Search

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]

A growing number of sport-for-development (SFD) organizations have emerged in the nonprofit sector to leverage sport for social change, yet many organizations struggle with chronic resource deficiencies that inhibit their long-term viability and highlight a pressing need to examine the sustainability of SFD organizations through resource-based perspectives. This study analyzed secondary financial and administrative data from SFD organizations in the United States to examine changes in key resources during early organizational life stages. Latent profile analysis was utilized to classify organizations based on their level of resources, and multilevel growth modeling revealed significant changes in key resources over the first 5 years of operation, as well as significant differences based on initial resource levels and rates of change. The results provide theoretical insight into the key resources associated with organizational sustainability in the SFD field and offer practical implications for resource procurement, prioritization, and management. [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]

Predicting the mobility patterns of vehicles together with their interactions among surrounding traffic objects is a critical task in autonomous driving systems. Existing graph neural network-based trajectory prediction models primarily capture the structural connectivity of network nodes (road objects) and assume equal priority to all neighbors of a node. However, in real-time traffic networks, the behavior of each vehicle is significantly influenced by its neighboring road objects and this influence is not uniform. This necessitates a neighbor interaction-aware trajectory prediction model that assumes non-uniform priority among neighboring nodes. In this article, we have designed a novel unified trajectory prediction model which is suitable for both highway and urban traffic conditions. The proposed approach seamlessly integrates multi-level context modeling using graph attention mechanisms, capturing and leveraging interactions and dependencies among objects at varied levels of proximity within a graph. Additionally, it employs an encoder–decoder long short-term memory architecture for long-term trajectory prediction, ensuring adaptability to different driving scenarios. The advanced graph attention mechanisms play a crucial role in modeling spatial dependencies between vehicles, allowing the proposed model to dynamically adapt to evolving interactions over time. The experimentations done on real-world trajectory datasets, namely, Next Generation Simulation US-101 highway dataset and diverse urban datasets such as ApolloScape and Argoverse demonstrate remarkable performance of MC-GATP in long-term trajectory prediction. The model showcases superior prediction accuracy, scalability, and computational efficiency for both highway and urban environments. [ABSTRACT FROM AUTHOR]

ABSTRACT Few studies have measured components of stress responses in real time—an essential step in designing just‐in‐time interventions targeting moments of risk. Using ecological momentary assessment (EMA), we characterised stress response components to everyday stressors, including reactivity (the response following a stressor), recovery (the return towards baseline), and pile‐up (the accumulation of stressors) (RRPs) by quantifying the dynamics of response indicators (i.e., subjective stress, negative affect, and perseverative cognition). To determine the utility of these novel measures in capturing and characterising acute moments of the stress response, this study evaluated the proportion of variance in RRPs attributed to (1) between‐person, (2) between‐days, and (3) within‐day (momentary) levels. Healthy adults (n = 123; aged 35–65, 79% women, 91% non‐Hispanic White) participated in a 14‐day study assessing stress response via EMA 6 times a day. RRPs were constructed from 10,065 EMA reports. Multilevel models with moments nested within days nested within persons were used to partition variance in the RRPs. Reactivity and recovery indicators captured the most variation within‐days (i.e., across moments; range 76%–80% and 87%–89%, respectively), with small amounts of variance between‐person. For pile‐up, variation was mostly observed between‐days (range 60%–63%) and between‐persons (range 27%–31%). In contrast, raw measures of stress response reflected substantial between‐person (range 32%–54%) and within‐day (range 34%–53%) variance. These results demonstrated that a person‐specific approach to measuring stress response components (i.e., RRPs) can capture the dynamic within‐person variation in stress response, as it occurs in real time, making it well‐suited for use in novel just‐in‐time interventions targeting moments of risk. [ABSTRACT FROM AUTHOR]

Sensor devices, such as accelerometers, are widely used for measuring physical activity (PA). These devices provide outputs at fine granularity (e.g., 10–100 Hz or minute‐level), which while providing rich data on activity patterns, also pose computational challenges with multilevel densely sampled data, resulting in PA records that are measured continuously across multiple days and visits. On the other hand, a scalar health outcome (e.g., BMI) is usually observed only at the individual or visit level. This leads to a discrepancy in numbers of nested levels between the predictors (PA) and outcomes, raising analytic challenges. To address this issue, we proposed a multilevel longitudinal functional principal component analysis (mLFPCA) model to directly model multilevel functional PA inputs in a longitudinal study, and then implemented a longitudinal functional principal component regression (FPCR) to explore the association between PA and obesity‐related health outcomes. Additionally, we conducted a comprehensive simulation study to examine the impact of imbalanced multilevel data on both mLFPCA and FPCR performance and offer guidelines for selecting optimal methods. [ABSTRACT FROM AUTHOR]

Smartphones and social media have become an integral part of human daily life and they influence mental well-being. These accounts have been researched in the general population, but not in athletes. This is critical given enhanced physical and emotional stressors in athletes versus non-athletes. Therefore, we here studied intra- and interindividual relationships of four social media sites (WhatsApp, TikTok, Instagram, and Snapchat) with mood, stress, recovery, and sleep using log-based media usage tracking as an objective measure in 53 competitive athletes aged 12–27 years. Multilevel modeling revealed that intraindividual TikTok usage negatively predicted sleep (β = −0.10, p = 0.040) and recovery (β = −0.15, p < 0.002), and positively predicted stress (β = 0.12, p = 0.018). Interindividual Instagram usage predicted feelings of calmness (β = 0.27, p = 0.029) and valence (β = 0.20, p = 0.043). Intriguingly, competition level moderated the usage outcomes of all four apps: Athletes on low performance levels showed lower mental well-being when using social media longer, yet in national and international athletes the strength of these relationships was weaker or even reversed. Our study unravels social media usage associations with mental well-being to vary as a function of performance level and provides findings on intra- and interindividual effects of critical importance to inform future population-tailored and expedient interventions. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Methods Results Conclusions This study examined long‐term changes in body composition and bone mineral characteristics among male long‐distance runners from a high‐profile university team, focusing on concerns about impaired musculoskeletal development due to extreme leanness and weight management practices in this population.Trajectory analyses were performed using multilevel modeling of 608 dual‐energy x‐ray absorptiometry datasets from 109 runners (mean age, height, and weight of 18.0 years, 171.4 cm, and 56.8 kg at baseline, respectively) collected biannually over 4 years.Linear increases in total and regional lean mass (LM) were observed on average, with the increase in leg LM being double that of arm LM (0.07 vs. 0.03 kg per occasion, respectively). Similarly, total bone mineral density (BMD) and content (BMC) exhibited linear growth on average, with BMD accrual being greater in the legs than in the arms (0.004 vs. 0.001 g/cm2 per occasion, respectively). However, rib BMD and BMC were predicted to decrease. Individually predicted growth rates in total LM were significantly associated with those in total BMD (r = 0.347, p < 0.001) and BMC (r = 0.424, p < 0.001).These results indicate site‐specific musculoskeletal adaptations to intensive long‐distance running training. Moreover, a random slope model accurately captured the trajectories of most dependent variables, highlighting the heterogeneity of training responses. The predictive models developed in this study offer practical strategies for identifying runners at risk of suboptimal physical development, thereby facilitating the development of personalized conditioning programs. [ABSTRACT FROM AUTHOR]

