Multivariate Multiple Regression Research Articles

Changes in processing speed during early abstinence from alcohol dependence.

Processing speed is a task-independent construct underpinning more complex goal-related abilities. Processing speed is impaired in alcohol dependence (AD) and is linked to relapse, as are the functions it underpins. Reliable measurement of processing speed may allow tracking of AD recovery trajectories and identify patients requiring additional support. To assess changes in reaction time (RT) from baseline (at the start of a detoxification programme) across early abstinence. Vibrotactile RT was assessed in early recovery between days 3 and 7 of treatment in 66 individuals with AD (25 females; aged 19-74, 44.60 ± 10.60 years) and against 35 controls tested on one occasion (19 females; 41.00 ± 13.60), using two multivariate multiple regressions. A mixed multivariate analysis of covariance (MANCOVA) of available AD data (n = 45) assessed change in RT between timepoints and between treatment settings (outpatient vs inpatient). The group (AD vs control) significantly predicted choice RT at baseline and follow-up but did not significantly predict simple RT or RT variability, which is inconsistent with previous findings. At follow-up, mental fatigue was also predicted by the group, and MANCOVA indicated that this had worsened in inpatients but improved in outpatients. Recovery of RT measures so early in the treatment journey was not in line with previous research which indicates persisting deficits. The interaction between setting and timepoint indicates that despite being typically less medically complex, outpatients require ongoing support and monitoring during their recovery.

First-generation students’ educational outcomes: The role of parental educational, cultural, and economic capital – A 9-years panel study

We examined the role of parental educational, cultural, and economic capital in differences between first-generation students’ (FGS) and continuous-generation students’ (CGS) educational outcomes: enrollment in a selective university, university performance, the probability of dropout, and the probability of pursuing a master’s or PhD program. We analyzed data from nine waves of a cohort of 5000 Russian students surveyed yearly from 2012 to 2020. We applied structural equation modeling that allowed to conduct a multiple multivariate regression analysis and to correct for measurement error. We found that FGS are 10.8 percentage points less likely to choose a selective university and are 10.7 percentage points less likely to choose to follow a graduate program. But they do not differ from CGS in university performance and the likelihood of dropout. FGS are clearly positively selected on capitals and performance, but they still have on average less parental capital and worse school performance than CGS. Parental educational and cultural capitals partly explain the differences in educational outcomes between FGS and CGS, because they improve school and university performance. Cultural capital is an especially important mediator for choosing a selective university, while educational capital is important for the other three educational outcomes. Parental economic capital plays no role in explaining educational differences between FGS and CGS. Generally, FGS and CGS benefit equally from parental capital, except FGS profiting less from parental educational capital when entering a graduate program.

Does artificial intelligence predict orthognathic surgical outcomes better than conventional linear regression methods?

ABSTRACT Objectives To evaluate the performance of an artificial intelligence (AI) model in predicting orthognathic surgical outcomes compared to conventional prediction methods. Materials and Methods Preoperative and posttreatment lateral cephalograms from 705 patients who underwent combined surgical-orthodontic treatment were collected. Predictors included 254 input variables, including preoperative skeletal and soft-tissue characteristics, as well as the extent of orthognathic surgical repositioning. Outcomes were 64 Cartesian coordinate variables of 32 soft-tissue landmarks after surgery. Conventional prediction models were built applying two linear regression methods: multivariate multiple linear regression (MLR) and multivariate partial least squares algorithm (PLS). The AI-based prediction model was based on the TabNet deep neural network. The prediction accuracy was compared, and the influencing factors were analyzed. Results In general, MLR demonstrated the poorest predictive performance. Among 32 soft-tissue landmarks, PLS showed more accurate prediction results in 16 soft-tissue landmarks above the upper lip, whereas AI outperformed in six landmarks located in the lower border of the mandible and neck area. The remaining 10 landmarks presented no significant difference between AI and PLS prediction models. Conclusions AI predictions did not always outperform conventional methods. A combination of both methods may be more effective in predicting orthognathic surgical outcomes.

