Multidimensional Scaling Research Articles

Specific learning disabilities and associated emotional-motivational profiles: a study in Italian university students.

In this study, we analyzed the emotional and motivational aspects characterizing the profile of university students with Specific Learning Disorders (SLD). We assessed 61 university students, 32 with SLD (age = 23.6) and 29 in the control group (age = 23.00). The results highlighted that individuals with SLD exhibit higher levels of anxiety and depression and lower resilience compared to the control group. The Multidimensional Perfectionism Scale - Short Form, which explores perfectionism, did not reveal differences between the groups. Conversely, lower scores emerged in SLD students for the intrinsic motivation sub-scales of the Academic Motivation Scale. This indicates less engagement in studying out of personal cognitive curiosity. The Self-Regulated Knowledge Scale - University, which measures various cognitive strategies, showed significantly lower scores in the SLD group for knowledge linking, knowledge training, and knowledge critique. This suggests a lower frequency with which SLD students attempt to connect new knowledge with what they already possess, apply their knowledge, ask questions, and critically analyze what they have learned. Therefore, psychological and motivational consequences are evident in this population and can impact well-being and quality of life.

The Imperfect Yet Valuable Difficulties in Emotion Regulation Scale: Factor Structure, Dimensionality, and Possible Cutoff Score.

The Difficulties in Emotion Regulation Scale (DERS) is frequently used to assess emotion regulation (ER) capabilities. Originally a multidimensional scale, many utilize its total score, without clear recommendations. We aimed to explore the DERS's structure, dimensionality, and utility and provide clinicians and researchers with clear guidelines. Self-report data on ER, personality, psychopathology, and life satisfaction were collected from 502 adults. Seventy also participated in a lab study evaluating group interactions, which included additional self-report and physiological monitoring. Findings suggested favoring the correlated-traits and bifactor models, the latter excelling in direct comparisons. The total score was found reliable and valid, explaining 53.3% of the variance, with a distinct emotional awareness subfactor, suggesting a non-pure unidimensional solution. A cutoff score of 95 identified significant ER difficulties, linked to psychopathology. We thus recommend using the DERS's total score and 95 as its cutoff, while calling for further validation in diverse and clinical samples.

Effects of AMF on Maize Yield and Soil Microbial Community in Sandy and Saline Soils.

This study aimed to investigate the effects of applying arbuscular mycorrhizal fungi (AMF) on maize root growth and yield formation under different soil conditions. This study was conducted under sandy soil (S) and saline-alkali soil (Y), with treatments of AMF application (AM) and no AMF application (CK). The root characteristics, yield, and quality of maize were measured. High-throughput sequencing technology was employed to assess the impact of AMF on the soil microbial community structure, and the correlation between soil microbes and soil physicochemical properties was elucidated. The results show that under both sandy and saline-alkali soil conditions, AMF application significantly enhanced maize root growth, yield, grain quality, and soil available nitrogen (AN), available phosphorus (AP), and available potassium (AK) contents compared to the CK treatment. Soil microbial Alpha diversity analysis indicated that AMF application effectively increased soil microbial diversity and richness. Principal coordinate analysis (PCoA) and microbial community structure analysis revealed significant differences in bacterial communities between AM treatment in sandy soil (SAM) and CK in sandy soil (SCK), and significant differences in both bacterial and fungal communities between AM treatment in saline-alkali soil (YAM) and CK in saline-alkali soil (YCK). Furthermore, significant correlations between microbial communities and soil physicochemical properties were found, such as AN, AP, AK, soil salinity (SS), and organic matter (OM) content. AMF application had a greater impact on bacterial communities than on fungal communities. This study demonstrated that the use of AMF as a bio-fungal fertilizer was effective in improving spring maize yields, especially in terms of yield increase and quality stability in sandy and saline soils, thereby contributing to safe and sustainable cropping practices.

How university students view disabled people: The role of wheelchairs, canes, and unspecified mobility aids.

