A deeper consideration of sex/gender in quantitative health research: a checklist for incorporating multidimensionality, variety, embodiment, and intersectionality throughout the whole research process.

BACKGROUND: There is a growing awareness of the need to adequately integrate sex and gender into health-related research. Although it is widely known that the entangled dimensions sex/gender are not comprehensively considered in most studies to date, current publications of conceptual considerations and guidelines often only give recommendations for certain stages of the research process and - to the best of our knowledge - there is a lack of a detailed guidance that accompanies each step of the entire research process. The interdisciplinary project "Integrating gender into environmental health research" (INGER) aimed to fill this gap by developing a comprehensive checklist that encourages sex/gender transformative research at all stages of the research process of quantitative health research. In the long term this contributes to a more sex/gender-equitable research. METHODS: The checklist builds on current guidelines on sex/gender in health-related research. Starting from important key documents, publications from disciplines involved in INGER were collected. Furthermore, we used a snowball method to include further relevant titles. The identification of relevant publications was continued until saturation was reached. 55 relevant publications published between 2000 and 2021 were identified, assessed, summarised and included in the developed checklist. After noticing that most publications did not cover every step of the research process and often considered sex/gender in a binary way, the recommendations were modified and enriched based on the authors' expertise to cover every research step and to add further categories to the binary sex/gender categories. RESULTS: The checklist comprises 67 items in 15 sections for integrating sex/gender in quantitative health-related research and addresses aspects of the whole research process of planning, implementing and analysing quantitative health studies as well as aspects of appropriate language, communication of results to the scientific community and the public, and research team composition. CONCLUSION: The developed comprehensive checklist goes beyond a binary consideration of sex/gender and thus enables sex/gender-transformative research. Although the project INGER focused on environmental health research, no aspects that were specific to this research area were identified in the checklist. The resulting comprehensive checklist can therefore be used in different quantitative health-related research fields.

Who pays for clean air, and why?: Analyzing the impact of resource, planned behavior, and government/policy factors on the multidimensional willingness to pay for reducing the particulate matter.

This study aimed to explore the determinants of willingness to pay for fine particulate matter reduction. Previous studies were mostly based on simple causal models, with few or similar predictors affecting a single dimension of willingness to pay. This study adopted a multidimensional model, dividing willingness to pay into three categories: cost burden, benefit to the community and benefit to specific groups. The independent variables were resources, planned behavior, and government/policy factors, with a total of 12 variables. The analysis showed that, first, the determinant structure varied across the dimensions of willingness to pay. Second, facility resources, information, personal norms, social norms, perceived control, trust in government, policy satisfaction, policy preference, and policy knowledge had significant positive effects on willingness to pay. Third, policy satisfaction and social norms had high explanatory power for willingness to pay for cost burden; policy preference and personal norms for benefit to community; and policy knowledge, policy preference, and perceived control for benefit to specific groups.

Development of a PROMIS multidimensional cancer-related fatigue (mCRF) form using modern psychometric techniques.

PURPOSE: To develop a PRO assessment of multidimensional cancer-related fatigue based on the PROMIS fatigue assessments. METHOD: Cancer patients reporting fatigue were recruited from a comprehensive cancer care center and completed a survey including 39 items from the PROMIS Cancer Item Bank-Fatigue. Component and factor structures of the fatigue items were explored with Monte Carlo parallel factor and Mokken analyses, respectively. Psychometric properties were determined using item response theory, ensuring unidimensionality, scalability, and item independence. RESULTS: Fatigue scores from a sample of 333 fatigued cancer patients (mean age = 59.50, SD = 11.62, 67% women) were used in all scale development analyses. Psychometric analyses yielded 3 dimensions: motivational fatigue (15 items), cognitive fatigue (9 items), and physical fatigue (9 items). The subscales showed strong unidimensionality, were scalable, and were free of differential item function. Confirmatory factor analyses in a new sample of 182 patients confirmed the findings. CONCLUSION: The resulting 33-item PROMIS multidimensional cancer-related fatigue (mCRF) form provides a novel measure for the assessment of the different dimensions of cancer-related fatigue. It is the only multidimensional scale specific for cancer patients that has been developed using modern psychometric approaches. With its 3 dimensions (motivational, cognitive, and physical fatigue), this scale accurately captures the fatigue experienced by cancer patients, allowing clinicians to optimize fatigue management and improve patient care. The scale could also advance research on the nature and experience of cancer-related fatigue.

[DIVERGesTOOL-development of a toolbox for the assessment of sex/gender diversity]. / DIVERGesTOOL ­ Entwicklung einer Toolbox zur Erfassung geschlechtlicher Vielfalt in der quantitativen Gesundheitsforschung.

