Strong Predictor Research Articles

Unravelling demographic and socioeconomic patterns of COVID-19 death and other causes of death: results of an individual-level analysis of exhaustive cause of death data in Belgium, 2020.

The COVID-19 pandemic led to significant excess mortality in 2020 in Belgium. By using microlevel cause-specific mortality data for the total adult population in Belgium in 2020, three outcomes were considered in this study aiming at predicting sociodemographic (SD) and socioeconomic (SE) patterns of (1) COVID-19 specific death compared to survival; (2) all other causes of death (OCOD) compared to survival; and (3) COVID-19 specific death compared to all OCOD. Two complementary statistical methods were used. First, multivariable logistic regression models providing odds ratios and 95% confidence intervals were fitted for the three study outcomes. In addition, we computed conditional inference tree (CIT) algorithms, a non-parametric class of classification trees, to identify and rank by significance level the strongest predictors of the three study outcomes. Older individuals, males, individuals living in collectivities, first-generation migrants, and deprived SE groups experienced higher odds of dying from COVID-19 compared to survival; living in collectivities was identified by the CIT as the strongest predictor followed by age and sex. Education emerged as one of the strongest predictors for individuals not living in collectivities. Overall, similar patterns were observed for all OCOD except for first- and second-generation migrants having lower odds of all OCOD compared to survival; age group was identified by the CIT as the strongest predictor. Older individuals, males, individuals living in collectivities, first- and second-generation migrants, and individuals with lower levels of education had higher odds of COVID-19 death compared to all OCOD; living in collectivities was identified by the CIT as the strongest predictor followed by age, sex, and migration background. Education and income emerged as among the strongest predictors among individuals not living in collectivities. This study identified important SD and SE disparities in COVID-19 mortality, with living in collectivities highlighted as the strongest predictor. This underlines the importance of implementing preventive measures, particularly within the most vulnerable populations, in infectious disease pandemic preparedness to reduce virus circulation and the resulting lethality.

Mathematics interest, self-efficacy, and anxiety predict STEM career choice in emerging adulthood.

To examine the combined effects of maths anxiety (MA), maths self-efficacy (MSE), and maths interest (MI) on STEM career choice, we analysed self-report data from 7908 Twins Early Development Study participants, collected at ages 16 (MSE, MI), 18 (MA) and 21 (STEM career choice). When analysed in the same model, MSE did not independently predict STEM career choice. MI (OR = 1.75) was a stronger predictor than MA (OR = 0.79), which was not significant after controlling for maths achievement. MI was a significant positive predictor of STEM career choices for both males (OR = 1.88) and females (OR = 1.77). However, MA was only predictive for males (OR = 0.62), and MSE was only predictive for females in the unadjusted model (OR = 1.77). These results highlight the importance of nurturing maths interest to bridge the STEM skills gap, regardless of sex. Future research should consider the co-development of maths-related psychological constructs to further understand their influence on STEM career paths.

Better face-name recall is associated with better face recognition ability.

Face recognition is a highly developed and specialised human ability, distinct from other cognitive abilities. Previous studies examining individual differences in face recognition have focused on face perception and specialised perceptual mechanisms such as holistic face processing. However, the contribution of specific face memory processes to face recognition ability remains unclear. In 99 neurotypical individuals, we administered validated face perception assessments, three face memory tasks (old/new task, face-scene task, face-name/occupation task), and the Cambridge Face Memory Test (CFMT) to assess face recognition ability. We found that after accounting for face perception ability (which significantly predicted face recognition ability), face-name recall and recollection of faces in the face-scene task predicted unique variance in face recognition ability, with face-name recall being the strongest predictor. This highlights that associative memory mechanisms contribute to face recognition abilities and suggests that the ability to learn and recall proper names is particularly important to face recognition.

