Polynomial Logistic Regression Research Articles

ENHANCING ELECTIVE SURGERY MANAGEMENT WITH OPENPREDICTOR: VALIDATION OF A CLINICAL DECISION AID FOR OPTIMIZING ELECTIVE PATHWAYS

OpenPredictor, a machine learning-enabled clinical decision aid, has been developed to manage backlogs in elective surgeries. It aims to optimise the use of high volume, low complexity surgical pathways by accurately stratifying patient risk, thereby facilitating the allocation of patients to the most suitable surgical sites. The tool augments elective surgical pathways by providing automated secondary opinions for perioperative risk assessments, enhancing decision-making. Its primary application is in elective sites utilising lighter pre-assessment methods, identifying patients with minimal complication risks and those high-risk individuals who may benefit from early pre-assessment.The Phase 1 clinical evaluation of OpenPredictor entailed a prospective analysis of 156 patient records from elective hip and knee joint replacement surgeries. Using a polynomial logistic regression model, patients were categorised into high, moderate, and low-risk groups. This categorisation incorporated data from various sources, including patient demographics, co-morbidities, blood tests, and overall health status.In identifying patients at risk of postoperative complications, OpenPredictor demonstrated parity with consultant-led preoperative assessments. It accurately flagged 70% of patients who later experienced complications as moderate or high risk. The tool's efficiency in risk prediction was evidenced by its balanced accuracy (75.6%), sensitivity (70% with a 95% confidence interval of 62.05% to 76.91%), and a high negative predictive value (96.7%).OpenPredictor presents a scalable and consistent solution for managing elective surgery pathways, comparable in performance to secondary consultant opinions. Its integration into pre-assessment workflows assists in efficient patient categorisation, reduces late surgery cancellations, and optimises resource allocation. The Phase 1 evaluation of OpenPredictor underscores its potential for broader clinical application and highlights the need for ongoing data refinement and system integration to enhance its performance.

Determinants of Household Poverty: Identification Using Logistic Regression

The fight against poverty is considered one of the most critical tasks in achieving sustainable development goals. This study aims to identify the key determinants of household poverty in Algeria. The information base is data from the Sixth Cluster Survey (MICS 6) conducted by the National Statistics Office during 2018-2019 with a sample of 31,325 households in each province, which are divided into three groups (poorest, poor, non-poor) using a well-being index, which is based on the data about household assets and living conditions. Polynomial logistic regression was used to model the correlation between the poverty status of households and various demographic (household size, gender, age and education level of the head of the household), socio-economic (employment of the head of the household) and spatial (place of residence (urban/rural), region) characteristics. The results showed that a higher level of education of the head of the household significantly increased the probability of households moving from the “poorest” to the “poor” or “non-poor”. As the age of the household head increases, the likelihood that the household will be non-poor increases. The gender of the head of the household was not a statistically significant factor. The increase in the number of dependents as a factor of creating additional financial pressure and falling into poverty is essential only in a situation of a very drastic change in status – when moving from the status of “non-poor” to “the poorest”. In contrast, a slight change in well-being (a shift from “poor” to “poorest”) is not associated with an increase in the number of household members. Modeling showed that extreme poverty is more common in rural areas than in cities. Regional differences are also revealed, as the poverty level is higher in the southern regions than in the northern ones. The slight increase in household welfare (transition from the category of “poorest” to “poor”) in Algeria is not due to the economic activity of the head of the household. Still, it may be related to the nature of the analyzed data (only the fact of employment was considered without specifying the nature and type of activity). Instead, a significant change in welfare (moving from the category of “non-poor” to “poorest” households) directly depends on whether the head of the household is employed or unemployed. The results of the study are essential in the context of the development of a targeted policy to reduce the poverty risks of Algerian households: increasing the level of education and skills should be a priority, especially for young people and in disadvantaged regions, targeted programs for the development of rural areas and mechanisms for the fair distribution of public investments between provinces are needed to overcome regional disproportions.

