Multilevel Linear Models Research Articles

The Role of State Versus Trait Anxiety on Cognition in Older Adults With Major Depressive Disorder

ObjectiveAnxiety superimposed on late life depression (LLD) results in greater changes to prefrontal and medial temporal brain regions compared to depression alone. Yet, the combined impact of anxiety and depression on cognition in LLD has not been thoroughly investigated. The current study investigated whether annual changes in state and trait anxiety were associated with cognitive changes in older adults with major depression. We hypothesized that the presence of anxiety among older depressed adults would be associated with worse cognitive performance in the domains of memory and executive functioning over time. DesignThree-year longitudinal observational study of older adults with LLD who were offered antidepressant treatment. SettingAcademic Health Center. MethodsParticipants included 124 adults aged 60+ who met criteria for major depression at baseline. The association between anxiety and cognition was examined with separate multilevel linear models that addressed both between-subject and within-person effects of state and trait anxiety on cognitive functioning tests. ResultsIndividuals who experienced annual increases in anxiety above his/her personal average also experienced cognitive decline. Increases in state anxiety were associated with declines in memory and global cognition. By contrast, increases in trait anxiety were associated with declines in mental flexibility and memory. These findings remained significant even when controlling for changes in depression over time. ConclusionIn LLD, individual increases in state and trait anxiety were associated with cognitive declines in different domains.

Differentiated impacts of environmental contexts on residents' environmental attitudes towards ecological restoration programs of China's drylands

Residents' environmental attitudes (EAs) towards ecological restoration programs are vital for evaluating program effectiveness and promoting environmental management. However, most local studies have neglected the indirect environmental contextual influences on residents' EAs, and have omitted the regional variations in the environmental contextual influences. To investigate the multilevel factors affecting residents' EAs, we conducted a transect survey that included the eastern, middle, and western regions in northern China's drylands, where have experienced ecological restoration. Multilevel linear models (MLMs) were applied to analyse the direct and indirect impacts of environmental contexts and individual characteristics on rural residents' EAs. The results showed the environmental context can indirectly impact EAs by amplifying the influence of individual characteristics such as family structure and income on EAs. The EAs are influenced by different local environmental contexts among the east, middle and west of China's drylands. The humidity attitude was influenced by precipitation only in the highly arid western and middle regions, while precipitation attitude is strongly influenced by land surface temperature and humidity in eastern China's drylands. These findings hold important implications for understanding the cross-scale impact of environmental contexts on EAs in drylands.

Does inclusive leadership influence employee innovation? A multilevel investigation

PurposeThe purpose of this research is to investigate the cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and further explore the boundary conditions of inclusive leadership.Design/methodology/approachThis study collected data from 237 leader-member dyads in 60 teams of Chinese firms. The research utilized multilevel linear models and multilevel structural equation models in the R language to test the hypothesized model.FindingsThe findings suggest that inclusive leadership has a positive impact on both employee incremental and radical innovation. Team psychological safety and employee role breadth self-efficacy mediate the effects. Employee risk avoidance propensity negatively moderates the mediating role of role breadth self-efficacy in the relationship between inclusive leadership and incremental innovation.Practical implicationsLeaders should pay attention to team psychological safety, employee role breadth self-efficacy and employee individual risk avoidance propensity that influence employee innovation to maximize the effectiveness of inclusive leadership.Originality/valueThis research expanded the level of analysis from individual to team, exploring cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and clarified the effectiveness conditions of inclusive leadership.

Small Sample Methods in Multilevel Analysis

Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian methods, one with weakly informative prior for random effect parameters (BayesW) and another with non-informative prior (BayesN) and compared their performance of parameter recovery with restricted maximum likelihood (REML) method, a frequentist-based estimation method commonly used in multilevel analysis. Specifically, we conducted two simulation studies using a two-level linear multilevel model and compared the performance of the BayesW, the BayesN, and the REML in various conditions that include scenarios of small sample data with a combination of small sample size both at level-1 and level-2. The results showed that the REML performed better than the BayesW, which showed overall better performance than the BayesN, in terms of convergence, bias, and coverage in some small sample scenarios. Therefore, based on the results of the present study, it is recommended to use the REML when adapting the two-level linear multilevel model and analyzing real-world data with small samples.