Brand Trust, Perceived Quality, and Parental Decision-Making: A Study of International School Selection in Chiang Mai

Background and Aim: This research investigates the factors influencing parents' decision-making process when choosing international schools in Chiang Mai Province, Thailand. With the increasing popularity of international education in Thailand, understanding the key determinants of school choice is crucial for both parents and educational institutions. This study focuses on the impact of brand trust and perceived brand quality on parental decision-making, aiming to provide valuable insights for school operators and stakeholders to develop competitive strategies and enhance educational services. Materials and Methods: The study employs a quantitative research design with a convenience sampling technique. Data is collected from parents of children attending or considering 21 international schools in Chiang Mai through a structured online questionnaire. The questionnaire assesses brand trust, perceived brand quality, and their influence on the school choice decision-making process. Multiple regression analysis is used to examine the relationships between these variables. Results: The findings reveal that both brand trust and perceived brand quality significantly influence parental decision-making. Brand trust emerges as the strongest predictor, indicating that parents prioritize the credibility and reputation of international schools. Perceived brand quality also plays a crucial role, as parents associate high-quality brands with superior educational outcomes. The study demonstrates that these two factors collectively account for a substantial portion of the variance in parental choices. Conclusion: This research confirms the importance of brand management for international schools in Chiang Mai Province. By focusing on building brand trust and enhancing perceived brand quality, schools can effectively attract and retain students. The study's findings offer valuable guidance for school administrators and marketers in developing targeted strategies to meet the evolving needs and expectations of parents in the international education market.

A novel clinical prediction model for hip fractures: a development and validation study in the total population of Sweden

Low bone density and osteoporosis are indications for bone-specific treatment. However, given the limited availability of bone density data in clinical practice and the fact that most patients with hip fracture do not have osteoporosis, accurate prediction of hip fracture risk in the absence of bone density data would be crucial. This development and validation study included the entire Swedish population aged 50 years or older in 2005 (N=3,340,977) and was conducted by cross-linking data from nationwide registers. Potential predictive variables included diagnoses, prescription medications, familial factors, frailty-related factors, and socioeconomic factors. The primary endpoint was the 5-year risk of hip fracture. Fracture prediction algorithms were developed and validated using multivariable models. Model performance and validation was also examined in a sub cohort restricted to 504,431 individuals with non-Swedish background. During a total follow-up of 15.2 million person-years, 87,089 individuals suffered a hip fracture within 5 years. In the final prediction model, 19 variables were associated with a population attributable fraction of 93.9% (95% CI, 93.7-94.1) in women and 92.7% (95% CI, 92.2-93.0) in men. The strongest predictor, besides old age, was the use of homemaker service, with a 5-year risk of hip fracture of 7.8% in women and 4.7% in men. The diagnoses most strongly predicting the 5-year risk of hip fracture was Parkinson's disease (6.8% in women, 4.6% in men) and dementia (6.1% in women, 3.6% in men). Validation of the prediction model suggested that the optimal threshold for treatment with bone-specific agents was an estimated 5-year hip fracture risk of 3%. Assuming a threshold of 3% and a 30% relative risk reduction from bone-specific treatment, the number needed to treat to prevent one hip fracture was estimated to 36 in women and 52 in men. Similar results were obtained in the sub cohort with non-Swedish background. A clinical prediction model developed and validated in the total Swedish population could predict the risk of hip fractures with high precision even in absence of data on bone density. The model was associated with a population attributable fraction for hip fracture of more than 90%, and the strongest predictor besides old age was the use of homemaker service, which likely reflect frailty. Based on the model, individuals with an estimated 5-year risk of hip fracture of at least 3% could be considered for bone-specific treatment. None.

ECG, clinical and novel CT-imaging predictors of necessary pacemaker implantation after transfemoral aortic valve replacement.

