Hierarchical Linear Regression Models Research Articles

Environmental and psychopathological predictors of clinical high-risk of psychosis in adolescence.

Clinical high-risk psychosis (CHRp) samples can be heterogeneous, consisting essentially of people with not only psychotic-like experiences but also nonspecific symptoms that may reflect common mental disorders such as depression, anxiety, or substance abuse pathologies. Few studies have attempted to analyze and understand psychosis risk in relation to both environmental (ER) and psychopathological risk (PsR) factors. This study aimed to determine the clinical risk of psychosis in adolescents. A representative sample of 1824 Spanish adolescents from the general population was evaluated using different scales to thoroughly examine the possible interaction of CHRp with various ER and PsR factors. Partial correlations were calculated to assess the relationships between the variables. A series of hierarchical linear regression models were then used to obtain a CHRp predictor model. The CHRp predictor model indicated that PsR was the most significant determining factor, explaining 22% of the total associated variance of CHRp. However, the ER factor also emerged as a significant predictor of high-risk psychosis (accounting for 9% of the variance). A predictive model for CHRp in adolescents was found, in which common psychological problems were presented as more determinant risk factors than ER disruptors. Furthermore, certain transdiagnostic processes, such as psychological inflexibility, may play a central role in the development of mental health problems, including psychosis. Specifying the mechanisms underlying the emergence of CHRp in adolescence is the key to optimizing the focus of preventive therapeutic interventions in these early stages.

Love yourself as a therapist, doubt yourself as an institution? Therapist and institution effects on outcome, treatment length, and dropout

Objective: Research suggests that some therapists achieve better outcomes than others. However, an overlooked area of study is how institution differences impact patient outcomes independent of therapist variance. This study aimed to examine the role of institution and therapist differences in adult outpatient psychotherapy. Method: The study included 1428 patients who were treated by 196 therapists at 10 clinics. Two- and three-level hierarchical linear regression models were employed to investigate the effects of therapists and institutions on three dependent patient variables: (1) symptom change, (2) treatment duration, and (3) dropout. Level three explanatory variables were tested. Results: The results showed that therapist effects (TE) were significant for all three types of treatment outcome (7.8%–18.2%). When a third level (institution) was added to the model, the differences between therapists decreased, and significant institution effects (IE) were found: 6.3% for symptom change, 10.6% for treatment duration, and 6.5% for dropout. The exploratory analyses found no predictors able to explain the systematic variation at the institution level. Discussion: TE on psychotherapy outcomes remain a relevant factor but may have been overestimated in previous studies due to not properly distinguishing them from differences at the institution level.

Impact of psychological safety and inclusive leadership on online learning satisfaction: the role of organizational support

The appeal of online education within the academic community has grown significantly due to advancements in technology and increased investments made during the pandemic. Despite the rapid expansion of research in online education, most studies have concentrated on technology and teaching techniques, overlooking social factors that also play a crucial role in students’ contentment with online learning. This study uses quantitative methods to investigate the impact of selected social variables on students’ satisfaction with online education. The research employed a designed questionnaire to gather data from African students engaged in online studies abroad. The collected data was then analyzed using SPSS-AMOS version 23. The study utilized a hierarchical linear regression model to assess the influence of different variables on students’ satisfaction with online education. The findings revealed that psychological safety and inclusive leadership positively influenced students’ satisfaction with online education. Conversely, perceived organizational support and learner–learner interaction adversely affected students’ satisfaction in the online learning environment. Moreover, the research highlighted that psychological safety, inclusive leadership, and perceived organizational support positively influenced learner–learner interaction. Additionally, perceived organizational support was identified as a moderator, affecting the relationships between other variables and students’ satisfaction with online education. Because of these findings, educational institutions and researchers are recommended to recognize social constructs’ critical role in students’ satisfaction with online education. It is essential to broaden the focus beyond technological aspects and teaching methods, as social variables are equally vital for students to have a fulfilling academic experience in online education.

Leading Stressors and Coping Strategies Associated With Maternal Physical and Mental Health During the Extended Postpartum Period.

