020 to 81.2% (1698/2091) and 73.0% (648/888) in 2022, respectively. The intervention improved patients’ BMI, waist circumference, blood uric acid levels, and low-density lipoprotein cholesterol levels. The drug compliance rate of patients with hypertension and diabetes increased from 33.6% (703/2091) and 36.0% (320/888) in 2020 to 73.3% (1532/2091) and 75.8% (673/888) in 2022, respectively. The intervention greatly improved the diet behavior, exercise behavior, and drinking behavior of patients with hypertension and diabetes. Conclusions Our digital health platform can effectively achieve the interconnection and exchange of different health information. The digital active health management carried out with the assistance of this platform improved the effectiveness of community chronic disease management. Thus, the platform is worth promoting and applying in practice.

The Implementation of the Food Quality Protection Act (FQPA) in Increasing the Safety Standards for New Pesticides Used on Foods

This paper examines the Food Quality Protection Act (FQPA) and its impact on enhancing safety standards for pesticides used on food in the United States. Initially, the study explores the Delaney Clause—a strict standard prohibiting carcinogenic food additives—which FQPA replaced with a more flexible "reasonable certainty of no harm" criterion. This shift allows the Environmental Protection Agency (EPA) to assess pesticide risk with consideration of potential benefits, even if a substance is carcinogenic at high doses. The paper also critiques the EPA's implementation challenges, including reliance on quantitative risk assessment (QRA) and cumulative risk assessment, which quantify risks of multiple chemical exposures but face informational and regulatory limitations. Recommendations focus on refining judicial review and integrating cumulative risk assessment to strengthen the FQPA’s capacity to safeguard public health, especially for vulnerable populations such as children. This study underscores the importance of regulatory clarity and rigorous assessment methods in pesticide management.

Comparative analysis of image quality and diagnostic performance among SS-EPI, MS-EPI, and rFOV DWI in bladder cancer.

To compare image quality and diagnostic performance among SS-EPI diffusion weighted imaging (DWI), multi-shot (MS) EPI DWI, and reduced field-of-view (rFOV) DWI for muscle-invasive bladder cancer (MIBC). This retrospective study included 73 patients with bladder cancer who underwent multiparametric MRI in our referral center between August 2020 and February 2023. Qualitative image assessment was performed in 73; and quantitative assessment was performed in 66 patients with maximum lesion diameter > 10mm. The diagnostic performance of the imaging finding of muscle invasion was evaluated in 47 patients with pathological confirmation of MIBC. T2-weighted imaging, SS-EPI DWI, MS-EPI DWI, rFOV DWI, and dynamic contrast-enhanced imaging were acquired with 3T-MRI. Qualitative image assessment was performed by three readers who rated anatomical distortion, clarity of bladder wall, and lesion conspicuity using a four-point scale. Quantitative assessment included calculation of SNR and CNR, and grading of the presence of muscle layer invasion according to the VI-RADS diagnostic criteria. Wilcoxon matched pairs signed rank test was used to compare qualitative and quantitative image quality. McNemar test and receiver-operating characteristic analysis were used to compare diagnostic performance. Anatomical distortion was less in MS-EPI DWI, rFOV DWI, and SS-EPI DWI, in that order with significant difference. Clarity of bladder wall was greater for MS-EPI DWI, SS-EPI DWI, and rFOV DWI, in that order. There were significant differences between any two combinations of the three DWI types, except between SS-EPI DWI and MS-EPI in Reader 1. Lesion conspicuity, diagnostic performance, SNR and CNR were not significantly different among the three DWI types. Among the three DWI sequences evaluated, MS-EPI DWI showed the least anatomical distortion and superior bladder wall delineation but no improvement in diagnostic performance for MIBC. MS-EPI DWI may be considered for additional imaging if SS-EPI DWI is of poor quality.

Quantitative assessment of ultrasound microvessel imaging in Crohn's disease: correlation with pathological inflammation.