Mobility aids are important to disabled people as a functional tool that can enhance their participation in leisure activities and work; however, mobility aids may also have implications for how disabled people are viewed by others. Using theories from social psychology, this study aimed to understand how mobility aids contribute to the perception of mobility aid users. A total of 259 participants without disabilities, who were primarily young, Caucasian, female-identifying university students, completed the questionnaires. The primary questionnaires of interest included the Multidimensional Attitudes Scale Toward Persons with Disabilities and the Stereotype Content Model. Every participant completed three conditions of the questionnaires to examine their attitudes and stereotypes associated with three mobility aid conditions: a wheelchair, a cane, and a control condition without a specified mobility aid. Affective attitudes toward the unspecified mobility aid condition and the manual wheelchair condition were more negative than the cane condition. Perceived warmth was higher for the manual wheelchair condition compared to the unspecified mobility aid condition and perceived competence was higher for the cane and manual wheelchair conditions compared to the unspecified mobility aid condition. This study explored how young women without disabilities, and potentially nondisabled people more generally, may hold a range of attitudes and stereotypes about the use of mobility aids by disabled people. These findings have implications for the design of effective attitudinal change programs and for rehabilitation professionals who work with individuals as they adopt mobility aids following the onset of disability. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Changes in the Microbiome in Yak Mastitis: Insights Based on Full-Length 16S rRNA Sequencing.

Mastitis is an inflammation of the mammary gland that can be caused by various factors, including biological, chemical, mechanical, or physical. Microbiological culture, DNA techniques, and high-throughput next-generation sequencing have been used to identify mastitis-causing pathogens in various animal species. However, little is known about microbiota and microbiome changes linked to yak milk mastitis. This study aimed to characterize the milk microbiota of healthy and mastitis-infected yaks using full-length 16S rRNA sequencing. The results showed that the bacterial microbiota comprises 7 phyla, 9 classes, 20 orders, 39 families, 59 genera, and 72 species. Proteobacteria and Firmicutes were the predominant microbial communities, with lower abundances of Bacteroidota, Actinobacteriota, Acidobacteriota, and other minor groupings also observed. Proteobacteria dominated the clinical and subclinical mastitis groups (95.36% and 89.32%, respectively), in contrast to the healthy group (60.17%). Conversely, Firmicutes were more common in the healthy group (39.7%) than in the subclinical and clinical mastitis groups (10.49% and 2.92%, respectively). The predominant organisms found in the healthy group were Leuconostoc mesenteroides, Lactococcus piscium, Carnobacterium maltaromaticum, and Lactococcus raffinolactis. Low abundances of Staphylococcus aureus species were found in both subclinical and clinical mastitis groups, with Moraxella osloensis and Psychrobacter cibarius dominating the subclinical mastitis group and Pseudomonas fluorescens dominating the clinical mastitis group. An alpha diversity study revealed that the healthy group had a higher microbial diversity than the clinical and subclinical mastitis groups. According to beta-diversity analysis, the principal coordinate analysis identified that mastitis-infected samples significantly differed from healthy ones. The milk microbiota of healthy yaks is more varied, and specific prominent taxa within various groups can act as marker microorganisms for mastitis risk. The genera Leuconostoc and Lactococcus are promising candidates for creating probiotics.

Pattern recognition in electromechanical impedance spectroscopy damage detection of adhesive joints using multidimensional scaling

Adhesive joints are prone to various types of damage sources, which may not be identifiable with current non-destructive tests (NDTs). Structural health monitoring techniques, such as those based on electromechanical impedance spectroscopy (EMIS), aim to outperform NDTs in damage detection, by continuously monitoring structures. Although the EMIS-based algorithmic performance of damage detection has been evaluated on metallic and composite components, integrity monitoring of adhesive joints is yet to be fully determined. Therefore, this article investigates the use of multidimensional scaling (MDS) to cluster and visualize experimental impedance measurements of bonded joints in a three dimensional space. With these results, an Euclidean distance damage metric is used to try and classify the type of damage. The results show that damage detection is easily performed with the MDS algorithm, but effectiveness is dependent on the spectral measurement conditions. Furthermore, reduced dimensional spaces can yield information regarding the size and location of the damage in the adhesive layer, yielding increased knowledge on the integrity of structural adhesive joints.