Pandemic Pressure: Changes in Hypertensive Management Adherence in Indonesia

PurposeThis study aimed to determine factors associated with changes in adherence to hypertension management (medication adherence and blood pressure control) in respondents with hypertension before and during the COVID-19 pandemic in Bogor City, Indonesia. MethodsAn observational study was conducted using two sources of data (before and during COVID-19 pandemic). Data before the pandemic were derived from the 2019 Cohort Study of Non-communicable Disease Risk Factors. Data during the pandemic were derived from an online survey conducted in September and October 2020. Information from 880 participants were analyzed. The dependent variable was the change in adherence to hypertension management before and during the COVID-19 pandemic. Multivariate analysis was performed using logistic polynomial regression. ResultsRespondents who adhered to hypertension management decreased from 82.0% in 2019 to 47.8% in 2020. The likelihood of non-adherence (respondents who did not adhere to hypertension management both before and during the pandemic) increased in respondents below 55 years old, who did not own any healthcare insurance, who were not obese, and who had no other comorbidities. In the partial adherence group (respondents who did not adhere to hypertension management either before or during the pandemic), we found that most respondents adhered before the pandemic but no longer adhered during the COVID-19 pandemic. We found an increased partial adherence in young and highly educated respondents. ConclusionEfforts to improve adherence to hypertension management after the COVID-19 pandemic should target those who were young, highly educated, who did not have any healthcare insurance, and who did not perceive themselves as not having comorbidities.

The link between functional response and longevity of Trichogramma evanescens strains indigenous to Türkiye: A comparative assessment of parameters

AbstractA previous comprehensive survey in the Mediterranean and Southeastern regions of Türkiye investigating the natural egg parasitism of lepidopteran maize pests, Sesamia spp, (Lepidoptera: Noctuidae) Ostrinia nubilalis Hbn. and Chilo partellus (Swinhoe; Lepidoptera: Crambidae) by Trichogramma evanescens Westwood (Hymenoptera: Trichogrammatidae) yielded successful establishment of laboratory cultures of six strains molecularly clustering into two main groups. In this study, the functional response and adult longevity of the strains reared and tested on a factitious host, Ephestia kuehniella Zeller (Lepidoptera: Pyralidae) were investigated to provide insights into their potential as candidate biocontrol agents under constant laboratory conditions. The functional response modelling process consisted of two main sequential steps: model selection using polynomial logistic regression and parameter estimation using an iterative maximum likelihood estimation method. The functional response of two strains showed negative linear parameters (type II): HAP068M and HAP268S. Although their attack rate did not differ, the handling time of HAP268S was longer than that of HAP068M. In contrast, four strains had positive linear and negative quadratic parameters (type III) in their functional response: HAP044S, HAP070S, HAP210S, and HAP258M. The strains exhibiting type III functional response did not differ in their handling time, while HAP044S had a higher attack coefficient than HAP070S, HAP210S, and HAP258M. The longevity of both female and male adults significantly differed between strains. More importantly, the females belonging to strains exhibiting type II functional response presented a shorter longevity, compared to those with type III functional response. Males also showed a similar trend in their longevity. This paper discusses the differences in functional response types and estimated parameters of the strains in relation to their relevance for biological control programs and reveals a link between their functional response and longevity as potential reciprocal predictors.

Probabilistic Safe WCET Estimation for Weakly Hard Real-time Systems at Design Stages

Weakly hard real-time systems can, to some degree, tolerate deadline misses, but their schedulability still needs to be analyzed to ensure their quality of service. Such analysis usually occurs at early design stages to provide implementation guidelines to engineers so they can make better design decisions. Estimating worst-case execution times (WCET) is a key input to schedulability analysis. However, early on during system design, estimating WCET values is challenging, and engineers usually determine them as plausible ranges based on their domain knowledge. Our approach aims at finding restricted, safe WCET sub-ranges given a set of ranges initially estimated by experts in the context of weakly hard real-time systems. To this end, we leverage (1) multi-objective search aiming at maximizing the violation of weakly hard constraints to find worst-case scheduling scenarios and (2) polynomial logistic regression to infer safe WCET ranges with a probabilistic interpretation. We evaluated our approach by applying it to an industrial system in the satellite domain and several realistic synthetic systems. The results indicate that our approach significantly outperforms a baseline relying on random search without learning and estimates safe WCET ranges with a high degree of confidence in practical time (< 23 h).