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods

ABSTRACT Objectives To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models. Materials and Methods A total of 1774 lateral cephalograms of 887 adult patients who had undergone orthodontic treatment were collected. Patients who had orthognathic surgery were excluded. On each cephalogram, 78 landmarks were detected using PIPNet-based AI. Prediction models consisted of 132 predictor variables and 88 outcome variables. Predictor variables were demographics (age, sex), clinical (treatment time, premolar extraction), and Cartesian coordinates of the 64 anatomic landmarks. Outcome variables were Cartesian coordinates of the 22 soft tissue and 22 hard tissue landmarks after orthodontic treatment. The AI prediction model was based on the TabNet deep neural network. Two conventional statistical methods, multivariate multiple linear regression (MMLR) and partial least squares regression (PLSR), were each implemented for comparison. Prediction accuracy among the methods was compared. Results Overall, MMLR demonstrated the most accurate results, while AI was least accurate. AI showed superior predictions in only 5 of the 44 anatomic landmarks, all of which were soft tissue landmarks inferior to menton to the terminal point of the neck. Conclusions When predicting changes following orthodontic treatment, AI was not as effective as conventional statistical methods. However, AI had an outstanding advantage in predicting soft tissue landmarks with substantial variability. Overall, results may indicate the need for a hybrid prediction model that combines conventional and AI methods.

Biochar from co-pyrolysis of biological sludge and woody waste followed by chemical and thermal activation: end-of-waste procedure for sludge management and biochar sorption efficiency for anionic and cationic dyes.

Nine biochars were produced by co-pyrolysis of sawdust and biological sludge following the "design of experiment" approach. Two kinds of sludge (both deriving from the treatment of mixed industrial-municipal wastewater) and two types of woody waste were selected as categorical predicting variables, while contact time, pyrolysis temperature, and sludge percentage were used as quantitative variables. Biochars were analysed for their product characteristics and environmental compatibility based on the European Standards (EN 12915-1:2009) for materials intended for water treatment (i.e. ash content, water leachable polycyclic aromatic hydrocarbons (PAHs) and elements), as well as for specific surface area (SSA), using them as response variables of a multivariate partial least square multiple regression, whose results provided interesting insights on the relationships between pyrolysis conditions and biochar characteristics. Biochars produced with sludge and/or providing the highest SSA values (258-370 m2g-1) were selected to undergo a sustainable chemical treatment using a by-product of the gasification of woody biomass, complying in all cases with European Standards and achieving therefore the end-of-waste status for sewage sludge. The biochar deriving from the highest percentage of sludge (30% by weight) and with the highest SSA (390 m2g-1) was thermally activated achieving SSA of 460 m2g-1 and then tested for the sorption of direct yellow 50 and methylene blue in ultrapure water and real wastewater, compared to a commercial activated carbon (AC). The biochar showed Langmuir sorption maxima (Qm) 2-9 times lower than AC, thus highlighting promising sorption performances. Qm for methylene blue in wastewater (28mg‧g-1) was confirmed by column breakthrough experiments.

Patient experiences and needs in cancer care– results from a nationwide cross-sectional study in Germany

BackgroundPatient-centredness has become a central quality indicator for oncology care. Elements include shared decision-making, patient navigation and integration of psychosocial care, which impact patient-reported and clinical outcomes. Despite efforts to promote patient-centred care in Germany in recent decades, implementation remains fragmented. Further, research on patient experiences with cancer care and its determinants is limited. Therefore, this study examines which patient- and facility-specific factors are associated with patient-centred quality care delivery.MethodsA cross-sectional study was conducted among 1,121 cancer patients in acute treatment, rehabilitation, and aftercare for different cancer entities across Germany. A participatory developed questionnaire was used. Outcome measures were the quality of physician-patient interaction and provision of psychosocial care during acute care. Predictors comprised patient-specific characteristics and treatment facility-specific factors. Multiple linear regression and multivariate binary logistic regression analyses were performed. In addition, a content analysis of open-ended comments on the patients’ overall cancer care needs was applied.ResultsMultiple linear regression analysis showed recent diagnosis (β=−0.12, p = < 0.001), being male (β=−0.11, p = 0.003), and having a preference for passive decision-making (β=−0.10, p = 0.001) to be significantly associated with higher interaction quality, but not age, education and health insurance type. An overall low impact of patient characteristics on interaction quality was revealed (adj. R2 = 0.03). Binary logistic regression analysis demonstrated the availability of central contact persons (OR = 3.10, p < 0.001) followed by recent diagnosis (p < 0.001), having breast cancer (p < 0.001) and being female (OR = 1.68, p < 0.05) to significantly predict offering psycho-oncological counselling to patients in acute care facilities. The availability of peer support visiting services (OR = 7.17, p < 0.001) and central contact persons (OR = 1.87, p < 0.001) in the care facility, breast cancer diagnosis (p < 0.001) and a higher level of education (p < 0.05) significantly increased the odds of patients receiving information about peer support in the treatment facility. Despite relatively satisfactory quality of physician-patient interactions in cancer care (M = 3.5 (± 1.1)), many patients expressed that better patient-centred communication and coordinated, comprehensive cancer care are needed.ConclusionThe findings reflect effective developments and improvements in cancer care and suggest that patients’ social characteristics are less decisive for delivering patient-centred quality care than systemic factors surrounding the care facilities. They can serve to inform oncology care in Germany.