Assessment of Mental Health Comorbidities and Relief Factors in Moroccan Women during the Third Trimester of Pregnancy: A Cross-Sectional Study.

During pregnancy, women can experience mental alterations, particularly anxiety and depression, which mark an important transition period in their lives. Social support appears to be a crucial alleviating factor for these disorders. The aim of this study is to assess the extent of psychological disturbances and their relieving factors by investigating correlations between mental status and different sociodemographic and clinical characteristics during the third trimester of pregnancy. A cross-sectional study including 160 pregnant women in their last trimester was carried out in Morocco, notably at the Ibn Sina University Hospital and in two health centers. A pre-structured questionnaire, including sociodemographic and clinical variables and internationally recognized scales such as the Multidimensional Scale of Perceived Social Support (MSPSS), the Perceived Stress Scale (PSS), the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Bergen Insomnia Scale (BIS), and the Hospital Anxiety and Depression Scale (HADS), was mobilized. The prevalence of depression and anxiety was 18.75% and 12.5%, respectively. A correlation between these two mental disorders and the level of education, pregnancy planning, monthly income, and provision of health coverage was found (p-value < 0.05). The main determinants of anxiety were stress (p-value = 0.047) and social support (p-value < 0.001), while depression was limited to social support (p-value < 0.001) and sleep quality (p-value = 0.015). It is essential to take action against these disorders and their predictive factors by raising awareness and implementing a diagnosis and care protocol with healthcare professionals to guide and orient distressed women.

Neural correlates of phonetic categorization under auditory (phoneme) and visual (grapheme) modalities.

We tested whether the neural mechanisms of phonetic categorization are specific to speech sounds or generalize to graphemes (i.e., visual letters) of the same phonetic label. Given that linguistic experience shapes categorical processing, and letter-speech sound matching plays a crucial role during early reading acquisition, we hypothesized sound phoneme and visual grapheme tokens representing the same linguistic identity might recruit common neural substrates, despite originating from different sensory modalities. Behavioral and neuroelectric brain responses (ERPs) were acquired as participants categorized stimuli from sound (phoneme) and homologous letter (grapheme) continua each spanning a /da/ - /ga/ gradient. Behaviorally, listeners were faster and showed stronger categorization of phoneme compared to graphemes. At the neural level, multidimensional scaling of the EEG revealed responses self-organized in a categorial fashion such that tokens clustered within their respective modality beginning ∼150-250 ms after stimulus onset. Source-resolved ERPs further revealed modality-specific and overlapping brain regions supporting phonetic categorization. Left inferior frontal gyrus and auditory cortex showed stronger responses for sound category members compared to phonetically ambiguous tokens, whereas early visual cortices paralleled this categorical organization for graphemes. Auditory and visual categorization also recruited common visual association areas in extrastriate cortex but in opposite hemispheres (auditory = left; visual=right). Our findings reveal both auditory and visual sensory cortex supports categorical organization for phonetic labels within their respective modalities. However, a partial overlap in phoneme and grapheme processing among occipital brain areas implies the presence of an isomorphic, domain-general mapping for phonetic categories in dorsal visual system.

Identifying and Prioritizing Factors to Improve Implementation of an Evidence-Based Program for Child Maltreatment Prevention in Rural Missouri Communities

AbstractPrevention of child abuse and maltreatment is critical in the Ozark region of Missouri where rates are higher than in other areas of the state. Community-based organizations seeking to address these issues in rural areas face significant challenges both internal and external to the organization. Guided by the Consolidated Framework for Implementation Research (CFIR), Whole Kids Outreach (WKO) utilized a modified concept mapping approach to identify strategies needed to address these challenges and more effectively implement the Healthy Families America (HFA) program in seven counties in the rural Missouri Ozark region. Semi-structured interviews were used to identify barriers and supports to the implementation of HFA. Statements were generated via in-person and telephone interviews with key stakeholders (WKO internal staff and external partners). These stakeholders then sorted statements into like piles and rated them according to importance. Concept mapping systems software, using multidimensional scaling and hierarchical cluster analysis, was used to determine the most salient cluster solution. The resulting cluster map depicted six thematic clusters and provided a visual representation of relationships between clusters. Stakeholders were then guided through a nominal group process to prioritize key issues and begin to develop strategies to address them.