In health research, there is a need for comprehensive survey instruments capable of assessing the multidimensionality and variability of sex/gender. The research project DIVERGesTOOL was conducted in response to this need, which has become increasingly evident in recent years. The aim was to develop an application-oriented toolbox for the assessment of sex/gender diversity in quantitative health-related research in Germany.The development process followed a participatory design, as representatives of large epidemiological studies in Germany were directly involved. During four collaborative workshops, a toolbox was developed that contains several different elements. The basic items are a generally usable set of three different questionnaire items based on the two-step approach. They are recommended as a replacement for the binary sex or gender item that are currently routinely used in health-related research. In addition, the toolbox contains further exemplary questionnaire items for specific research questions or study populations. The developed items were supplemented with detailed instructions for their application and additional information. The toolbox is an open online resource accessible to any user ( https://www.uni-bremen.de/divergestool-projekt/divergestool-toolbox ).In the long term, the DIVERGesTOOL is intended to support researchers in integrating sex/gender diversity into their own research and thus to contribute to more sex/gender sensitivity in health-related research and valid findings.

A general pattern of plant traits and their relationships with environmental factors and microbial life-history strategies.

The trait-based unidimensional plant economics spectrum provides a valuable framework for understanding plant adaptation strategies to the environment. However, it is still uncertain whether there is a general multidimensionality of how variation of both leaf and fine root traits are influenced by environmental factors, and how these relate to microbial resource strategies. Here, we examined the coordination patterns of four pairs of similar leaf and fine root traits of herbaceous plants in an alpine meadow at the community-level, and their environmental driving patterns. We then assessed their correlation with microbial life-history strategies, as these exhibit analogous resource strategies with plants in terms of growth and resource utilization efficiency. Results exhibited an analogous multidimensionality of the economics spectrum for leaf and fine root traits: the first dimension, collaboration gradient, primarily represented a tradeoff between lifespan and resource foraging efficiency; the second dimension, conservation gradient, primarily represented a tradeoff between conservation and acquisition in resource uptake. Climate variables had a stronger impact on both dimensions for leaf and fine root traits than soil variables did; whereas, the primary drivers were more complex for fine root traits than for leaf traits. The collaboration gradient of leaf and fine root traits exhibited consistent relationships with soil microbial life-history strategies, both showed negative and positive correlation with bacterial and fungal strategies, respectively. Our findings suggest that both leaves and fine roots have general multidimensional strategies for adapting to new environments and provide a solid basis for further understanding the relationships between the adaptive strategies of plants and microbes.

What Affects the Quality of Score Transformations? Potential Issues in True-Score Equating Using the Partial Credit Model.

This simulation study investigated to what extent departures from construct similarity as well as differences in the difficulty and targeting of scales impact the score transformation when scales are equated by means of concurrent calibration using the partial credit model with a common person design. Practical implications of the simulation results are discussed with a focus on scale equating in health-related research settings. The study simulated data for two scales, varying the number of items and the sample sizes. The factor correlation between scales was used to operationalize construct similarity. Targeting of the scales was operationalized through increasing departure from equal difficulty and by varying the dispersion of the item and person parameters in each scale. The results show that low similarity between scales goes along with lower transformation precision. In cases with equal levels of similarity, precision improves in settings where the range of the item parameters is encompassing the person parameters range. With decreasing similarity, score transformation precision benefits more from good targeting. Difficulty shifts up to two logits somewhat increased the estimation bias but without affecting the transformation precision. The observed robustness against difficulty shifts supports the advantage of applying a true-score equating methods over identity equating, which was used as a naive baseline method for comparison. Finally, larger sample size did not improve the transformation precision in this study, longer scales improved only marginally the quality of the equating. The insights from the simulation study are used in a real-data example.

"It is for God to judge"1: Understanding Why and When Islamic Religiosity Inhibits Homotolerance.

In Western Europe, Muslims' cultural attitudes take center stage in debates in media and politics. In these debates, the claim that Muslims' religious interpretations cause them to be intolerant of homosexual people is often repeated. While previous public opinion studies have time and again shown that Muslims are indeed on average more homonegative than other people, the present study theoretically explores and empirically tests whether those differences are because of Islamic religiosity. This assumption is often made but has yet to be empirically addressed. Using unique data on young Muslim adults in the Netherlands and more direct measurements of religious interpretations on homosexuality, we find that Islamic religiosity as such hardly fuels intolerance of homosexual people. In fact, our results show that even believing that Islam forbids homosexuality does not necessarily fuel Muslims' intolerance of homosexual people. Rather, what is pivotal, is whether such beliefs are coupled with a willingness to judge, rather than leaving judgment to Allah. We conclude that only among young adult Dutch Muslims who believe it is up to them to judge homosexuality, do homonegative interpretations of Islam feed into intolerance of homosexual people.