Introduction: Fluid assessment and management is a key aspect of good dialysis care and is affected by patient-level characteristics and potentially centre-level practices. In this secondary analysis of the BISTRO trial we wished to establish whether centre-level practices with the potential to affect fluid status were stable over the course of the trial and explore if they had any residual associations with participant's fluid status. Methods: Two surveys (S) of fluid management practices were conducted in 32 participating centres during the trial, (S1: 2017–18 and S2: 2021–22). Domains interrogated included: dialysate sodium concentration, (D-[Na+]), fluid and salt intake, residual kidney function, use of diuretics, incremental start, approaches to fluid assessment, management and dialysate temperature, (D-oC). Associations of these practices with the closeness of the participant's post-dialysis target weight to their normally hydrated weight, pre- and post-dialysis systolic (SBP) and diastolic blood pressure, (DBP), were analysed using intra-class correlations and multilevel modelling with adjustment for visit, age, sex and comorbidity burden. Results: Variations in centre practices were reported but did not change during the trial, apart from some relaxation in salt and fluid restriction in S2. For our measures of fluid status, measured 2501 times in 439 non-anuric incident haemodialysis patients, centre-level intraclass correlations were extremely low, whereas patient-level correlations ranged between 0.12 and 0.47, strongest for pre- and post-dialysis-SBP, less so for post-dialysis-DBP. Multi-level analysis found no associations between D-[Na+], or assessment methods of fluid status. In S2, one centre, routinely using a D-Co of 35°C had more divergence between the target and normally hydrated weight, but this was not observed in S1, and no other associations were found. Conclusions: Centre-level fluid management practices were stable over the course of the BISTRO trial, and in contrast to patient-level factors, no centre-level associations were detected with fluid status or blood pressure. This may be because the trial imposed a standardised approach to fluid assessment in all trial participants who at least initially had residual kidney function, potentially over-riding the effects of other centre practices. Survey responses revealed substantial scope for developing and evaluating standardised protocols to optimise fluid management. [ABSTRACT FROM AUTHOR]

Introduction: The integration of technology in educational settings, particularly in physical education, has shown potential in enhancing learning experiences and improving physical health outcomes. This study aims to investigate the effects of technology use on student engagement and fitness outcomes, considering the mediating role of student engagement and the moderating influence of personal attributes. Methods: Utilizing a time-lagged design, the research collected data from 513 Chinese undergraduate students (52% male and, 48% female) aged between 18 and 24 years over three waves using structured questionnaires rated on a 5-point Likert scale. Results: Results revealed a significant positive relationship between technology use and both student engagement (β = 0.68, p < 0.01) and fitness outcomes (β = 0.60, p < 0.01). Student engagement significantly mediated the relationship between technology use and fitness outcomes (β = 0.57, p < 0.01). Personal attributes moderated the effects of technology use on student engagement (β = 0.54, p < 0.01) and fitness outcomes (β = 0.52, p < 0.01), indicating varied benefits among students based on individual characteristics. Discussion: These findings highlight the importance of tailoring technological applications in physical education to individual needs, suggesting that personalized approaches can significantly enhance the effectiveness of technology in improving fitness and engagement. [ABSTRACT FROM AUTHOR]

Background: Although Ethiopia has substantial improvements in various health indicators such as maternal and child mortality, the burden of neonatal mortality remains high. Between 2016 and 2019, neonatal mortality increased from 29 deaths per 1,000 live births to 33 deaths per 1,000 live births. This study aimed to explore the spatial patterns and factors contributing to neonatal mortality in Ethiopia. Methods: Data from the Ethiopian Demographic and Health Surveys (EDHS) for the years 2000, 2005, 2011, 2016, and 2019 were analyzed. The EDHS sampling design uses a two-stage cluster sampling technique, considering census enumeration areas as primary sampling units and households as secondary sampling units. We used the Spatial Scan analysis in SaTScan and Getis-Ord Gi* statistic in Geographic Information System (GIS), to analyse the spatiotemporal patterns of neonatal mortality. Maternal, newborn and health service-related factors contributing to neonatal mortality were also analyzed using a multilevel logistic regression model. Adjusted Odds Rios (AOR) with corresponding 95% CI were presented as a measure of association and a P-value of 0.05 was used to declare statistical significance. Results: During the initial three consecutive surveys, there was a consistent pattern of hot spot clusters in the Amhara and Benshangul Gumuz regions, along with certain parts of the Oromia region. However, in later surveys, these clusters shifted to the eastern parts of the country, notably including the Somali region. Early initiation of breast feeding was associated with reduced chances of neonatal death (Adjusted Odds Ratio [AOR]) = 0.27; 95% Confidence Interval [CI]: 0.23, 0.32). Neonates born at home (AOR = 1.46; 95% CI: 1.16, 1.82) and male babies had a higher likelihood of mortality during the neonatal period compared to their counterparts (AOR = 1.36; 95% CI: 1.24, 1.51). The odds of neonatal mortality increased with the number of children a mother had ever given birth to (AOR = 1.36; 95% CI: 1.24, 1.51). In contrast, longer birth intervals were associated with a reduced risk of neonatal mortality (AOR = 0.76; 95% CI: 0.68, 0.83). Conclusion: The central southern, central-western, north-western, and northern parts of Ethiopia had most of the neonatal death clusters in the first three rounds of DHS while eastern Ethiopia had the highest neonatal mortality clusters in the latest two surveys. Our results underscore the importance for policymakers and health administrators to reassess intervention approaches and reallocate resources to regions identified as hot spots for neonatal mortality. Enhancing the initiation of breastfeeding within the first hour of birth would improve newborn survival rates. Special attention and care need to be given to babies born of smaller sizes. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the influence of patient and implant‐related factors on the changes of marginal bone levels (MBL) at implants with a follow‐up ≥5 years. Materials and Methods: At baseline (within 6 months from prosthetic insertion) and long‐term (≥5 years after implant placement) visits, interproximal (mesial and distal) MBL were radiographically evaluated. To analyze factors predicting MBL change, the site (either mesial or distal) showing the highest MBL change (hChMBL site) was identified for each implant. Multilevel regression models were built to explain MBL change as well as the probability for a bone loss ≥2 mm at long‐term. Results: 942 implants in 312 patients with a mean follow‐up of 8.02 ± 2.5 years were analyzed. MBL change was significantly predicted by baseline MBL, oral bisphosphonate (BP) intake, history of periodontitis, diabetes, and super‐hydrophilic implant surface. Higher risk for a bone loss ≥2 mm was observed in patients with history of periodontitis (OR = 9.52, 95% CI 0.72–3.79) and taking BP (OR = 6.84, 95% CI 0.21–3.63). Mandibular implants had higher odds for bone loss ≥2 mm compared to maxillary implants (OR = 3, 95% CI 0.39–1.87). Conclusions: The findings of the present study contribute to the identification of specific clinical scenarios at higher risk for implant‐supporting bone loss that need to be strictly monitored during maintenance. [ABSTRACT FROM AUTHOR]

Remote sensing image change captioning (RSICC) has received considerable research interest due to its ability of automatically providing meaningful sentences describing the changes in remote sensing (RS) images. Existing RSICC methods mainly utilize pre-trained networks on natural image datasets to extract feature representations. This degrades performance since aerial images possess distinctive characteristics compared to natural images. In addition, it is challenging to capture the data distribution and perceive contextual information between samples, resulting in limited robustness and generalization of the feature representations. Furthermore, their focus on inherent most change-aware discriminative information is insufficient by directly aggregating all features. To deal with these problems, a novel framework entitled Multi-Attentive network with Diffusion model for RSICC (MADiffCC) is proposed in this work. Specifically, we introduce a diffusion feature extractor based on RS image dataset pre-trained diffusion model to capture the multi-level and multi-time-step feature representations of bitemporal RS images. The diffusion model is able to learn the training data distribution and contextual information of RS objects from which more robust and generalized representations could be extracted for the downstream application of change captioning. Furthermore, a time-channel-spatial attention (TCSA) mechanism based difference encoder is designed to utilize the extracted diffusion features to obtain the discriminative information. A gated multi-head cross-attention (GMCA)-guided change captioning decoder is then proposed to select and fuse crucial hierarchical features for more precise change description generation. Experimental results on the publicly available LEVIR-CC, LEVIRCCD, and DUBAI-CC datasets verify that the developed approach could realize state-of-the-art (SOTA) performance. [ABSTRACT FROM AUTHOR]