Prospective study of hepatitis B and D epidemiology and risk factors in Romania: A 10-year update.

The global burden of hepatitis D virus (HDV) infection represents a major medical challenge and a public health crisis worldwide. However, there is a lack of accurate data on the epidemiology and risk factors for HDV. Hepatitis B virus (HBV) and HDV coinfection causes the most severe form of viral hepatitis, leading to a higher cumulative incidence of liver-related events compared with HBV monoinfection, including the need for liver transplantation and death. To investigate the epidemiology, natural history, risk factors and clinical management of HBV and HDV coinfection in Romanian patients. This prospective study was conducted between January and July 2022 in six tertiary gastroenterology and hepatology referral centres in Romania. All consecutive adults admitted for any gastroenterology diagnosis who were HBV-positive were enrolled. Patients with acute hepatitis or incomplete data were excluded. Of the 25390 individuals who presented with any type of gastroenterology diagnosis during the study period, 963 met the inclusion criteria. Testing for anti-HDV antibodies and HDV RNA was performed for all participants. Demographic and risk factor data were collected by investigators using medical charts and patient questionnaires. All data were stored in an anonymized online database during the study. The prevalence of HBV was 3.8%; among these patients, the prevalence of HBV/HDV coinfection was 33.1%. The median age of the study population was 54.0 years, and it consisted of 55.1% men. A higher prevalence of HBV/HDV coinfection was observed in patients 50-69 years old. Patients with HBV/HDV coinfection were significantly older than those with HBV monoinfection (P = 0.03). Multivariate multiple regression analysis identified female gender (P = 0.0006), imprisonment (P < 0.0001), older age at diagnosis (P = 0.01) and sexual contact with persons with known viral hepatitis (P = 0.0003) as significant risk factors for HDV. This study shows that HDV infection among those with HBV remains endemic in Romania and updates our understanding of HDV epidemiology and associated risk factors. It emphasizes the need for systematic screening for HDV infection and collaborative initiatives for controlling and preventing HBV and HDV infection.

ANALYSIS OF THE DIMENSIONS OF HEALTH SERVICE QUALITY ON PATIENT SATISFACTION AT ROYAL PRIMA MARELAN HOSPITAL IN 2024

One indicator of quality in health services is patient satisfaction, where high-quality health services will generally create a high level of patient satisfaction, leading to loyalty to health services. The study aimed to analyze the dimensions of Health Service Quality toward Patient Satisfaction at Royal Prima Marelan Hospital in 2024. The method used in this research is quantitative non-experimental with a descriptive approach (cross-sectional survey) and associative analysis. The population was 318 people, and the sample determination used Slovin so that the sample size was 197, rounded up to 200 samples, with incidental sampling technique-data analysis using univariate, bivariate (Chi-Square), multivariate (multiple logistic regression Enter method). The results of the Chi-Square analysis obtained the variables of Physical Evidence (p-value 0.004), reliability (p-value 0.006), Responsiveness (p-value 0.008), assurance (p-value 0.004), empathy (p-value 0.002) have a p-value ≤ 0.05 with a significant level of 0.05. It is concluded that the most influential variable is the empathy variable, with a p-value of 0.000 &lt;0.05. The OR value obtained is 10.224, meaning that ease of relationship, good communication, and understanding of the needs of patients have an opportunity of 10.224 times to increase patient satisfaction at Royal Prima Marelan Hospital in 2024. KEYWORDS: quality, satisfaction, patient, empathy

Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles

Variable parameters (VP) schemes are the most effective adaptive schemes in increasing control charts' sensitivity to detect small to moderate shift sizes. In this paper, we develop four VP adaptive memory-type control charts to monitor multivariate multiple linear regression profiles. All the proposed control charts are single-chart (single-statistic) control charts, two use a Max operator and two use an SS (squared sum) operator to create the final statistic. Moreover, two of the charts monitor the regression parameters, and the other two monitor the residuals. After developing the VP control charts, we developed a computer algorithm with which the charts' time-to-signal and run-length-based performances can be measured. Then, we perform extensive numerical analysis and simulation studies to evaluate the charts’ performance and the result shows significant improvements by using the VP schemes. Finally, we use real data from the national quality register for stroke care in Sweden, Riksstroke, to illustrate how the proposed control charts can be implemented in practice.

Trait dimensions of anticipatory and consummatory reward relate differently to self-injurious thoughts and behaviors in a community adult sample

BackgroundSelf-injurious thoughts and behaviors (SITBs) are a major problem worldwide and continue to be a serious public health concern. Research investigating risk factors for suicide has shown that reward processes, such as the inability to feel pleasure, may confer risk for SITBs. However, less work has examined how different dimensions of trait reward relate to SITBs. Accordingly, the present study investigated the unique and interactive effects of trait anticipatory and consummatory reward for explaining SITBs. Methods260 community adults ages 18–55 (M/SD = 32.79/10.54, females = 49.6 %, males = 50.4 %) completed an interview, neuropsychological tests, and questionnaires. We used hierarchical multivariate multiple regression analysis to assess cross-sectional associations between trait anticipatory and consummatory reward and different types of SITBs [self-injurious thoughts, nonsuicidal self-injury (NSSI), and suicide attempts] from the Risky, Impulsive, and Self-destructive Behavior Questionnaire. ResultsThe unique variance associated with anticipatory and consummatory reward were differentially related to self-injurious thoughts but unrelated to self-injurious behaviors (NSSI/suicide attempts). The interaction of anticipatory and consummatory reward was associated with self-injurious behavior, such that the inability to experience both anticipatory and consummatory reward was associated with higher frequency of NSSI. LimitationsLimitations of the study include its cross-sectional nature and reliance on self-reported measures. ConclusionsLow anticipatory reward and high consummatory reward may confer risk for self-injurious thoughts. Low levels of both trait anticipatory and consummatory reward may confer risk for NSSI. Findings suggest reward sensitivity may be an understudied risk factor for a range of SITBs.

Experience of violence and attitudes of staff members towards coercion in psychiatric settings: observational study.

Among important dimensions related to the use of coercive measures, professionals' attitude towards coercion is of particular interest. Little is known about how experiences of violence in the workplace might influence these attitudes. The present study aimed to investigate potential correlates of attitudes towards coercion, especially experiences of violence in the workplace. Mental health professionals were contacted through an online survey to assess their attitudes towards coercion using the Staff Attitude to Coercion Scale (SACS). The three subscales of the SACS (critical, pragmatic and positive attitudes) were analysed in a multivariate multiple linear regression, using a set of covariates including experiences of violence in the workplace. We hypothesised that experience of violence in the workplace would correlate with less critical attitudes of staff members towards coercion. A total of 423 professionals were included in the regression analysis. Age, professional category, feeling of insecurity, having witnessed or used coercion, and the emotional burden associated with coercive measures had a joint significant effect on the three SACS subscales. A feeling of insecurity, but not the experience of violence, was associated with a less critical, more positive appraisal of coercive measures. The emotional burden related to the use of coercion was associated with a more critical attitude. The present results highlight the importance of considering staff members' training and well-being regarding their feelings of insecurity when addressing attitudes towards coercion. The experience of patients should be integrated into staff training and coercion reduction programmes.

