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Rapid advances in new-generation information technologies have been the main driving force for the transformation of manufacturing enterprises in Industry 4.0. Digital twin (DT), as a key technology to promote intelligent manufacturing, has shown great potential for manufacturing enterprises to create an industrial intelligence-driven production equipment through in-depth integration of cyber-physical systems. However, the lack of a systematic effective DT modelling method with a supporting evaluation metric is the most important factor restricting the application of DT in manufacturing enterprises. To bridge the gap, this paper proposes a novel multi-level modelling and fidelity evaluation (MLM&FE) method of DT for creating smart production equipment in manufacturing enterprises, which could help enterprises establish an industrial intelligence-driven production environment to quickly respond to changes in the customised global market, thus greatly improving competitiveness of the enterprises. Specifically, this paper firstly designs a reference framework for DT-enhanced smart production equipment, on which an MLM&FE architecture is proposed. Then, key implementation methodologies and tools for MLM&FE are introduced from the perspective of data space modelling, virtual space modelling, knowledge space modelling, model integration and evaluation. Finally, the developed smart production equipment prototype demonstrates the feasibility and effectiveness of DT MLM&FE. [ABSTRACT FROM AUTHOR]

Selling is often associated with competitiveness, which has led many scholars to examine trait competitiveness as a driver of salesperson performance. However, it is also suggested that competitiveness contributes to less cohesive work environments which can have adverse effects on firms and their stakeholders. The authors explore this dichotomy by first conducting a field study utilizing multilevel, multisource data acquired from 358 salespeople working at 86 offices of a large company. Using Mplus, the authors employ a 1-2-1 multilevel model to test the effects of trait competitiveness on work group cohesion, along with subsequent effects on sales performance and turnover. Findings reveal a surprising positive relationship between trait competitiveness and work group cohesion, with the latter reducing turnover likelihood. Thus, trait competitiveness has indirect effects, through work group cohesion, in reducing turnover, while having direct and positive effects on sales performance. Results of a follow-up qualitative study reveal that the positive relationship between trait competitiveness and work group cohesion can be attributed to the competitive focus (i.e. interpersonal, intergroup, or intrapersonal) of the individuals within the sales organization. Overall, this work shows that organizations can have both competitive salespeople and cohesive work environments, contributing beneficially toward sales output and turnover. [ABSTRACT FROM AUTHOR]

Early writing is a critical factor in children's literacy development and academic success. This study observed and analyzed videos from twenty-eight teachers working in prekindergarten, kindergarten, and first-grade classrooms in under-resourced schools. The coding process focused on categorizing the type (language- and code-based) and demand (low- and high-demand) of strategies that teachers used to support children's development of the foundational skills for early writing. We use the Not So Simple View of Writing as a framework to outline which writing-related skills (specifically, vocabulary and literacy) are important to explore. Multilevel models explored unique links between teachers' (N = 28) supports for various early writing-related component skills, as well as children's (N = 324) vocabulary and early literacy outcomes. The findings demonstrated that, regardless of grade level, teachers tended to emphasize code-based skills over language-based ones as children composed. Multilevel models showed that the vocabulary and literacy skills of children improved in classrooms where teachers provided higher levels of both high-demand language- and code-based writing support. The findings indicate that teachers' support for children's translation and transcription processes during composing may result in reciprocal and mutually beneficial effects on the foundational component skills of writing. [ABSTRACT FROM AUTHOR]

Objective: The role of affective experiences (AE) in cognitive–behavioral therapy (CBT) has rarely been investigated. We examined between- and within-person effects of AE on coping in CBT for family caregivers and interactions with therapeutic alliance and resource activation. Methods: 67 family caregivers rated AE, therapeutic alliance, resource activation, and coping after each of 12 sessions of telephone-based CBT. We examined direct session-to-session effects of AE on coping in structural equation modeling and interactions of AE with therapeutic alliance and resource activation in multilevel models. Results: AE did not directly predict coping. Instead, within-person effects of AE interacted with simultaneous within-person emotional bond. Given strong emotional bond, AE positively predicted coping, whereas given weak emotional bond, AE negatively predicted coping. Further, cross-level interactions of between-person AE and within-person agreement on collaboration and resource activation indicated that these positively predicted coping only in dyads with high between-person AE. Conclusion: AE may enhance coping when complemented with strong emotional bond. Further, within-person effects of agreement on collaboration and resource activation seem to rely on a certain degree of between-person AE. Results are discussed in relation to current findings on emotional processing in CBT. [ABSTRACT FROM AUTHOR]

Prospective memory (PM) is the accurate execution of an intention in the future. PM may be negatively impacted by negative affect, but the underlying mechanisms remain unclear. Rumination may increase the frequency of task-irrelevant thoughts, which deplete attentional capacity and reduce performance. To date, no studies have examined state and trait rumination on an online measure of PM. The present study examined the effects of state and trait rumination on an event-based, focal PM task embedded within a one-back task over multiple sessions. 95 non-depressed adults (18–53 years) completed measures of state/trait rumination, mood, and PM on at least two occasions. Using multi-level modelling, we found that a derived measure of trait rumination, but not an established trait rumination survey, nor negative mood, predicted poorer PM accuracy. These novel findings demonstrate that trait rumination may partially underlie the association between negative affect & PM in a non-clinical sample, and highlight the potential of online methods to study PM. [ABSTRACT FROM AUTHOR]

West Bengal, a middle-ranking Indian state in terms of development indicators with more than two-thirds rural population, is on the verge of becoming a lowest low fertility zone. While the rural TFR (Total Fertility Rate) of West Bengal (1.6 births/woman) is on par with many developed countries (Norway, Germany, Netherlands, Belgium, etc.), its developmental stage is not—which poses a paradox. Using data from a primary survey of 405 mothers aged 15–35 years alongside focus group data of parents, the present study employs a society-specific approach to explain contemporary low fertility in rural West Bengal. We argue that the presence of high aspirations for children in an economically insecure setting initiates a distinctive sense of parental responsibility that generates a unique local socio-ecology of low fertility not previously observed in the context of rural fertility decline in India. Responsibility-laden aspirations toward children and reasoned-rational deliberations regarding fertility outcomes act as subliminal motives to have a small family, challenging common assumptions regarding the relationship between economic hardship, rurality, and fertility. [ABSTRACT FROM AUTHOR]

