Multilevel Approach Research Articles

Linking childhood maltreatment to cyberbullying perpetration and victimization: A systematic review and multilevel meta-analysis

Both theoretical and empirical evidence has suggested that childhood maltreatment is positively associated with cyberbullying involvement (perpetration and victimization). However, empirical evidence on the strength of such positive associations is not yet clear. To clarify the strength of the associations, the current meta-analysis examined the extent to which childhood maltreatment is correlated with cyberbullying (perpetration and victimization), and whether these associations varied by sample, publication, and research design characteristics. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 57 studies (N = 98,351 participants) involving 281 effect sizes were included through a systematic literature search of five databases and auxiliary searches. An advanced multilevel meta-analysis approach was employed in R to synthesize the effect sizes. No significant publication bias was found. Results showed that childhood maltreatment was significantly and positively related to both cyberbullying perpetration (mean r = 0.349, p < 0.001) and victimization (mean r = 0.237, p < 0.001). Further, moderator analyses revealed that the association between childhood maltreatment and cyberbullying perpetration was stronger for young adults than for adolescents. Finally, the associations between childhood maltreatment and both cyberbullying perpetration and victimization were stronger for emotional abuse than neglect. The findings suggest that childhood maltreatment is a risk factor for developing both cyberbullying perpetration and victimization. Childhood maltreatment warrants attention in the design of comprehensive prevention and intervention programs for cyberbullying (perpetration and victimization).

Neural inhibition as implemented by an actor-critic model involves the human dorsal striatum and ventral tegmental area.

Inhibition is implicated across virtually all human experiences. As a trade-off of being very efficient, this executive function is also prone to many errors. Rodent and computational studies show that midbrain regions play crucial roles during errors by sending dopaminergic learning signals to the basal ganglia for behavioural adjustment. However, the parallels between animal and human neural anatomy and function are not determined. We scanned human adults while they performed an fMRI inhibitory task requiring trial-and-error learning. Guided by an actor-critic model, our results implicate the dorsal striatum and the ventral tegmental area as the actor and the critic, respectively. Using a multilevel and dimensional approach, we also demonstrate a link between midbrain and striatum circuit activity, inhibitory performance, and self-reported autistic and obsessive-compulsive subclinical traits.

Digital Village Construction: A Multi-Level Governance Approach to Enhance Agroecological Efficiency

This study conducts a comprehensive analysis of China’s digital village construction, emphasizing its role in rural organizational governance, from bureaucracies to self-governance bodies to market forces and social organizations. Utilizing sample data from 30 provinces from 2014 to 2020, the study dissects the dynamics and diversity of multi-level governance in bolstering agroecological efficiency (AEE). Notable insights include a significant positive correlation between digital villages and AEE. However, it wanes in an “inverted U” pattern beyond a digital development index of 0.8. Furthermore, rural bureaucrats and self-governing entities independently advance AEE, while market forces and social organizations require enhancement. These findings contribute to the field of digital village construction and inform sustainable agricultural strategies in developing nations.

Question of Fraudulent Registration of Ships and Fraudulent Ship Registries; the Response of the International Community

The aim of this paper is to address the issue of fraudulent registration and fraudulent Ship Registries, mainly as a means of concealing illicit activities, such as piracy, slavery, maritime migration, IUU fishing, and the evasion of UN sanctions. The method that has been followed includes the presentation of all types of fraudulent flagging as reported by the interested Flag States, Port States, and the associated international organisations of IMO and FAO. The analysis compares the findings that have been collected by the various sources and the drawing of strong conclusions. The results of this essay extend to cover the various forms of fraudulent registration, the legal framework that governs the registration of ships, and the proposed measures to deal with this phenomenon. The novelty lies in the multi-level approach of fraudulent registration, covering all of its forms, and the solutions proposed, either already applied or innovative. In conclusion, insufficiency to deal with this phenomenon so far leaves room for the application of new strategies, like the ones proposed in the current essay.