Ultrasound microvessel imaging (UMI) may offer noninvasive, highly sensitive microvessel imaging for assessing Crohn's disease (CD). However, a quantification metric that demonstrates a strong correlation with pathological inflammation is preferred. The objective was to determine if UMI can enhance IBD imaging interrogations. UMI was performed on bowel wall segments from patients with CD requiring surgery (n = 55 patients). The vessel-length ratio (VLR) measured by UMI was compared with that obtained using color flow imaging (CFI) and with a histopathologic standard evaluated on all bowel layers. Correlations between VLR and pathological inflammation and receiver operating characteristic (ROC) curves between different groups were analyzed to demonstrate the advantages of VLR with UMI. The correlation between VLR from UMI and pathological inflammation (R = 0.80) outperformed that of VLR from CFI (R = 0.59). UMI showed a significant difference (p < 0.01) between mild and non-mild inflammation cases, while CFI could not (p = 0.014). In the ROC analysis, VLR with UMI demonstrated an area under the curve (AUC) of 0.93, compared to the AUC of 0.80 for VLR with CFI, indicating better identification of pathological inflammation between mild and non-mild cases. For a sub-cohort of patients with stricture without penetrating complications (n = 19), VLR using UMI also showed better correlation (R = 0.93) with pathological inflammation scores and a higher AUC (0.96) than those of VLR using CFI (R = 0.66 and 0.88, respectively). UMI enhances vessel detection sensitivity compared to CFI and more accurately reflects transmural inflammation in small bowel Crohn's disease. VLR using UMI strongly correlates with pathological inflammation, distinguishing between mild and non-mild cases, notably including patients with stricture without penetrating complications. Question Bowel wall thickness and Limberg score from ultrasound are insufficient quantitative metrics for reliable diagnosis of inflammation severity for Crohn's disease. Findings Ultrasound microvessel imaging (UMI) with vessel-length ratio (VLR) is strongly correlated with pathological inflammation and had improved distinction between mild and non-mild inflammation cases. Clinical relevance UMI with VLR has the potential to enhance clinicians' ability to assess disease activity and evaluate therapeutic responses, thereby improving Crohn's disease patient outcomes.

Volumetric Imaging From Raman Perspective: Review and Prospect

AbstractVolumetric imaging, which supports quantitative and comprehensive assessment of a 3D sample from an entire volume, has attracted tremendous attention in biomedical research. Fluorescence imaging techniques, such as optical sectioning and light sheet microscopy, enable to reconstruct the 3D distribution of chemicals within a sample. However, current methods rely on exogenous labels, from which considerable perturbation may be introduced in living systems. Raman imaging offers a feasible solution to visualize components in biological samples in a label‐free manner. Besides, the integration of Raman microscopy with 3D approaches will benefit the research of biomedical samples on novel devices, which is dominated by the strongly enhanced spatial resolution, imaging speed, and overall field of view as well as complemented more details of samples. In this overview, recent achievements in 3D visualization of biological samples from the Raman perspective, are explored including scanning mechanism, light sheet, tomography strategy, compressive sensing, holography, and tissue clearing. Importantly, these platforms are compatible with biomedical research, thus allowing the imaging of chemical constituents and the distribution of samples in a whole volume. As a unique volumetric imaging tool for biological discovery, these methods may provide a strategy to accelerate new discoveries across diverse fields of research.

METHODOLOGICAL APPROACH TO OPTIMIZING THE MANAGEMENT STRATEGY OF THE ASSORTMENT POLICY OF A PHARMACEUTICAL COMPANY BASED ON INVENTORY CONTROL

Abstract Aim is a methodological solution for optimizing the assortment policy management strategy of a pharmaceutical company based on inventory control. Research materials and methods. The study was conducted using the example of the pharmaceutical company Bayer and is based on the principles of positivistic philosophy and a deductive approach. The research materials include primary data from an interview with a pharmaceutical logistics manager and secondary data from prescriptions. The collected data were analyzed by calculating a number of values ​​(economic order volume, reorder point, safety stock, average assortment level) using ABC analysis and cycle counting methods. According to the collected initial information, the assortment portfolio of the analyzed company includes 400 pharmaceutical products. The proposed methodological approach is based on a consistent assessment of the assortment management system in effect in the pharmaceutical company. A qualitative assessment of the assortment status is given for individual items: was it insufficient, excessive, acceptable, or discontinued. Finally, an assortment management strategy was recommended aimed at increasing the efficiency of the assortment policy while minimizing overall costs. The accuracy of the product range accounting process is improved by using the cyclic counting method and ABC classification for each product. Results. The article presents the author's methodological approach to optimizing the product range portfolio of a pharmaceutical company. The proposed approach is based on data on inventory control under conditions of uncertain demand for pharmaceutical products using a continuous analysis policy. A quantitative and qualitative assessment of the product range status for individual drug names was conducted and an adapted product range management strategy was recommended, aimed at improving the efficiency of the product range policy while minimizing overall costs. Conclusion. The accuracy of the product range dynamics accounting process is improved by using the cyclic counting method and ABC analysis of products.