A growing number of toddlers are attending childcare institutions as part of China's establishment of its infant – toddler childcare service system. However, there is limited empirical evidence available regarding the quality of these childcare services. The purpose of this study is to investigate the quality of teacher – child interactions in Chinese toddler classrooms. Eighty-eight childcare institutions were assessed using the Classroom Assessment Scoring System, Toddler Version (CLASS – Toddler). The findings indicated that, on average, teacher – child interactions were rated as being of moderate quality. The Emotional and Behavioral Support (EBS) domain scored higher quality levels compared to the Engaged Support for Learning (ESL) domain. Multilevel models revealed significant variations in teacher – child interactions across different types of activities. Free play activities demonstrated the highest EBS quality, while whole-group activities ranked the highest in terms of the ESL quality. Moreover, the children-to-teacher ratio was found to predict both the EBS and ESL quality, whereas group size was only associated with the EBS quality. The results from this study have important implications for future research and professional development of Chinese toddler teachers. [ABSTRACT FROM AUTHOR]

AbstractAlthough climate change remains a top environmental threat, significant portions of the global population continue to exhibit climate change skepticism. Currently, an extensive literature identifies the micro-level determinants of climate skepticism, often manifesting as a form of populist “backlash” to the adverse effects of globalization. However, the potential of macro-level global cultural forces—particularly embeddedness in liberal world society—to counter such pushback is unclear. Using multilevel modeling to analyze International Social Survey Program data spanning 37 countries from 2000 to 2020, we find that in general, increased embeddedness is linked to reduced climate skepticism. However, when global liberal forces encounter anti-liberal undercurrents within nation-states, a situation we refer to as cultural dissonance, the impact of liberal world society on tempering skepticism varies. Embeddedness mitigates skepticism at the national level, particularly within authoritarian regimes, but not at the individual level, especially among right-wing individuals. Paradoxically, world society also heightens ideological polarization of individual worldviews on climate change. By illuminating the contradictory role of liberal world society, which simultaneously exacerbates and inhibits anti-liberal, populist attitudes about climate change, we advance existing work examining the post-liberal turn and holds promise for making sense of other issue domains where liberal perspectives are contested. [ABSTRACT FROM AUTHOR]

ObjectivesMethodsResultsConclusionDespite the established impact of care recipient cognitive impairment on care partner (CP) distress, limited quantitative research has explored how social and leisure engagement may moderate this relationship, offering a potential avenue for enhancing well-being in both care partners and recipients. The current study therefore examined the between- and within-dyad associations between cognitive impairment of persons with dementia (PwD) and their family CP’s distress, and whether social and leisure activity moderated this relationship.Data were utilized from dyads (PwD, n = 33, and their CPs, n = 34) engaged in the Voices in Motion project, a social-cognitive choral intervention for PwD and their family CPs. Measures indexing PwD cognitive status, CP distress, and PwD and CP social and leisure engagement were assessed using an intensive repeated-measures burst design, with multilevel models of change employed to disaggregate between- and within-person effects.Diminished cognitive functioning in PwD was associated with increased CP distress (p < 0.01) between-dyads; however, this relationship was not significant within-dyads. The between-dyad association was significantly moderated by the extent of social and leisure engagement of both CPs (p < .001) and PwD (p = .04). Follow-up simple slopes demonstrated that, at mean- and high-levels (+1SD) of social and leisure engagement for PwD and/or CP, increased PwD cognitive function significantly predicted lower CP distress.The significant moderating influence of social and leisure engagement of dyads underscores the protective role of such engagement for reducing care-related distress. Activity engagement for CPs and PwD may help modulate the deleterious impact of PwD cognitive impairment and attenuate CP distress. These findings highlight the potential for dyadic interventions that promote social and leisure activities to mitigate caregiving challenges and enhance quality of life for both CPs and PwD. [ABSTRACT FROM AUTHOR]

Leisure activities engagement could promote freshmen's well-being by providing social support and improving positive mood. Little is known about the day-to-day variability in leisure activities and stress and their links to daily well-being. Using a month-long daily diary design among 273 Canadian freshmen (Mage = 18, 73% female, 32% White), this study investigated the relations between daily leisure activities, stress, and well-being. Multilevel modeling revealed that daily leisure activities showed concurrent positive effects on daily well-being, whereas daily stress had negative effects. There were substantial inter-individual differences in these links, which were partly explained by coping orientations and person-average levels of stress. Engaging in more diverse leisure activities was related to better well-being. The findings demonstrate the immediate beneficial effects of leisure activities on well-being in everyday life and provide interventions with amendable targets to promote freshmen's positive socioemotional development during their transition to university. [ABSTRACT FROM AUTHOR]

An ideal theoretical model integrating four revolute joints is developed to capture the kinematic behaviour of a vehicle scissor door joint mechanism. Then, triaxial acceleration experiments are conducted to validate the effectiveness of the developed theoretical model. Furthermore, to improve dynamic responses of the mechanism, a novel discrete multi-objective optimization (DMO) method is proposed to address optimization problems where design variables cannot be parameterized. This method integrates the Taguchi method, grey relational analysis and a hybrid multi-objective decision-making approach, and iteratively updates the orthogonal array to perform optimization for handling design variables with multiple levels. Compared to the conventional non-dominated sorting genetic algorithm-II (NSGA-II), the developed DMO is capable of achieving the Pareto frontier with fewer evaluations of the objective function. The optimization results reveal that the optimized design for the electric and gas struts exhibits favourable dynamic responses of scissor door operation compared to the initial design. [ABSTRACT FROM AUTHOR]