Moral disengagement and empathy in cyberbullying: how they are related in reflection activities about a serious game

Cyberbullying is a complex phenomenon with multiple factors involved, both contextual and individual factors, such as moral disengagement and empathy. This study investigated how moral disengagement and empathy could be related, longitudinally in cyberbullying events. Specifically, two gamified tasks (one for empathy and other for moral disengagement) were analyzed. These tasks were developed attending to the specificities of the cyberbullying scenarios presented in a serious game. To accomplish this goal, data from gamified tasks (N = 208), from 4 different moments, were analyzed through multilevel linear modeling. Results suggested that there was a change in adolescents’ moral disengagement over time. Participants with greater empathy revealed lower moral disengagement overall. Over time, adolescents with greater empathy revealed lower moral disengagement within their own growth rate. Overall, our results provide important information about the dynamic relationship between moral disengagement, empathy and cyberbullying, which informs future studies and interventions.

Assessing health determinants worldwide: Econometric analysis of the Global Burden of Diseases Study 2000-18 - Highlighting impactful factors on DALY, YLL, and YLD indicators.

As the health status of a population is influenced by a variety of health determinants, we sought to assess their impact on health outcomes, both at the global and regional levels. This ecological study encompassed all 194 member countries of the World Health Organization (WHO) from 2000 to 2018. We first identified all health determinants and then retrieved the related data from various global databases. We additionally considered three indicators - disability-adjusted life years (DALYs), years of life lost (YLL), and years lived with disability (YLD) - in evaluating health outcomes; we extracted their data from the Global Burden of Disease (GBD) 2019 study. We then applied econometric analyses using a multilevel mixed-effects linear regression model. The analysis using the DALY indicator showed that the variables of sexually transmitted infections, injuries prevalence, and urbanisation had the highest effect size or regression coefficients (β) for health outcomes. The variables of sexually transmitted infection (β = 0.75, P < 0.001) in the African region; drinking water (β = -0.60, P < 0.001), alcohol use (β = 0.20, P < 0.001), and drug use (β = 0.05, P = 0.036) in the Americas region; urbanisation (β = -0.34, P < 0.001) in the Eastern Mediterranean region; current health expenditure (β = -0.21, P < 0.001) in the Europe region; injuries (β = 0.65, P < 0.001), air pollution (β = 0.29, P < 0.001), and obesity (β = 0.92, P < 0.001) in the South-East Asia region; and gross domestic product (β = -0.25, P < 0.001), education (β = -0.90, P < 0.001), and smoking (β = 0.28, P < 0.001) in the Western Pacific region had the most significant role in explaining global health outcomes. Except for the drug use variable in regional findings, the role of other variables in explaining the YLL indicator was greater than that of the YLD indicator. To address global health disparities and optimise resource allocation, global and interregional policymakers should focus on determinants that had the highest β with health outcomes in each region compared to other regions. These determinants likely have a higher marginal health product, and investing in them is likely to be more cost-effective.

Energy imbalance gap was associated with body mass index and sex in Latin American adolescents-results from the ELANS study.

Energy imbalance gap (EIG) is defined as the average daily difference between energy intake (EI) and energy expenditure (EE). This study aimed to examine the associations between EIG and sociodemographic and anthropometric variables in the adolescent population of eight Latin America countries. A total of 680 adolescents aged 15 to 18 were included in this study. The estimation of EI was based on two non-consecutive 24-h dietary recalls. EE was predicted from Schofield equations using physical activity level obtained through the long version of the International Physical Activity Questionnaire. Sociodemographic data and anthropometric measurements were also obtained. A descriptive analysis and multilevel linear regression models were used to examine associations between variables. The mean EI, EE, and EIG were 2091.3 kcal, 2067.8 kcal, and 23.5 kcal, respectively. Argentina had the highest EI and EIG, whereas Chile had the lowest EI and EIG. Males had a higher EI (2262.4 kcal) and EE (2172.2 kcal) than females (1930.1 kcal and 2084.5 kcal), respectively (p < 0.05). Overweight subjects had a lower EIG than did underweight and normal-weight subjects (p < 0.05). Subjects with low socioeconomic status (SES) had a lower EE (2047.0 kcal) than those with a high SES (2164.2 kcal) (p < 0.05). Sex and BMI were associated with EIG in adolescents from Latin America.