Background: Surgery is an indispensable component of a functional healthcare system. To date there is limited information regarding how many people die during the perioperative period globally. This study describes a protocol for a systematic review and multilevel meta-regression to evaluate time trends regarding the odds of perioperative mortality among adults undergoing a bellweather surgical procedure while accounting for higher order clustering at the national level. Methods: Published studies reporting the number of perioperative deaths from bellweather surgical procedures among adults will be identified from MEDLINE, Embase, Cochrane CENTRAL, LILACS and Global Index Medicus. The primary outcome will be the rate of perioperative mortality across time and the secondary outcome will be investigating cause of death over time as a proportion of overall perioperative mortality. Two reviewers will independently conduct full text screening and extract the data. Disagreements will first be resolved via consensus. If consensus cannot be reached a third reviewer will be included to arbitrate. Due to human resource limitations, a risk of bias appraisal will not be conducted. From the included studies a multilevel meta-regression will be constructed to synthesize the results. This model will conceptualize patients as nested in studies which are in turn nested within countries while taking into account potential confounding variables at all levels. Discussion: The systematic review and multilevel meta-regression that will be conducted based on this protocol will provide synthesized global evidence regarding the trends of perioperative mortality. This eventual study may help policymakers and other key stakeholders with benchmarking surgical safety initiatives as well as identify key gaps in our current understanding of global perioperative mortality. Trial registration: Systematic review registration: PROSPERO registration number 429040. [ABSTRACT FROM AUTHOR]

Due to their high variability, the growth responses of western hemlock (Tsuga heterophylla (Raf.) Sarg.) stands to fertilization have been regarded as unresponsive or inconsistent. Tree-level fertilization response models for western hemlock were constructed to clarify the inconsistent stand-level responses, using extensive datasets from the United States and Canada. Tree growth in diameter and height, mortality, were assessed by fertilization, stand- and tree-level variables using generalized linear and nonlinear mixed-effects models. Western hemlock fertilization response was influenced not only by stand-level variables and application rates but also by tree social status and crown characteristics. Greater dominance and crown ratio in trees increased height growth responses but decreased diameter growth. The peak of fertilization effect on diameter growth was observed 3 years after application, while effect on height growth peaked at 6 years. Fertilization increased the overall mortality rate, but also ameliorated it for suppressed and steady-growing trees. These complicated fertilization responses of western hemlock may imply its tolerance and allocation strategy of resources at a given size and social status. The results highlight the importance of adopting a tree-level modeling approach to better understanding how western hemlock trees respond to fertilization, improving the accuracy of growth and yield prediction after fertilization. [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]

The design of a manufacturing supply network (MSN) requires the consideration of decisions made by different groups at multiple levels and their interactions that include potential conflicts. Decisions are typically made based on information from computational simulations that are abstractions of reality and, therefore, embody uncertainty. This necessitates focusing on design space exploration to identify robust satisficing solution sets that are relatively insensitive to uncertainty. Current frameworks that support robust satisficing design space exploration are limited by their capability to support the efficient exploration of multilevel design spaces simultaneously. In this paper, we present the Framework for Robust Multilevel Co-Design Exploration (FRoMCoDE), a decision support framework that allows designers to (i) model decision problems across multiple levels and their interactions, (ii) consider uncertainties in the decision problems, and (iii) visualize and systematically carry out simultaneous exploration of multilevel design spaces, termed co-design exploration. In FRoMCoDE, we combine the coupled-compromise Decision Support Problem construct, where a combination of the Preemptive and Archimedean formulations is used, with robust design constructs and interpretable-Self-Organizing Maps (iSOM)-based visualization to facilitate robust co-design. We use a steel MSN problem with decisions made at two levels to test the framework. Using the problem, we demonstrate FRoMCoDE's efficacy in supporting designers in (i) modeling multilevel decision problems and their interactions, considering the uncertainties, and (ii) the efficient co-design exploration of multilevel design spaces. FRoMCoDE is generic and supports designers in the robust co-design exploration of multilevel systems. [ABSTRACT FROM AUTHOR]

To work with a psychological therapies service to implement a recovery plan, as required by a government body, aimed at improving patient outcomes (effectiveness) and decreasing practitioner variability (equity). A case-study utilizing components of a learning health system, including nationally mandated patient outcome data, comprising three 18-month phases: (1) retrospective baseline; (2) improving patient outcomes (management-led); and (3) reducing practitioner variability (clinician-led). Primary analyses focused on 35 practitioners (NPR = 35) who were constant across the three phases and their patients in each phase (NPA = 930, 1226, 1217, respectively). Reliable improvement rates determined patient outcomes and multilevel modeling yielded practitioner effects. To test generalizability, results were compared to the whole practitioner sample for each phase: (1) NPR = 81, NPA = 1982; (2) NPR = 80, NPA = 2227; (3) NPR = 74, NPA = 2267. Ethical approval was granted by the Health Research Authority. Patient outcomes improved in successive phases for both the core and whole practitioner samples with the largest impact occurring in the management-led intervention. Practitioner variability decreased in successive phases in both the core and whole practitioner samples except in the management-led intervention of the whole sample. Compared with the management-led intervention, the practitioner-led intervention yielded a decrease in practitioner effect exceeding 60% in the core sample and approaching 50% in the whole sample. The implementation of multiple components of a learning health system can lead to improvements in both the effectiveness and equity of a psychological therapy service. Clinical or Methodological Significance of this Article: A sequential combination of management-led interventions targeted at improving patient outcomes followed by a compassionate and bespoke feedback to practitioners utilizing principles derived from deliberate practice is a feasible strategy for improving patient outcomes (effectiveness) and reducing practitioner variability (equity), thereby yielding a more equitable delivery of patient care. [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 profound developmental experience is the emergence of adolescent romantic relationships and first feelings of love. However, the daily nature of feeling loved in adolescents' everyday lives is poorly understood. We investigated how daily stress severity was associated with adolescents' levels of feeling loved and whether romantic partner support moderated these associations. Furthermore, we investigated this for non‐interpersonal and interpersonal stressors. N = 97 mixed‐gender adolescent romantic couples (age M = 16.38, SD = 1.02) from an ethnically diverse sample (42.2% Hispanic/Latino/a/x, 44.7% White) participated in dyadic diary assessments twice a week for 12 consecutive weeks. Both partners independently completed open‐ended questions about a daily stressor, indicating stress severity, perceived partner support, and feeling loved. Daily stressors were coded for non‐interpersonal and various types of interpersonal stressors. Results from the dyadic multilevel model showed that days with lower than average support from a romantic partner amplify the adverse effects of stress severity on feeling loved, especially when the partner is involved in the stressor. We discuss the spillover of stress in romantic relationships and the stress‐buffering functions of adolescent romantic partner support. Adolescent romantic partners are potentially essential regulators of stress, increasing adolescents' feelings of love. Research Highlights: Romantic love is central in adolescents' lives; we showed that adolescents generally feel loved by romantic partners.Feeling loved fluctuates daily as adolescents feel less loved on stressful days.However, when adolescents perceive their partner as supportive, there is no association between stress and feeling loved. Partner support is protective for feeling loved.The current study provides essential insights into when adolescents and why adolescents feel loved. [ABSTRACT FROM AUTHOR]

Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associated with each level, and accurate standard errors. Social network analysis is another important approach to analysing complex data that incoproate the social relationships between a number of individuals. Extended linear regression models, such as network autoregressive models, have been proposed that include the social network information to account for the dependencies between persons. In this article, we propose three types of models that account for both the multilevel structure and the social network structure together, leading to network autoregressive multilevel models. We investigate theoretically and empirically, using simulated data and a data set from the Dutch Social Behavior study, the effect of omitting the levels and the social network on the estimates of the regression coefficients, variance components, network autocorrelation parameter, and standard errors. [ABSTRACT FROM AUTHOR]

Introduction: Clinical guidelines and quality improvement initiatives have identified reducing the use of end‐of‐life cancer therapies as an opportunity to improve care. We examined the extent to which oncologists differed in prescribing systemic therapies in the last 30 days of life. Methods: Using Surveillance, Epidemiology, and End Results–Medicare data, we identified patients who died of cancer from 2012 to 2017 (N = 17,609), their treating oncologists (N = 960), and the corresponding physician practice (N = 388). We used multilevel models to estimate oncologists' rates of providing cancer therapy for patients in their last 30 days of life, adjusted for patient characteristics and practice variation. Results: Patients' median age at the time of death was 74 years (interquartile range, 69–79); patients had lung (62%), colorectal (17%), breast (13%), and prostate (8%) cancers. We observed substantial variation across oncologists in their adjusted rate of treating patients in the last 30 days of life: oncologists in the 95th percentile exhibited a 45% adjusted rate of treatment, versus 17% among the 5th percentile. A patient treated by an oncologist with a high end‐of‐life prescribing behavior (top quartile), compared to an oncologist with a low prescribing behavior (bottom quartile), had more than four times greater odds of receiving end‐of‐life cancer therapy (OR, 4.42; 95% CI, 4.00–4.89). Conclusions: Oncologists show substantial variation in end‐of‐life prescribing behavior. Future research should examine why some oncologists more often continue systemic therapy at the end of life than others, the consequences of this for patient and care outcomes, and whether interventions shaping oncologist decision‐making can reduce overuse of end‐of‐life cancer therapies. We examined the extent to which oncologists differed in prescribing systemic therapies to their patients in the last 30 days of life. Results showed substantial variation in end‐of‐life prescribing behavior, with oncologists in the 95th percentile exhibiting a 45% adjusted rate of treatment, compared to just 17% among oncologists in the 5th percentile. [ABSTRACT FROM AUTHOR]

Objective: Police officers' use of force (UoF) has traditionally been understood vis-à-vis subject resistance, but researchers have recently argued for a greater emphasis on subject threat. We examine the role of static and dynamic threat measures, consisting of indicators for ability, opportunity, and intent, in police UoF while accounting for subject resistance. Data and Methods: We use data from a large multiagency sample of coded police force narratives and a series of multilevel models that nest temporally ordered force sequences (dyadic exchanges between officers and subjects) within their respective UoF incidents. Results: Our results suggest that (1) police force incidents are dynamic with levels of force and resistance often fluctuating throughout the incident, (2) each element of subject threat significantly predicts force, net of resistance and other variables, and (3) the elements of threat interact with one another to explain force, but not completely as expected. Conclusions: Our results suggest that subject threat, in addition to resistance, provides important insights for understanding when officers either use or escalate force. We conclude with suggestions for those interested in further exploring the intersection of threat, resistance, and police UoF. [ABSTRACT FROM AUTHOR]

The existing knowledge graph embedding (KGE) models based on graph neural networks (GNNs) typically aggregate unreliable neighboring node information, leading to a decrease in the accuracy of inference results. Additionally, incomplete triples commonly found in knowledge graphs(KGs) pose challenges for KGE models to conduct inductive reasoning. To address these issues, this paper proposes a KGE model named MAKE, which is based on GNN and multi-level analogical reasoning. MAKE model features include: (1) Utilization of multi-level semantic information: MAKE explicitly models semantic information at the levels of relations, entities, and triples using GNN. Through multi-level aggregation, it effectively combines semantic information to generate original aggregated representations, balancing the noise impact from neighbors and enhancing model robustness. (2) Multi-level analogical reasoning: MAKE introduces analogical reasoning methods at the aforementioned levels to generate analogical aggregated representations, thus compensating for the limitations of inductive reasoning. (3) Integration of inductive and analogical reasoning capabilities: By concatenating two representations using a transformation matrix, MAKE produces the final aggregated representation of semantic information, enabling the model to conduct inference more effectively. Extensive experiments demonstrate that MAKE outperforms all baseline models significantly on the FB15K-237 and WN18RR datasets. Particularly noteworthy is its performance on the complex dataset FB15K-237, where MAKE surpasses baseline values by 1 and 2.3% on the MRR and Hits@1 metrics, respectively. [ABSTRACT FROM AUTHOR]

This article proposes the multilevel model to draw how corporate social responsibility (CSR) can increase pro-environmental behaviors and employs green identity as the mediator based on cognitive consistency theory. This article employs the multilevel model to test the theoretical framework using 400 employees from 100 different workgroups in the clean energy technology businesses of Greater China. The findings revealed that when an employee perceived more individual-level CSR at the initial time (Time 1) would increase more individual-level green self-categorization (GSC), green affective commitment (GAC), and green self-esteem (GSE), which consequently increased pro-environmental behaviors (PBs) at the individual level and work-unit level. This finding suggests that managers not only must build individual-level perceived CSR of employees but must also foster work-unit-level (atmosphere) CSR within a group to increase work-unit-level GI, which consequently can increase PBs. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to clarify the relationship between organizational work-family practices and employee work-family conflict in light of the boundary conditions of commitment-based human resource management (HRM) and employee human capital. Design/methodology/approach: The paper opted for a multi-source, multi-level design and surveyed 1,717 individuals (including CEOs, HR managers and employees) from 159 firms in China. The model was tested using hierarchical linear modeling. Findings: The paper provides empirical insights that the effect of work-family practices on work-family conflict is indispensably dependent on the adoption of commitment-based HRM. In addition, employee human capital further moderated this interaction in that the effect of work-family practices on reducing work-family conflict was most salient with high-education employees who were embedded in a high-commitment HRM system. Research limitations/implications: Testing the hypotheses in the Chinese context has both its merits and drawbacks. Specific results are pursuant to the Chinese context. Therefore, a cross-cultural comparative study is called upon. Practical implications: The paper includes implications for organizations striving to minimize employee work-family conflict. Originality/value: This paper primarily applies the resource-building perspective to examine the synergistic effects of organizational resources (targeting work-family practices together with general commitment-based HRM) and individual intellectual resources (human capital) on employee work family conflict. [ABSTRACT FROM AUTHOR]

Objective: Although previous studies have illuminated associations between body mass and physical activity (PA), there have been scant insights regarding the physical, cognitive, and motivational determinants of PA in relationship to body mass. This study aimed to model courses of competencies for health‐enhancing PA across the spectrum of BMI. Methods: We used cross‐sectional data of 3670 individuals (mean [SD]: BMI, 25.54 [5.71] kg/m2; age, 46.11 [14.96] years) from a large data pooling with 18 primary samples employing the PA‐related health competence (PAHCO) instrument. ANCOVA determined differences in 10 PAHCO indicators by BMI categories (underweight, normal weight, overweight, and obesity). Covariate‐adjusted multilevel models described the nonlinear courses of the PAHCO indicators across the BMI spectrum. Results: The levels of all 10 PAHCO indicators differed significantly among the BMI categories (F ≥ 14.8; p < 0.001). All competencies for health‐enhancing PA could be best described by cubic functions having their maximum around normal weight while regressing with underweight and with increasing grades of obesity (0.02 ≤ Rmarg2 ≤ 0.31). Conclusions: This study adds to associations between BMI and PA levels by specifying individuals' multidimensional requirements for health‐enhancing PA. The present findings call for an integration of physical, motivational, and cognitive factors in practices of PA promotion and sustainable obesity treatment. [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]