Prevalence and determinants of areca nut use among pregnant women in India

ABSTRACT Background Areca nut is the fourth most commonly used substance worldwide after nicotine, alcohol, and caffeine. Women in many countries use it in cultural and religious ceremonies. The use of areca nut is harmful to health; but when women consume it during pregnancy, it exerts several harmful effects on the fetus. This paper examines the prevalence and determinants of areca nut use among pregnant women in India. Methods Data from the Global Adult Tobacco Survey-2, India, are used for analysis (N = 1403 pregnant women). Multiple classification analysis and multivariate logistic regression model were applied to estimate the effect of various determinates. Results About 16% pregnant women used areca nut in any form in India. Areca nut use with (24%) and without (13%) tobacco was higher among scheduled tribes. Region, caste, religion, place of residence, educational attainment, occupation, and economic status are found to be important determinants of areca nut use. Conclusion More specific programs which can effectively reduce the use of areca nut among pregnant women should be adopted. Programs related to prevention of areca nut use should be expanded effectively through health awareness interventions during pregnancy, including media messages, and involvement of frontline health workers, especially focusing on the socio-economically backward groups.

Cognitive Appraisals of Organizational Stressors and Coping Styles of Football Coaches and Players in Ghana

The study assessed how football coaches and players appraised and coped with stressors they experienced or encountered. Specifically, the study assessed the following: (1) stress appraisal mechanisms employed by coaches and players, (2) coping mechanisms adopted by coaches and players, and (3) association between stress appraisals and coping styles among coaches and players in the Ghana national football league. Employing the descriptive survey design, census sampling was used to select 424 footballers and 44 coaches who answered the Stress Appraisal Measure (SAM) and the Modified Coping Orientation to Problems Experienced (MCOPE) inventories. Descriptive statistics (means and standard deviation) and multivariate multiple regression were used to analyze the data. The findings showed that football coaches and players reportedly used more controllable-by-self and challenge appraisals and employed more problem-focused coping styles (increasing effort, active coping, and planning) than emotion-focused coping styles (seeking social support for emotional reasons, venting of emotions, and self-blame) during stressful situations. Further, those who used facilitative appraisal mechanisms adopted functional coping mechanisms and vice versa. Sport psychologists are encouraged to organize regular psychological training workshops on a variety of functional coping styles (e.g., cognitive restructuring, planning, increasing effort and active coping) to help football coaches and players deal with the demands associated with competitions to enhance their psychological well-being.

The Dominance of Fandom: An Analysis of How Gender and Fandom Impact Live and Non-Live Sport Event Consumption Behaviours

This quantitative study featuring a representative sample from four Canadian regions (n = 1,011) investigates the impact of fandom and gender on 12 consumption behaviors pertaining to the 2019 NBA Championships. To analyze the panel survey results, multivariate multiple and ordinal probit regressions were used to measure the impact of gender, fandom, and the gender-fandom interaction on live and non-live consumption behaviors respectively. Fandom significantly predicted all 12 consumption behaviors, while gender and the fandom-gender interaction only significantly impacted live television consumption. Specifically, men viewed more live games via television than women, driven in-large-part by non-fan men viewing more games than non-fan women. Results indicated fandom is the dominant driver of consumption, stressing its importance and inclusion within academic and marketing decisions, with gender playing a near negligible role. Yet, given live television viewing is a gateway consumption behavior, strategies targeting gender parity should target this consumption mode, particularly among non-fans.

Modeling of kappa factor using multivariate adaptive regression splines: application to the western Türkiye ground motion dataset