Optimization of benzene exposure risk assessment: An integrated approach utilizing internal and external concentrations with a focus on biomarkers S-PMA & t, t-MA

In the majority of occupational settings within China, the concentrations of benzene are observed to fall markedly below the demarcated detection thresholds. Employing traditional risk assessment models, the presence of exceptionally low airborne benzene exposure concentrations may infuse heightened degrees of uncertainty. Consequently, the necessity arises to investigate risk assessment methodologies more apt for the prevalent exposure environment among employees. In the present study, a pharmacokinetic model premised on urinary benzene metabolites (S-PMA and t, t-MA) was employed to ascertain a more precise daily airborne benzene exposure concentration per individual. This value was integrated into the linear multistage model as the ‘internal exposure concentration’. In conjunction with the U.S National Environmental Protection Agency's (EPA) inhalation risk assessment model predicated on the external exposure concentration, the Singapore Ministry of Manpower's (MOM) model, and the linear multistage (LMS) model, the carcinogenic and non-carcinogenic effects of benzene were evaluated for 1781 benzene-exposed employees across 76 enterprises in Jiangsu Province. Findings suggest that in the linear multilevel model assessment, the cancer risk levels based on t, t-MA and S-PMA were higher in the printing and recording media reproduction industry, automobile manufacturing industry, general equipment manufacturing industry and the furniture manufacturing industry (median 2.842 × 10−4, 2.819 × 10−4, 2.809 × 10−4, and 2.678 × 10−4), which align more consistently with the actual benzene exposure circumstances of each industry's study participants, with overall risk levels calculated by the linear multistage model exceeding those of the EPA inhalation risk assessment model and the MOM model. This implies that the linear multistage model of internal exposure, based on the reciprocal of benzene biomarkers S-PMA and t, t-MA for airborne benzene exposure, presents enhanced sensitivity and suitability for the current occupational health risk assessment of workers. Without doubt, biomarker-based benzene exposure risk assessment emerges as the optimal choice.

Effects of the Communities that Heal (CTH) intervention on perceived opioid-related community stigma in the HEALing Communities Study: results of a multi-site, community-level, cluster-randomized trial

Community stigma against people with opioid use disorder (OUD) and intervention stigma (e.g., toward naloxone) exacerbate the opioid overdose crisis. We examined the effects of the Communities that HEAL (CTH) intervention on perceived opioid-related community stigma by stakeholders in the HEALing Communities Study (HCS). We collected three surveys from community coalition members in 66 communities across four states participating in HCS. Communities were randomized into Intervention (Wave 1) or Wait-list Control (Wave 2) arms. We conducted multilevel linear mixed models to compare changes in primary outcomes of community stigma toward people treated for OUD, naloxone, and medication for opioid use disorder (MOUD) by arm from time 1 (before the start of the intervention) to time 3 (end of the intervention period in the Intervention arm). Intervention stakeholders reported a larger decrease in perceived community stigma toward people treated for OUD (adjusted mean change (AMC)-3.20 [95% C.I.-4.43,-1.98]) and toward MOUD (AMC-0.33 [95% C.I.-0.56,-0.09]) than stakeholders in Wait-list Control communities (AMC-0.18 [95% C.I.-1.38, 1.02], p=0.0007 and AMC 0.11 [95% C.I.-0.09, 0.31], p=0.0066). The relationship between intervention status and change in stigma toward MOUD was moderated by rural-urban status (urban AMC-0.59 [95% CI,-0.87,-0.32], rural AMC not sig.) and state. The difference in stigma toward naloxone between Intervention and Wait-list Control stakeholders was not statistically significant (p=0.18). The CTH intervention decreased stakeholder perceptions of community stigma toward people treated for OUD and stigma toward MOUD. Implementing the CTH intervention in other communities could decrease OUD stigma across diverse settings nationally. US National Institute on Drug Abuse.

The Association of Total Meat Intake with Cardio-Metabolic Disease Risk Factors and Measures of Sub-Clinical Atherosclerosis in an Urbanising Community of Southern India: A Cross-Sectional Analysis for the APCAPS Cohort.