CONSUMER INTEREST IN THE PROBOLAJANG PIPELINED DRINKING WATER SUPPLY SYSTEM

Procurement of regional piped drinking water supply system for Probolinggo and Lumajang Regency (Probolajang) is an effort by Government to improve drinking water supply system services. This research aims to analyze the public's interest in becoming consumers of the Probolajang piped drinking water supply system. The research area consist of 6 districts in Probolinggo Regency, 3 districts in Lumajang Regency and 3 districts in Probolinggo City. Respondents are families who are not subsribing to existing water system. The dependent variable is the respondent's interest in subscribing to the drinking water supply system. The independent variables are education, income, quality, quantity and continuity of raw water. Analysis method that used for this study is polynomial logistic regression. The result proves that the variables of education level, income and quantity of raw water have positive relationship with respondents' interest in becoming consumers. Meanwhile, quality and continuity of raw water have negative relationship.

SCAI Staging Application for Acute Myocardial Infarction-Related Cardiogenic Shock at a Single-Center Russian Registry.

To access the features of the course of myocardial infarction (MI) in patients with different stages of MI complicated by cardiogenic shock (MI CS) according to the SCAI scale. We retrospectively described the portrait of CS MI (n = 117) at different stages of SCAI from the hospital MI registry (n = 1253). Hospital mortality increased from stage to stage (p ≤ 0.001). Significant differences in biochemical parameters were found both for indicators characterizing intensive care measures, such as the presence of mechanical lung ventilation or an intra-aortic balloon pump, and for indicators of organ hypoperfusion such as lactate level, pHv (7.39 (7.36; 7.44) at stage A-B; 7.14 (7.06; 7.18) at stage E), creatinine, and glomerular filtration rate. Parameters related to MI characteristics, such as instrumental and laboratory data, anamnesis of ischemia, and performed treatment, did not differ between groups. Polynomial logistic regression showed that lactate level, mechanical ventilation, and monocyte count upon admission (1.15 (0.96; 1.23) at stage A-B; 0.78 (0.49; 0.94) at stage E, p = 0.005) correlated with CS severity. The characteristics of MI at different stages of SCAI do not have differences and do not determine the severity of shock. We revealed a high discriminatory potential of the pH level in predicting refractory shock. The value of monocytes at admission may be a promising predictor of the severity of MI CS. The question of the causes of heterogeneity of MI CS, taking into account the homogeneity of MI characteristics, remains open and promising.

Analysis of the Impact of Livelihood Capital on Livelihood Strategies of Leased-In Farmland Households: A Case Study of Jiangxi Province, China

In the context of the implementation of the rural revitalization strategy, the industrialization of agriculture and rural areas is rapidly increasing, and more and more capable people in rural management are actively leasing land to develop modern agriculture, broaden diversified livelihood channels, and pursue sustainable development. We used leased-in farmland households as an entry point, focusing on the development of rural industries and the choice of livelihood strategies to fill a gap in the existing literature. Based on sustainable livelihood theory, we constructed a sustainable livelihood analysis framework for leased-in farmland households using the survey data of 283 leased-in farmland households in Yudu County. A livelihood capital indicator system was constructed, and the entropy value method and other measurement methods were used. Firstly, we analyzed and comprehensively evaluated the livelihood capital and livelihood strategies of leased-in farmland households in Yudu County, Jiangxi Province. We then used binary logistic regression models and polynomial logistic regression models to analyze the influence of the differentiation in leased-in farmland households’ livelihood capital on the choice of livelihood strategies and their transformation and conducted robustness tests on the relevant findings. Different types of livelihood capital have different effects on agriculture-led livelihood strategies. Natural capital and physical capital have significant positive effects on agriculture-led livelihood strategies, but financial capital, human capital, and social capital have negative effects. Natural capital has a significant negative effect on the pluriactivity strategy, while physical, human, and social capital have insignificant effects on it. For off-farm livelihood strategies, natural capital and financial capital have insignificant effects, physical capital has a significant negative effect, and human capital and social capital have a significant positive contribution.