Partners of fly‐in fly‐out (FIFO) workers face increases in demands, for instance in care and family responsibilities, particularly in the absence of workers; however, little is known about how their daily life experiences influence their health across the FIFO work cycle. This study examined the within‐person effects of workload, job control and social support on affective states and health behaviours of partners of FIFO workers. Forty‐four (N = 44) partners of FIFO workers completed online diary surveys on affective states and health behaviours once a day for 28 consecutive days during on‐and off‐shift periods of the FIFO worker. Multilevel models were used to analyse day‐level data. The results of the study demonstrated significant differences in partners' depressed affect and alcohol consumption during both on‐ and off‐shift periods of FIFO workers. Daily increases in workload were associated with anxious affect, whereas daily increases in job control and social support were associated with low depressed affect and positive affect in partners of FIFO workers. Daily increase in social support was also found to be associated with an increase in daily alcohol intake. Interventions could support partners in managing the daily workload and encouraging the creation of social support networks in partners of FIFO workers. [ABSTRACT FROM AUTHOR]

Introduction: Early marriage, defined as marriage under the age of 18, is widely recognized as a human rights violation with deleterious consequences on women's health and well-being. It persists as a significant global public health issue, predominantly being practiced in South Asian countries. In Countries like Bangladesh, this practice contributes to an increase in early pregnancies among women of reproductive age, further exacerbating adverse maternal and child health outcomes. While certain predictors of early marriage are recognized, additional investigation is warranted due to diverse socio-economic and demographic circumstances. This study, therefore, aimed to identify the prevalence and determinants of early marriage among women in Bangladesh. Methods: This study included a total weighted sample of 18,228 married women aged 18 to 49 years, extracted from the most recent nationally representative Bangladesh Demography and Health Survey (2017–18). We estimated the survey weighted pooled prevalence of early marriage among women and stratified by their different characteristics. We used multilevel mixed-effect binary logistic regression model and estimated the odds ratios (ORs) with their 95% confidence intervals (CIs) to identify the individual-, household-, and community-level factors associated with early marriage practice. All analyses were performed by Stata software version 18. Results: Overall, 74.27% [95% CI: 73.15, 75.35] women got married before reaching the age of 18 years. Early marriage was more prevalent in Rajshahi (82.69%), Rangpur (81.35%), and Khulna division (79.32%). Women with higher education (OR = 0.10, 95% CI: 0.08, 0.12), husband's higher education (OR = 0.57, 95% CI: 0.48, 0.67), and non-Muslim women (OR = 0.46, 95% CI: 0.40, 0.52) were associated with a lower likelihood of experiencing early marriage. Compared to those household heads aged ≤35 years, the likelihood of early marriage among women was lower for those household heads aged 36–55 years (OR = 0.84, 95% CI: 0.76, 0.93) and >55 years (OR = 0.78, 95% CI: 0.69–0.88). Women aged 18–24 years (OR = 1.24, 95% CI: 1.10, 1.40), husbands with agricultural occupation (OR = 1.22, 95% CI:1.06, 1.41), middle wealth index level (OR = 1.14, 95% CI: 1.02, 1.28), family size five or more (OR = 1.21, 95% CI: 1.11, 1.31), and rural residence (OR = 1.17, 95% CI: 1.04, 1.30) were more likely to experience early marriage. Conclusion: This study underscores the alarming prevalence of early marriage among women in Bangladesh, with three-fourths experiencing early marriage, particularly in specific regions. Notably, women education and older household heads were significantly associated with a reduced likelihood of early marriage. Our findings suggest that culturally sensitive interventions should focus on empowering older household heads, alongside initiatives to increase awareness among younger household heads, and enhance education, particularly in rural and impoverished households. These efforts could potentially alter socio-cultural practices and reduce early marriage in Bangladesh. [ABSTRACT FROM AUTHOR]

Introduction: The majority of pregnancy-related complications were preventable. However, the magnitude of complications during pregnancy and childbirth was high in sub-Saharan Africa. There was limited evidence on the magnitude of obstetric complications during childbirth and its predictors among postpartum women in Ethiopia. Methods and materials: The research used secondary data sources based on performance monitoring for action in Ethiopia's second cohort longitudinal survey. It was a national survey that was conducted in three large, predominantly agrarian regions (Oromia, Amhara, and SNNP) and one urban region (Addis Ababa) of Ethiopia between 2021 and 2023. It was conducted to track pregnant women's use of essential maternal and newborn health services. It involved the enrollment of pregnant women and tracking them at six weeks, six months, and one year after giving birth. The data collected at the beginning of the survey and six weeks after childbirth were used for the analysis. Sample weights were applied to account for differences in sample allocation and response rates across regions and urban/rural areas. Multi-collinearity and intra-cluster correlation were assessed before fitting the multilevel models to ensure the accuracy of the estimates. A multi-level logistic regression model was used to assess the magnitude and predictors for the occurrence of obstetric complications during delivery. The model fit was evaluated using Akaike's Information Criterion and Bayesian Information Criterion. Adjusted odds ratio with its 95% confidence interval was used to measure the strength of association for this study. Results: The magnitude of obstetric complications during delivery was found to be 33.86% with 95% CI (31.56, 36.24. Among the obstetric complications that occurred during delivery, about 15.73%with 95% CI(14.02, 17.61) of women experienced bleeding, 4.14% with 95% CI (3.30, 5.17) had their membrane rupture but labor did not start within 24 h, 2.29% with 95% CI(1.67, 3.13) had their membrane rupture before 9 months, 3.95% with 95% CI(3.16, 4.93) had faced malpresentation or malposition of the baby, 12.70% with 95% CI (11.18, 14.39) had prolonged labor lasting more than 12 h, and 12.40% with 95% CI (10.83,14.17) had convulsions. The odds of occurrence of obstetric complication during delivery among women from severely food insecure households were 1.88 times [AOR = 1.88; 95% CI (1.22, 2.90)] more likely to occur than women from food secure households. Moreover, the odds of occurrence for obstetric complications during delivery among women who had complications during their pregnancy were 2.39 times [AOR = 2.39; 95% CI (1.81, 3.16)] more likely to occur as compared to those women who had no complication during their pregnancy. On the other hand, women's who had 1–4 live births given before this delivery were 0.61 times [AOR = 0.61; 95% (0.43, 0.88)] less likely to develop complications as compared to those women's who had no prior live birth. Conclusion and recommendation: Delivery-related obstetric complications during delivery in Ethiopia were high. Approximately one-third of postpartum women in Ethiopia experienced obstetric complications during delivery. Based on this study, women's from severely food insecure households, those women's who had no prior live birth, and women's who had complications during their pregnancy were more likely to develop delivery-related obstetric complications. Thus, policy makers and program implementers who were working on maternal and newborn health should give special attention for women's from severely food insecure households, women's who had no prior live births, and those women's who encountered obstetric complications during their pregnancy to decrease the occurrence of obstetric complications during delivery. In Ethiopia, various governmental organizations, such as the Ministry of Health and the Ministry of Agriculture, are dedicated to addressing food insecurity and improving nutritional access. The country has launched several effective nutritional programs, including the Productive Safety Net Program, the Targeted Supplementary Feeding Program, and the National Nutrition Program, aimed at alleviating food insecurity and enhancing nutrition. Ongoing efforts are crucial to tackle the food insecurity experienced by women, which can help to reduce obstetric related complications of women's during delivery. It is crucial for everyone involved in maternal and newborn health to prioritize addressing the factors that lead to obstetric complications during delivery in women in order to reach the goal of ending all preventable maternal and newborn deaths by 2030. [ABSTRACT FROM AUTHOR]