Meat is commonly consumed in India; however, in comparison to Western settings, it is eaten in relatively lower quantities and with minimal processing. The association between meat intake and cardio-metabolic diseases (CMDs) and their risk factors in India is currently uncertain. We examined whether meat intake is associated with risk factors for CMDs and the measures of subclinical atherosclerosis in urbanising villages in southern India. We conducted a cross-sectional analysis of 6012 adults (52.3% male) participating in the Andhra Pradesh Children and Parents' Study (APCAPS), which is a large prospective, intergenerational cohort study in Southern India that began with the long-term follow-up of the Hyderabad Nutrition Trial (1987-1990). We used cross-sectional data from the third wave of data collection conducted in 2010-2012, where total meat intake was assessed using 100-item, semi-quantitative validated food frequency questionnaires (FFQ). The FFQs were validated using multiple weighed 24 h dietary recalls. The main predictor, 'total meat intake', was calculated as the sum of chicken, red meat, and fish consumption. The risk factors for CMDs [systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), waist circumference (WC), fasting glucose, total cholesterol, homeostasis model assessment insulin resistance (HOMA-IR), total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, triglycerides, and C-reactive protein] and measures of subclinical atherosclerosis [Carotid Intima-Media Thickness, Pulse Wave Velocity, and Augmentation Index] were assessed using standardised clinical procedures. Stratified by gender, the association of meat intake with the risk factors of CMDs and measures of subclinical atherosclerosis was examined using linear multilevel models with random intercept at the household level. The mean (SD) age of the male (n = 3128) and female participants (n = 2828) was 34.09 years (15.55) and 34.27 years (12.73), respectively. The median (IQR) intake of meat was 17.79 g/day (8.90, 30.26) in males and 8.90 g/day (4.15, 18.82) in females. In males, a 10 g increase in total meat intake/1000 Kcal/day was positively associated with DBP, BMI, WC, total cholesterol, LDL-C, and triglycerides, whereas in females, a 10 g increase in total meat intake/1000 Kcal/day was positively associated with SBP, DBP, fasting glucose, HOMA-IR, total cholesterol, LDL-C, and triglycerides. There was no relationship between meat consumption and measures of subclinical atherosclerosis. Meat intake had a linear positive association with CMD risk factors among the relatively younger Indian population who were consuming meat at lower levels compared to their European counterparts.

Reliability of a Measure of Admission Intensity for Emergency Physicians

We assess the stability of a measure of emergency department (ED) admission intensity for value-based care programs designed to reduce variation in ED admission rates. Measure stability is important to accurately assess admission rates across sites and among physicians. We sampled data from 358 EDs in 41 states (January 2018 to December 2021), separate from sites where the measure was derived. The measure is the ED admission rate per 100 ED visits for 16 clinical conditions and 535 included International Classification of Disease 10 diagnosis codes. We used descriptive plots and multilevel linear probability models to assess stability over time across EDs and among physicians. Across included 3,571 ED-quarters, the average admission rate was 27.6% (95% confidence interval [CI] 26.0% to 28.2%). The between-facility standard deviation was 9.7% (95% CI 9.0% to 10.6%), and the within-facility standard deviation was 3.0% (95% CI 2.95% to 3.10%), with an intraclass correlation coefficient of 0.91. At the physician-quarter level, the average admission rate was 28.3% (95% CI 28.0% to 28.5%) among 7,002 physicians. Relative to their site's mean in each quarter, the between-physician standard deviation was 6.7% (95% CI 6.6% to 6.8%), and the within-physician standard deviation was 5.5% (95% CI 5.5% to 5.6%), with an intraclass correlation coefficient of 0.59. Moreover, 2.9% of physicians were high-admitting in 80%+ of their practice quarters relative to their peers in the same ED and in the same quarter, whereas 3.9% were low-admitting. The measure exhibits stability in characterizing ED-level admission rates and reliably identifies high- and low-admitting physicians.