AbstractThe recent seismic activity on Türkiye’s west coast, especially in the Aegean Sea region, shows that this region requires further attention. The region has significant seismic hazards because of its location in an active tectonic regime of North–South extension with multiple basin structures on soft soil deposits. Recently, despite being 70 km from the earthquake source, the Samos event (with a moment magnitude of 7.0 on October 30, 2020) caused significant localized damage and collapse in the Izmir city center due to a combination of basin effects and structural susceptibility. Despite this activity, research on site characterization and site response modeling, such as local velocity models and kappa estimates, remains sparse in this region. Kappa values display regional characteristics, necessitating the use of local kappa estimations from previous earthquake data in region–specific applications. Kappa estimates are multivariate and incorporate several characteristics such as magnitude and distance. In this study, we assess and predict the trend in mean kappa values using three–component strong–ground motion data from accelerometer sites with known VS30 values throughout western Türkiye. Multiple linear regression (MLR) and multivariate adaptive regression splines (MARS) were used to build the prediction models. The effects of epicentral distance Repi, magnitude Mw, and site class (VS30) were investigated, and the contributions of each parameter were examined using a large dataset containing recent seismic activity. The models were evaluated using well–known statistical accuracy criteria for kappa assessment. In all performance measures, the MARS model outperforms the MLR model across the selected sites.

Effect of biophilic shopping environments featuring Christmas trees on perceived attentional and mental fatigue: A national study

The Mayo Clinic and the American Psychiatric Association recognize that many people experience stress around the holidays. For example, households with children, people living alone, etc. during the Christmas holiday might be feeling mentally fatigued or maybe they simply want to improve their mental state. We aimed to investigate the extent to which Christmas tree shopping environments that include real trees in the outdoors (a common type of biophilic store design) provide opportunities to help them recover from mental and attentional fatigue (derived from Attention Restoration Theory) when compared to artificial indoor tree displays. A nationwide online survey (n=1208, 45 questions, and two video evaluations) was used to compare real-time and post video evaluations of outdoor displays of real Christmas trees with indoor displays of artificial Christmas trees using two measures of overall perceived restorative quality. The key finding indicates that real/outdoor trees have a higher perceived restorative quality (real-time video evaluation p <.05 and post-video evaluation p <.001). Although the fascination ratings for artificial/indoor tree ratings were significantly higher (p <.01), it had a much weaker effect than real trees (less than half) on overall restorative quality. That is, although indoor artificial trees were more fascinating, it appears to be the kind of “hard” fascination that does not contribute nearly as much to restoration when compared to the “softer” fascination associated with real trees. The positive effect of coherence (e.g., orderly tree displays) and scope (e.g., perception of depth and spaciousness) on overall restorative quality that was perceived by respondents was greater for real/outdoor tree displays. These larger effects were measured in a multivariate multiple regression model but also identified in most of the peak restorative moments during the video evaluation.

Scheduling and Vendor Consistency Improves Turnover Time Efficiency in Total Joint Arthroplasty

BackgroundMaximizing operative room (OR) efficiency is important for hospital efficiency, patient care, and positive surgeon and staff morale. Reducing turnover time (TOT) has become a popular focus to improve OR efficiency. The present study evaluated if TOT is influenced by changing case type, implant vendor, and/or laterality. MethodsIn total, 444 turnovers from January to July 2023 were retrospectively analyzed. All turnovers were same-surgeon turnovers between primary arthroplasty cases in dedicated, overlapping rooms. Single linear regression models tested the predictability of TOT based on case type, vendor, and laterality. A multivariate multiple regression and 1-way Analyses of Variance analyzed variables against each other. Independent sample t-tests evaluated TOTs when all variables were the same or different. ResultsChanging versus keeping the same case type increased TOT by 2.4 minutes (95% confidence interval [CI] = 0.7, 4.0; P = .004). Changing vendors increased TOT by 2.9 minutes (95% CI = 1.1, 4.7; P = .002). Laterality did not affect TOT, with a change of 0.9 minutes (95% CI = −0.6, 2.5; P = .229). Vendor (P = .030) independently predicted TOT when analyzed as a covariate with case type (P = .410). The TOT with same case type and vendor (mean 38.2 minutes; range, 22 to 62) was less than that of different case types and vendors (mean 41.4 minutes; range, 26 to 73) (P = .017). Mean TOT differed by 5.5 minutes when keeping all variables the same versus all different (P = .018). ConclusionsMaintaining a consistent case type, vendor, and laterality had a synergistic effect in reducing TOT in arthroplasty ORs with the same primary surgeon running 2 overlapping rooms. Changing vendor representatives was found to independently predict TOT increases, which is likely attributed to a disruption in workflow and collaboration of the multidisciplinary OR team. Level of EvidenceLevel III.