A critical gap exists in understanding stressors and coping that affect women's health beyond 6 weeks postpartum. Using new stressor and coping scales tailored to postpartum women, we examined the relationship of postpartum-specific stressors and coping to women's physical and mental health between 2 to 22 months after childbirth. A total of 361 women of diverse race, ethnicity, and functional abilities recruited through clinical and online methods completed online surveys that included Sources of Stress-Revised subscales, such as overload, changes after pregnancy, and low support resources; Postpartum Coping Scale subscales, such as self-regulation, self-care, and health promotion; Patient-Reported Outcomes Measurement Information System Global Health, covering physical and mental health dimensions; and social demographic items. Analyses included hierarchical linear regression models adjusted for social factors. Education and employment were the only social factors associated with physical and mental health, respectively. After adjusting for social factors, overload (P <.001) and coping through health promotion (P =.020) were the only additional variables associated with physical health. After adjusting for social factors, overload (P <.001) and low support resources (P =.002) and coping through self-care (P =.036) were the only additional variables associated with mental health. Thus, being overloaded was the key stressor associated with decreases in physical and mental health. Health promotion was associated with increases in physical health, and self-care was associated with increases in mental health. These findings point to directions for health care and community interventions to promote health for postpartum women under stress. Strengths of our study include application of stress and coping scales tailored to postpartum women, whereas a limitation is use of a cross-sectional design.

Eveningness chronotype influences social functioning by deteriorating depressive symptoms in remitted patients with schizophrenia

ABSTRACT Sleep and circadian rhythm disruption (SCRD) is common in schizophrenia patients, who also typically experience impaired social functioning. While various factors influence social functioning in schizophrenia, the specific impact of sleep and circadian rhythm disruption remains unclear. This study aimed to investigate the connection between chronotype and social functioning in remitted schizophrenia patients, examining the mediating roles of depression and sleep quality. The study included 185 patients diagnosed with schizophrenia based on DSM-5 criteria. After categorizing the patients into morningness, eveningness, or intermediate chronotypes using the Morningness-Eveningness Questionnaire(MEQ), they were assessed with the Positive and Negative Syndrome Scale(PANSS), Calgary Depression Scale for Schizophrenia(CDSS), Personal and Social Performance Scale(PSPS) and Pittsburgh Sleep Quality Index(PSQI). The eveningness chronotype group showed higher CDSS and PSQI scores and lower PWBS and PSPS-Total scores than the other groups (p < 0.05). A hierarchical linear regression model assessed MEQ, PSQI, and CDSS scores’ effects on PSPS total scores. MEQ scores’ significance diminished when CDSS scores were included. Eveningness chronotype, particularly with increased depressive symptoms, negatively impacts social functioning in remitted schizophrenia patients.These findings contribute to the understudied area of chronotype in schizophrenia and its impact on social functioning, including its interaction with sleep..

Gender differences in PTSD severity and pain outcomes: Baseline results from the LAMP trial.

Post-traumatic stress disorder (PTSD) and chronic pain are highly prevalent comorbid conditions. Veterans dually burdened by PTSD and chronic pain experience more severe outcomes compared to either disorder alone. Few studies have enrolled enough women Veterans to test gender differences in pain outcomes [catastrophizing, intensity, interference] by the severity of PTSD symptoms. Examine gender differences in the association between PTSD symptoms and pain outcomes among Veterans enrolled in a chronic pain clinical trial. Participants were 421 men and 386 women Veterans with chronic pain who provided complete data on PTSD symptoms and pain outcomes. We used hierarchical linear regression models to examine gender differences in pain outcomes by PTSD symptoms. Adjusted multivariable models indicated that PTSD symptoms were associated with higher levels of pain catastrophizing (0.57, 95% CI [0.51, 0.63]), pain intensity (0.30, 95% CI [0.24, 0.37]), and pain interference (0.46, 95% CI [0.39, 0.52]). No evidence suggesting gender differences in this association were found in either the crude or adjusted models (all interaction p-values<0.05). These findings may reflect the underlying mutual maintenance of these conditions whereby the sensation of pain could trigger PTSD symptoms, particularly if the trauma and pain are associated with the same event. Clinical implications and opportunities testing relevant treatments that may benefit both chronic pain and PTSD are discussed.