ObjectivesMethodsResultsConclusionThis study examined the factors affecting the use of personal protective equipment (PPE) among US agriculture producers, specifically focusing on chemical, respiratory, and hearing protection. The primary goals were to identify demographic and farm-related factors linked to lower PPE usage and to explore the associations between PPE use and self-reported injuries or diseases in this occupational context.We developed generalized multilevel multinomial logistic regressions for the agricultural safety and health survey data from 2018 and 2020. Our models aimed to explore associations between PPE use, covariates, and their impact on skin diseases, hearing loss, and respiratory diseases. The hierarchical structure of the data was accommodated by designating the survey year as the level-3 variable and the state of residence as the level-2 variable, further delineating the nested structure of the respondents. We proposed using Adaptive Quadrature methods to approximate marginal maximum likelihood function, along with Gauss-Hermite quadrature weights when estimating fixed-effects and random effects in the proposed models. Missing data in this hierarchical structure were addressed through a multiple imputation method.Our findings revealed older age is associated with lower PPE usage across all types. Males exhibited higher PPE use, particularly for chemical (OR: 1.26, 95% CI: 1.08, 1.47) and respiratory protection (OR: 1.33, 95% CI: 1.18, 1.52). Producers on grain-only farms showed increased chemical PPE use (OR: 1.26, 95% CI: 1.10, 1.43) compared to those on livestock-only farms. Additionally, individuals spending 0%–24% of their worktime on the farm/ranch demonstrated lower PPE use than those who spent more time engaged in farm-related activities.The study underscores the importance of addressing low PPE usage among agriculture producers. Interventions tailored to specific groups, such as female producers, livestock-only farms, older-aged producers, and part-time producers, can effectively improve PPE use. By identifying these high-risk groups, interventions can be better adapted and targeted to enhance the adoption of PPE, subsequently reducing the risk of health hazards in the agriculture sector. [ABSTRACT FROM AUTHOR]

Immigration in Africa has increased significantly in the past two decades, with a record number of people moving to Africa from other non-African countries as well as Africans moving to other countries on the continent. This increase in immigration requires an empirical exploration to understand how Africans feel and think about immigrants. Therefore, the purpose of the current study is to explore Africans' willingness to accept immigrants and foreign workers into their neighbourhoods. Analyzing large-scale data from more than 45,000 citizens across 34 countries, we examined individual- and country-level factors using a multilevel hierarchical linear approach. At the individual level, our analysis revealed that gender, religious affiliation, nationalism, fear of extremism, and security are important indicators of Africans' willingness to live with immigrants in their neighbourhoods. While we did not observe any effect for country-level economic variables, it was revealed that regional location was a vital consideration. These observations are helpful in understanding immigration in Africa as well as offering insights for policy development. [ABSTRACT FROM AUTHOR]

The Canadian Family-Friendly Community Resources for Better Balance, Health, and Well-Being study (FFCR) is the first study in North America to comprehensively examine the impact of regional community context on work-family conflict, health, and wellbeing. The study was designed to collate data from disparate sources on a variety of community characteristics across Canada over time, including education services, food stores, recreational facilities, religious organizations, police, and fire protection services, for example. These data were then linked to individual-level data from the Canadian Work, Stress and Health study – a longitudinal national sample of Canadians across a myriad of work and family circumstances. These data are more comprehensive than any other dataset attempting to link work, family, and community data. We situate our contribution of the FFCR in literature on 'work-family conflict', which is defined as the incompatibility between role obligations. Context-level data were compiled at years corresponding to the individual-level data (2011–2019). Using multilevel analyses based on both cross-sectional and longitudinal data, we find that that resources, like the prevalence of food stores, education resources, recreation facilities, and public safety outlets are negatively associated with residents' work-family conflict levels. However, these findings are more pronounced across a combination of FFCR overtime. [ABSTRACT FROM AUTHOR]

The use of multilevel regression models is prevalent in policy analysis to estimate the effect of group level policies on individual outcomes. In order to allow for the time varying effect of group heterogeneity and the group specific impact of time effects, we propose a group interactive fixed effects approach that employs interaction terms of group factor loadings and common factors in this model. For this approach, we consider the least squares estimator and associated inference procedure. We examine their properties under the large n and fixed T asymptotics. The number of groups, G, is allowed to grow but at a slower rate. We also propose a test for the level of grouping to specify group factor loadings, and a GMM approach to address policy endogeneity with respect to idiosyncratic errors. Finally, we provide empirical illustrations of the proposed approach using two empirical examples. [ABSTRACT FROM AUTHOR]

AbstractOver the past decade, the climate movement and especially action groups like Fridays for Future have been effective in raising awareness of environmental issues and mobilizing protesters, especially among younger age groups. However, it remains unclear whether this recent surge in activism reflects a broader societal shift or if this trend is primarily driven by younger generations. Using data from 24 countries that participated in waves three and four of the International Social Survey Programme Environment Module, this study employs, for the first time, an Age-Period-Cohort (APC) analysis of environmental Public-Sphere Behavior in an international comparative context. Based on Bayesian negative binominal multilevel models, the results provide empirical evidence for a period effect: PSB have indeed increased across generational cohorts and age groups. [ABSTRACT FROM AUTHOR]

AbstractThe effectiveness of educational interventions has traditionally been evaluated using effect size measures which focus on a single feature of the distribution of the outcomes under intervention and control conditions: a (standardized) mean difference. Recently there has been increased interest in methods which assess the information contained in the full distributions of outcomes under intervention and control, providing measures of separation from these distributions which do not depend on arbitrary cutoffs, hence which are “threshold-free”. We investigate the statistical relationship between several concepts of this type, and discuss how they can be used to estimate alternative effect size metrics as well as their uncertainties in the context of multilevel models as commonly used for the analysis of educational data. A specific aim of this paper is to investigate how the recently proposed “gain index” relates to other measures of separation including the Area under the Curve (AUC) and the overlapping index. A simulation study, using data with an educationally motivated structure, is presented to compare the different methodologies. [ABSTRACT FROM AUTHOR]

ObjectiveMethodResultsConclusionsThis pre-registered analysis aimed to examine the moderating role of nicotine-use motives on the association between minority stress and nicotine use and craving among sexual minority youth.Data stem from a 30-day ecological momentary assessment study conducted among 83 sexual minority youth ages 15–19 years old (M age = 17.96, SD = 1.10; 56.63% cisgender women; 73.5% non-Hispanic White). Participants were instructed to complete at least four assessments per day on wireless devices. Two types of multilevel models were estimated: models predicting day-level nicotine use and models predicting momentary nicotine use craving.Experiencing minority stressors was not associated with day-level nicotine use, but it was associated with greater momentary nicotine craving. Nicotine use-motives did not moderate the association between minority stress and nicotine use. In contrast, stress-reduction motives, assessed as a person-level trait, moderated the association between minority stress and nicotine craving, such that nicotine craving after experiencing a minority stressor was consistently higher relative to when minority stress had not been reported. Sensitivity analyses that examined associations between minority stress and nicotine use on a given day, regardless of temporal order, showed that minority stress was associated with higher odds of nicotine use on that day.Experiencing minority stressors did not predict day-level nicotine use but does contribute to greater momentary nicotine craving, informing minority stress theory. Consistency of the minority stress and nicotine craving relation, largely regardless of trait-level motives, highlights the potential context dependence of nicotine craving among sexual minority youth.Preregistration: This study was preregistered at osf.io/w5sz9. [ABSTRACT FROM AUTHOR]