Assessment of the Relationship Between Humic Acid Contents and Trace Elements of Some Agricultural Soils in Diyarbakır Region by Multivariate Statistical Methods

There are important relationships between humic acid (HA) and the bioavailability, reactions and mobility of trace elements in the soil. For this reason, soils are tried to be improved chemically, biologically and physically with HA applications. In this study, the relationship of humic acid contents of 118 agricultural soil samples from Diyarbakır region with some trace elements (Al, As, Ba, Be, Cd, Fe, Mn, Pb, Sb, Sn, Se, V and P) was evaluated by multivariate statistical analysis. After the soil samples were solubilized by the microwave wet digestion method, the element contents were determined with the ICP OES (Inductively Coupled Plasma Optical Emission Spectrometer) device. SRM NIST 2586 was used as SRM (Standard Reference Material) for the accuracy of the method. Recovery values were found between 91.6% and 105.9% as a result of the analysis. Humic acid was extracted from soils by the International Society for Humic Substances (IHSS) method and determined using a shaker and centrifuge device. For the accuracy of the method, it was tested with Humic Acid Sodium Salt (HA-Na). Pearson correlation and partial correlation analysis were applied to the obtained data set. In addition, multivariate statistical analyses such as multiple regression HCA (Hierarchical Cluster Analysis) and PCA (Principal Component Analysis) were applied. Multiple regression analysis was performed according to the Step-wise method. Manganese and P (p&lt; 0.01) were significant when HA was taken as the dependent variable. According to the Pearson correlation coefficient, the correlation between HA and As (r = -0.282**) in soil was negative and significant, while Fe (r = 0.185*), Mn (r = 0.273**)), Sn (r = 0.242*), Se (r = 0.325**) and P (r = 0.315**) were determined as positive and significant. In clustering and PCA analysis, HA, P Mn and Fe were found to be in the same group. The analyses have shown that HA has a positive effect on the plant nutrients in the soil.

Work-Related Mental Health Problems in Switzerland.

The study identifies work-related risk factors that are relevant to mental health and quantifies their influence. This allows estimation of risk levels for individual workplaces and of the proportion of occupational causation in the emergence of mental health problems. Swiss Health Survey data, containing information on several potential risk factors and health indicators that cover aspects of mental health, were used in multiple multivariate logistic regression analyses. Stress was the predominant risk factor, followed by exposure to violence, unergonomic work processes, and work that conflicted with family life. Hotel and restaurant industries and health and social services had high exposure to risk factors. One of 20 workplaces was deemed high-risk based on an odds ratio >4. Up to one-third of mental health problems within the active workforce may have highly predominant occupational causation.

Relationship between the Latent Profile of Online Socially Regulated Learning and Collaborative Learning Motivation

Socially regulated learning (SoRL) is an important way to maintain the sustainable development of collaborative learning (CL). Usually, learners can achieve sustainable and high-quality SoRL with the intervention of teachers. To improve the appropriateness of the intervention, teachers need to clarify the profiles of SoRL to which learners belong, as well as the influence of collaborative learning motivation (CLM) and the relevant background variables. This study used three non-duplicate samples to provide evidence for the psychometric properties of the SoRL and CLM scales through item analysis, exploratory factor analysis (sample 1, n = 531), and confirmatory factor analysis (sample 2, n = 1278). The profiles of SoRL among university students were determined through latent profile analysis (sample 3, n = 909). This study identified three profiles of regulation (strong SoRL, progressive SoRL, and weak SoRL). The analysis of multivariate variance and multiple logistic regression methods further explored the differences in the dimensions of SoRL structures across different profiles and the extent to which CLM and background variables predicted profiles. The results showed that collaborative motivation (CM) and learning motivation (LM) were the predictors of learners’ transformation from a low regulation level to a medium regulation level. CM, LM, altruistic motivation, and major background were the predictors of learners’ transition from the medium regulation level to the high regulation level. Accordingly, teachers can provide learners with an appropriate external intervention to promote the improvement of SoRL. This study contributes to improving learners’ SoRL levels and promoting the sustainable development of education. In the future, the changing characteristics of learners’ SoRL profiles over time will be explored, and the application of learning process data will be strengthened.