Automated algorithm for diagnosing gastrointestinal bleeding

BACKGROUND: Gastrointestinal bleeding (GIB) is a complication of many diseases of the gastrointestinal tract (GIT), including erosive and ulcerative lesions, vascular malformations, diverticula, and tumors. In developed countries, the GIB mortality rate ranges from 5% to 15%, reaching 30%40% in the group of patients with severe recurrent bleeding.
 AIM: The study aimed to develop an automated diagnostic algorithm for patients with GIB.
 METHODS: Knowledge engineering is used to extract terms and their relationships from the scientific literature related to the GIT. After agreement with the experts, information on the diagnosis and treatment of patients with GIB was arranged using a MS Excel spreadsheet editor. For building GIB localization rules, the study included data from histories of 280 patients aged 2094 years (61 [44; 74]); of these, 47.5% were women, while all others were men. The patients were diagnosed and treated at the Municipal Clinical Hospital No. 31 between 2008 and 2021. For testing the algorithm, data from histories of 514 patients aged 2096 years (62 [46; 74]) were used; of these, 57% were men, while the rest were women. The patients under study were diagnosed and treated at the Municipal Clinical Hospital No. 17 and the Municipal Clinical Hospital No. 31 between 2008 and 2022. For each study subject, data were available on 37 signs, including 19 clinical, 3 laboratory, and 15 endoscopic signs. Statistical data analysis was performed using the Statistica 13 software package, R Project programming language, and GraphPad online calculator. The software implementation of the algorithm was performed using the JavaScript programming language.
 RESULTS: Using polynomial logistic regression, an algorithm for differential diagnosis of GIB according to the preliminary localization of the bleeding source was developed. Having the data from 8 clinical and laboratory parameters with probability, a preliminary localization of the bleeding source may be determined. Thus, the probability of bleeding localization in the upper, middle, and lower GIT accounts for 84% (95% CI [78%; 89%]), 84% (95% CI [74%; 91%]), and 75% (95% CI [69%; 80%]), respectively. A final algorithm to support clinical decision-making in the management of patients with GIB (sergisa.smrtp.ru/medical/edit.html) was developed and implemented as a web-service, working with 92.2% efficiency.
 The sequence of operations of the algorithm for diagnosing GIB is as follows:
 
 Obtaining clinical and laboratory signs of a patient with suspected GIB.
 Determining the nature of bleeding (overt/occult) using literature data, assessing the severity of bleeding (mild/medium/severe) based on Gorbashko classification, and detecting the preliminary localization of bleeding (upper/middle/lower GIT) by regression equation.
 Providing recommendations for selecting a research method based on production rules and expert opinions.
 Obtaining endoscopic signs.
 Determining the localization and source of bleeding using the production rules.
 Providing recommendations for stopping/preventing GIB based on literature and expert opinions.
 
 CONCLUSIONS: An algorithm to support clinical decision-making for the management of patients with GIB, considering the nature of clinical manifestations and the severity and the cause of bleeding based on expert opinions, production rules, and polynomial logistic regression, which allows to assume a preliminary localization of the source of bleeding, was developed for the first time in the Russian Federation. The developed algorithm is implemented as a web-service and may be integrated into the medical information system at the automated workstation of a surgeon, an endoscopist, and a gastroenterologist to support clinical decision-making in the management of patients with GIB.

Numerical analysis of predatory potentiality of Toxorhynchites splendens against larval Aedes albopictus in laboratory and semi-field conditions

Larvae of the elephant mosquitoes, Toxorhynchites spp. (Diptera: Culicidae) are predacious on larvae of other mosquito species and some small aquatic organisms; this predatory behavior can be applied in (mosquito) vector control. The present study examined the feeding behavior of Toxorhynchites splendens on Aedes albopictus in relation to search area [volume of water (X1)] and prey density (X2), prey instars, predatory preference and larvae's functional response on variable prey densities. Experiments were conducted to determine changes in the feeding activity of T. splendens with different search areas and showed that rate of prey consumption was inversely proportional to the search area as evidenced by a negative value of X1 in the regression equation and positively related to prey density. The non-linear polynomial logistic regression estimated a significant linear parameter (P1 < 0) for the functional response analysis suggesting a Type II functional response. Differences in feeding response related to the different combinations of prey instars were statistically not significant (p > 0.05), expressing that all the instars of prey were equally susceptible to the predator. Toxorhynchites splendens preferred to consume Ae. albopictus larvae rather than Tubifex when supplied together as a food source.