The multiple mediating effects of self-efficacy and resilience on the relationship between social support and procrastination among vocational college students: a cross-sectional study

BackgroundPrevious research has revealed a negative association between social support and procrastination. However, few studies have investigated the mechanism underlying this relationship among vocational college students.ObjectiveBased on the social cognitive theory, this study was intended to investigate the multiple mediating effects of self-efficacy and resilience on the relationship between social support and procrastination among vocational college students.MethodsThis study employed a cross-sectional design involving a sample of 1,379 students from a vocational college in China. Data were collected using the General Procrastination Scale, the Multidimensional Scale of Perceived Social Support, the General Self-Efficacy Scale, and the Resilience Scale-14. The PROCESS macro for SPSS was used to examine the multiple mediation model.ResultsOur findings indicate significant negative correlations between social support, self-efficacy, resilience, and procrastination. The multiple mediation analysis showed that social support did not have a significant direct impact on procrastination. Instead, the relationship between social support and procrastination was fully mediated by self-efficacy (indirect effect: -0.017; 95% CI: -0.032, -0.004) and resilience (indirect effect: -0.047; 95% CI: -0.072, -0.025), and sequentially mediated by both factors (indirect effect: -0.013; 95% CI: -0.020, -0.007).ConclusionsThe results emphasise the importance of enhancing self-efficacy and resilience in initiatives aimed at preventing and intervening in case of procrastination among vocational college students. Additionally, strengthening social support may also be crucial to preventing or reducing procrastination among this population.

Illness uncertainty, resilience, and perceived social support among patients with moyamoya disease: a cross-sectional study.

The present study aims to investigate the levels of illness uncertainty in patients with moyamoya disease and to determine the association of socio-demographic characteristics, perceived social support and resilience with illness uncertainty in patients with moyamoya disease. A cross-sectional survey using convenience sampling was conducted in two hospitals in China from August to December 2023.A socio-demographic characteristics questionnaire, the Chinese versions of Mishel's Unsurety in Disease Scale (MUIS), the Chinese version of Connor-Davidson Resilience Scale (CD-RISC), and the Chinese version of Multidimensional Scale of Perceived Social Support (MSPSS) were used to perform this research. The collected data were analyzed using SPSS 24.0 statistical software. The t-test, one-way analysis of variance (ANOVA), pearson correlation analysis and hierarchical regression analysis were used to identify associated factors. A total of 263 patients with moyamoya disease were recruited in this survey. The score of illness uncertainty was at a moderate level of (100.03 ± 18.59). The present study identified a negative correlation between illness uncertainty with resilience perceived social support. Hierarchical regression analysis showed that gender, occupation, education level, resilience and perceived social support were the related factors of illness uncertainty. Patients with moyamoya disease experienced moderate disease uncertainty on average, which was related to gender, occupation, education level, resilience and perceived social support. Future research is needed to better explore the complex relationships between illness uncertainty, resilience, and perceived social support with different types of moyamoya disease using longitudinal research.

The Association Between Proneness to Smartphone Addiction and Social Anxiety Among School Students and the Mediating Role of Social Support: A Call to Advance Jordanian Adolescents' Mental Health.