Opportunities and challenges of using circulating tumor DNA to predict lung cancer immunotherapy efficacy.

Immune checkpoint inhibitors (ICIs), particularly anti-programmed death 1 (PD-1)/ programmed death ligand 1 (PD-L1) antibodies, have led to significant progress in lung cancer treatment. However, only a minority of patients have responses to these therapies. Detecting peripheral blood of circulating tumor DNA (ctDNA) allows minimally invasive diagnosis, characterization, and monitoring of lung cancer. ctDNA has potential to be a prognostic biomarker and a predictor of the response to ICI therapy since it can indicate the genomic status and tumor burden. Recent studies on lung cancer have shown that pretreatment ctDNA analysis can detect residual proliferative disease in the adjuvant immunotherapy setting and evaluate tumor burden in patients with metastatic disease. Early ctDNA dynamics can not only predict the clinical outcome of ICI therapy but also help distinguish between pseudoprogression and real progression. Furthermore, in addition to quantitative assessment, ctDNA can also detect genetic predictors of response to ICI therapy. However, barriers still exist in the application of ctDNA analysis in clinical lung cancer treatment. The predictive value of ctDNA in lung cancer immunotherapy requires further identification and resolution of these challenges. This review aims to summarize the existing data of ctDNA analysis in patients receiving immunotherapy for lung cancer, understand the limitations of clinical treatment, and discuss future research directions.

Shear wave elastography based analysis of changes in fascial and muscle stiffness in patients with chronic non-specific low back pain

BackgroundThe quantitative assessment of individual muscle and fascial stiffness in patients with low back pain remains a challenge. This study aimed to compare the stiffness of the thoracolumbar fascia (TLF), erector spinae (ES), and multifidus (MF) in patients with and without chronic non-specific low back pain (CNLBP) using shear wave elastography (SWE). It also sought to explore the relationship between muscle and fascial stiffness and the levels of pain and dysfunction in patients with CNLBP.MethodsIn this cross-sectional study, 30 patients with CNLBP (age 27.40 ± 4.57 years, 19 males, 11 females, BMI 22.96 ± 2.55 kg/m2) and 32 healthy controls (age 27.94 ± 4.94 years, 15 males, 17 females, BMI 22.52 ± 2.26 kg/m2) were enrolled. Stiffness of the TLF, ES, and MF was measured using SWE, and Young’s modulus values were recorded. The numeric rating scale (NRS) for quantifying pain intensity and the Oswestry Disability Index (ODI) scores were recorded for the case group to examine their correlations with the resilience index.ResultsThe CNLBP group exhibited significantly higher shear modulus values at the L4-5 bilateral TLF (left: p = 0.014, d = 0.64; right: p = 0.002, d = 0.86), ES (left: p = 0.013, d = 0.66; right: p = 0.027, d = 0.58), and MF (left: p = 0.009, d = 0.69; right: p = 0.002, d = 0.85) compared to the control group. Comparable findings were observed for the right ES (p = 0.026, d = 0.59) and left MF (p = 0.020, η2 = 0.09) at L1-2. Strong correlations were observed between the shear modulus of the bilateral TLF (left: r = 0.57, p = 0.001; right: r = 0.65, p &amp;lt; 0.001) at L4-5 and the NRS scores. Moderate correlations were noted between the shear modulus of the ES (left: r = 0.42, p = 0.022; right: r = 0.48, p = 0.007) and MF (left: r = 0.50, p = 0.005; right: r = 0.42, p = 0.023) at L4-5 and the NRS scores. Additionally, the shear modulus of the MF (r = 0.50, p = 0.005) on the left side of L1-2 showed similar correlations. Strong correlations were observed between the shear modulus of the bilateral TLF (left: r = 0.60, p &amp;lt; 0.001; right: r = 0.58, p &amp;lt; 0.001) at L4-5 and the ODI scores. Moderate correlations were observed between the shear modulus of the right TLF (r = 0.43, p = 0.017), ES (r = 0.38, p = 0.037), and MF (r = 0.44, p = 0.015) at L1-2, as well as the bilateral MF (left: r = 0.46, p = 0.011; right: r = 0.45, p = 0.012) at L4-5, and the ODI scores. No significant correlations were found at other measurement sites.ConclusionIn patients with CNLBP, the stiffness of the lumbar fascia and muscles is generally higher than in individuals without LBP. However, this increase is not uniform across all lumbar regions, with the most significant changes observed in the L4-5 segments. In addition, higher stiffness may be associated with pain and dysfunction, primarily manifested in the TLF.