Consensus Paper: Current Perspectives on Abstract Concepts and Future Research Directions.

concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition.

Basic Income in Belgium survey: experimental data on citizens' attitudes toward a variety of basic income policies.

This article presents the BAsic income in BELgium (BABEL) dataset on public opinion on the introduction of a universal basic income (UBI) in Belgium, collected through an online panel among a sample of 3000 respondents in spring 2021. The BABEL survey implements an innovative vignette experiment in which both the policy design (i.e., the benefit level, the universality) and the potential policy outcomes (i.e., effect on poverty, unemployment) of a UBI are set to vary randomly. This full factorial experimental design is appropriate to analyze the complex of process of opinion formation about a UBI which entails multiple considerations. Accordingly, the data enables researchers to assess the net effect of the different design characteristics and hypothetical outcomes, as well as the trade-offs people are (not) willing to make to support basic income. Additionally, the survey includes items about benefit recipiency, COVID-19, demographic characteristics, general welfare attitudes, behavioral intentions, and political opinion. These data are thus appropriate for examining which design or outcome factors are relevant in shaping support for a UBI as well as extensive subgroup analysis.

The unique contribution of handwriting accuracy to literacy skills in Japanese adolescents.

There is widespread concern about declining literacy skills in recent young Japanese. The present study investigated how higher-level reading and writing proficiencies are underpinned by basic literacy skills in Japanese adolescents. From a large database of the most popular literacy exams in Japan, we retrospectively analyzed word- and text-level data for middle and high school students who had taken the exams during the same period in the 2019 academic year using structural equation modeling. We extracted main data for 161 students as well as six independent datasets for validation. Our results validated the three-dimensional view of word-level literacy (reading accuracy, writing accuracy, and semantic comprehension) and demonstrated that writing and semantic skills underpinned text writing and reading, respectively. The semantic comprehension of words affected text writing indirectly via text reading; however, it could not replace the direct effect of word writing accuracy. These findings, which were robustly replicated with multiple independent datasets, provided new evidence of dimension-specific relationships between word- and text-level literacy skills and confirmed the unique contribution of word handwriting acquisition to text literacy proficiency. The replacement of handwriting by digital writing (e.g., typing) is a global trend. However, the dual-pathway model of literacy development identified in this study suggests there are advantages in sustaining early literacy education by handwriting for the growth of higher-level language skills in future generations. Supplementary Information: The online version contains supplementary material available at 10.1007/s11145-023-10433-3.

Why and how to use the quality of life as an evaluation criterion?

Within the EU policies, quality of life as a criterion has been rarely used in evaluations. The concept of quality of life is vague and multidimensional. The unclear and ambiguity of the definition of what is included in the concept of quality of life makes it challenging to compare different studies with each other. The multidimensionality with pre-defined criteria makes sense when comparing the quality of life internationally or among regions. In case of improvement in quality of life, also criteria of local stakeholders need to be taken into account. Most published papers on quality of life evaluations are from health studies. The reason for such dominance lies in the importance of health conditions for the perception of the quality of life. The concept is, though, exploited in many other disciplines with various meanings. Beyond health conditions, many other factors influence the quality of life, including economic, social, work, or psychological ones. Another challenge concerns measuring the quality of life from objective and subjective perspectives. Objective factors like investment in civil infrastructure could sometimes be perceived differently across the population. Health, psychological, and social circumstances also influence the perception of quality of life. Moreover, the application of the same subjective indicator at different time points provides different information even if the same respondents participate in data collection. We can answer only partially the two questions used in the name of this contribution on why and how to use the quality of life as an evaluation criterion. It is because of the subjectivity of the understanding of the concept and multidimensionality of measuring it according to the needs of a particular evaluation.

Exploring and Deepening the Facets of Mentalizing: The Integration of Network and Factorial Analysis Approaches to Verify the Psychometric Properties of the Multidimensional Mentalizing Questionnaire (MMQ).

Mentalization is a complex and multifaceted trans-theoretical and trans-diagnostic construct that has found increasing application in the clinical context. This research aimed at deepening the psychometric properties of the Multidimensional Mentalizing Questionnaire (MMQ), a 33-item theoretically based self-report questionnaire allowing for a comprehensive assessment of mentalizing, by integrating factor analysis and network analysis approaches. A sample of 1640 participants (Mage = 33 years; SD = 13.28) was involved in the research. The six-factor structure was confirmed for the MMQ, and both the total and the subdimensions demonstrated good reliability. The network analysis has further enriched these results, showing the central role of the items attributable to Emotional Dysregulation or Reflexivity in influencing the network as well as the contribution of aspects related to Relational Discomfort in managing the flow of communication flow. Such findings may have useful clinical implications and emphasize the usefulness of the MMQ in both research and clinical practice.