Newly onset conduction disturbances with the need for permanent pacemaker (PPM) implantation remain the most common complication of transcatheter aortic valve replacement (TAVR). The objective was to evaluate the predictive value of clinical, ECG and new pre-procedural CT-imaging parameters for the requirement of PPM-implantation after TAVR. 2105 consecutive patients receiving TAVR using a balloon expandable prosthesis (Sapien 3, Edwards Lifesciences, Irving, CA, USA) at our institution were enrolled. Patients receiving a valve-in-valve prosthesis, TAVR after surgical repair, with missing or non-diagnostic CT-scans, with pre-implanted PPM and after TAVR in mitral position were excluded. The most suitable classification model for the given dataset was first identified through benchmark testing and later applied for prediction analysis. 312 eligible patients requiring PPM implantation were compared to an age- matched control group of 305 patients not requiring PPM implantation. A scaled LASSO model allowed for most accurate prediction with an AUC of 0.70. Right bundle branch block was the strongest predictor (OR 2.739), followed by atrioventricular block 1° (OR 2.091), prosthesis diameter (OR 1.351), atrial fibrillation (OR 1.255), arterial hypertension (OR 1.215), coronary artery disease (1.070), the angle of ventricle axis and aortic root (OR 1.030), sinotubular junction height (OR 1.014) and the calcification of the left coronary cuspid (OR 1.007). ECG- and clinical outperform imaging parameters in predicting PPM-implantation following TAVR. Right bundle branch block emerged as the most significant predictor overall, while the angle of ventricle axis and aortic root as a novel imaging-based predictor.

Predictors of stunting and pathway analysis for linear growth among children 2-3 years of age after a trial of small-quantity lipid-based nutrient supplements and home-installed growth charts in three districts in Zambia

Globally, 148 million children under 5 are stunted, with risk factors varying by context. Our 'Impact of Growth Charts and Nutritional Supplements on Child Growth in Zambia' (ZamCharts) trial observed persistently high rates of stunting in all treatment groups after 18-months of intervention with monthly distributions of small-quantity lipid-based nutrient supplements (SQ-LNS) and/or installation of a wall-mounted growth chart in children's homes. We sought to identify determinants of stunting and height-for-age z-score in children 27-36 months who participated in the ZamCharts endline survey (n=1911). Multi-level, log-binomial models were used to estimate univariable and multivariable prevalence ratios for predictors of stunting. Multi-level models were also used to predict height-for-age z-score (HAZ) with and without baseline HAZ (assessed at ages 2-11 months). We also conducted a path analysis using covariance analysis of linear structural equations to assess underlying and modifiable risk factors for impaired linear growth. Significant predictors of stunting in the multivariable model included: low asset ownership; being male; using biomass as cooking fuel; lower maternal height; a mother with ≤ primary education; lower baseline HAZ. and not being randomized to SQ-LNS. Significant predictors of a lower mean HAZ in the full multivariable models included all the same risk factors that predicted stunting, but also living in an urban area, having more than one child <5 years in the household and diarrhea in the previous 2 weeks. The multivariable model explained 48% of variability in endline HAZ; the strongest predictor was baseline HAZ, which explained 29% of endline HAZ variability in the univariable model. Preventing stunting in Zambia will require investments in early life (pre- and post-natal) determinants of growth trajectory as well as improving complementary feeding practices and addressing risk factors for infectious diseases; SQ-LNS can also improve linear growth and reduce stunting.

Elevated Plasma High Sensitive C-Reactive Protein and Triglyceride/High-Density Lipoprotein Cholesterol Ratio are Risks Factors of Diabetes Progression in Prediabetes Patients After Kidney Transplant: A 3-Year Single-Center Study in Vietnam.