Relevant issues of hygienic and sanitary education of military personnel in modern conditions

Introduction. Maintaining the health in military personnel is impossible without hygienic training, education and sanitary education, for which it is necessary to conduct research that allows updating the knowledge base and ways to bring them to the military. &#x0D; Materials and methods. In February – April 2022, a cross-sectional medical and social study was carried out by interviewing military personnel serving under a contract. The volume of the sample population was 352 people. The effect of independent factors on the targets was evaluated by regression analysis using the method of constructing polynomial logistic regression. &#x0D; Results. Information about reasons of the most common diseases among military personnel in the region was not important for 39.8%, and information about prevention these diseases – for 33% of respondents. When asked about the frequency of hygienic education classes, the 55.9% of respondents noted the frequency of 1 once a month and less often. The most convenient form of communicating information in the hygienic education system, 33.8% of respondents chose a lecture format, another 31.3% indicated a way to disseminate information through the Internet site. For 45.2% of respondents, information about respiratory diseases was most relevant at the time of the survey. The importance of knowledge about reasons of the most common diseases among military personnel was influenced by marital status, monthly income, number of children, frequency of alcohol consumption, presence of chronic diseases, and weight of military personnel. The assessment of the importance of knowledge about the prevention of these diseases was significantly influenced by military rank and frequency of alcohol consumption. &#x0D; Limitations. The volume of a sample of 352 contracted servicemen serving in the Severodvinsk garrison; climatogeographic features of the region; cross-sectional nature of the study. &#x0D; Conclusion. The obtained data make it possible to justify the need to modernize the existing system of hygienic education, including creating specialized Internet resources, and using modern marketing achievements to create the necessary motivation for military personnel. The existing nature of planning training in the Armed Forces of the Russian Federation requires its correction, taking into account the importance of the issue of forming a healthy behaviour among military personnel.

Estimating Probabilistic Safe WCET Ranges of Real-Time Systems at Design Stages

Estimating worst-case execution time (WCET) is an important activity at early design stages of real-time systems. Based on WCET estimates, engineers make design and implementation decisions to ensure that task executions always complete before their specified deadlines. However, in practice, engineers often cannot provide precise point WCET estimates and prefer to provide plausible WCET ranges. Given a set of real-time tasks with such ranges, we provide an automated technique to determine for what WCET values the system is likely to meet its deadlines and, hence, operate safely with a probabilistic guarantee. Our approach combines a search algorithm for generating worst-case scheduling scenarios with polynomial logistic regression for inferring probabilistic safe WCET ranges. We evaluated our approach by applying it to three industrial systems from different domains and several synthetic systems. Our approach efficiently and accurately estimates probabilistic safe WCET ranges within which deadlines are likely to be satisfied with a high degree of confidence.

Association between use of psychotropic medications prior to SARS-COV-2 infection and trajectories of COVID-19 recovery: Findings from the prospective Predi-COVID cohort study.