Effects of internet-based health education on patients with acute intermittent porphyria.

Acute intermittent porphyria (AIP) is a rare genetic metabolic disorder characterized by acute attacks of neurovisceral symptoms. This disease not only poses a threat to patients' physical and mental well-being, but its frequent acute attacks also have a profound impact on patients' mental state and overall quality of life (QoL). This study aimed to explore the impact of internet-based health education on the acute attacks, mental health, and QoL of patients with AIP. This study employed a pre-post comparison design, recruiting 52 patients diagnosed with AIP and treated at the Second Hospital of Hebei Medical University between September 2021 and May 2023 as the subjects of investigation. All participants underwent a 12-month internet-based health education intervention. Quantitative assessments of the intervention's efficacy in reducing acute attacks, enhancing mental health status, and improving QoL among AIP patients were conducted using various instruments, including measures of acute episode frequency and severity, the Depression Anxiety Stress Scales-21 (DASS-21), the Positive and Negative Affect Schedule (PANAS), and the MOS 36-Item Short Form Health Survey (SF-36). Data were collected at two distinct time points: pre- and post-health education interventions, which were then subjected to comparative analysis. Compared to pre-health education, the frequency of acute attacks among patients with AIP significantly decreased post-health education intervention (p < 0.05). Furthermore, notable improvements were observed in the severity of acute attacks, PANAS scores, DASS-21 scores, and SF-36 scores (p < 0.05). This study validated that health education effectively reduced the frequency and severity of acute attacks in AIP patients while enhancing their mental health status and quality of life. Internet-based health education emerges as a practical and productive strategy for AIP patients.

The last decade of air pollution epidemiology and the challenges of quantitative risk assessment.

Epidemiologic research and quantitative risk assessment play a crucial role in transferring fundamental scientific knowledge to policymakers so they can take action to reduce the burden of ambient air pollution. This commentary addresses several challenges in quantitative risk assessment of air pollution that require close attention. The background to this discussion provides a summary of and conclusions from the epidemiological evidence on ambient air pollution and health outcomes accumulated since the 1990s. We focus on identifying relevant exposure-health outcome pairs, the associated concentration-response functions to be applied in a risk assessment, and several caveats in their application. We propose a structured and comprehensive framework for assessing the evidence levels associated with each exposure-health outcome pair within a health impact assessment context. Specific issues regarding the use of global or regional concentration-response functions, their shape, and the range of applicability are discussed.

Longitudinal ultra-sensitive mutation burden sequencing for precise minimal residual disease assessment in AML.

Relapse is one of the major challenges in clinical treatment of acute myeloid leukemia (AML). Though minimal residual disease (MRD) monitoring plays a crucial role in quantitative assessment of the disease, molecular MRD analysis has been mainly limited to patients diagnosed with gene fusions and NPM1 mutations. Here, we report a longitudinal ultra-sensitive mutation burden (UMB) monitoring strategy for accurate MRD analysis in AML patients regardless of genetic abnormality types. Using a Quantitative Blocker Displacement Amplification (QBDA) sequencing panel with limit of detection below 0.01% variant allele frequency (VAF), a hazard ratio of 14.8 (p < 0.001) is observed in cumulative incidence of relapse analysis of 20 patients with ≥ 2 samples during complete remission (CR). The ROC area under curve (AUC) is 0.98 when predicting relapse within 30 weeks of CR timepoint 2 (N = 20). Furthermore, we demonstrate quantitating VAF below 0.01% is essential for accurate relapse prediction.