Hospital Length of Stay and Associated Factors in Patients with Osteoarthritis from Germany: A Cross-Sectional Study.

Objective: There is a scarcity of data on hospital length of stay (LOS) in the osteoarthritis population. Therefore, this study aimed to investigate hospital LOS and associated factors in patients with osteoarthritis from Germany. Methods: The present cross-sectional study included patients hospitalized for osteoarthritis in one of fourteen hospitals in Germany between 2018 and 2023 (hospital database; IQVIA). The study outcome was the duration of hospital stay in days. Study covariables included age, sex, hospital department, osteoarthritis type, co-diagnosis, and hospitalization-related procedure. Associations between covariables and hospital LOS were analyzed using hierarchical linear regression models. Results: There were 8770 patients included in the study (mean [standard deviation] age 68.7 [10.8] years; 60.2% women). The mean (standard deviation) hospital LOS was 8.5 (5.0) days. Factors positively and significantly associated with hospital LOS were older age, female sex, orthopedic surgery and other medical specialty departments (compared with other surgery departments), knee and other and unspecified osteoarthritis (compared with hip osteoarthritis), multiple co-diagnoses (e.g., acute posthemorrhagic anemia, other disorders of fluid, electrolyte, and acid-base balance, and disorders of purine and pyrimidine metabolism), and several hospitalization-related procedures (i.e., geriatric rehabilitation, hip arthroplasty, and knee arthroplasty). Conclusions: The mean hospital LOS was higher than eight days in this osteoarthritis population from Germany, with a spectrum of demographic, clinical, and hospitalization-related factors associated with this hospital LOS. In this context, interventions are needed to reduce the LOS of hospitalizations for osteoarthritis in Germany.

Sex moderates the association between quantitative sensory testing and acute and chronic pain after total knee/hip arthroplasty.

Acute postsurgical pain (APSP) may persist over time and become chronic. Research on predictors for APSP and chronic postsurgical pain (CPSP) has produced inconsistent results. This observational study aimed to analyze psychological and psychophysical variables associated with APSP and CPSP after total knee or hip arthroplasty, and to explore the role of sex. Assessments were conducted before surgery, 48 h, and 3 months postsurgery, including questionnaires (sociodemographic, pain related, and psychological) and quantitative sensory testing (QST). Hierarchical linear regression models analyzed potential predictors of APSP and CPSP, and moderation analyses evaluated the role of sex. The study included 63 participants undergoing total knee (34, 54%) or hip (29, 46%) arthroplasty. Thirty-one (49.2%) were female and 32 (50.8%) were male. APSP (48 h) was associated with impaired conditioned pain modulation (CPM) (β = 0.301, p = 0.019). CPSP (3 months) was associated with being female (β = 0.282, p = 0.029), longer presurgical pain duration (β = 0.353, p = 0.006), knee arthroplasty (β = -0.312, p = 0.015), higher APSP intensity (β = 373, p = 0.004), and impaired CPM (β = 0.126, p = 0.004). In multivariate analysis, these clinical variables were significant predictors of CPSP, unlike sex, and CPM (adj. R 2 = 0.349). Moderation analyses showed that wind-up ratio (WUR) was a significant predictor of APSP in men (WUR × sex: b = -1.373, p = 0.046) and CPM was a significant predictor of CPSP in women (CPM × sex: b = 1.625, p = 0.016). Specific QST parameters could identify patients at risk for high-intensity APSP and CPSP, with sex as a moderator. This has important clinical implications for patient care, paving the way for developing tailored preventive pain management strategies.

Neurocognitive markers during maximum alcohol use in late adolescence as predictors of change in later drinking behaviors