Psychological disturbances are frequent following COVID-19. However, there is not much information about whether pre-existing psychological disorders are associated with the severity and evolution of COVID-19. We aimed to explore the associations between regular psychotropic medication use (PM) before infection as a proxy for mood or anxiety disorders with COVID-19 recovery trajectories. We used data from the Predi-COVID study. We followed adults, tested positive for SARS-CoV-2 and collected demographics, clinical characteristics, comorbidities and daily symptoms 14 days after inclusion. We calculated a score based on 16 symptoms and modeled latent class trajectories. We performed polynomial logistic regression with PM as primary exposure and the different trajectories as outcome. We included 791 participants, 51% were men, and 5.3% reported regular PM before infection. We identified four trajectories characterizing recovery dynamics: "Almost asymptomatic," "Quick recovery," "Slow recovery," and "Persisting symptoms". With a fully adjusted model for age, sex, socioeconomic, lifestyle and comorbidity, we observed associations between PM with the risks of being in more severe trajectories than "Almost Asymptomatic": "Quick recovery" (relative risk (95% confidence intervals) 3.1 (2.7, 3.4), "Slow recovery" 5.2 (3.0, 9.2), and "Persisting symptoms"11.7 (6.9, 19.6) trajectories. We observed a gradient of risk between PM before the infection and the risk of slow or no recovery in the first 14 days. These results suggest that a pre-existing psychological condition increases the risk of a poorer evolution of COVID-19 and may increase the risk of Long COVID. Our findings can help to personalize the care of people with COVID-19.

예비유아교사의 놀이성에 기초한 놀이성 유형구분 및 영향요인 탐색

Purpose: In order to understand the characteristics that early childhood teachers should have as playsupporters, this study identified playfulness types according to the playfulness of pre-early childhoodteachers, explored predictive variables that affected them, and compared the differences in understandingof children’s play, student engagement, academic self-efficacy, and learning motivation between groups.&#x0D; Methods: To this end, 123 students from S university in Gwangju were subjected to latent profilingand polynomial logistic regression analyses.&#x0D; Results: First, three latent classes were derived: a ‘low playfulness group’, a ‘middle playfulnessgroup’, and a ‘high playfulness group’. Second, as a result of analyzing the difference between groups,it was found that the ‘high playfulness group’ recognized understanding of children's play and academicself-efficacy was higher than the ‘middle playfulness group’. Finally, it was found that self-directedlearning, participation in high-efficiency programs, academic motivation, and academic self-efficacyaffected group classification.&#x0D; Conclusion: Based on these results, discussions and educational implications for the developmentof playfulness for pre-early childhood teachers were proposed.

Comparison of earthquake-induced shallow landslide susceptibility assessment based on two-category LR and KDE-MLR

Geological hazards caused by strong earthquakes have caused continuous social and economic losses and destruction of the ecological environment in the hazard area, and are mostly manifested in the areas with frequent occurrence of geological hazards or the clustering of geological hazards. Considering the long-term nature of earthquakes and geological disasters in this region, this paper takes ten earthquake-stricken areas in Wenchuan earthquake zone as examples to collect shallow landslide data in 2010, combined with the spatial location of landslides and other factors. Kernel density estimation (KDE) method is used to analyze the spatial characteristics of shallow landslide. Taking the space of shallow landslide as the characteristic variable and fully considering the regulating factors of earthquake-induced landslide: terrain complexity, distance to river, distance to fault, distance to road, lithology, normalized vegetation difference index (NDVI) and ground peak acceleration (PGA) as independent variables, based on KDE and polynomial logistic regression (MLR), A quantitative model of shallow landslide in the earthquake area is constructed. The results show that: (1) PGA has the greatest impact on landslide in the study area. (2) Compared with the two-category logistic regression (two-category LR) model, the susceptibility map of landslide prediction results based on the KDE-MLR landslide susceptibility prediction model is more consistent with the actual situation. (3) The prediction accuracy of the model validation set is 70.7%, indicating that the landslide susceptibility prediction model based on KDE-MLR can effectively highlight the spatial characteristics of shallow landslides in 10 extreme disaster areas. The research results can provide decision-making basis for shallow landslide warning and post-disaster reconstruction in earthquake-stricken areas.