Going with the flow: Implementing a 4D flow MRI program at a children's hospital.

Four-dimensional phase contrast MRI (4D flow) has emerged as a versatile imaging technique for comprehensive visualization and both qualitative and quantitative assessment of cardiovascular blood flow. 4D flow is a three-dimensional, time-resolved acquisition that is gated to the cardiac cycle. 4D flow provides cardiovascular velocity and flow assessment across the volume of acquisition and yields a multitude of advanced hemodynamic parameters that help to assess the impact of cardiovascular disease on flow and vice versa, guiding the clinical and surgical management of patients with congenital and acquired heart disease. In the past, lengthy scan acquisition and complex post-processing workflows hindered 4D flow adoption into routine clinical practice. Decreasing image acquisition times and improvements in post-processing techniques have made 4D flow a clinically useful tool. The purpose of this communication is to facilitate more widespread adoption of 4D flow by describing its clinical utility, technical acquisition, optimization, and post-processing in pediatric cardiovascular imaging at our center.

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Coming out of isolation: impacts of COVID-19 on physical activity, diet, mental well-being, and sleep over time

IntroductionThe COVID-19 pandemic lockdown significantly disrupted daily routines and impacted physical activity, diet, mental well-being, and sleep. This mixed-methods study investigates these changes over three periods—pre-pandemic, pandemic onset, and one-year post-onset—to understand their causes and inform public health policy for improved resilience during future crises.MethodsA mixed-methods study was conducted with 34 US participants who completed open-ended qualitative questions and quantitative assessments in May 2020 and May 2021. Participants were recruited via social media from 10 states with high COVID-19 cases. Quantitative data categorized health changes (positive, negative, or no change), while qualitative data were analyzed thematically to explore reasons for these changes and uncover interrelationships among health behaviors.ResultsQuantitative results showed that, during the pandemic onset, most participants experienced negative changes in diet, mental well-being, and sleep, while physical activity varied. By one-year post-onset, improvements were noted across all health pillars, with mental well-being and sleep showing the most significant positive changes. Thematic analysis of qualitative data revealed stress, anxiety, and personal motivations as key drivers of health behaviors. Participants’ narratives provided a deeper understanding of these shifts that a Likert-style survey alone could not capture, highlighting the interconnectedness of health pillars.DiscussionThe findings demonstrate the importance of addressing mental well-being to improve overall health resilience. Public health interventions should prioritize mental health and consider the interrelated nature of health behaviors. The mixed-methods approach combined quantitative trends with qualitative insights, offering a comprehensive understanding of why health changes occurred, providing actionable guidance for future public health policy.

Evaluating small-scale eucalyptus growers’ experience of the EVO mobile application: a comparative analysis of quantitative and qualitative assessment techniques

ABSTRACT Mobile applications (apps) have become widely available as decision support tools in agriculture and forestry worldwide. Owing to the above-mentioned development trend, identifying testing methods that can be easily implemented for evaluating mobile app development targeting rural livelihood-related topics is urgently required. This study examined user experiences with a previously launched and published mobile app (EVO) that small-scale eucalyptus growers can utilize to estimate their gross income and net profit from timber sales. The survey incorporated three user experience assessment methods. The study involved two rounds of data collection regarding the mobile app: the first round concerned version 1.0, whereas the second round referred to version 2.0. The aim was to identify the user experience of the EVO app for guiding further software development to improve its suitability among potential user groups, as well as to estimate the feasibility and usability of survey methods for evaluating mobile apps among smallholders and related stakeholders. The results indicated a remarkable improvement in user satisfaction between the two rounds. Using a combination of system usability scale, user acceptance testing, and quality questions is recommended for collecting valuable and useful feedback for the development of mobile apps.