Examining student, parent, and school factors predicting science achievement using a multilevel approach: the case of Hong Kong from the Program for International Student Assessment 2015

Examining student, parent, and school factors predicting science achievement using a multilevel approach: the case of Hong Kong from the Program for International Student Assessment 2015

Understanding momentary engagement in university students: Exploring the interaction between competence and value beliefs on emotions and cognitive engagement – A multilevel investigation

Using an intensive longitudinal design, this study investigated the predictive role of and interaction between competence beliefs and task value in relation to four achievement emotions (enthusiasm, excitement, anxiety, and irritation) as well as cognitive engagement. Data were collected using an experience sampling method to capture the momentary experiences of 81 university students over 14 days. Using a multilevel modeling approach, the study disentangled variations between and within individuals across learning situations. The results indicated that associations between competence and value beliefs and emotions were primarily observed at the situational level. Both competence and value beliefs played important roles in predicting cognitive engagement. In addition, high competence beliefs acted as a buffer, mitigating the positive association between opportunity cost and anxiety and reducing the negative impact of low intrinsic value on irritation. Positive value beliefs emerged as instrumental in fostering cognitive engagement, particularly in situations characterized by limited competence beliefs. Educational relevance statementThe motivation and engagement displayed by university students in diverse learning events offer valuable insights into their dedication and academic involvement in pursuing their degrees. This study highlights the importance of perceiving both high competence beliefs and intrinsic value, which results in stronger associations with enthusiasm and excitement during learning. Conversely, high opportunity cost is linked to greater anxiety, but high competence beliefs act as a protective factor, mitigating this effect. High competence beliefs also counteract the negative impact of low intrinsic value on irritation. Value beliefs, particularly importance and intrinsic value, have a compensatory effect on cognitive engagement. Positive value beliefs play a crucial role in driving cognitive engagement, especially when competence beliefs are lacking. Gaining insight into changes within individuals and variations between students enables educators to effectively tailor instructional strategies and provide support, which in turn fosters students' motivation and engagement.

Gender-specific prolactin thresholds to determine prolactinoma size: a novel Bayesian approach and its clinical utility.

In clinical practice, the size of adenomas is crucial for guiding prolactinoma patients towards the most suitable initial treatment. Consequently, establishing guidelines for serum prolactin level thresholds to assess prolactinoma size is essential. However, the potential impact of gender differences in prolactin levels on estimating adenoma size (micro- vs. macroadenoma) is not yet fully comprehended. To introduce a novel statistical method for deriving gender-specific prolactin thresholds to discriminate between micro- and macroadenomas and to assess their clinical utility. We present a novel, multilevel Bayesian logistic regression approach to compute observationally constrained gender-specific prolactin thresholds in a large cohort of prolactinoma patients (N = 133) with respect to dichotomized adenoma size. The robustness of the approach is examined with an ensemble machine learning approach (a so-called super learner), where the observed differences in prolactin and adenoma size between female and male patients are preserved and the initial sample size is artificially increased tenfold. The framework results in a global prolactin threshold of 239.4 μg/L (95% credible interval: 44.0-451.2 μg/L) to discriminate between micro- and macroadenomas. We find evidence of gender-specific prolactin thresholds of 211.6 μg/L (95% credible interval: 29.0-426.2 μg/L) for women and 1,046.1 μg/L (95% credible interval: 582.2-2,325.9 μg/L) for men. Global (that is, gender-independent) thresholds result in a high sensitivity (0.97) and low specificity (0.57) when evaluated among men as most prolactin values are above the global threshold. Applying male-specific thresholds results in a slightly different scenario, with a high specificity (0.99) and moderate sensitivity (0.74). The male-dependent prolactin threshold shows large uncertainty and features some dependency on the choice of priors, in particular for small sample sizes. The augmented datasets demonstrate that future, larger cohorts are likely able to reduce the uncertainty range of the prolactin thresholds. The proposed framework represents a significant advancement in patient-centered care for treating prolactinoma patients by introducing gender-specific thresholds. These thresholds enable tailored treatment strategies by distinguishing between micro- and macroadenomas based on gender. Specifically, in men, a negative diagnosis using a universal prolactin threshold can effectively rule out a macroadenoma, while a positive diagnosis using a male-specific prolactin threshold can indicate its presence. However, the clinical utility of a female-specific prolactin threshold in our cohort is limited. This framework can be easily adapted to various biomedical settings with two subgroups having imbalanced average biomarkers and outcomes of interest. Using machine learning techniques to expand the dataset while preserving significant observed imbalances presents a valuable method for assessing the reliability of gender-specific threshold estimates. However, external cohorts are necessary to thoroughly validate our thresholds.