The decline of females in Science, Technology, Engineering, and Mathematics (STEM) fields has drawn global discourse among researchers and policymakers, including Cambodia. At Cambodian upper secondary schools, female students' enrolment rates in science classes dramatically decreased from 97% in 2014–42% in 2019. In contrast, female students' enrolment rates in social science classes significantly increased from 4% in 2014–58% in 2019. This study aimed to examine factors influencing female students to leave science classes at upper secondary schools. It included 421 female grade-12 students from 20 secondary schools as samples. Due to the nested structure of the data, the two-level hierarchical linear model (HLM) was used for data analysis. The findings revealed that ease of national examination, high passing rates, pursuits for grades, attitudes toward science, and financial burden of private tutoring significantly influenced female students to opt for social science classes over science classes. Female students had no intention to pursue STEM majors and reported that their parents advised them not to involve in science. The findings were discussed with a call for policy implications and improved practices at the school level to promote female students' enrolment in science classes in Cambodia. [ABSTRACT FROM AUTHOR]

The present study focused on the emotional experience of anger among individuals with and without social anxiety disorder (SAD). Eighty-eight participants took part in the study, half (n = 44) met diagnostic criteria for SAD and half (n = 44) did not meet criteria for SAD. Participants completed a 21-day experience sampling measurement (ESM) in which they reported on daily social interactions and emotions. Using multilevel linear modeling we found that individuals with SAD experienced more anger compared to individuals without SAD. We also found a Diagnosis × Social Context interaction such that interactions with distant others were associated with elevated anger compared to interactions with close others for individuals with SAD but not for individuals without SAD. Finally, we found that for individuals with SAD (but not those without SAD) anger on a given day (day t) was associated with elevated anxiety on the following day (day t + 1), above and beyond previous anxiety, sadness and guilt (i.e. anxiety, sadness and guilt reported on day t). This suggests that anger may play a unique role in maintaining or exacerbating anxiety among individuals with SAD. Additional implications of our findings for models of psychopathology and for treatment of SAD are discussed. [ABSTRACT FROM AUTHOR]

This study examines the impact of multilingualism and socioeconomic status on academic performance within the UK, utilising data from 3,213 pupils from the National Pupil Database who also took part in the Study of Cognition, Adolescents and Mobile Phones (SCAMP). We employed multilevel modelling to analyse the relationship between language experience, socioeconomic status and Key-Stage 2 (KS2∼11 years) and Key-Stage 4 (KS4∼16 years) performance in English, Mathematics and Science. Findings reveal that multilingual learners initially face academic challenges at KS2, particularly in English and Science, but achieve comparable results with monolingual peers by KS4, overcoming early setbacks. Notably, simultaneous multilinguals not only catch up but excel beyond their monolingual counterparts by KS4, demonstrating the significant long-term academic benefits of early multilingual exposure and /or its associated cultural factors. Further analysis indicates that multilingual group membership mitigated the adverse effects of low socioeconomic status, with pupils from these backgrounds making substantial academic strides between KS2 and KS4 compared to monolingual peers. This challenges prevalent misconceptions about multilingualism in education. These findings underscore the need for educational policies that harness linguistic diversity to foster academic equity and success, emphasising the crucial role of language experience and socioeconomic factors in shaping educational outcomes. [ABSTRACT FROM AUTHOR]

Sexual desire has often been conceptualized and studied as an individual trait. However, empirical evidence suggests that there is also value in studying it as a state and dyadic construct. Through a daily diary study with a randomized controlled experimental design, we aimed to explore (i) how the roles that partners fulfill in dyadic interactions are associated with daily fluctuations in dyadic sexual desire, (ii) whether these roles can be leveraged to affect sexual desire for one’s partner, and (iii) whether effects of partner interactions on dyadic sexual desire vary by gender. In total, 163 mixed-gender couples (N = 326), with a mean age of 30.3 years (SD = 7.95), participated. During 22 consecutive days, participants reported daily on their dyadic sexual desire, as well as on several aspects of their interactions. Couples in the experimental condition additionally received assignments that manipulated their partner interactions. Analyzing our data using Multilevel Modelling techniques for longitudinal dyadic data, we found that daily dyadic sexual desire was associated with what each partner takes, gives, and receives in relation with their affiliation, sexuality and exploration needs. Additionally, women’s sexual desire was associated with what their partner reported taking, giving, and receiving during affiliative interactions, and with perceived but not enacted responsiveness to their sexuality and exploration needs. Our results suggest that daily ebbs and flows of sexual desire may be partly explained by temporal changes in interactions between partners, making them possible valuable targets for clinical interventions. [ABSTRACT FROM AUTHOR]

SYNOPSISObjective. In our pilot exploratory study, we recruited a sample of cannabis-using parents to understand (1) the extent to which parents were using cannabis in the presence of their child(ren); (2) the relationship between cannabis use and parenting behaviors; (3) whether the context of cannabis use (who was present, how was cannabis consumed) was related to parenting behavior in concurrent and subsequent time periods. Design. We conducted a 15-day geographic ecological momentary assessment (gEMA) with 77 parents who used cannabis and lived in the greater Sacramento, California region. Parents were asked to complete 5 surveys per day for 14 days and 1 survey on day 15. In total, parents completed 4,138 total observations. For our study, we focus on 2,458 daily observations when parents were with their children. Respondents answered questions about their cannabis use, the context in which it was used, and about parenting behaviors. Data were analyzed using multi-level logistic models. Results. Parents rarely used cannabis with their children present. Parents had greater odds of using positive parenting during the same and subsequent time periods when using cannabis. The relationship of the parent to individuals who were present during the cannabis use was related to the use of positive and aggressive parenting. Conclusions. Our findings reveal a complicated relationship between cannabis use and parenting among a sample of cannabis users. However, it also provides some information on ways parents can engage in harm reduction to support positive parenting. [ABSTRACT FROM AUTHOR]