Social anxiety is an emerging public health issue associated with significant impairment of social functioning during adolescence. Among many determinants of social anxiety, proneness to smartphone addiction may significantly contribute to the development of social anxiety. To cope with the consequential development of social anxiety, adolescent school students may rely on various forms of social support. Particularly in the Middle East, including Jordan, the relationship between proneness to smartphone addiction and adolescent social anxiety is understudied. To examine the mediating role of social support in the relationship between proneness to smartphone addiction and social anxiety in a sample of adolescent school students. In this cross-sectional study, 432 adolescents were recruited via a random cluster sample from public schools across three provinces in Jordan. The data were collected face-to-face using the Social Anxiety Scale for Adolescents, the Smartphone Addiction Proneness Scale, and the Multidimensional Scale of Perceived Social Support. Significantly higher levels of social anxiety were associated with females of lower economic status who reported more gaming hours and higher levels of proneness to smartphone addiction. Familial social support significantly mediated the relationship between proneness to smartphone addiction and social anxiety, controlling for the other covariates in the social anxiety model. Familial social support reduced the impact of proneness to smartphone addiction on social anxiety. Nurses may supplement treatment for reducing social anxiety in adolescents suffering from proneness to smartphone addiction by fostering sources of familial social support.

Factors Related to Quality of Life among People Living with HIV in Indonesia: A Cross-Sectional Study

People living with HIV (PLWH) have a complex problem with their disease including stigma and psychological problems. This research focused on measuring level of self-esteem, perceived human immunodeficiency virus (HIV) stigma, social support, and quality of live (QOL) among PLWH in Surabaya, Indonesia. Comparing part of social support which were by family and by friends would be explained. Our study used a cross-sectional correlation design. Variable self-esteem was measured using State Self-Esteem Scale by Heatherton and perceived HIV stigma by The Berger Scale, the social support was the multidimensional scale of social support by Zimet and WHOQOL-HIV instrument was by WHO. Univariate analyses and multiple regression analyses examine between predictors. The existence of moderate level of perceived HIV stigma was observed (mean: 95.67). There were significantly positive relationships between self-esteem and QOL (p &lt; .01; r = .642); social support and QOL (p &lt; .01; r = .592). In contrast, perceived HIV stigma showed a negative correlation with QOL (p &lt; .05; r = -.222). In self-esteem (p &lt; .01), social support by family (p &lt; .01), and that by friends (p &lt; .01) were shown to be significant predictors of higher QOL level. Self-esteem and support by family and friends were considered possible promoting factor of QOL of PLWH.

A novel hybrid efficiency prediction model for pumping well system based on MDS–SSA–GNN

AbstractThe prediction of the efficiency of oil well pumping systems plays an important role in optimizing the energy efficiency parameters of these systems. Currently, the prediction of oil well pumping system efficiency relies primarily on mechanistic models, but these models are often overly complex in predicting efficiency. Some researchers have attempted to use deep learning to predict system efficiency, but due to insufficient consideration of influencing factors and the causal relationships between these factors and system efficiency, they often include irrelevant variables as influencing factors, leading to less accurate prediction models. In this paper, a hybrid model (MDS–SSA–GNN) is proposed for the prediction of pumping well system efficiency. The model consists of six parts: Pearson's product moment correlation coefficient (PPMCC), multidimensional scaling (MDS) transform, maximum–minimum normalization, sparrow optimization algorithm (SSA), graph neural network (GNN), and maximum–minimum inverse normalization. First, the size of the correlation coefficient between each influencing factor and the system efficiency is quantitatively calculated by using PPMCC. Second, the main influencing factors are downscaled by using MDS and normalized based on the principle of maximum–minimum normalization. Third, the GNN algorithm is used for the prediction of the pumping unit system efficiency, and the SSA algorithm is used for the optimization of the initial values of the network parameters. Finally, the prediction results are obtained by the maximum–minimum antinormalization. To validate the model's accuracy, this study randomly selected 100 actual oil wells for comparative analysis and analyzed the impact of structural parameters of the hybrid algorithm on the prediction accuracy of system efficiency. The analysis results demonstrate that the proposed model can effectively predict system efficiency and has a certain role in improving the accuracy of oil well pumping system efficiency predictions.