Вибір економетричного інструментарію при побудові скорингової моделі на основі фіктивних змінних

The aim of the study is to select adequate econometric instruments for building a scoring model on a specific array of initial data, which contains the vast majority of fictitious variables. Despite a significant number of developments devoted to the construction of scoring models, a universal method allowing to obtain a highly efficient classifier for any data has not been identified. Therefore, the task of selection of the best method for building a scoring model remains relevant, depending on the characteristics of the available data. The most successful approach when selecting a model for solving the problem of binary classification is the use of several types of econometric models and the choice of the best of them according to the results of classification. In the presented study, the following types of models were applied: discriminant model, logit and probit regressions, and polynomial logistic regression. Training samples with different structure were used. Comparison of all obtained models allows us to conclude that polynomial logistic regression is preferable in this case. This model demonstrates high classification rates for all introduced object classes and has an important advantage compared to models that make a binary selection. The advantage of polynomial logistic regression is also the possibility of selecting in each case a convenient scale for dividing borrowers into more than two classes and determining the level of probability of reliability of the borrower acceptable for its own conditions, at which it should be assigned to one of the selected classes. Prospects for further research in this direction are the use of machine learning methods that will be able to use ensembles of the best of the considered models. In addition, the proposed models can be used in solving similar problems in other spheres of economic activity.

Modelling the Dynamics of Language Change: Logistic Regression, Piotrowski’s Law, and a Handful of Examples in Polish

ABSTRACT The study discusses modelling diachronic processes by logistic regression. The phenomenon of nonlinear changes in language was first observed by Raimund Piotrowski (hence labelled as Piotrowski’s law), even if actual linguistic evidence often speaks against using the notion of a ‘law’ in this context. In our study, we apply logistic regression models to changes which occurred between 15th and 18th century in the Polish language. The attested course of the majority of these changes closely follow the expected values, which proves that the language change might indeed resemble a nonlinear phase change scenario. We also extend the original Piotrowski’s approach by proposing polynomial logistic regression for these cases which can hardly be described by its standard version. Also, we propose to consider individual language change cases jointly, in order to inspect their possible collinearity or, more likely, their different dynamics in the function of time. Last but not least, we evaluate our results by testing the influence of the subcorpus size on the model’s goodness-of-fit.

Analysis of Latent Classes of Self-Directed Learning and Impact Variables in Middle and High School Students During the COVID-19 Pandemic

본 연구는 코로나19로 인해 등교수업과 원격수업이 함께 진행된 2020년 2학기에 중‧고등학생이 경험한 학습양상을 이해하기 위해 자기주도학습에 따라 학습유형을 구분하고, 이에 영향을 미친 변인을 탐색하였으며, 잠재집단 간 수업 태도, 자기효능감, 학업정서 변화의 차이를 비교하였다. 이를 위해 서울지역 중‧고등학생 783명을 대상으로 잠재프로파일분석과 다항 로지스틱 회귀분석을 실시하였다. 그 결과는 다음과 같다. 첫째, 중‧고등학생 모두 전체 학생 수의 반 이상을 차지하는 ‘자기주도학습 보통 집단’, 그 외 ‘자기주도학습 높은 집단’과 ‘자기주도학습 낮은 집단’의 3개의 잠재집단이 도출되었다. 둘째, 자기주도학습을 잘하는 집단일수록 중‧고등학생 모두 자기효능감과 수업 태도가 좋은 것으로 나타났다. 더불어 고등학생의 경우 자기주도학습을 잘하는 학생에 비해 보통이나 낮은 집단에서 코로나19 이전보다 불안과 스트레스를 더 많이 느끼는 것으로 나타났다. 마지막으로 집단 구분에 영향을 주는 변인으로는 중학생은 사교육, 자기효능감, 학부모지원, 디지털기기 활용능력이, 고등학생은 자기효능감과 학부모지원이 영향을 미치는 것으로 나타났다. 이러한 결과는 코로나19로 인한 학습회복과 관련하여 교수‧학습과정에 초점을 맞춘 학생지원 프로그램 개발과 운영에 대한 기초자료를 제공할 수 있을 것이다.In order to understand the learning patterns of middle and high school students in the second semester of 2020, when in-school and remote classes were conducted in tandem due to the COVID-19 situation, this study identified learning types according to self-directed learning, explored the predictive variables that affected them, and compared differences in class attitudes, self-efficacy, and academic emotions between groups. To this end, 783 middle and high school students in Seoul were subjected to latent profile and polynomial logistic regression analyses. The results are as follows. First, three latent classes were derived: an "average group for self-directed learning," which accounted for more than half of the number of students in both middle and high school; a "high group for self-directed learning"; and a "low group for self-directed learning." Second, the better the self-directed learning group, the better the self-efficacy and class attitude of both middle and high school students. In addition, high school students in the average or lower group felt more anxiety and stress than before the COVID-19 restrictions than did those students who were good at self-directed learning. Finally, it was found that the variables that impact latent class classification for middle school students were out-of-school classes, self-efficacy, parental support, and the ability to use digital devices, while for high school students, they were self-efficacy and parental support. These results could provide the basis for the development and operation of student support programs focused on the teaching and learning process in relation to learning recovery made necessary by the COVID-19 pandemic.