More aggressive campaigning styles focusing on criticizing opponents (negativity) or using inappropriate language to vilify opponents (incivility) tend to be disliked by voters, and remain thus risky for parties facing off in competitive elections. Backlashes against attackers often cancel out any dent the attacks may leave in the support for the targets. Yet, research on the conditions under which these backlashes are more likely to happen remains fragmentary. In this article, we argue that the nature of the electoral competition – specifically, the presence of viable alternative parties for voters to choose from – matters. Voters could be more likely to withdraw political support from the attacker when such alternatives exist. We test whether the availability and ideological attractiveness of alternatives intervene to explain the backlash effect associated with negativity and incivility, at the election, party, and voter levels. We do so comparatively in the context of the 2019 European Parliament elections in 27 EU countries, by linking a cross-sectional post-election survey (N = 18,790) with an expert survey covering the campaigning strategies of 175 parties that participated in the election across the continent. Estimating mixed effects multi-level models, we find support for the moderating effect of alternatives at the voter-level; voters who have at least equally attractive alternatives available to them are less likely to support parties that go negative than voters to whom the attacking party is the most viable option. Alternatives do not seem to play a major role, however, at the party and election levels. [ABSTRACT FROM AUTHOR]

Continuous-time modeling using differential equations is a promising technique to model change processes with longitudinal data. Among ways to fit this model, the Latent Differential Structural Equation Modeling (LDSEM) approach defines latent derivative variables within a structural equation modeling (SEM) framework, thereby allowing researchers to leverage advantages of the SEM framework for model building, estimation, inference, and comparison purposes. Still, a few issues remain unresolved, including performance of multilevel variations of the LDSEM under short time lengths (e.g., 14 time points), particularly when coupled multivariate processes and time-varying covariates are involved. Additionally, the possibility of using Bayesian estimation to facilitate the estimation of multilevel LDSEM (M-LDSEM) models with complex and higher-dimensional random effect structures has not been investigated. We present a series of Monte Carlo simulations to evaluate three possible approaches to fitting M-LDSEM, including: frequentist single-level and two-level robust estimators and Bayesian two-level estimator. Our findings suggested that the Bayesian approach outperformed other frequentist approaches. The effects of time-varying covariates are well recovered, and coupling parameters are the least biased especially using higher-order derivative information with the Bayesian estimator. Finally, an empirical example is provided to show the applicability of the approach. [ABSTRACT FROM AUTHOR]

A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their cols : rows is related to the magnitude of eigenvalue bias in sample covariance matrices. Previous studies have shown similar performance for both approaches, but they were limited to settings where cols ≪ rows in both data formats. We conducted a Monte Carlo study to investigate whether varying cols : rows result in differing performances. Specifically, we examined the p : N ( cols : rows ) effect on convergence and estimation accuracy in multilevel settings. Our findings suggest that (1) the LF approach is more likely to achieve convergence, but for the models that converged in both, (2) the LF and WF approach yield similar estimation accuracy, which is related to (3) differential cols : rows effects in both approaches, and (4) smaller ICC values lead to less accurate between-group parameter estimates. [ABSTRACT FROM AUTHOR]

Pansharpening is an important technology for obtaining high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) images and high-resolution panchromatic (PAN) images. Although many pansharpening models have emerged by taking advantage of deep learning (DL) technology, there remains a pressing need to further assess pansharpening accuracy and stability when LRMS images with complex land-cover types. What's more, these models often overlook the exploitation of PAN images' inherent high-frequency information. To address these issues, we propose a pansharpening model combining multi-level and multi-scale network architectures. The multi-level network architecture is used to build spatial-spectral dependence on LRMS-PAN pairs, and strengthen the network's feature capture capability by keeping the multi-level texture details. The multi-scale architecture is subsequently used to extract the spatial structure and deep texture of the PAN images at different scales. Downsampled experiments and real experiments in four standard datasets show that the proposed model achieves a state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Objective: This study investigated the relationship between therapeutic techniques and session impact, by examining the replicability of findings observed in a university-based training clinic (Boswell et al., 2010) in another practice-oriented setting: private practice. Method:N = 8 therapists completed session-level assessments of their technique use for N = 38 clients. The same client sample completed session-level assessments of session outcome. Technique-outcome associations were examined with multilevel models. Results: As in Boswell et al., common factors were associated with positive session impact. For clients who received higher average common factor techniques (relative to their own therapist's caseload), session impact was the poorest in sessions with higher behavioral change techniques use (relative to the client's own average). Moreover, clients with the lowest average common factor techniques (relative to their therapist's caseload) reported better session impact in sessions that involved a higher degree of session-level behavioral change techniques (relative to their own average). Conclusion: In line with Boswell et al., therapists should be mindful of the consistency of their routine technique use between- and within-clients, and this can be aided through collection of their own practice-oriented data. [ABSTRACT FROM AUTHOR]

(Non-)implementation of rules is a key issue in the EU literature. During the European 'migration crisis' in 2015/16, several member states openly deviated from the clear rules the legal framework of Schengen and Dublin established. Although these controversies have attracted much attention, member states' authorities can also deviate from European rules in everyday decision making. Little is known about this leeway. For example, the Dublin system allows countries to send asylum seekers in an 'outgoing procedure' when they conclude that another Dublin state is responsible for the asylum application. This paper develops the argument that efficiency considerations lead national authorities to specialise in asylum seekers from countries from which they already have many residents. Asylum seekers from these countries are less likely to be sent in an outgoing procedure. The Dublin system does not intend this type of selection based on nationality. Using unique, high-quality register panel data from Switzerland, the statistical analysis of multilevel models shows that an outgoing procedure is indeed more likely for applicants from countries with a comparatively small number of residents. The findings of this analysis have broader implications for the Common European Asylum System. [ABSTRACT FROM AUTHOR]

In this case study, we illustrate the use of a data-driven degradation model in a nuclear-specific application called void swelling. Void swelling is a complex, radiation-induced degradation mechanism that changes the dimensions of materials and damages the structural integrity. Accurate modeling and prediction of void swelling processes is crucial in nuclear power plant (NPP) management and maintenance planning by providing a guideline on the future state of the materials subject to reactor irradiation. Using a Bayesian hierarchical piecewise linear regression framework with a real-world void swelling dataset, we address the following three research questions: (1) How can we construct a data-driven degradation model such that its predictions satisfy the physical properties of void swelling? (2) How can we measure the joint effect of multiple experimental factors on the swelling process? (3) How can we accurately predict the future swelling status under limited data availability? The results on a real-world void swelling dataset not only improve our understanding of the swelling process but also provide a useful reference for nuclear practitioners and degradation researchers. [ABSTRACT FROM AUTHOR]