Rapid Initialization Method of Unmanned Aerial Vehicle Swarm Based on VIO-UWB in Satellite Denial Environment

In environments where satellite signals are blocked, initializing UAV swarms quickly is a technical challenge, especially indoors or in areas with weak satellite signals, making it difficult to establish the relative position of the swarm. Two common methods for initialization are using the camera for joint SLAM initialization, which increases communication burden due to image feature point analysis, and obtaining a rough positional relationship using prior information through a device such as a magnetic compass, which lacks accuracy. In recent years, visual–inertial odometry (VIO) technology has significantly progressed, providing new solutions. With improved computing power and enhanced VIO accuracy, it is now possible to establish the relative position relationship through the movement of drones. This paper proposes a two-stage robust initialization method for swarms of more than four UAVs, suitable for larger-scale satellite denial scenarios. Firstly, the paper analyzes the Cramér–Rao lower bound (CRLB) problem and the moving configuration problem of the cluster to determine the optimal anchor node for the algorithm. Subsequently, a strategy is used to screen anchor nodes that are close to the lower bound of CRLB, and an optimization problem is constructed to solve the position relationship between anchor nodes through the relative motion and ranging relationship between UAVs. This optimization problem includes quadratic constraints as well as linear constraints and is a quadratically constrained quadratic programming problem (QCQP) with high robustness and high precision. After addressing the anchor node problem, this paper simplifies and improves a fast swarm cooperative positioning algorithm, which is faster than the traditional multidimensional scaling (MDS) algorithm. The results of theoretical simulations and actual UAV tests demonstrate that the proposed algorithm is advanced, superior, and effectively solves the UAV swarm initialization problem under the condition of a satellite signal rejection.

Cultural divergence and morphological variation of isolated remnant populations of the endangered Floreana mockingbird

Context Cultural divergence refers to changes over time in behavioural traits. These cultural changes could have important implications for conservation planning, and impact the success of conservation efforts such as translocations. Aims Here, we investigate the extent, and potential impacts, of cultural divergence in two isolated populations of the Floreana mockingbird (Mimus trifasciatus) on the Galápagos Islands. Methods Using contemporary recordings of vocalisations we test for spatial vocal differentiation between mockingbird populations. Furthermore, we explore the potential drivers of change using morphological measurements and historical recordings of the species. Key results We found evidence of spatial and temporal differentiation in vocalisations between the two populations of the Floreana mockingbird. We accurately classified over 75% of the birds to the correct populations based on multivariate measures of audio recordings using canonical analysis of principal coordinates (CAP). We also found significant differences in morphometrics between populations; specifically, beak depth was associated with frequency modulation, an acoustic measure that is significantly different between populations. Furthermore, we found evidence of change in the complexity of the vocalisations over a period of 57 years. Conclusions Cultural divergence was found in the two remaining populations of this endangered species. Factors such as changes in morphology and cultural drift might have been influenced the change in vocalisation across time and populations. Implications We highlight the importance of considering behavioural factors when planning reintroductions of endangered species where there is a need to minimise the risk of assortative mating so as to maximise genetic diversity.

Phytoplankton Diversity, Spatial Patterns, and Photosynthetic Characteristics Under Environmental Gradients and Anthropogenic Influence in the Pearl River Estuary.