Determination the rate of developing post-transplant diabetes mellitus (PTDM) in prediabetic patients and the relationship with plasma hs-CRP levels and TG/HDL-C ratio in patients after kidney transplantation from living donors followed for 3 years. A total of 206 post-transplant patients diagnosed with prediabetes by oral glucose tolerance test (OGTT) were included in the study. At the time of diagnosis of prediabetes, all patients were clinically examined, paraclinical tests were performed, plasma hs-CRP was quantified, and the TG/HDL-C ratio was determined. Patients are individualized and given a reasonable diet and exercise regimen. Patients had their fasting blood glucose measured monthly or had an OGTT every 3 months. Patients meeting the criteria for diagnosis of PTDM according to the American Diabetes Association (ADA)-2018 were collected during 3 years of follow-up. The study group had an average age of 39.46 ± 10.26 years old, including 74.8% males and 25.2% females. The rate of patients who had a development of PTDM from prediabetes was 29.6% (61/206 patients). BMI, plasma TG, HDL-C, hs-CRP, and TG/HDL-C ratio at the time of prediabetes diagnosis were factors related to the progression of PTDM, in which hs-CRP and TG/HDL-C ratio were good predictors (with AUC = 0.85 and 0.874, respectively; p < 0.001). After 3 years of follow-up, nearly one-third of prediabetic patients developed PTDM post-living donor kidney transplantation. BMI, plasma TG, HDL-C, hs-CRP, and the TG/HDL-C ratio were linked to DM progression, with hs-CRP and TG/HDL-C being the strongest predictors.

Influences of speaking task demands on sensorimotor oscillations in adults who stutter: Implications for speech motor control

ObjectiveMotivated by previous inconsistent findings, this study aims to improve understanding of sensorimotor beta (β; 15–30 Hz) and alpha (α; 8–14 Hz) speech-related power differences between stuttering and non-stuttering adults. MethodsElectroencephalography was recorded as adults who stutter (AWS) and matched fluent controls answered questions in Quiet and Informational Masked backgrounds. Bilateral sensorimotor β and α power during speech planning and execution were measured from mu (μ) rhythm components. ResultsCompared to controls, AWS exhibited reduced left hemisphere β and α power in both speaking conditions during speech planning and execution. AWS displayed reduced left α power in the Informational Masking compared to Quiet. Within AWS β and α power, which were tightly coupled, oppositely predicted stuttering severity and β-α dissociation (β minus α) was the strongest predictor. ConclusionNeither β nor α power are reliable markers of speech motor stability due to their sensitivity to speech task automaticity. However, relationships between these two sensorimotor rhythms warrant further investigation for understanding motor control. SignificanceData help explain previous mixed findings in reference to extant models of speech motor control in stuttering and may have clinical implications for developing neurostimulation protocols targeting improved speech fluency.

Perceived protective behavioral changes in Chinese residents post-dynamic zero-COVID policy lifting: a cross-sectional study.

To investigate how Chinese residents perceived changes in their protective behaviors in the early stage after the lifting of the dynamic zero-COVID policy, and to explore the associations between the overall perceived change and factors such as demographic and health-related information, COVID-19 related perceptions, negative emotions, and coping styles. This cross-sectional study involved 798 Chinese residents who completed an online questionnaire between 16 and 25 December 2022. The questionnaire covered demographic and health-related information, COVID-19 related perceptions, negative emotions, coping styles, and perceived changes in protective behaviors. Multiple linear stepwise regression analysis was used to determine the factors associated with the overall perceived change in protective behaviors. The mean score for perceived protective behavioral change among participants was 61.38 (SD = 10.20), which was significantly higher than the hypothesized no-change value of 49 (p < 0.001). The mean scores for each of the 15 behaviors (excluding the two vaccination-related items) were significantly greater than the hypothesized no-change value of 3 (p < 0.001). The mean scores for the two vaccination-related items were significantly greater than the hypothesized no-change value of 2 (p < 0.001). Among all behaviors, avoiding dining out or gathering with friends had the highest mean score (Mean = 4.16), while engaging in regular physical activity had the lowest (Mean = 3.32). Avoiding dining out or gathering with friends had the highest percentage of individuals reporting an increase (71.3%), whereas maintaining a social distance of more than 1 m had the highest percentage of individuals reporting a decrease (17.5%). Regression analysis indicated that age, worry, positive coping, female sex, negative coping, and perceived severity were associated with the overall perceived change in protective behaviors, with worry being the most predictive variable. This study suggested that Chinese residents perceived an increase in their protective behaviors in the early stage after the policy change, with varying magnitudes across behaviors. We identified some potentially modifiable factors associated with perceived protective behavioral change, with worry emerging as the strongest predictor, followed by positive coping, negative coping, and perceived severity. These insights offer valuable information for developing effective communication strategies, psychological support, and comprehensive models in health behavior research.