In this article, we evaluate the impact of ethnic and national identities on satisfaction with democracy in Nigeria, a state with deep historical ethno-regional divisions. Applying Easton's (1965) seminal framework of diffuse versus specific support, we examine how Nigerians combine their ethnic and national identities (diffuse support), and analyze the extent to which territorial identities influence democratic satisfaction vis-à-vis evaluative factors (specific support), such as trust in institutions and the current government's performance in addressing the needs of its citizens. We employ a multilevel model using the seventh round of the Nigeria Afrobarometer survey. We find that a dominant ethnic identity does decrease democratic satisfaction. However, a number of specific support measures, such as trust in the state and local governments and evaluations of the government's economic performance are stronger predictors. We interpret this as a decline in the salience of the ethnic cleavage in Nigeria. [ABSTRACT FROM AUTHOR]

At present, electric vehicle (EV) development has been widely accepted as a coping strategy by countries encountering environmental issues. However, there remain some uncertainties surrounding the future of China's EV industry. The super-network provides an effective solution to the research on optimising subject decisions in a multilevel network model. On this basis, a closed-loop super-network model of the EV industrial chain system is proposed, which involves four different participants: EV manufacturer, sales company, consumer market, and recycling company. Furthermore, the variables are extracted based on practice, the behavioural strategies of each participant are analysed, and the dynamic equilibrium is determined with variational inequalities. Through numerical analyses, a further study is conducted on the main influencing factors and the extent of their impact on the dynamic equilibrium of the system. According to the results, the main research questions are answered, and some suggestions are made on the formulation of appropriate regulations. [ABSTRACT FROM AUTHOR]

Contact hypothesis and threat hypothesis are among the most influential theories of xenophobia. The former proposes that intergroup contact may reduce prejudice. The latter suggests that a large outgroup may increase xenophobic attitudes. Using data of a 2018 German representative sample (N = 2,016), we employed multilevel analyses. As predictors, we looked at outgroup size, gross domestic product, and unemployment rate on a county level. On the individual level, we included authoritarianism and a wide range of sociodemographic variables. Individual authoritarianism was identified as the strongest predictor of xenophobic attitudes. On the county level, a higher proportion of migrants was associated with lower values of xenophobia. This serves as an indicator for contact hypothesis. Our results suggest that contextualizing social psychological and micro-sociological theories and employing multilevel analyses are valuable tools to detangle the interplay of individual and contextual influences on xenophobic attitudes. [ABSTRACT FROM AUTHOR]

ObjectiveMethodResultsConclusionsWe used longitudinal youth- and caregiver-reports of adolescent psychological symptoms from three samples of youth receiving mental health services in routine treatment settings to derive expected change trajectories and identify cases at risk for treatment failure.Participants were 1906 youth (1053 caregivers) receiving treatment in community mental health settings, merged across three samples. The Symptoms and Functioning Severity Scale (SFSS) was used as an indicator of weekly clinical change. Multilevel modeling methods were used to develop expected change trajectories and identify cases at risk for treatment failure (not on track; NOT). Logistic regression was used to predict client improvement as a function of NOT status.The SFSS was a reliable indicator of therapeutic change according to youth-reported symptoms. Caregiver reports were not as robust. Whereas predictive accuracy of NOT status yielded moderately high sensitivity in detecting improvement according to youth report, caregiver reports were not as predictive.The youth-reported version of the SFSS-based algorithm seems appropriate for implementation in clinical care. Future studies should search for similarly predictive measures for caregivers. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodResultConclusionTo examine the characteristics of speech-language pathology (SLP) consumers prior to and during the COVID-19 pandemic, with respect to the mode of service delivery within a local health district in New South Wales, Australia, to inform future health service planning.Observational study examining SLP occasions of service data pre-COVID-19 (2019–2019; n = 6413) and during the COVID-19 pandemic (2020–2021; n = 6908). Spatial mapping and multilevel models were used to examine associations between sociodemographic characteristics, telehealth utilisation, and videoconferencing.During COVID-19, SLP occasions of service increased by 7.7% compared to pre-COVID-19. Model 1 found odds of adopting telehealth (telephone or videoconference) during COVID-19 were significantly higher for those aged 0–4 and 5–17 years compared to older age groups. Consumers in inner regional areas were significantly less likely to adopt telehealth than in major city areas, whereas females were significantly more likely to adopt telehealth. Those living in areas experiencing higher relative disadvantage were less likely to use telehealth. Model 2 found odds of adopting videoconferencing only were also significantly higher for the younger age groups (0–4 and 5–17 years) and females.A rapid transition to a virtual model of care was critical to the successful delivery of SLP services during COVID-19. Immediate prioritisation and integration of targeted models of care, where suitability is high and benefits most likely to be experienced, is feasible. [ABSTRACT FROM AUTHOR]

The sexual incentive motivation model suggests that attractive stimuli activate the sexual response system. Attraction toward one’s partner has been linked to greater sexual satisfaction, but no quantitative studies have examined its links to sexual desire or distress among those with sexual dysfunction. We examined associations between daily attraction toward one’s partner and sexual satisfaction, desire, and distress for individuals with Sexual Interest/Arousal Disorder (SIAD) and their partners. Participants (N = 227 couples) completed daily online surveys measuring attraction for one’s partner, sexual desire, satisfaction, and distress. Multilevel models showed that on days when women and gender diverse individuals with SIAD reported higher attraction for their partner, they and their partners reported higher sexual satisfaction and desire, and their partners reported lower sexual distress. On days when partners reported higher attraction, both they and participants with SIAD reported higher sexual desire and partners reported lower sexual distress; however, women and gender diverse individuals with SIAD reported higher sexual distress. Daily fluctuations in attraction may be important for daily fluctuations in sexual wellbeing among couples coping with SIAD. Findings may inform novel treatment targets for SIAD. [ABSTRACT FROM AUTHOR]

This study examined the relationships among the Big Five personality traits, self-esteem levels, self-esteem stability, and life satisfaction over a 15-year period. The primary objectives were to examine whether: (1) self-esteem stability contributed to the prediction of life satisfaction beyond self-esteem level, and (2) both self-esteem level and stability mediated the associations between personality traits and life satisfaction. Bayesian multilevel modelling was conducted on a sample of Dutch adults (N = 4,880), with self-esteem stability operationalised using within-person variance and mean square successive difference. Results indicated that higher levels of self-esteem and self-esteem stability were significantly associated with greater life satisfaction. All Big Five traits predicted higher self-esteem level, while emotional stability and conscientiousness emerged as robust predictors of self-esteem stability with both stability operationalizations. Self-esteem level mediated the relationship between all personality traits and life satisfaction. However, self-esteem stability only mediated the effects of emotional stability and conscientiousness on life satisfaction across both operationalizations of stability. This study provides new insights into the importance of self-esteem stability, in addition to self-esteem level, in shaping well-being. These findings underscore self-esteem levels and dynamics as a crucial mechanism linking personality dispositions to life evaluations. [ABSTRACT FROM AUTHOR]