Background: Causal mediation analysis is widespread in applied medical research, especially in longitudinal settings. However, estimating natural mediational effects in such contexts is often difficult because of the presence of post-treatment confounding. Moreover, many models frequently used in applied research, like multilevel and latent growth models, present an additional difficulty, i.e. the presence of latent variables. In this paper, we propose a causal interpretation of these two classes of models based on a novel type of causal effects called separable, which overcome some of the issues of natural effects. Methods: We formally derive conditions for the identifiability of separable mediational effects and their analytical expressions based on the g-formula. We carry out a simulation study to investigate how moderate and severe model misspecification, as well as violation of the identfiability assumptions, affect estimates. We also present an application to real data. Results: The results show how model misspecification impacts the estimates of mediational effects, particularly in the case of severe misspecification, and that the bias worsens over time. The violation of assumptions affects separable effect estimates in a very different way for the mixed effect and the latent growth models. Conclusion: Our approach allows us to give multilevel and latent growth models an appealing causal interpretation based on separable effects. The simulation study shows that model misspecification can heavily impact effect estimates, highlighting the importance of careful model choice. [ABSTRACT FROM AUTHOR]

Objectives Methods Results Conclusion The current study examined the association between the possession of personal growth initiative (PGI) skills and symptoms of mental illness (i.e., depression, anxiety, and stress) and the potential mediating role of daily engagement of PGI skills during the COVID‐19 pandemic.The participants consisted of 73 individuals (Mage = 41.62, SDage = 12.44) who were recruited from Amazon's Mechanical Turk (MTurk). Data for possessed PGI was collected in April 2020, and the daily survey started approximately 1 month later at the beginning of May 2020 for 29 days.Controlling for demographic variables, multilevel mediation models revealed significant association between PGI skills and PGI engagement. However, our hypothesized indirect effects were not found. When inspecting the direct effects controlling for the effect of PGI engagement and demographic variables, the paths between PGI skills and both depression and anxiety were negatively associated. When examining the effect of time, there were no significant changes during the period of 29 days in the levels of PGI skills among individuals. However, a significant fluctuation within individuals in how much participants have utilized PGI skills during the study period was found.The current study highlights the influence of PGI skills at both the between‐individual as well as within‐individual levels in predicting symptoms of mental illness, and it also uncovers the role of PGI skills by separating into general PGI skills and individual's daily engagement in utilizing the PGI skills in predicting symptoms of mental illness. [ABSTRACT FROM AUTHOR]

Habits are cue‐behavior associations learned through repetition that are assumed to be relatively stable. Thereby, unhealthy habits can pose a health risk due to facilitating relapse. In the absence of research on habit decay in daily life, we aimed to investigate how habit decreases over time when trying to degrade a habit and whether this differs by four health‐risk behaviors (sedentary behavior, unhealthy snacking, alcohol consumption, and smoking). This 91‐day intensive longitudinal study included four parallel non‐randomized groups (one per behavior; N = 194). Habit strength was measured daily with the Self‐Report Behavioral Automaticity Index (11,805 observations) and modelled over time with constant, linear, quadratic, cubic, asymptotic, and logistic models. Person‐specific modelling revealed asymptotic and logistic models as the most common best‐fitting models (54% of the sample). The time for habit decay to stabilize ranged from 1 to 65 days. Multilevel modelling indicated substantial between‐person heterogeneity and suggested initial habit strength but not the decay process to vary by behavioral group. Findings suggest that habit decay when trying to degrade a habit typically follows a decelerating negative trend but that it is a highly idiosyncratic process. Recommendations include emphasizing the role of person‐specific modelling and data visualization in habit research. [ABSTRACT FROM AUTHOR]

This study examines the connection between social capital and the perceived health status for the Chinese public. Extending from previous research that uses unrepresentative samples, the current project analyzes nationally representative samples of approximately 60,000 respondents. The data are drawn from six waves of the Chinese General Social Survey conducted in 2010, 2012, 2013, 2015, 2017, and 2018, respectively. The multilevel regression approach is used for statistical estimation. Findings show a consistent pattern that social capital, encompassing social network and generalized trust, is positively related to one's perceived health status across these years. In addition, the moderating impact of personal capital on the link between social capital and perceived health status is identified. Social capital has a greater health impact on those with lower personal capital than those with higher personal capital. This study complements current literature and has implications for public health policies. [ABSTRACT FROM AUTHOR]

This work showed the capability of handling large number of classes for classification with human cognition inspired methods. A cognition based techniques for both feature extraction, (self-similarity feature, Intensity Level Multi Fractal Dimension (ILMFD)) as well as classification purpose (decision tree clustering based multi-level Artificial Neural Network classifier-MLANN-DTC) were employed to implement facial recognition based object detection system. A DTC based approach reduces the search space time and also provides opportunity for very less amount of classes (a smaller part of the large number of classes) to be handled by the respective classifier for classification. It also mimics fast recognition capability of humans. In this work, two different databases were used for experiment, first one is our own collected facial images from rotation based video clips (117 persons and 40 facial images per person) named as NS database, and other is standard ORL database (40 persons and 10 facial images per person). In pre-processing step, the facial images were segmented to obtain facial part using context window based texture of pixels (CWTP) & back-propagation neural network (BPNN) based model and then a scale and rotation independent ILMFD feature was computed from each segmented image. Further, a combination of K-means and hierarchal clustering was used to build super classes. All classes' data were distributed among these 6 super classes (heuristically chosen) for own NS database and 3 for ORL database as per their similarity based on ILMFD features. Multi-level ANNs models were employed for all super classes and further their classification results were fed into decision clustering based model to obtain fine-tuned results, which showed significant improvement in terms of classification efficiency. This approach believes in center tendency of largest cluster to refer the actual class decision from multiple decisions obtain corresponding to multiple input data of the same class. In this work, the MLANN-DTC based proposed model has produced 89.542 ± 1.167% and 87.098 ± 2.066% classification efficiency (± standard deviation) for single input and for group based decision (decision clustering), 95.042 ± 0.719% and 89 ± 2.549% for NS and ORL database respectively. This improved classification results motivate its application for other object recognition and classification problems. The basic idea of this work also supports better handling of classification which deals with a large number of classes. [ABSTRACT FROM AUTHOR]