AbstractThe influence of alcohol use on later neurocognitive functioning is well researched, yet few studies have investigated whether neurocognition post‐drinking initiation in adolescence predicts changes in later alcohol use. The objective of this study was to investigate neurocognitive task performance during maximum alcohol use in late adolescence as predictors of drinking behaviors 3–7 years later. Analyses (n = 105) were conducted on a longitudinal data set involving adolescents (12–13 years old) who were followed for 16 years. Time 1 (T1) was defined as the individuals' maximum drinking year within the first 10 study years and Time 2 (T2) was the first available data entry 3–7 years after T1. Four hierarchical linear regression models predicting follow‐up alcohol use were estimated: drinking days, average drinks per drinking day, peak drinks, and binge episodes. All models included inhibition/cognitive flexibility, visuospatial ability, verbal memory, working memory, and their interactions with sex, while covarying for age at T1, follow‐up duration, and controlling for T1 drinking. Better visuospatial ability at T1 predicted decreases in later binge episodes at T2 (β = −0.19, p = 0.048, partial r2 = 0.039). While better inhibition/cognitive flexibility at T1 predicted increases in follow‐up drinks per drinking day at T2 (β = 0.18, p = 0.016, partial r2 = 0.057). Findings suggest specific neurocognitive abilities during maximum drinking in late adolescence are useful as predictors of change in later drinking quantity per occasion and could potentially inform intervention research targeting this age group.

Birthweight trends and their explanatory factors in Hungary between 1999 and 2018: an analysis of the Hungarian Tauffer registry

BackgroundThe increasing birthweight trend stopped and even reversed in several high income countries in the last 20 years, however the reason for these changes is not well characterized. We aimed to describe birthweight trends of term deliveries in Hungary between 1999 and 2018 and to investigate potential maternal and foetal variables that could drive these changes.MethodsWe analysed data from the Hungarian Tauffer registry, a compulsory anonymized data collection of each delivery. We included all singleton term deliveries in 1999–2018 (n = 1,591,932). We modelled birthweight trends separately in 1999–2008 and 2008–2018 in hierarchical multiple linear regression models adjusted for calendar year, newborn sex, maternal age, gestational age at delivery, and other important determinants.ResultsMedian birthweights increased from 3250/3400 g (girl/boy) to 3300/3440 g from 1999 to 2008 and decreased to 3260/3400 g in 2018. When we adjusted for gestational age at delivery the increase in the first period became more pronounced (5.4 g/year). During the second period, similar adjustment substantially decreased the rate of decline from 2.5 to 1.4 g/year. Further adjustment for maternal age halved the rate of increase to 2.4 g/year in the first period. During the second period, adjustment for maternal age had little effect on the estimate.ConclusionsOur findings of an increasing birthweight trend (mostly related to the aging of the mothers) in 1999–2008 may forecast an increased risk of cardiometabolic diseases in offsprings born in this period. In contrast, the decreasing birthweight trends after 2008 may reflect some beneficial effects on perinatal morbidity. However, the long-term effect cannot be predicted, as the trend is mostly explained by the shorter pregnancies.

Association between dietary magnesium intake, inflammation, and neurodegeneration.

Consistent evidence shows that magnesium (Mg) intake is associated with lower blood pressure (BP), and that lower BP is associated with improved cerebral health. However, recent findings indicate that the positive effect of dietary Mg intake on cerebral health is not mediated by a decrease in BP. As Mg's anti-inflammatory action is a plausible alternative mechanism, the objective of this study was to investigate the associations between Mg intake and inflammation to determine whether it mediates any neuroprotective effect. Participants from the UK Biobank (n = 5775, aged 40-73 years, 54.7% female) were assessed for dietary magnesium using an online food questionnaire, brain and white matter lesion (WML) volumes were segmented with FreeSurfer software, and inflammation markers including high-sensitivity C-reactive protein (hs-CRP), leukocyte, erythrocyte count, and Glycoprotein acetylation (GlycA) were measured using specific laboratory techniques such as immunoturbidimetry, automated cell counting, and nuclear magnetic resonance. Hierarchical linear regression models were performed to investigate the association between dietary Mg, and inflammatory markers and between dietary Mg, brain and WMLs volumes. Mediation analysis was performed to test a possible mediation role of inflammation on the association between dietary Mg and brain and WMLs volumes. Higher dietary Mg intake was associated with lower inflammation: hs-CRP level (- 0.0497%; 95% confidence interval [CI] - 0.0497%, - 0.0199%) leukocytes count (- 0.0015%; 95%CI - 0.00151%, - 0.0011%), and GlycA (- 0.0519%; 95%CI - 0.1298%, - 0.0129%). Moreover, higher dietary Mg intake was associated with larger grey matter volume (0.010%; 95%CI 0.004%, 0.017%), white matter volume (0.012%; 95%CI 0.003, 0.022) and right hippocampal volume (0.002%; 95%CI 0.0007,-0.0025%). Lower hs-CRP levels mediated the positive association between higher dietary Mg intake and larger grey matter volume. The anti-inflammatory effects of dietary Mg intake in the general population, appears to mediate its neuroprotective effect.