Do men and women differ in time-use? Analysing the complexity of activity patterns in Germany

Individuals’ participation in daily routine activities varies according to the situations they live in. Gender roles and marital status drive them to take part in various economic, leisure and travel activities. Married (or cohabiting) individuals, in comparison to singles, juggle activities interdependently with their partners' resources and work allocation, resulting in potentially complex intersecting schedules. The primary aim of this research is to explore the complexity (measured using Shannon’s entropy) of individuals’ activity patterns by considering diverse factors such as demographics, job/education, residential location, travel behaviour, gendered multitasking behaviour, time use preferences and partner interactions. To examine variations in complexity, we developed three separate models for single and partnered respondents, and all respondents, respectively. We used German Time Use Survey 2012/13 data and employed multilevel linear regression models. Gender interaction variables were additionally included in the analysis to examine the gender differences in coefficients. In general, our results suggest that activity pattern complexity is positively associated with demographics (being women, having young children), job/education (high levels of education, working in non-market sector), travel behaviour (number of trips, car, public transport and cycling), time spent on unpaid multitasking, preference for time use (leisure and unpaid work) and additional work hour preferences, whereas full-time/overtime working, paid multitasking negatively affects the complexity. For partnered respondents, factors such as increase in age, increase in income, working in shifts and time spent on paid multitasking have significant negative effects on the complexity of activity patterns, while partners’ time spent on unpaid work and leisure activities positively affects respondents’ complexity. The gender interaction with multitasking behaviour reveals that men’s activity patterns are increasingly complex with more time spent on unpaid multitasking, while for women, the complexity of activity patterns is positively associated with more time spent on paid multitasking.

The COVID-19 ambulance response assessment (CARA) study: a national survey of ambulance service healthcare professionals' preparedness and response to the COVID-19 pandemic.

The COVID-19 pandemic placed significant demand on the NHS, including ambulance services, but it is unclear how this affected ambulance service staff and paramedics in other clinical settings (e.g. urgent and primary care, armed services, prisons). This study aimed to measure the self-perceived preparedness and impact of the first wave of the pandemic on paramedics' psychological stress and perceived ability to deliver care. Ambulance clinicians and paramedics working in other healthcare settings were invited to participate in a three-phase sequential online survey during the acceleration (April 2020), peak (May 2020) and deceleration (September/October 2020) phases of the first wave of COVID-19 in the United Kingdom. Recruitment used social media, Trust internal bulletins and the College of Paramedics' communication channels, employing a convenience sampling strategy. Data were collected using purposively developed open- and closed-ended questions and the validated general health questionnaire-12 (GHQ-12). Data were analysed using multi-level linear and logistic regression models. Phase 1 recruited 3717 participants, reducing to 2709 (73%) by phase 2 and 2159 (58%) by phase 3. Participants were mostly male (58%, n = 2148) and registered paramedics (n = 1992, 54%). Mean (standard deviation) GHQ-12 scores were 16.5 (5.2) during phase 1, reducing to 15.2 (6.7) by phase 3. A total of 84% of participants (n = 3112) had a GHQ-12 score ≥ 12 during the first phase, indicating psychological distress. Participants that had higher GHQ-12 scores were feeling unprepared for the pandemic, and reported a lack of confidence in using personal protective equipment and managing cardiac arrests in confirmed or suspected COVID-19 patients. Most participants reported psychological distress, the reasons for which are multi-factorial. Ambulance managers need to be aware of the risks to staff mental health and take action to mitigate these, to support staff in the delivery of unscheduled, emergency and urgent care under these additional pressures.

How does mobility and urban environment affect the migrants' settlement intention? A perspective from the intergenerational differences.

With China embracing a new people-centered urbanization stage, the problem of migrants "flowing without moving" has become increasingly prominent, and settlement intention has gradually garnered attention. Our research, based on questionnaire data from the China Labor Force Dynamic Survey 2016, uses a multilevel linear regression model to explore the influence of mobility, social environment, built environment, and demographics characteristics on settlement intention in the migrants and discusses differences between settlement intention of new and old generations and their internal influence mechanism. The findings are as follows: (1) Compared to the old generation, the new migrant generation generally has higher settlement intention. (2) The migrants' settlement intention is influenced mainly by mobility, social environment, built environment, and demographic characteristics. (3) For the new migrant generation, social and demographic characteristics significantly influence their settlement intention. (4) The floating and built environment of the old generation significantly influence their settlement intention. Finally, this paper argues that there are differences in the influence mechanism of the same factors on the settlement intention of the new and old generations of migrants. It proposes differentiated policy suggestions for the migrants to promote city social integration. Finally, this paper argues that there are differences in the influence mechanism of the same factors on the settlement intention of the new and old generations of migrants. It proposes differentiated policy suggestions for the migrants to promote city social integration.