The Effect of Digital Literacy, Technological Adoption, and Collaborative Learning on Student Engagement in Business Education

This study explores the influence of digital literacy, technological adoption, and collaborative learning on student engagement in business education. Utilizing a quantitative research design, data were collected from 300 undergraduate students enrolled in business programs through a structured questionnaire. The analysis employed descriptive statistics, correlation analysis, and multiple regression techniques to investigate the relationships between the variables. The results revealed that digital literacy, technological adoption, and collaborative learning significantly contribute to student engagement, with collaborative learning emerging as the strongest predictor. The findings underscore the importance of enhancing digital literacy and promoting technology use in educational settings, alongside fostering collaborative learning experiences, to improve student engagement in business education. These insights have implications for educators and curriculum designers seeking to create more effective and engaging learning environments.

Prevalence and determinants of distress at the start of chemotherapy among adult cancer patients in two tertiary hospitals in Kenya

BACKGROUND Chemotherapy is considered the cornerstone in the treatment of many cancers, but it also comes with its challenges. The distress experienced by patients at the commencement of chemotherapy is a critical aspect of their cancer journey, with profound implications for their overall well-being and treatment outcomes. This study aimed to assess the prevalence and determinants of distress before the first dose of chemotherapy among adult cancer patients in two tertiary hospitals in Kenya. METHODOLOGY This was a cross-sectional study. A total of 438 patients who were scheduled for the first dose of chemotherapy were interviewed using a structured questionnaire. Those who were not able to give consent, those who were only on oral chemotherapy and those who were not chemotherapy naïve were excluded. Distress was measured using the Distress thermometer with a cutoff point of four. Data analysis was performed using SPSS V26. RESULTS The study participants interviewed were predominantly women (63%), older than 50 (53%), unemployed (87%), married (65%), Christian (99%), lived less than 100 Kilometers (55%), lived with family (90%), educated up to the primary level (49%), and had insurance (92%). The most prevalent cancers were reproductive organ tumours, and 43% of the participants had stage four disease. A total of 89 % of the participants were clinically distressed (DT ≥ 4). In a chi-square analysis, there was a significant relationship between unemployment (P=0.003), residence (P=0.002), income level (P=0.001), insurance status (P= 0.004), living conditions (P=0.003), education level (P=0.001), tumour type (P=0.004), goal of therapy (P=0.001) and stage of disease (P=0.000) with clinical distress. On a multi-variate regression analysis, the strongest predictors were the cancer stage with (aOR: 8.4 P=0.000), education level (aOR: 8.3 P=0.001) along with unemployment (aOR: 4.1 P=0.003) and goal of therapy (aOR: 6.32 P=0.001) CONCLUSION The prevalence of distress at the start of chemotherapy is high, and interventions should be initiated before chemotherapy. Sociodemographic and disease characteristics should be considered when developing targeted interventions to manage distress among patients starting chemotherapy.