AbstractObjectivesMethodResultsConclusionMost studies examining age differences in coping across adulthood come from cross-sectional studies and focus on the broader categories of problem- and emotion-focused coping. We aimed to establish a factor structure for coping items used in a national, longitudinal study of aging (MIDUS) and examine age patterns in coping strategies over 10 years.We performed exploratory and confirmatory factor analysis, and factorial invariance testing. Next we conducted a series of multilevel models for each coping factor with participants from waves II and III of the MIDUS study (N = 2,661, Mage = 55, 58% women, 84% White).We found a four-factor solution: instrumental action; denial/disengagement; positive reappraisal; focus and venting of emotions. Invariance was established across time and age. At baseline, age was positively associated with the use of three strategies, though younger adults used more focus and venting of emotions. There was an overall decrease over 10 years in use of all strategies, which was moderated by age. Positive reappraisal declined more steeply among midlife participants, whereas the remaining strategies declined more for older participants.Results highlight the multi-dimensionality of MIDUS coping items and underscores the import of age in understanding changes in coping across midlife and older adulthood. [ABSTRACT FROM AUTHOR]

How does global integration affect environmental activism? I develop a theoretical argument which highlights that global integration’s effect is conditional on political ideology. Countries’ integration in the world society leads to diffusion of environmental attitudes. However, people’s political ideology restrains this positive effect. The assumed incompatibility between economic prosperity and environmental reform exerts a strong influence on attitudes of right-leaning individuals, who end up acting less for promoting environmental protection. I test this argument using multilevel model techniques on data from 35 European countries from 1980 to 2020. The results support my argument and show that global integration has an effect only on left-leaning individuals. In light of these results, the paper offers insights on the expansion of the environmental divide – ‘action gap’ – among individuals with different ideologies. The study also highlights how concerns about environmental consequences are still linked to an ideological commitment to laissez-faire economics. [ABSTRACT FROM AUTHOR]

The maximization-well-being relationship has been extensively studied at the person level, but rarely at the day level. Based on an event reconstruction method, daily data from 200 South Korean adults across 14 days were obtained to examine associations between maximization dimensions (i.e. maximization goal and strategy) and well-being, and the moderating effects of choice domains and characteristics. Results of multilevel analyses indicated that at the day level, maximization goal was significantly associated with well-being, while maximization strategy was not. Choice domain moderated the relationship between maximization goal and well-being; significant positive associations were shown in time use and life decisions but not in consumer goods. Finally, choice irreversibility was the only significant moderator among choice characteristics; it strengthened the positive association between maximization goal and well-being and weakened the negative association between maximization strategy and well-being. Theoretical implications, study limitations and future directions for research are discussed. [ABSTRACT FROM AUTHOR]

Using multi-level modeling and lenses of gender socialization and gendered organizations, we investigated the role of U.S. girls' high schools in adolescent political participation and social engagement, characterized by voting interest, volunteerism, and interactions with diverse communities among other variables, with a focus on the role of all girls' schooling. Results demonstrate benefits for graduates of girls' schools in community-orientation, civic engagement, social agency, and political involvement compared to similar peers in coeducational environments. The conclusions provide broader insight for all types of schooling into the ways that they can focus on increasing engagement for their students. Implications for policy and future research are discussed. [ABSTRACT FROM AUTHOR]

Worry proneness is a transdiagnostic trait that predicts increased negative affect (NA), potentially in the service of preventing negative emotional contrasts. Although discrete types of NA vary along the dimension of arousal, the extent to which trait worry predicts high vs. low arousal forms of NA in daily life is unclear. This distinction has important implications for conceptualising how worry may perturb adaptive emotionality in various disorders. The present study (not pre-registered) aimed to isolate the effects of trait worry on high (N = 88) and low (N = 122) arousal NA in daily life using ecological momentary assessment while controlling for potential physical and psychological confounds. Participants were assessed for trait worry and depressive symptoms at baseline then reported their affect, heart rate, and exercise three times per day for one week. Multilevel models revealed that trait worry predicted both increased high and low arousal NA after controlling for momentary heart rate, daily exercise, and depression. In contrast, baseline depressive symptoms only predicted low arousal NA in daily life. Findings support the contrast avoidance model of worry and suggest that worry is linked to increased state NA in daily life, independent of arousal. [ABSTRACT FROM AUTHOR]

This study focuses on gender disparities in defiance prison -infractions—an understudied and highly discretionary type of rule violation—which have important implications for individuals' prison experiences and outcomes. Using administrative data on a release population in a large western state (N = 23,818), we employed multilevel modeling techniques to test whether (1) women were more likely than men to receive defiance infractions; (2) whether women received a greater number of defiance infractions than men, and (3) whether the gender differences observed for defiance were unique from other types of infractions (e.g. any infraction, nonviolent, violent) net of individual- and prison unit-level controls. Results confirmed that defiance infractions are uniquely gendered, which subjects incarcerated women to harsh consequences for far less serious behavior than their male counterparts. Our work fills key gaps in the literature and contributes to recent policy reform efforts aimed at prison disciplinary reform. [ABSTRACT FROM AUTHOR]

The power of Bayesian multilevel modeling and contrast analysis for food research is illustrated by meta-analysis of weight–diameter relations of apples (first level) at the factors cultivar, orchard site, year of harvest and tree (second level). Contrast analysis compares the effect of factors. Multilevel modeling connects levels, prevents over- and underfitting and accounts for dependencies in measurements/observations. A nonlinear power–law relation of weight-diameter is derived with parameters for spherical approximation and density. Literature data were analyzed in three ways: i) completely pooled (ignoring variation between groups), ii) per factor (no-pooling, ignoring similarities between groups) and iii) partially pooled (acknowledging variation and similarities, i.e. multilevel modelling). The power–law relation was obeyed at tree, orchard, harvest year and cultivar level. Very small differences were found per tree, orchard site and year of harvest, but differences between cultivars were more substantial. Parameter estimates from multilevel modeling differed between complete pooling and no-pooling. Spherical approximation of apples appeared reasonable, whereas apple densities differ considerably per cultivar. Bayesian analysis appears very suitable for model building, validation, predictive capacity and visualisation of parameter uncertainties. The approach can be applied in a much wider context and more complicated relations than considered here for apple characteristics. [ABSTRACT FROM AUTHOR]