Potential role of cannabis in ameliorating observed racialized disparities in cancer pain management.

Cancer-related pain affects a large proportion of all patients with cancer yet remains inadequately managed, particularly among patients from certain racialized backgrounds. Recently, there has been increased research and clinical interest in the use of medical cannabis for cancer pain management, including its potential to ameliorate race-based disparities in cancer pain control. Although medical cannabis is not currently a US Food and Drug Administration-approved treatment option for cancer-related pain, many oncologists discuss and recommend its use with their patients, underscoring the need for researchers and clinicians to proactively identify barriers to cannabis for cancer pain management that may disproportionately affect patients from certain racial groups. In this commentary, we highlight challenges that patients from racialized backgrounds may face when incorporating cannabis into their palliative care regimens and discuss opportunities for researchers and clinicians to address these challenges should medical cannabis become a recommended treatment option for cancer pain management. In particular, we identify challenges at the structural (eg, lack of insurance coverage), clinician (eg, racialized stereotypes regarding addiction and pain), and individual (eg, internalized stigma) levels and emphasize the importance of multilevel approaches in combating these challenges as the evidence base regarding medical cannabis and its potential harms and therapeutic benefits continues to accumulate.

Individual and school correlates of body mass index and cardiorespiratory fitness in primary school children from the REACT project: A multivariate multilevel analysis.

This paper examines the relationship between body mass index (BMI) and cardiorespiratory fitness (CRF) using a multivariate multilevel approach and investigates the links between individual and school-related correlates with children's BMI and CRF. This cross-sectional sample included 1014 children (6-10 years) from 25 Portuguese primary schools. BMI was calculated, and CRF was assessed with the PACER test. Fundamental movement skills (FMS) included five object control tasks. Moderate-to-vigorous physical activity (MVPA), sleep, and sedentary time were assessed with the ActiGraph wGT3X-BT accelerometer. Socioeconomic status (SES) and school variables were also obtained. A multivariate multilevel model was used, and alpha was set at 5%. BMI and CRF systematically increased with age. Most of the joint variance (94.4%) was explained at the child level, and BMI and CRF were correlated at this level (ρ = -.37). More active children demonstrated higher CRF levels and had lower BMI levels; sedentary and sleep time were not significantly associated with BMI or CRF. FMS were positively associated with CRF but were not significantly associated with BMI. Children at higher SES were more fit and had lower BMI than their peers of lower SES. Finally, school-level variables were not significantly related to BMI and CRF. BMI and CRF had a low but statistically significant negative correlation in this sample of children. Most of the variation in BMI and CRF was explained by child-level characteristics.

Patterns and predictors of alcohol misuse trajectories from adolescence through early midlife.

We took a multilevel developmental contextual approach and characterized trajectories of alcohol misuse from adolescence through early midlife, examined genetic and environmental contributions to individual differences in those trajectories, and identified adolescent and young adult factors associated with change in alcohol misuse. Data were from two longitudinal population-based studies. FinnTwin16 is a study of Finnish twins assessed at 16, 17, 18, 25, and 35 years (N = 5659; 52% female; 32% monozygotic). The National Longitudinal Study of Adolescent to Adult Health (Add Health) is a study of adolescents from the United States, who were assessed at five time points from 1994 to 2018 (N = 18026; 50% female; 64% White, 21% Black, 4% Native American, 7% Asian, 9% Other race/ethnicity). Alcohol misuse was measured as frequency of intoxication in FinnTwin16 and frequency of binge drinking in Add Health. In both samples, trajectories of alcohol misuse were best described by a quadratic growth curve: Alcohol misuse increased across adolescence, peaked in young adulthood, and declined into early midlife. Individual differences in these trajectories were primarily explained by environmental factors. Several adolescent and young adult correlates were related to the course of alcohol misuse, including other substance use, physical and mental health, and parenthood.