Post-Stroke Impairments of Manual Dexterity and Finger Proprioception: Their Contribution to Upper Limb Activity Capacity

Background Knowing how impaired manual dexterity and finger proprioception affect upper limb activity capacity is important for delineating targeted post-stroke interventions for upper limb recovery. Objectives To investigate whether impaired manual dexterity and finger proprioception explain variance in post-stroke activity capacity, and whether they explain more variance than conventional clinical assessments of upper limb sensorimotor impairments. Methods Activity capacity and hand sensorimotor impairments were assessed using clinical measures in N = 42 late subacute/chronic hemiparetic stroke patients. Dexterity was evaluated using the Dextrain Manipulandum to quantify accuracy of visuomotor finger force-tracking (N = 36), timing of rhythmic tapping (N = 36), and finger individuation (N = 24), as well as proprioception (N = 27). Stepwise multivariate and hierarchical linear regression models were used to identify impairments best explaining activity capacity. Results Dexterity and proprioceptive components significantly increased the variance explained in activity capacity: (i) Box and Block Test was best explained by baseline tonic force during force-tracking and tapping frequency (adjusted R2 = .51); (ii) Motor Activity Log was best explained by success rate in finger individuation (adjusted R2 = .46); (iii) Action Research Arm Test was best explained by release of finger force and proprioceptive measures (improved reaction time related to use of proprioception; adjusted R2 = .52); and (iv) Moberg Pick-Up test was best explained by proprioceptive function (adjusted R2 = .18). Models excluding dexterity and proprioception variables explained up to 19% less variance. Conclusions Manual dexterity and finger proprioception explain unique variance in activity capacity not captured by conventional impairment measures and should be assessed when considering the underlying causes of post-stroke activity capacity limitations. URL: https://www.clinicaltrials.gov. Unique identifier: NCT03934073.

Spatial distribution and policy implications of the exhaust emissions of two-stroke motorcycle taxis: a case study of southwestern state in Nigeria

Two-stroke motorcycles emit harmful exhaust fumes because of incomplete combustion. Although they constitute the main fleet of motorcycle taxis in sub-Saharan Africa, monitoring, spatial assessment, and regulation are weak, leaving dire health consequences in cities. This study collected motorcycle raw exhaust emissions of 1,950 two-stroke petrol-driven motorcycle taxis, otherwise called okada, in Ogun State, Nigeria, using an idle mode test approach under 10 minutes and employed correlations, hierarchical multiple linear regression models, and spatial analysis. It was found that carbon monoxide (CO) and hydrocarbons (HC) were the most highly concentrated, and the latter were beyond allowable limits. The concentration of CO was found to be at the minimum of 0.00 % and the highest being at 6.40% (an average of 1.05%), while the HC concentration was reported at the minimum of 18.00 ppm and the highest at 15446 ppm (an average of 3560 ppm). Notably, Kriging interpolation analysis indicated that cumulative effects due to the clustering and operations of motorcycle taxis could increase these concentrations over time, extending their long-term impacts. Given the severe effects of these emissions on health and the wider environment, a DPSIR policy framework is proposed to regulate two-stroke motorcycle taxis in sub-Saharan Africa.