Unravelling COVID-19 social mortality patterns using conditional inference tree algorithm

Abstract Background The COVID-19 pandemic led to significant excess mortality in 2020 in Belgium. By using microlevel cause-specific mortality data for the total Belgian adult population in 2020, three outcomes were considered in this study aiming at predicting sociodemographic (SD) and socioeconomic (SE) patterns of 1) COVID-19 specific death compared to survival; 2) all other causes of death (OCOD) compared to survival; 3) COVID-19 specific deaths compared to all OCOD. Methods Multivariable logistic regression models were fitted for the three outcomes. In addition, we computed conditional inference tree (CIT) algorithms, complementing regression models, to identify and rank the strongest SD and SE predictors of the three outcomes. Results Older people, males, people living in collectivities, first-generation migrants, and deprived SE groups experienced higher odds of dying from COVID-19 compared to survival; living in collectivities was identified by the CIT as the strongest predictor followed by age and sex. Education emerged as one of the strongest predictors for people not living in collectivities. Overall, similar patterns were observed for all OCOD except for first- and second-generation migrants having lower odds of all OCOD compared to survival; age group was identified by the CIT as the strongest predictor. Older people, males, people living in collectivities, first- and second-generation migrants, and people with lower levels of education had higher odds of COVID-19 death compared to all OCOD; living in collectivities was identified by the CIT as the strongest predictor followed by age, sex, and migration status. Education and income emerged as the strongest predictors among people not living in collectivities. Conclusions This study identified important SD and SE disparities in COVID-19 mortality underlying the importance of implementing preventive measures, particularly within the most vulnerable populations, in infectious disease pandemic preparedness. Key messages • Living in collectivities appeared to be the strongest predictor of COVID-19 death across all age groups, highlighting the importance of preventive measures in reducing the transmission of the virus. • Poor education plays a crucial role in predicting COVID-19 death among people not living in collectivities, highlighting the importance of targeting preventive measures towards low educated groups.

The influence of health literacy on health outcomes and behaviors in fourth-graders in Germany

Abstract Background For the adult population, evidence suggests that a high level of subjective health literacy is associated with a number of favorable health outcomes and behaviors. However, for younger populations, particularly children, little evidence is available. This study investigates the relationship between subjective health literacy, health outcomes, and health behaviors in children. Methods We conducted a representative survey of 4th-grade students (age 8-11) in North Rhine-Westphalia, Germany, between Oct. 2022 and Feb. 2023. Subjective health literacy was measured with the HLS-Child-Q15 questionnaire. For mental and physical well-being, the KINDL-R was used. For health behaviors, we asked about the frequency of (1) brushing teeth, (2) eating fruit and (3) vegetables, (4) exercising, (5) consuming sweetened drinks, and (6) wearing a helmet when riding the bike. Regression analysis was used to determine the impact of health literacy on outcomes, controlling for a number of sociodemographic indicators (birthplace, home language, sex, age), as well as the tendency to give socially desirable responses. Health behaviors were rated on a Likert scale and where dichotomized for ordinal regression. Results n = 1085 students are included with a mean age of 9.5 years (SD=.6). 50.3% are female. While controlling for a number of variables, health literacy was a significant predictor (p&amp;lt;.05) for every indicator except the frequency of (1) brushing teeth, (4) exercising, and (5) consumption of sweetened drinks. For mental well-being, health literacy was the strongest predictor. Conclusions Our findings highlight the potentially enabling role of subjective health literacy regarding favorable health outcomes and health behaviors. However, because this is a study among younger children, further research is needed on the interplay of individual subjective health literacy, social contexts (e.g., parental health literacy and health behaviors), and children’s health outcomes and behaviors.

Understanding Maritime Subjects in Vocational High Schools through Online Learning

This study explores the effectiveness of online learning for maritime subjects in Indonesian vocational high schools, focusing on how the rapid advancement of information technology has reshaped education in this unique field. Using a quantitative approach with 275 respondents, the research analyzes key factors that influence students' understanding of maritime subjects, such as digital literacy, motivation, and their perceptions of the effectiveness of online learning. The findings indicate moderate levels of both digital literacy and motivation for online learning, with flexibility being the most appreciated benefit. However, challenges related to social isolation were also noted. A predictive model developed during the research accounts for 43% of the variance in comprehension of the subject matter, identifying digital literacy and perceived online learning effectiveness as the strongest predictors. Additionally, the grade level of students significantly influenced their comprehension scores. This study emphasizes the need to integrate digital skills training and to employ engaging instructional strategies to enhance learning outcomes. Future research could investigate the use of immersive technologies, such as virtual reality or simulations, to better support practical skills development in maritime education, ensuring that students are well-prepared for real-world challenges in the maritime industry