The influence of negative urgency and mood inductions on alcohol cognitions.

Negative urgency (NU), the tendency to act rashly during negative emotional states, is a robust risk factor for alcohol misuse that is posited to function in part through alcohol-related cognitions. Nonetheless, relatively little research has examined mood-based fluctuations in such cognitions, which could help to explain how the trait of NU translates to impulsive alcohol-related behaviors. We examined how NU impacted several alcohol cognitions (positive/negative alcohol expectancies, positive/negative alcohol valuations, and alcohol craving for positive/negative emotional reinforcement) before and after negative, neutral, or positive mood inductions. We hypothesized that NU would predict greater and more favorable endorsement of alcohol and its effects following negative (vs. positive or neutral) mood induction. Participants (N = 428) were southern-midwestern college students recruited for an online experiment. Following the provision of consent, participants rated NU and preinduction alcohol cognitions, and were then randomly assigned to one of three (negative, neutral, or positive) mood inductions; subsequently, postinduction alcohol-cognition ratings were immediately obtained. We conducted six robust multilevel linear models (one per DV) examining NU's influence on within-person changes in alcohol cognitions across each mood induction. No three-way interactions were identified and only one two-way interaction involving NU was identified. There were main effects across mood induction conditions and time points for NU predicting greater endorsement of positive and negative alcohol outcome expectancies, and greater alcohol craving for positive and negative emotional reinforcement. Greater NU predicts greater perceived likelihood of alcohol's effects, alongside greater desire for mood improvement from alcohol. The absence of three-way interactive effects indicates NU's influence on mood-dependent fluctuations in alcohol cognitions may manifest over longer timescales (e.g., months and years), involve alternative cognitive processes (e.g., drinking motives and implicit alcohol cognitions), and apply more broadly to desires for mood improvement than purely negative emotional reinforcement.

Predicting the Production and Depletion of Rare Earth Elements and Their Influence on Energy Sector Sustainability through the Utilization of Multilevel Linear Prediction Mixed-Effects Models with R Software

For many years, rare earth elements (REEs) have been part of a wide range of applications (from cell phones and batteries to electric vehicles and wind turbines) needed for daily life all over the world. Moreover, they are often declared to be part of “green technology”. Therefore, the data obtained from the United States Geological Survey (USGS) on the reserve and production of rare earth elements underwent treatment using the multivariate imputation by chained equations (MICE) algorithm to recover missing data. Initially, a simple linear regression model was chosen, which only considered fixed effects (β) and ignored random effects (Ui). However, recognizing the importance of accounting for random effects, the study subsequently employed the multilevel Linear Mixed-Effects (LME) model. This model allows for the simultaneous estimation of both fixed effects and random effects, followed by the estimation of variance parameters (γ, ρ, and σ2). The study demonstrated that the adjusted values closely align with the actual values, as indicated by the p-values being less than 0.05. Moreover, this model effectively captures the sample’s error, fixed, and random components. Also, in this range, the findings indicated two standard deviation measurements for fixed and random effects, along with a variance measurement, which exhibits significant predictive capabilities. Furthermore, within this timeframe, the study provided predictions for world reserves of rare earth elements in various countries until 2053, as well as world production forecasts through 2051. Notably, China is expected to maintain its dominant position in both reserve and production, with an estimated production volume of 101,985.246 tons, followed by the USA with a production volume of 15,850.642 tons. This study also highlights the periodic nature of production, with a specific scale, as well as periodicity in reserve. These insights can be utilized to define and quantify sustainability and to mitigate environmental hazards associated with the use of rare earth materials in the energy industry. Additionally, they can aid in making informed decisions regarding at-risk rare earth reserves, considering potential future trends in electric vehicle (EV) production up to the year 2050.