Relationship satisfaction and metabolic health parameters: a cross-sectional study in Burkinabe population of older adults

BackgroundOver- and undernutrition coexist in many African countries and pose a threat to metabolic health. This study assessed the associations between relationship satisfaction and Body Mass Index (BMI), waist circumference (WC), and glycated hemoglobin (HbA1c), in a rural population of older adults in Burkina Faso. It also explored potential gender differences and the mediating role of depressive symptoms.MethodsData from the “Centre de Recherche en Santé de Nouna (CRSN) Heidelberg Aging Study (CHAS),” a cross-sectional population-based study conducted in 2018 in Burkina Faso, were used in our study. Hierarchical linear regression models were applied for each of the three outcome variables. Among 2291 participants aged 40 years or older who provided data on relationship satisfaction, 2221, 2223, and 2145 participants had BMI, waist circumference (WC), and HbA1c values respectively.ResultsHigher relationship satisfaction (CSI-4 score) was associated with increased BMI (β = 0.05, p = 0.031) and WC (β = 0.12, p = 0.039). However, the association of CSI-4 and BMI became non-significant after controlling for depressive symptoms (PHQ-9 score) and physical inactivity (BMI: β = 0.04, p = 0.073). Depressive symptoms fully mediated the relationship between relationship satisfaction and BMI (β = -0.07, p = 0.005). There was no significant association between relationship satisfaction and HbA1c. These results were consistent across genders and age groups.ConclusionHigher relationship satisfaction may lead to increased body weight among Burkinabe adults aged 40 years and older, and depressive symptoms may be a mediator in this association.

Quantifying the relationship between gardening and health and well-being in the UK: a survey during the covid-19 pandemic

BackgroundRates of non-communicable diseases, including cardiovascular disease and type 2 diabetes, and mental health problems, such as anxiety and depression, are high and rising in the urbanising world. Gardening could improve both mental and physical health and help prevent a range of conditions by increasing fruit and vegetable (F&V) consumption, promoting physical activity, and reducing stress. However, good quality quantitative research in the area is scarce, and our understanding of the role of allotments and home gardens, and the effects of the level of engagement in gardening and involvement with food production has thus far been limited.MethodsWe quantitatively assess the relationship between home and allotment gardening and various indicators and predictors of health and well-being using an online survey of gardeners (n = 203) and non-gardeners (n = 71) in the UK. The survey was composed of multiple validated questionnaires (including the Short Form Food Frequency Questionnaire (SFFFQ), the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), the Physical Health Questionnaire (PHQ) and the Self-Rated Health question (SRH)) and self-defined questions relating to participants’ involvement with gardening and food production, and relevant demographic and lifestyle factors. Data were analysed using a series of hierarchical logistic and multiple linear regression models adjusting for socio-demographic variables.ResultsAfter adjusting for relevant socio-demographic factors, gardening related variables were associated with better self-rated health, higher mental well-being, increased F&V consumption. Higher F&V intake was in turn also associated with better self-rated health and decreased odds of obesity. Thus, gardening had a positive association with four different aspects of health and well-being, directly or indirectly via increased F&V consumption.ConclusionsOur results suggest that gardening in UK allotments and domestic gardens may promote different aspects of health and well-being via multiple mechanisms. Improving access to growing space and promoting regular gardening could provide a range of benefits to public health. More research on how socio-economic factors influence the health and well-being benefits of gardening will help policymakers devise strategies to maximise these benefits.

Sleep, Alcohol and Cannabis Use in College Students With and Without Attention-Deficit/Hyperactivity Disorder

Background: Relations among attention-deficit/hyperactivity disorder (ADHD), sleep, and substance-related negative consequences are largely unknown. In this cross-sectional study, we examined associations among ADHD diagnosis, sleep, and alcohol-related consequences. We also evaluated the independent and interactive effects of sleep and ADHD on alcohol-related negative consequences, above and beyond levels of alcohol use. Methods: College students who drink alcohol with (n = 51) and without (n = 50) ADHD completed an assessment that included a diagnostic interview assessing ADHD, and questionnaire measures of sleep quality, substance use, and associated consequences. Analyses utilized a series of hierarchical linear regression models and explored these aims for cannabis use in a subset of participants (n = 52 participants that used cannabis). Results: College students who drink alcohol with ADHD reported significantly worse sleep quality and more alcohol-related consequences, relative to those without ADHD. When ADHD and sleep quality were included in the model, ADHD—but not sleep quality—was independently associated with alcohol consequences, but not cannabis consequences. There were no moderating effects of ADHD on the associations between sleep and substance-related consequences. Conclusions: Students who drank alcohol with ADHD may be particularly vulnerable to experiencing poor sleep and consequences from their substance use, compared to their heavy drinking peers without ADHD. Future, larger scale studies should consider longitudinal effects as well as underlying mechanisms of risk.