With the development of remote sensing technology and computing science, remote sensing data present typical big data characteristics. The rapid development of remote sensing big data has brought a large number of data processing tasks, which bring huge challenges to computing. Distributed computing is the primary means to process remote sensing big data, and task scheduling plays a key role in this process. This study analyzes the characteristics of batch processing of remote sensing big data. This paper uses the Hungarian algorithm as a basis for proposing a novel strategy for task assignment optimization of remote sensing big data batch workflow, called optimal sequence dynamic assignment algorithm, which is applicable to heterogeneously distributed computing environments. This strategy has two core contents: the improved Hungarian algorithm model and the multi-level optimal assignment task queue mechanism. Moreover, the strategy solves the dependency, mismatch, and computational resource idleness problems in the optimal scheduling of remote sensing batch processing tasks. The proposed strategy likewise effectively improves data processing efficiency without increasing computer hardware resources and without optimizing the computational algorithm. We experimented with the aerosol optical depth retrieval algorithm workflow using this strategy. Compared with the processing before optimization, the makespan of the proposed method was shortened by at least 20%. Compared with popular scheduling algorithm, the proposed method has evident competitiveness in acceleration effect and large-scale task scheduling. [ABSTRACT FROM AUTHOR]

Building on the broaden-and-build theory of positive emotions and the regulatory focus theory, we develop a multilevel model to investigate how employees' daily positive and negative emotions trigger daily promotive and prohibitive voice, and further incorporate employees' leader-member exchange (LMX) and trait self-control capacity as boundary conditions of the daily emotions-voice relationships. To test the proposed model, we conducted two studies utilizing the experience sampling method to collect daily data over 10 working days. In Study 1, we gathered 1458 daily responses from 146 employees. In Study 2, we collected 729 matched daily responses from 75 employees and their co-workers, utilizing a multi-phase design. The results of multilevel path-analyses from both studies reveal that: (1) daily positive emotions are positively related with daily promotive voice, and daily promotion focus mediates this association; (2) daily negative emotions are positively related to daily prohibitive voice, however, daily prevention focus does not mediate this relationship; (3) LMX enhances the positive relationship between daily positive emotions and daily promotive voice, and its indirect effect via daily promotion focus; and (4) self-control capacity strengthens the positive relationship between daily negative emotions and daily prohibitive voice, and its indirect effect via daily prevention focus. [ABSTRACT FROM AUTHOR]

AbstractGiven the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has been limited guidance on which specifications are most appropriate for enumerating latent classes when data are nested. This study utilized longitudinal, state-collected student data to demonstrate the impact of different specifications (i.e., ignoring nested data, using a post-hoc adjustment, and a parametric and non-parametric approach) of a latent class model when analyzing nested data. The overarching goal of this study was to provide the implications of four different model specifications commonly used to adjust for clustering in the context of mixture modeling. We highlight factors that may influence researchers’ decisions to employ one approach over another when conducting multilevel mixture modeling. We conclude with a set of recommendations that may be particularly helpful for the use of these methods in educational settings, where nested data is common. [ABSTRACT FROM AUTHOR]

AbstractObjective: To examine trends in self-reported psychological distress among Canadian postsecondary students between 2020 and 2023. Participants and Methods: Using data collected from postsecondary students (n = 103,936) through the Canadian Campus Wellbeing Survey (CCWS), multilevel regression models were fitted to determine how distress levels, as measured by the Kessler Psychological Distress Scale, differed across six-time points of the CCWS. Results: Across the cycles, students reported high levels of distress (mean across cycles = 26.16, SD = 8.61). Considering the impact of time on distress, when compared to pre-COVID-19 pandemic, Fall 2020 (β = 1.4, p < .001), Spring 2021 (β = 1.2, p < .001), Spring 2022 (β = 1.6, p < .001), and Spring 2023 (β = 0.80, p < .017) had significantly higher levels of distress. Distress levels were associated with ancestry, age, gender, and sexual orientation. Conclusion: It is imperative to develop strategies and allocate resources to address the high levels of psychological distress among Canadian postsecondary students. [ABSTRACT FROM AUTHOR]

The literature on tourist experience commonly puts the current en-route experience at the center stage through single-level analysis. This research steers away from that tradition to improvise a triple-experience model through multiple inquiries. Data were collected from a survey to assess how prior and current travel app usage experiences could impact app-induced site attitude and revisit intention via the app, based on a multilevel design with survey data collected from 21 sites. The cross-level moderation of others’ experiences was also explored. This research draws on the functional theory of attitude and the theory of normative conduct to acknowledge the knowledge and social functions of attitude change. It contributes to the literature by bridging the divide between the online app and offline travel evaluations. It builds a theoretical synthesis between the aforementioned theoretical lens to demonstrate how the experiences of others through travel apps can impact an individual’s experience, ultimately affecting attitude toward app-induced tourism destinations. [ABSTRACT FROM AUTHOR]

ObjectiveMethodResultsConclusionThis study employs a person-centered transdiagnostic approach to examine how schema and mode profiles predict symptom severity reduction in schema group therapy for patients with personality disorders and enduring clinical syndromes.We analyzed symptom reduction in 248 patients across three formats of manualized, time-limited schema group therapy. Latent profile analysis and mixed multilevel modeling were used to determine the extent to which schema/mode classes predict symptom reduction, and whether the inclusion of individual schemas and modes enhances these predictions.No significant differences in treatment outcomes were found across the group modalities. A three latent profile solution for schemas and modes showed external validity with clinical variables and demonstrated that declines in symptom severity varied by schema and mode class, even after adjusting for baseline symptom severity. Adding the Vulnerability to Harm schema and Vulnerable Child mode to the model increased the explained variance.Patients with more severe personality problems show more substantial symptom reduction. Both schema and mode profiles significantly contribute to predicting post-treatment symptom levels. Understanding these profiles may help therapists tailor interventions more effectively, consistent with Young’s theoretical model.Trial registration: ISRCTN.org identifier: ISRCTN17262253. [ABSTRACT FROM AUTHOR]