Amygdala functional connectivity in borderline personality disorder

Borderline personality disorder (BPD) is characterised by structural and functional brain alterations. Yet, there is little data on functional connectivity (FC) across different levels of brain networks and parameters. In this study, we applied a multi-level approach to analyse abnormal functional connectivity. We analysed resting-state functional magnetic resonance imaging (fMRI) data sets of 69 subjects: 17 female BPD patients and 51 age-matched psychiatrically healthy female controls. fMRI was analysed using CONN toolbox including: a) seed-based FC analysis of amygdala connectivity, b) independent component analysis (ICA) based network analysis of intra- and inter-network FC of selected resting-state networks (DMN, SN, FPN), as well as c) graph-theory based measures of network-level characteristics. We show group-level seed FC differences with higher amygdala to contralateral (superior) occipital cortex connectivity in BPD, which correlated with schema-therapy derived measures of symptoms/traits across the entire cohort. While there was no significant group effect on DMN, SN, or FPN intra-network or inter-network FC, we show a significant group difference for local efficiency and cluster coefficient for a DMN-linked cerebellum cluster. Our findings demonstrate BPD-linked changes in FC across multiple levels of observation, which supports a multi-level analysis for future studies to consider different aspects of functional connectome alterations.

Superpixel-wise contrast exploration for salient object detection

Salient object detection (SOD) methods typically consider SOD as a pixel-wise binary classification problem and utilize the binary cross-entropy (BCE) loss for optimization. However, the BCE loss ignores the global dependencies between pixels of the entire image, which is important for ensuring the accuracy and integrity of objects. To address this limitation explicitly, contrastive learning is introduced to enhance both the intra-pixel compactness of the foreground and inter-pixel separability between the foreground and background. Unfortunately, the random pixel sampling strategies of existing contrast algorithms cannot ensure that the sampled pixels cover all semantic contents across the entire image because of the lack of fine-grained semantic categories for pixels in SOD. Hence, in this study, a SuperPixel-wise Contrastive (SPCont) algorithm is proposed, which samples all superpixel centers to improve the diversity and representativeness of the sampled pixels. In addition, a SOD-specific hard pixel sampling strategy is designed to refine the edge details of the objects. An intra-image multi-level negative sampling approach is presented to increase the number of negative samples. Extensive experiments are conducted to demonstrate that incorporating the SPCont algorithm into the state-of-the-art network results in significant performance improvements. We expect that our work will open new paths for the application of contrastive learning to SOD.

Communicative practices and perceptions towards stuttering people in South Africa.

A few studies have explored the life experiences of people who stutter. Research has shown that stuttering affects a significant number of people in the population. The study was designed to explore the experiences of people who stutter and the perception of stuttering in South Africa. Four people who identified as South Africans who stutter participated in this study. The primary investigator conducted semi-structured interviews with each of the participants. In addition, a questionnaire was administered to 20 acquaintances of all the participants. Transcriptions of interviews and results of questionnaires were analysed for major and minor themes. Results of this study suggest different perceptions by those who stutter and those acquainted with them. The findings of the study show that people who stutter experience communication barriers, so they adopt certain strategies to manage and cope with their speech disorder. The findings showed that stuttering has a pervasive impact on the lives of people who stutter and how they view themselves, considering negative societal views. Evaluation of the results from the study reveals that although stuttering is a common speech disorder, many people who are less informed about it harbour various stereotypes and myths that stigmatise stuttering. This study concludes by outlining recommendations for creating awareness of stuttering. It suggests vigorous campaigns aiming at promoting a multilevel approach that extends beyond the mere social and professional understanding of stuttering but addresses the inherent perceptions, myths, and stereotypes around stuttering.Contribution:Experiences of people who stutter and perceptions towards stuttering can help to better understand the speech disorder and overcome myths and stereotyping of stuttering.