Dental Students' Satisfaction With Web-Based Learning During the Initial Phase of the COVID-19 Pandemic: Mixed Methods Study.

The COVID-19 pandemic has precipitated an accelerated shift in education, moving from traditional learning to web-based learning. This transition introduced a notable transactional distance (TD) between the instructors and learners. Although disease control and staff and students' safety are the top priorities during a pandemic, the successful delivery of education is equally crucial. However, the ramifications of this swift transition are particularly critical in the context of dental education. Dental education is inherently practice oriented, necessitating hands-on training and manual skills development, which poses unique challenges to distance learning approaches. This study aims to examine dental students' web-based learning satisfaction and experience of TD, investigate the predictors of web-based learning satisfaction, and explore the perceptions of students about the advantages and disadvantages of web-based learning. This study explored the factors associated with web-based learning satisfaction using TD theory during the transition to web-based education. Psychological factors that could influence satisfaction were adapted from the health belief model. We conducted a cross-sectional web-based survey of 345 dental students from 2 institutions in South Korea who were enrolled in the spring semester of 2020. Data were collected between July 8 and September 14, 2020. Qualitative analysis was used to examine responses to open-ended questions concerning perceptions of web-based learning. A multivariate hierarchical linear regression model was used to analyze the effects of student characteristics, TD, and psychological factors (ie, perceived risk of infection and efficacy belief of web-based learning) on web-based learning satisfaction. The average score for web-based learning satisfaction was 3.62 (SD 0.84), just above the midpoint of the possible range (1-5). Self-regulated learning (β=0.08; P=.046), learner-instructor interaction (β=0.08; P=.03), and learner-content interaction (β=0.64; P<.001) were associated with higher levels of satisfaction. Moreover, a significant association was revealed between high efficacy beliefs in web-based learning (β=0.20; P<.001) and satisfaction. Although the learning structure (synchronous vs asynchronous) did not exhibit a significant association with satisfaction, the qualitative analysis results revealed that each structure possesses distinct strengths and weaknesses. The students in synchronous learning (79/345, 22.9%) recognized heightened autonomy in the "learning environment" (19/79, 24%); however, technical issues (28/79, 35%) and reduced concentration (15/79, 19%) were identified as downsides. Conversely, the students in asynchronous settings (266/345, 77.1%) emphasized unlimited access to learning content (74/266, 27.8%) and the flexibility of "learning in preferred time" (69/266, 25.9%). Nevertheless, challenges, such as self-management difficulties (66/266, 24.8%) and limited interactions (55/266, 20.7%), were evident. The findings suggest that efforts to minimize TD, facilitating self-regulated learning and interaction among students and instructors, are critical for achieving web-based learning satisfaction. Moreover, establishing a common understanding among students regarding the necessity and efficacy of web-based learning during epidemics could enhance their satisfaction.

Correcting the Cognitive Bias for Commuting Time to Relieve the Driving Stress Level in Snow Weather Condition: A Naturalistic Driving Study in Harbin, China

As a negative emotion, professional drivers’ stress levels significantly affected driving behavior and thus were related to driving safety issues. Nevertheless, current evidence fell considerably short of explaining whether and why private drivers’ stress levels might be influenced while commuting driving in a specific scenario and how to relieve their stress levels. This study aimed to identify and analyze the contributing factors of the drivers’ stress levels while commuting driving in various scenarios (clear or snow weather conditions). On weekdays between 1st October 2020 and 31st January 2022, the questionnaire data from a sample of 985 private drivers were collected from six different locations of business districts in Harbin, China. Based on the naturalistic driving study (NDS) database, a 7-item questionnaire was designed for participants to self-report their driving stress levels in various scenarios, which was generated from the shortened and adapted version of the Perceived Stress Scale (PSS). The results showed that participants’ stress levels had significantly increased in snow weather conditions, especially nervous and stressed feeling, and unable to control the arrival time, which indicated that participants’ highly increased cognitive bias for commuting time could be the critical reason. The results of hierarchical linear regression models indicated that overall stress scores could be predicted through participants’ sociodemographic characteristics, driving experience, commuting driving, and cognitive bias for commuting time. Such an association was significantly strongest with commuting time gaps, especially in snow weather conditions. In addition, a recommendation was derived from these results that correcting the cognitive bias for commuting time could relieve participants’ stress levels. The implication of the reminder message supported this recommendation. The participants’ stress levels were reduced significantly after providing a reminder message every 10 mins while commuting driving in clear weather conditions and every 5 mins in snow weather conditions.