Readiness for hospital discharge on people after hip replacement surgery in Vietnam: A cross-sectional study

Background &amp; Aim: Readiness for hospital discharge is closely linked to post-operative complications, readmission rates, and the post-discharge health status of patients after hip replacement surgery. This study aimed to assess discharge readiness and identify the factors that predict it in patients undergoing hip replacement surgery. Methods &amp; Materials: This cross-sectional descriptive study included 112 patients who had undergone hip replacement surgery at Hospital X in Middle Vietnam. Participants were selected using a convenience sampling method, and data were collected within 4 hours before hospital discharge. The Readiness for Discharge Scale, developed by Weiss et al. was used to measure discharge readiness. Data analysis was conducted using SPSS 20.0 statistical software. Results: The average discharge readiness score was 6.06± 2.10, indicating a low discharge readiness level. Multivariable linear regression analysis revealed that age, living conditions, planned admission, previous admission for the same diagnosis, and length of hospital stay significantly predicted 78.5% of the variance in discharge readiness (F= 77.626, p&lt; 0.001). Among these factors, the strongest predictor was previous admission for the same diagnosis (β= 0.341, p&lt; 0.001), followed by planned admission (β= 0.324, p&lt; 0.001). Conclusion: The findings indicate that patients' readiness for discharge after hip replacement surgery remains low, with various factors influencing their readiness. Nurses caring for these patients should consider these factors to improve discharge readiness and patient outcomes.

Flourishing levels among health and non-health profession students in Saudi Arabian colleges.

This study aimed to evaluate the levels of flourishing among university students, compare these levels between students in health-related and non-health-related colleges, and identify factors that predict flourishing. A cross-sectional study was conducted at Imam Abdulrahman Bin Faisal University, Saudi Arabia, involving 1,148 students from the first to fourth year across both academic sectors. Data were collected utilizing the self-reported Global Flourishing Study Questionnaire (GFS) during the period from September 2023 to June 2024. Multistage sampling techniques were employed to ensure a representative sample, with data collection facilitated through a self-administered electronic link on QuestionPro resulting in a response rate of 51.7%. Data analysis was performed using SPSS version 22, incorporating descriptive statistics, t-tests, ANOVA, and regression analysis to identify predictors of flourishing. The reliability and validity of the questionnaire were assessed using Cronbach's alpha and Pearson's correlation analysis. The study included nearly equal proportions of students from health (51.0%) and nonhealth (49.0%) colleges. The average flourishing score was 85.6 (SD=18.6), with a slight increase in health colleges (85.7) compared with non-health colleges (85.4). Factors that significantly affected flourishing included gender, employment status, exercise frequency, experiences of abuse, and income. In the multiple regression analysis, well-being emerged as the strongest predictor, followed by external factors, disposition, and behavior. Gender exhibited a positive association with flourishing, whereas religion had a negative influence. Furthermore, employment and higher income levels were found to positively contribute to flourishing. This study revealed elevated levels of flourishing among university students in Saudi Arabia, with a notable average score of 85.6. Although the differences between students enrolled in health-related and non-health-related colleges were minimal, significant predictors of flourishing were identified, including well-being, external factors, disposition and behavior, gender, religious affiliation, employment status, income, frequency of exercise, and experience of abuse. These findings underscore the complexity of flourishing and highlight the necessity of considering a range of sociodemographic and lifestyle factors to promote student well-being.