Multi-Level Hazard Detection Using a UAV-Mounted Multi-Sensor for Levee Inspection

This paper introduces a developed multi-sensor integrated system comprising a thermal infrared camera, an RGB camera, and a LiDAR sensor, mounted on a lightweight unmanned aerial vehicle (UAV). This system is applied to the inspection tasks of levee engineering, enabling the real-time, rapid, all-day, all-round, and non-contact acquisition of multi-source data for levee structures and their surrounding environments. Our aim is to address the inefficiencies, high costs, limited data diversity, and potential safety hazards associated with traditional methods, particularly concerning the structural safety of dam bodies. In the preprocessing stage of multi-source data, techniques such as thermal infrared data enhancement and multi-source data alignment are employed to enhance data quality and consistency. Subsequently, a multi-level approach to detecting and screening suspected risk areas is implemented, facilitating the rapid localization of potential hazard zones and assisting in assessing the urgency of addressing these concerns. The reliability of the developed multi-sensor equipment and the multi-level suspected hazard detection algorithm is validated through on-site levee engineering inspections conducted during flood disasters. The application reliably detects and locates suspected hazards, significantly reducing the time and resource costs associated with levee inspections. Moreover, it mitigates safety risks for personnel engaged in levee inspections. Therefore, this method provides reliable data support and technical services for levee inspection, hazard identification, flood control, and disaster reduction.

The impact of school support for professional development on teachers' adoption of student-centered pedagogy, students’ cognitive learning and abilities: A three-level analysis

Student-centered pedagogy (SCP) is highly considered for its potential to facilitate cognitive learning in Computational Thinking (CT) education. However, there is a noticeable gap in understanding its influence on students' cognitive development from a multilevel perspective. This study delves into cognitive learning theories and aims to bridge the existing gap by introducing a three-level conceptual model to illustrate how the influence of SCP on students' cognitive CT abilities is mediated through the cognitive learning processes. This multilevel approach simultaneously explores SCP within the intricate school environment where factors at the school, teacher, and student levels are closely intertwined. Data was collected from 82 programming teachers and their 2433 students across 43 Hong Kong primary schools. Using multilevel modeling, results indicate that the adoption of SCP is significantly anchored by school support on teacher professional development (TPD), which in turn enhances students’ cognitive learning (i.e., active, interactive, constructive, and reflective learning) in class, further contributing to their enhanced cognitive CT abilities. The findings underscore the nuances of SCP adoption in school scenarios, advocating for strategic approaches to maximize student achievements in CT education. Recommendations for future research are discussed.

Legitimacy spillovers and hybrid rhetoric in crowdfunded microloans

Microfinance institutions (MFIs) operate in diverse institutional contexts and serve as the backbone for microenterprises typically excluded from traditional financial markets. At the same time, MFIs and the microenterprises they support solve tangible social problems, such as alleviating hunger, lifting people out of poverty and creating more sustainable communities. When appealing for resources, MFIs work with microenterprises to create rhetoric that communicates both the financial needs and the social good that supporting them can do. Building on previous research concerning the hybrid rhetoric of microenterprises and the literature rooted in organisational legitimacy, we take a multi-level approach and assess whether country stability and MFI financial performance influence the hybrid rhetoric of microenterprises.

Intersectional discrimination and mental health inequalities: a qualitative study of young women’s experiences in Scotland