Introduction: The umbilical cord (UC) serves as the main pathway for bacteria to reach the neonate's body, potentially causing local and severe infections, sepsis, and even death. Consequently, neonatal mortality remains a significant public health concern, particularly in Ethiopia. The World Health Organization (WHO) recommends that the umbilical cord stump be kept clean and dry, with the exception of applying topical antiseptics. However, various harmful substances are still applied to the umbilical cord of neonates. Data on the geographical distribution and risk factors for harmful umbilical cord stump (UCS) care are scarce. Therefore, this study aims to fill this gap. Methods: A secondary data analysis of the Ethiopian Demographic Health Survey (EDHS 2016) was conducted using a weighted sample of 7,168 live births. ArcGIS version 10.7.1 software was utilized to visualize the spatial distribution of harmful umbilical cord stump (UCS) care practices in Ethiopia. Additionally, a Bernoulli probability model-based spatial scan statistic was applied using Kulldorff's SaTScan version 9.6 software to identify significant clusters of harmful UCS care. A multilevel logistic regression model was used to determine the factors associated with UCS care practices in Ethiopia. Statistical significance was declared at a two-sided P-value of < 0.05. Results: Overall, the prevalence of harmful UCS care in Ethiopia was 15.09% (95% CI: 13.9–16.3), with significant spatial heterogeneity across geographical areas. The hotspot areas of harmful US care were observed in the eastern (Somali) and northern (Tigray and Amhara) parts of Ethiopia. In spatial scan analysis, the most likely primary clusters were observed in South Nation Nationalities and Peoples region (SNNPR), secondary clusters in the Somali, tertiary clusters in Tigray, and the next clusters in the Amhara regions, respectively. In the final multilevel model, maternal age (Adjusted odds ratio/AOR 1.07, 95% CI: 1.02–1.12), institutional delivery (AOR 0.64, 95% CI: 0.42–0.97), female neonates (AOR 1.31, 95% CI: 1.04–1.61), rural residence (AOR 2.18, 95% CI: 1.05–4.52), living in Tigray region (AOR 3.79, 95% CI: 1.38–9.38), living in Somali region (AOR, 2.95% CI: 1.02–8.52), and living in Harari region (AOR 3.51, 95% CI: 1.28–9.60) were identified as a significant factors of harmful US care practice in Ethiopia. Conclusion: In Ethiopia, the distribution of harmful UCS care practices is non-random and highly clustered in the SNNPR, Somalia, Tigray, and Amhara regions. Both individual and community-level factors were significantly associated with the practice. Special emphasis needs to be provided for neonates from those hot-spot areas and to address the identified predictors of harmful umbilical cord stump care practices. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to investigate whether there is a significant association between teachers' and students' perceptions of school climate, and if not, whether teacher factors are associated with the respective perceptions. Methods: The participants included 1,831 students and 59 homeroom teachers from 11 public elementary and junior high schools in Japan. Multilevel models were used to examine the association between students' and teachers' perceptions of school climate. Results: Of the three teacher-rated school climate scales, only teacherperceived disciplinary climate was associated with students' perceptions of school climate. Teachers' working conditions, such as self-efficacy and stress, were associated with teachers' perceptions but not students' perceptions of school climate. Disciplinary climate was associated with students' perceptions of school climate, even after accounting for the teachers' working conditions. Discussion: Items questioning specific student behaviors, such as those included in the disciplinary climate scale, may be effective in avoiding incongruence with student evaluations. Moreover, maintaining disciplinary climate itself is important for students' positive perceptions of the school climate. A disciplinary climate in which teachers and students share responsibility for learning and classroom organization, and strategies that support positive student behavior are preferable to exclusionary discipline strategies. Incorporating feedback data gathered through classroom observations or student perceptions is also important in resolving the incongruence between teachers' and students' perceptions of the school climate. [ABSTRACT FROM AUTHOR]

The current study anchors on the self-determination theory (SDT) to predict the influence of mindful leadership on sports team performance through the mediator effect of team cohesion and the moderating role of teamwork quality. The study samples athletes and coaches from various sports teams in China and assesses the hypothesized model using Mplus software, appropriate to gauge multilevel modeling (N = 342). Besides, the authors gather data across a two-time wave in order to predict the causal relationships amongst variables. Our findings indicate that mindful leadership significantly predicts team performance via the mediating path of team cohesion. In addition, teamwork quality significantly and positively moderates the linkage between mindful leadership and team creativity (and then team performance via team cohesion). The study explores a moderated mediation model capturing the unique dynamics of leadership and team phenomenon in sports teams. Our findings contribute substantial insights for both theory and practice by assessing the critical roles of leadership and team dynamics to influence team outcomes. [ABSTRACT FROM AUTHOR]

In the context of an emerging new additional learning needs (ALN) system in Wales, this research explores who was likely to be identified with special educational needs (SEN) under the previous system. Our study reveals analysis of linked Welsh education and health data on SEN identification in learners in mainstream education settings born between 2002/3 and 2008/9. Using longitudinal multilevel modelling, we explore (i) who is likely identified with SEN and (ii) whether there is evidence of social patterning in SEN identification. We find that 48% of those born in the year 2002/3 were identified with SEN at some point during their schooling years. Furthermore, when controlling for health‐related variables, those who are identified with SEN in Wales were more likely to be male, White, from a deprived background, with lower school attendance, had not experienced breastfeeding and were born later in the academic year. Taken together, the research findings suggest that SEN identification was influenced by a child's context. The study thus underscores the critical importance of examining the relationship between socioeconomic, environmental and biological factors in SEN identification, urging for a comprehensive and cross‐organisation approach to enhance outcomes for learners with diverse needs. It also highlights the need for follow‐up research to explore unfolding trends as the new ALN system in Wales becomes fully implemented and integrated over the coming years. [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]

Background: This study investigates the determinants of engagement in questionable research practices (QRPs), focusing on both individual-level factors (such as scholarly field, commitment to scientific norms, gender, contract type, and career stage) and institution-level factors (including industry type, researchers' perceptions of their research culture, and awareness of institutional policies on research integrity). Methods: Using a multi-level modelling approach, we analyse data from an international survey of researchers working across disciplinary fields to estimate the effect of these factors on QRP engagement. Results: Our findings indicate that contract type, career stage, academic field, adherence to scientific norms and gender significantly predict QRP engagement. At the institution level, factors such as being outside of a collegial culture and experiencing harmful publication pressure, and the presence of safeguards against integrity breaches have small associations. Only a minimal amount of variance in QRP engagement is attributable to differences between institutions and countries. Conclusions: We discuss the implications of these findings for developing effective interventions to reduce QRPs, highlighting the importance of addressing both individual and institutional factors in efforts to foster research integrity. [ABSTRACT FROM AUTHOR]

Background and Aims Design Setting Participants Measurements Findings Conclusions Opioid use disorder (OUD) is treatable with buprenorphine/naloxone (buprenorphine), but many patients discontinue treatment prematurely. The aim of this study was to assess the influence of patient‐ and prescriber‐level characteristics relative to several patient outcomes following the initiation of buprenorphine treatment for OUD.This was a retrospective observational investigation. We used the Public Health Data Warehouse from the Massachusetts Department of Public Health to construct a sample of patients who initiated buprenorphine treatment between 2015 and 2019. We attributed each patient to a prescriber based on information from prescription claims. We used multilevel models to assess the influence of patient‐ and prescriber‐level characteristics on each outcome.Massachusetts, USA.The study cohort comprised 37 955 unique patients and 2146 prescribers. Among patients, 64.6% were male, 52.6% were under the age of 35 and 82.2% were White, non‐Hispanic. For insurance coverage, 72.1% had Medicaid.The outcome measures were poor medication continuity, treatment discontinuation and opioid overdose, all assessed within a 12‐month follow‐up period that began with a focal prescription for buprenorphine. Each patient had a single follow‐up period. Poor medication continuity was defined as medication gaps totaling more than 7 days during the initial 180 days of buprenorphine treatment and treatment discontinuation was defined as having a medication gap for 2 consecutive months within the 12‐month follow‐up period.The patient‐level rates for poor medication continuity, treatment discontinuation and opioid overdose were 59.7% [95% confidence interval (CI) = 59.2–60.2], 57.4% (95% CI = 56.9–57.9) and 10.3% (95% CI = 10.0–10.6), respectively, with 1.1% (95% CI = 1.0–1.2) experiencing a fatal opioid overdose. At the patient level, after adjustment for covariates, adverse outcomes were associated with race/ethnicity as both Black, non‐Hispanic and Hispanic patients had worse outcomes than did White, non‐Hispanic patients (Black, non‐Hispanic ‐‐ poor continuity: 1.50, 95% CI = 1.34–1.68; discontinuation: 1.44, 95% CI = 1.30–1.60; Hispanic ‐‐ poor continuity: 1.21, 95% CI = 1.12–1.31; discontinuation: 1.38, 95% CI = 1.28–1.48). Patients with insurance coverage through Medicaid also had worse outcomes than those with commercial insurance (poor continuity: 1.18, 95% CI = 1.11–1.26; discontinuation: 1.09, 95% CI = 1.03–1.16; overdose: 1.98, 95% CI = 1.75–2.23). Pre‐treatment mental health conditions and other types of chronic illness were also associated with worse outcomes (History of mental health conditions ‐‐ poor continuity: 1.11, 95% CI = 1.06–1.17; discontinuation: 1.05, CI = 1.01–1.10; overdose: 1.47, 95% CI = 1.36–1.60; Chronic health conditions ‐‐ poor continuity: 1.15, 95% CI = 1.05–1.27; discontinuation: 1.15, 95% CI = 1.05–1.26; overdose: 1.83, 95% CI = 1.60–2.10; History of substance use disorder other than for opioids ‐‐ poor continuity: 1.54, 95% CI = 1.46–1.62; discontinuation: 1.54, 95% CI = 1.47–1.62; overdose: 1.93, 95% CI = 1.80–2.07). At the prescriber level, after adjustments for covariates, adverse outcomes were associated with clinical training, as primary care physicians had higher rates of adverse outcomes than psychiatrists (poor continuity: 1.12, 95% CI = 1.02–1.23; discontinuation: 1.04, 95% CI = 1.01–1.09). A larger prescriber panel size, based on number of patients being prescribed buprenorphine, was also associated with higher rates of adverse outcomes (poor continuity: 1.36, 95% CI = 1.27–1.46; discontinuation: 1.21, 95% CI = 1.14–1.28; overdose: 1.10, 95% CI = 1.01–1.19). Between 9% and 15% of the variation among patients for the outcomes was accounted for at the prescriber level.Patient‐ and prescriber‐level characteristics appear to be associated with patient outcomes following buprenorphine treatment for opioid use disorder. In particular, patients' race/ethnicity and insurance coverage appear to be associated with substantial disparities in outcomes, and prescriber characteristics appear to be most closely associated with medication continuity during early treatment. [ABSTRACT FROM AUTHOR]