Dielectric spectroscopy with machine learning integrated approach to analysis the influence of N:P ratio on algae growth modeling for forecasting

The task of monitoring algal biomass is a significant challenge in contemporary environmental conservation. A novel technique called dielectric spectroscopy with machine learning integration is an intelligent approach to address this challenge. This work optimized a machine learning supervised PCA, Hierarchical cluster analysis & linear regression model -strengthen the real-time dielectric spectroscopy approach to study the influence of N:P ratios on a model algae Desmodesmus sp. growth for forecasting. As a primary feature, different N:P concentrations (1:1, 2:1, 3:1, 1:2, and 1:3) were utilized to characterize the relationship between dielectric (S11(dB) & ε'') and conventional UV–vis spectroscopy properties (OD686 & Chl-a). The dielectric measurements of S11(dB) & ε'' are consistent with the OD686 & Chl-a value. Highest Desmodesmus sp. OD686 0.87, 0.76 recorded at N:P 3:1, 2:1 ratio respectively. The machine learning based PCA, Hierarchical cluster analysis and linear regression model were applied and found at 0–8 days incubation Desmodesmus sp. growth biomass negatively corelated with S11(dB) & ε“ and positively correlatedly with OD686 & Chl-a respectively, with R2 values > 0.95. While for the 0&8days measured ε”& S11(dB) were −6.169&-0.4765; −7.956 &-0.6775 respectively, the linear regression model was applied to predicted OD686 for 0&8 days was 0.299, 0.234; 0.817, 0.716 respectively, at the ratios N:P (3:1) and the RMES were 0.0047 & 0.0319 respectively. This analysis revealed that the machine learning based integrated approach has high accuracy. Thus, Dielectric spectroscopy and machine learning-integrated method could strengthen to the real-time monitoring of algal biomass or predicting to control the N:P ratios to protecting aquatic ecosystem.

How health risk factors affect inpatient costs among adults with stroke in China: the mediating role of length of stay.

As stroke has become the leading cause of death and disability in China, it has induced a heavy disease burden on society, families, and patients. Despite much attention within the literature, the effect of multiple risk factors on length of stay (LOS) and inpatient costs in China is still not fully understood. To analyse the association between the number of risk factors combined and inpatient costs among adults with stroke and explore the mediating effect of LOS on inpatient costs. A retrospective cross-sectional study was conducted among stroke patients in a tertiary hospital in Nantong City from January 2018 to December 2019. Lifestyle factors (smoking status, exercise), personal disease history (overweight, hypertension, dyslipidemia, diabetes mellitus, atrial fibrillation), family history of stroke, and demographic characteristics were interviewed by trained nurses. Inpatient costs and LOS were extracted from electronic medical records. Hierarchical multiple linear regression models and mediation analysis were used to examine the direct and indirect effects of the number of risk factors combined for stroke on inpatient costs. A total of 620 individuals were included, comprising 391 ischaemic stroke patients and 229 haemorrhagic stroke patients, and the mean age was 63.2 years, with 60.32% being male. The overall mean cost for stroke inpatients was 30730.78 CNY ($ 4444.91), and the average length of stay (LOS) was 12.50 days. Mediation analysis indicated that the greater number of risk factors was not only directly related to higher inpatient costs (direct effect = 0.16, 95%CI:[0.11,0.22]), but also indirectly associated with inpatient cost through longer LOS (indirect effect = 0.08, 95% CI: [0.04,0.11]). Furthermore, patients with high risk of stroke had longer LOS than those in low-risk patients, which in turn led to heavier hospitalization expenses. Both the greater number of risk factors and high-risk rating among stroke patients increased the length of stay and inpatient costs. Preventing and controlling risk behaviors of stroke should be strengthened.