The Pearl River Estuary (PRE) is one of the world's most urbanized subtropical coastal systems. It presents a typical environmental gradient suitable for studying estuarine phytoplankton communities' dynamics and photosynthetic physiology. In September 2018, the maximum photochemical quantum yield (Fv/Fm) of phytoplankton in different salinity habitats of PRE (oceanic, estuarine, and freshwater zones) was studied, revealing a complex correlation with the environment. Fv/Fm of phytoplankton ranged from 0.16 to 0.45, with taxa in the upper Lingdingyang found to be more stressed. Community composition and structure were analyzed using 18S rRNA, accompanied by a pigment analysis utilized as a supplementary method. Nonmetric multidimensional scaling analysis indicated differences in the phytoplankton spatial distribution along the estuarine gradients. Specificity-occupancy plots identified different specialist taxa for each salinity habitat. Dinophyta and Haptophyta were the predominant taxa in oceanic areas, while Chlorophyta and Cryptophyta dominated freshwater. Bacillariophyta prevailed across all salinity gradients. Canonical correlation analysis and Mantel tests revealed that temperature, salinity, and elevated nutrient levels (i.e., NO3--N, PO43--P, and SiO32--Si) associated with anthropogenic activities significantly influenced the heterogeneity of community structure. The spatial distribution of phytoplankton, along with in situ photosynthetic characteristics, serves as a foundational basis to access estuarine primary productivity, as well as community function and ecosystem health.

Developing and Validating a Perceived Digital Customer Value Scale in Restaurants

ABSTRACT Customers are switching to being “digital customers” when interacting with restaurants more digitally than traditionally. Therefore, the current study aims to create a multidimensional scale for measuring perceived digital customer value derived from ordering and payment functionalities in restaurants. Seven stages were taken in the development of the scale; the first was qualitative for item generation, and the other steps were quantitative for empirically establishing the scale’s psychometric qualities. Four hundred twenty-five customers filled out the questionnaires from two different types of restaurants (i.e. fast-food and casual dining restaurants) in Cairo, Egypt. This study found five dimensions of the perceived digital customer value scale: price, hedonic, experiential, transient, and service quality. This measurement helps restaurants comprehend digital customer behavior and change customer preferences and interactions in a digitalized environment. Accordingly, the study extends customer value theory and previous models within the hospitality industry, addresses gaps in the literature, and improves understanding of customer value in digital transformation. The developed multidimensional scale helps restaurant management understand their digital customers’ preferences and deliver value that meets their desires in a digital transformation.

Confirmatory Factor Analysis of the Structure of the Social Support Scale (MOSS - SSS)

The research question was to examine the factor structure of the Multidimensional Scale of Perceived Social Support (MOSS - SSS). This scale was constructed to provide a brief, multidimensional self-assessment instrument for social support. Social support is defined as the interaction between individuals that aims to exchange resources that enable feelings of control over a situation, competence, self-esteem, and a sense of belonging. Additionally, social support represents a resource whose contribution is crucial for positive coping with stressors and psychophysical well-being. The goal of this study was to investigate whether the assumed four-factor model, confirmed in previous studies, that explored the factor structure of the MOSS - SSS scale, fits the model obtained in a sample of 397 participants from the general population of Bosnia and Herzegovina. Confirmatory factor analysis was used to assess the model's adequacy. The results showed that all fit indices (X2/df = 4 RMSEA = 0.087, CFI = .925, NFI = .902, TLI = .912) were within the recommended criteria. Additionally, the Cronbach's α coefficient was .94, indicating good scale reliability. Based on the fit index values, it is possible to conclude that the four-factor model of MOSS - SSS corresponds to the theoretically assumed four-factor structure.

Compositional Data and Microbiota Analysis: Imagination and Reality.

The relationships among bacterial flora, diseases, and diet have been described by many authors. An operational taxonomic units (OTUs) are the result of clustering the 16S rRNA gene sequences at a certain cutoff value, and they are considered compositional data. As Pearson's correlation coefficient is difficult to interpret, Aitchison's ratio analysis was used to develop a method to handle compositional data. Multivariate analysis was developed because univariate analysis can be subject to large biases. Simulations regarding absolute abundance based on certain assumptions and some analyses, such as nonparametric multidimensional scaling (NMDS), principal component analysis (PCA), and ratio analysis, were conducted in this study. The same content as a 100% stacked bar graph could be expressed in low dimensions using PCA. However, the relative diversity was not reproducible with NMDS. Various assumptions were made regarding absolute abundance based on the relative abundance. However, which assumptions are true could not be determined. In summary, ratio analysis and PCA are useful for analyzing compositional data and the gut microbiota.