Background: The engagement of preschool teachers in their work is pivotal for maintaining teaching quality, ensuring teacher well-being, and fostering children's development. Despite its significance, there is limited knowledge regarding the daily fluctuations in work engagement and the underlying factors influencing it. This study, guided by the Job Demands-Resources model and Affect Event Theory, utilized an experience sampling methodology to investigate the impact of challenge and hindrance stressors on daily work engagement, as well as the mediating role of affect and the moderating effect of mindfulness. Methods: Utilizing an experience sampling method, this study collected data from 220 preschool teachers in Shanghai over five consecutive workdays, conducting surveys once daily. Data analysis was performed using multilevel linear models. Results: The results from multilevel regression indicated that: (1) daily challenge stressors were positively related to work engagement, (2) daily hindrance stressors were negatively related to work engagement, (3) daily positive affect mediated the relationship between challenge stressors and work engagement, (4) daily negative affect mediated the relationship between hindrance stressors and work engagement, and (5) daily mindfulness played a crucial moderating role by alleviating the adverse effects of hindrance stressors on daily negative affect. Conclusions: This study provides valuable insights into the daily experiences of preschool teachers and the factors that influence their work engagement. Understanding the impact of stressors, affect, and mindfulness on work engagement can inform the development of interventions and strategies to improve teacher well-being and work engagement. [ABSTRACT FROM AUTHOR]

Introduction: According to the World Health Organization and Ethiopian Demographic and Health Survey on birth spacing, there should be at least a two-year gap between conception and the first of two children born in quick succession. In poor nations like Ethiopia, resource issues were complex, making it difficult to get statistics for the entire country. However, by examining Ethiopian mini demographic and health survey data, we were able to provide data at the national level. Method: The cross-sectional survey-based study was conducted in several of Ethiopia's administrative cities and nine regions. In the analysis, sampling weight was used to correct the survey's non-proportional sample distribution to strata and areas throughout the survey process and restore representative data. The study's household population was presented and described using descriptive statistics such as weighted frequencies and percentages. The statistically significant factors linked to frequent short birth intervals were found using a multivariable, multilevel logistic regression analysis. Result: Overall, 4306 weighted multigravida mothers nested within 305 enumeration areas were included in the analysis. The respondents' mean (standard deviation) of the birth interval was 42.027(26.69). Higher-educated women had 12% lower odds of having a shorter pregnancy (AOR = 0.88; 95% CI: 0.35, 0.98) than women without higher education. The odds of a short birth interval were 3.04 times greater among women in the age category of 40–49 years at first marriage (AOR = 3.04; 95% CI: 1.08, 8.46) than among women in the age category of 15–19 years. This indicates that older women were most likely to have short birth intervals. Conclusion: In the multilevel logistic regression model, maternal age, maternal educational status, the wealth quintile index, use of contraceptives, duration of breastfeeding, and contextual regions were significantly associated with short birth intervals in Ethiopia. [ABSTRACT FROM AUTHOR]

Habit is a key psychological determinant for physical activity behavior change and maintenance. This study aims to deepen the understanding of habit formation in physical activity and identify promotion strategies. We examined the habit formation trajectory and its relationships with cue‐behavior repetition (a cue‐triggered 15‐minute brisk walk) and unconditional physical activity (daily steps). We also tested whether the behavior change techniques (BCTs) ‘commitment’ and ‘prompts and cues’ promote habit, cue‐behavior repetition, and daily steps within persons. This micro‐randomized trial included a 7‐day preparatory and a 105‐day experimental phase delivered via the HabitWalk app. Participants (N = 24) had a 50% probability of receiving each BCT daily, leading to four conditions. Habit strength was assessed daily using the Self‐Report Behavioral Automaticity Index, while cue‐behavior repetition and steps were measured via an activity tracker. Person‐specific growth functions indicated that habit strength trajectories were highly idiosyncratic. Multilevel models indicated a positive effect of cue‐behavior repetition on habit strength, but not vice versa. The effect of habit strength on daily steps varied by the operationalization of cue‐behavior repetition. Tentative findings suggest that commitment and prompts and cues are effective habit‐promotion strategies when delivered together. [ABSTRACT FROM AUTHOR]

The Progress in International Reading Literacy Study (PIRLS) was conducted in paper and online reading modes in 2016 using the same samples of students in a number of countries. Differences in reading literacy scores were found in several European countries. In some countries, the differences favored the electronic reading mode. Yet in others, the paper reading mode was favored. As the electronic reading mode differs substantially in the cognitive demands compared to the paper mode, it can be expected that the differences between the two modes are related to the variables related to technology: availability and access, general use, use for educational purposes in class or out-of-school, and self-efficacy with technology. This study investigates the Information and Communication Technology (ICT) factors related to the differences in paper and online reading in six European countries participating in both modes in PIRLS 2016. This study uses linear regression models as the application of multilevel modeling is not suitable because of the low between-school variances across countries. The results from this study show limited support for the relative effect that the student individual, school, and classroom ICT variables have on the differences between paper and electronic reading. Access to technology is related to mode differences only in Italy, and the use of computer devices in and out of school is related to the mode differences in Italy and Portugal. Student self-efficacy is related to the mode differences in Portugal and Slovenia. School resources show significant effects in Denmark (computers to students ratio) and Italy (instruction affected by digital resource shortages). None of the classroom variables showed any significant relationship in any of the countries. In addition, socio-economic status (which is proxied by the variable on home resources for learning) is a significant predictor in half of the countries. In addition to these findings, the general technological context within countries is discussed as part of an evaluation of the difference in reading in the two test delivery modes. The general uptake of technology in different social and economic aspects, as measured by the Digital Economy and Society Index (DESI), follows the differences between the two reading modes. [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]