Effects of online leisure education on leisure behaviors and experiences among university students

Leisure education (LE) is designed to help foster positive leisure attitudes, identify leisure constraints and opportunities, and develop leisure skills and knowledge. Although LE is effective in many populations, its delivery has been predominantly in-person. We conducted an experimental study of a fully online LE intervention (ONLEI) with 96 university students. Our 8-week intervention occurred on a Moodle platform, featuring pre-module and post-module quizzes, information videos on YouTube, learning activities, online discussion forum, and private journaling. Our fidelity checks suggested intervention participants, on average, watched 63% of the videos, while also increasing their quiz scores. Rates for forum and journal engagement were moderate to low. Multilevel linear modeling indicated the ONLEI group showed statistically better trends for leisure participation, leisure satisfaction, and frustration of competence and relatedness needs in leisure, than the control group. However, the groups did not differ in terms of autonomy frustration and needs satisfaction in leisure.

The onset of mental health disparities in sexual minority and majority youth: evidence from the UK Millennium Cohort Study.

Decades of research shows that sexual minority youth (SMY) display heightened risk for mental health problems, although the onset of such disparities remains unclear. The Millennium Cohort Study is the largest nationally representative longitudinal study of adolescents in the United Kingdom. In this study, participants (N = 10,047, 50% female) self-reported their sexual identity at age 17 and had parent-reported mental health data, from the Strengths and Difficulties Questionnaire, reported across five waves at ages 5, 7, 11, 14, and 17. Multilevel linear spline models, stratified by sex, were used to examine mental health trajectories between sexual identity groups (completely heterosexual, mostly heterosexual, SMY). SMY showed heightened peer problems from the baseline assessment at age five, increasing over time, and heightened emotional problems from age 11, increasing over time. Mostly heterosexual youth showed heightened emotional problems at age 11 in males, and at age 17 in females. Findings are discussed in light of the literature on minority stress and gender conformity in youth. The use of parent-reported mental health data means that estimates are likely to be conservative. We conclude that interventions supporting SMY should start early and be available throughout adolescence.

Attitudes Toward Immigration in Europe. Understanding the Links Between Pronatalism and Voluntary Childlessness

Many European societies follow pronatalist family policies; nevertheless, in all countries, the total fertility rate is below replacement level and the rate of childless people is growing. Meanwhile, among demographers and policymakers, immigration is discussed as a way to increase the labor force and recently also to maintain the population size. This study contributes to a better understanding of individuals’ attitudes on these issues by examining the factors that influence the acceptance of immigration from the prism of attitudes toward voluntary childlessness. Attitudes toward immigrants as well as attitudes toward voluntary childlessness vary across and within European societies. From a selective pronatalist perspective, both factors might threaten the survival of the nation. Therefore, in this study, we assess the extent to which attitudes toward voluntary childlessness relate to attitudes toward immigrants. We differentiate attitudes toward immigrants as an economic and as a cultural threat. We use data from the European Social Survey (Round 9) and apply multilevel linear regression models. Our results show that there is a strong association between the acceptance of immigrants and voluntary childlessness at the individual level. At the country level, the female childlessness rate is associated with attitudes toward immigration: higher female childlessness rates are associated with more favorable attitudes toward immigration.

Residential greenspace exposure, particularly green window-views, is associated with improved sleep quality among older adults: Evidence from a high-density city

Preliminary evidence suggests a potential link between greenspace exposure and better sleep quality. Here we aimed to investigate the specific associations between residential greenspace exposure, green-window views, and sleep quality among older adults and determine whether these associations were mediated through mitigation (i.e., perceived noise annoyance, air pollution, and artificial light pollution) and restoration (i.e., psychological stress) pathways. A total of 1007 older adults with an average age >70 years were recruited from 40 residential communities in the Old City District of Nanjing, China. We developed a set of fine-grained greenspace exposure indices based on 3D point cloud data derived from unmanned aerial vehicle photogrammetry, incorporating vegetation coverage and green volume ratio at the community level and green window ratio at the individual level. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. We examined the complex interrelationships between residential greenspace exposure, environmental stressors (air pollution, artificial light pollution, and noise), perceived mental stress, and sleep quality using multilevel linear regression models. The results suggested the following: (1) Vegetation coverage, green volume ratio, and green window ratio were significantly associated with sleep quality in older adults. (2) The green window ratio was more strongly associated with improved sleep quality than other greenspace exposure metrics. (3) These associations may be partially explained by noise mitigation and mental stress reduction. In conclusion, it seems advantageous to consider immediate residential greenspace, particularly through green-window views, as part of the interventions aimed at supporting sleep quality improvement among older adults.