BackgroundIn 2021, Scotland became the first UK country to launch a Women’s Health Plan. This policy signals increasing commitment to broader ambitions surrounding gender equality in health. Research shows a connection between discrimination and health, representing a contributor to health inequalities. There remains sparse evidence on how certain groups experience discrimination that could be useful for policymaking. This research set out to address this evidence gap through exploring how discrimination shapes young women’s experiences of mental health and inequalities in Scotland.MethodsWe interviewed women aged 16-25 years (n=28), living in Scotland, UK, adopting an intersectional approach to recruitment and data analysis. We used a semi-structured topic guide to facilitate open discussion about discrimination and health. Transcripts were analysed by two researchers using Thematic Analysis and NVivo software.FindingsWe identified three themes that illuminate intersectional discrimination and the impact on mental health. The first outlines how experiences of discrimination in school, work and public spaces (and the anticipation of such) creates stress leading to mental health problems, particularly for participants from ethnic minority groups. The second highlights the lack of support for mental health, both at structural and interpersonal levels, which was viewed by young women as a form of intersectional discrimination, largely because of their gender and age. Finally, we developed a mid-level theory termed the ‘chain of dismissal’ that displays that for both physical or mental health symptoms, young women’s concerns are immediately “written off” as anxiety-related and in turn a natural attribute of young women. These themes show that discrimination has the potential to amplify mental health problems for young women and is a likely contributor to health inequalities.ConclusionsStructural disadvantages such as racism intersect with gender and age to compound the experience of discrimination for marginalised young women. To improve mental health and reduce health inequalities for young women, multi-level approaches are needed, with strong consideration of how the structural and cultural landscape as well as assumptions made by healthcare professionals have critical implications for young women’s health.

Impact of Perceived and Collective Norms on COVID-19 Preventive Behaviors in 23 Countries: A Multi-Level Approach

ABSTRACT Social norms can be studied at both the individual and societal levels. While the influence of individual perceived norms on health behaviors has been well-documented, the role of societal-level factors in social normative influence remains unclear. We adopted a multilevel approach to investigate the impact of individual-level perceived norms, country-level collective norms, and individualistic culture on mask-wearing behavior during the COVID-19 pandemic. A secondary analysis of cross-sectional data collected from 23 countries (N = 450,223) was conducted. The findings reveal that perceived descriptive norms, perceived injunctive norms, and collective norms conjointly influenced mask-wearing behavior. Positive relationships between perceived descriptive and injunctive norms and mask wearing were stronger in countries with a higher collective norm. Furthermore, positive relationships between norms (i.e., perceived descriptive norms, perceived injunctive norms, and collective norms) and mask wearing were stronger in countries with a more individualistic culture. The study provides evidence for theorizing social normative influence beyond the individual level and underscores the importance of incorporating multilevel factors in social norm research.

Urban water security assessment: investigating inequalities using a multi-scale approach

Abstract Water security is a multi-faceted concept that encompasses dimensions such as water quantity, quality, human health, well-being, water hazards, and governance. The evaluation of water security is an important step towards understanding and improving it, particularly in urban settings where disparities resulting from unequal distribution of population and resources are present and often evade citywide assessments. To address the diversity of the urban space, we propose a multi-level assessment approach based on downscaling the spatial dimension. Using a comprehensive indicator-based framework, we evaluate the city of Campinas in Brazil across citywide and intra-city scales. Employing the Theil index to measure inequality, the results reveal nuanced disparities less apparent at broader scales. Despite an overall favourable water security condition, spatial heterogeneity is still noticeable in the urban area of Campinas. The methodology highlights different aspects, such as vegetation cover, social green areas, and wastewater collection, which are inequitably distributed in the urban area. This integrated approach, linking inequality and water security assessment, has the potential to unveil specific needs within urban areas, helping guide targeted interventions to improve water security levels for all.

Building Organizational Resilience in the Era of Uncertainty: Strategies and Best Practices

This literature review aims to explore strategies and best practices for building organizational resilience in the era of uncertainty. The research synthesizes existing literature to identify key predictors of organizational resilience, including resilient leadership, human capital management strategies, proactive resilience approaches, and cost optimization techniques. The methodology employed in this study involves a systematic literature review using reputable international academic databases over the past five years. Findings reveal that resilient leadership plays a crucial role in fostering organizational resilience by cultivating a resilient culture, enhancing awareness, facilitating learning processes, and strengthening physiological capital. Additionally, human capital management strategies focusing on individual capability development and resilience-building contribute significantly to organizational resilience. Proactive resilience approaches and cost optimization techniques further enhance organizational resilience by enabling quick adaptation and response to unexpected events. This study highlights the importance of adopting a multi-level approach to cost optimization and emphasizes the need for empirical research to validate the effectiveness of different resilience-building strategies. The findings offer practical insights for organizations seeking to enhance their resilience in uncertain environments.