Environmental, Social and Governance Awareness and Organisational Risk Perception Amongst Accountants

The relationships between accountants’ environmental, social and governance (ESG) awareness and their perceptions of organisational risk are examined in this study. The emphasis is on the operational, strategic, financial and compliance risks of business organisations. A total of 462 accountants in Hong Kong were included via stratified random sampling and snowball sampling to ensure population diversity. A stratified random approach was used to include factors such as age, gender, income and experience, and snowball sampling amongst professional networks was used to ensure representativeness. A significant positive relationship exists between ESG awareness and risk perception, with environmental and governance factors emerging as the strongest predictors. Accountants with deep ESG awareness, especially in the aforementioned areas, can successfully identify and manage nontraditional risks such as regulatory changes and environmental threats. The findings highlight the need for institutionalising ESG-focused education in accounting and corporate governance to improve risk management capabilities. Increased ESG awareness can ensure responsible and sustainable business behaviour. Future research can expand the sample of accountants to executives and use longitudinal designs to capture the dynamic nature of ESG awareness and risk perception.

Evaluation of clinical and radiographic warning signs for prediction of oroantral communication following tooth extractions

ObjectivesOroantral communication (OAC) is a relatively common and mild complication of maxillary tooth extractions. Preoperative prediction of OAC can reduce treatment duration and prepare both operators and patients for the procedure. This study aims to identify alarming radiographic and clinical indicators that can predict OAC therefore assisting clinical decision making to practicing general dentists.MethodsIn this retrospective case–control study the OAC group consisting of 97 cases and a control group twice the size was established. Clinical data were collected, and measurements were conducted separately by two blinded observers on digital panoramic radiographs. Inter-rater reliability was assessed. In case of disagreement a third observer’s results were utilized. The correlation between OAC and demographic data (age, sex), as well as various factors assessed on panoramic radiographs (including, but not limited to, the length of the root, root projection into the sinus, bone width, presence of mesial and distal adjacent teeth), was statistically evaluated.ResultsInter-rater reliability was found to be excellent. Several factors were identified as potential predictors of OAC. According to our model, the strongest predictors were the distance between the cemento-enamel junction and marginal bone, extent of root projection into the sinus, presence of sinus recess around the roots, angulation, and absence of the mesial adjacent tooth.ConclusionsWell-defined measurements on panoramic radiographs may aid in predicting OAC. Further prospective investigations are necessary to confirm these indicators and address factors related to clinical examination and operation.Clinical relevanceWe present several clinical and radiographic warning signs of OAC that can facilitate pre-extraction decision-making.

Phenotyping in vivo chronic inflammation in multiple sclerosis by combined 11C-PBR28 MR-PET and 7T susceptibility-weighted imaging.

11C-PBR28 positron emission tomography (PET), targeting the translocator protein, and paramagnetic rim lesions (PRL) have emerged as promising imaging markers of MS chronic inflammation. No consensus on which is the optimal marker exists. To investigate the ability of 11C-PBR28 PET and PRL assessment to identify chronic inflammation in white matter (WM) MS lesions and their relation to neurological impairment. Based on 11C-PBR28 uptake, brain WM lesions from 30 MS patients were classified as PET active or inactive. The PRL presence was assessed on 7T phase reconstructions, T1/T2 ratio was calculated to measure WM microstructural integrity. Less than half (44%) of non-PRL WM lesions were active on 11C-PBR28 imaging either throughout the lesion (whole active) or at its periphery. PET peripherally active lesions and PRL did not differ in T1/T2 ratio and 11C-PBR28 uptake. A positive correlation was observed between PRL and active PET lesion count. Whole active PET lesion volume was the strongest predictor (β = 0.97, p < 0.001) of increased Expanded Disability Status Scale scores. 11C-PBR28 imaging reveals more active WM lesions than 7T PRL assessment. Although PRL and PET active lesion counts are related, neurological disability is better explained by PET whole active lesion volume.