Correlation analysis between vitamin A, D, and E status with altitude, seasonal variation, and other factors, among children aged 0-6 years in a Chinese population living in the Tibetan plateau of Ganzi prefecture.

ObjectiveWe attempted to understand the status of vitamin (Vit) A, D, and E in children aged 0–6 living in the Tibetan plateau areas of Ganzi prefecture, to provide the basis for relevant government departments to carry out physical examinations of these children and to prevent and cure four key diseases (Infantile diarrhea, nutritional anemia, rickets, and infantile pneumonia).MethodsSerum retinol and tocopherol levels were detected using high‐performance liquid chromatography (HPLC). Serum levels of 25‐(OH)D were detected by high‐performance liquid chromatography–tandem mass spectrometry (LC–MS). The polynomial logistic regression was used to analyze the effects of age, season, altitude, and gender on Vit A, D, and E levels.ResultsVit A and D had the lowest mean serum levels before the age of 1 year and with the most significant deficiency rates. The lowest Vit E levels were seen in the Toddlerhood group. The rates of deficiency and insufficiency were the highest. Vit A, D, and E levels were significantly affected by seasonal changes and were significantly higher in the summer than in any other season. Vit A and D were significantly affected by altitude, and their levels were lowest above 4 km.ConclusionThe overall levels of Vit A, D, and E in children aged 0–6 in the Tibetan plateau areas of Ganzi prefecture were lower than those in the plain's areas.

Latent Profiles of Pain, Insomnia, Depression, and Resilience in U.S. Veterans

Chronic pain is a widespread health condition that disproportionately affects Veterans. It is highly comorbid with insomnia and depression, which significantly contribute to pain-related disability and poorer quality of life. Alternately, resilience is a well-established protective factor against mental and physical health conditions but little is known about patterns of resilience, pain, insomnia, and depression in Veterans and their relationship to demographic and modifiable characteristics. Veterans (N = 4,292) registering for healthcare at the VA San Diego Healthcare System completed validated standardized self-report measures. Latent profile analysis was used to identify subgroups of resilience, pain intensity and interference, insomnia, and depression. Polynomial logistic regression was used to examine associations between profiles and demographic characteristics with Profile 1 as the referent. Six profiles emerged: 1) High resilience with very low symptomatology; 2) Low resilience with moderate insomnia and depression; 3) Average resilience with high pain; 4) Moderate to high resilience with low symptomatology; 5) Low resilience with moderate symptomatology; 6) Low resilience with high symptomatology. Greater odds of being married/partnered distinguished Profiles 2, 4, and 6 compared to Profile 1 (ORs: 1.693-2.538, p's<0.05). Lower odds of endorsing Asian race distinguished Profiles 4 and 6 compared to Profile 1 (ORs: 0.310 and 0.267; p's<0.05). Individuals in Profile 6 had lower odds of endorsing higher education (OR: 0.462) and higher odds of unreliable work or being unemployed (OR: 2.956; p<0.05). Those in Profiles 2 and 5 were less likely to have high social support (ORs: 0.313 and .521; p's<0.05). Findings indicate distinct patterns of resilience, pain symptoms, insomnia, and depression in healthcare-seeking U.S. Veterans. These are uniquely related to demographic characteristics and potentially modifiable risk and protective factors (e.g., social support), highlighting the importance of patient-tailored care in the VA system.