Resolving Dimensionality in a Child Assessment Tool: An Application of the Multilevel Bifactor Model.

Multidimensionality and hierarchical data structure are common in assessment data. These design features, if not accounted for, can threaten the validity of the results and inferences generated from factor analysis, a method frequently employed to assess test dimensionality. In this article, we describe and demonstrate the application of the multilevel bifactor model to address these features in examining test dimensionality. The tool for this exposition is the Child Observation Record Advantage 1.5 (COR-Adv1.5), a child assessment instrument widely used in Head Start programs. Previous studies on this assessment tool reported highly correlated factors and did not account for the nesting of children in classrooms. Results from this study show how the flexibility of the multilevel bifactor model, together with useful model-based statistics, can be harnessed to judge the dimensionality of a test instrument and inform the interpretability of the associated factor scores.

The Dimensional Structure of the Gambling Attitudes and Beliefs Survey: Challenging the Assumption of the Unidimensionality of Gambling-Specific Cognitive Distortions.

The aim of the present study was to examine the dimensional structure of the Gambling Attitudes and Beliefs Survey (GABS). The GABS was administered to a sample of 415 individuals with self-reported problem or pathological gambling who were taking part in two different treatment studies preregistered with the German Clinical Trials Register (DRKS00013888) and ClinicalTrials.gov (NCT03372226). Exploratory factor analyses revealed a three-factor structure. We labeled the factors sensation seeking/illusion of control, luck/gambler's fallacy, and attitude/emotions. Subsequent confirmatory factor analyses proved the three-factor model superior to the one-factor model proposed by the developers of the GABS. All dimensions were significantly correlated with symptom severity scores. Group comparisons showed significantly higher factor scores on the first factor (sensation seeking/illusion of control) for individuals reporting both skill-based and chance-based gambling compared to those reporting only chance-based gambling. The present study questions the unidimensionality of the GABS. A multidimensional assessment of gambling-related cognitive biases, beliefs, and positively valued attitudes may be useful in determining treatment outcomes and goals and in the development of novel interventions.

Soil water content and nitrogen differentially correlate with multidimensional leaf traits of two temperate broadleaf species.

The variation and correlation of leaf economics and vein traits are crucial for predicting plant ecological strategies under different environmental changes. However, correlations between these two suites of traits and abiotic factors such as soil water and nitrogen content remain ambiguous. We measured leaf economics and vein traits as well as soil water and nitrogen content for two different shade-tolerant species (Betula platyphylla and Acer mono) in four mixed broadleaved-Korean pine (Pinus koraiensis) forests along a latitudinal gradient in Northeast China. We found that leaf economics traits and vein traits were decoupled in shade-intolerant species, Betula platphylla, but significantly coupled in a shade-tolerant species, A. mono. We found stronger correlations among leaf traits in the shade tolerant species than in the shade intolerant species. Furthermore, leaf economic traits were positively correlated with the soil water gradient for both species, whereas vein traits were positively correlated with soil water gradient for the shade intolerant species but negatively correlated in the shade tolerant species. Although economic traits were positively correlated with soil nitrogen gradient in shade intolerant species but not correlated in shade tolerant species, vein traits were negatively correlated with soil nitrogen gradient in shade tolerant species but not correlated in shade intolerant species. Our study provides evidence for distinct correlations between leaf economics and vein traits and local abiotic factors of species differing in light demands. We recommend that the ecological significance of shade tolerance be considered for species when evaluating ecosystem functions and predicting plant responses to environmental changes.

Bifactor exploratory structural equation modeling: A meta-analytic review of model fit.

Multivariate behavioral research often focuses on latent constructs-such as motivation, self-concept, or wellbeing-that cannot be directly observed. Typically, these latent constructs are measured with items in standardized instruments. To test the factorial structure and multidimensionality of latent constructs in educational and psychological research, Morin et al. (2016a) proposed bifactor exploratory structural equation modeling (B-ESEM). This meta-analytic review (158 studies, k = 308, N = 778,624) aimed to estimate the extent to which B-ESEM model fit differs from other model representations, including confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), hierarchical CFA, hierarchical ESEM, and bifactor-CFA. The study domains included learning and instruction, motivation and emotion, self and identity, depression and wellbeing, and interpersonal relations. The meta-analyzed fit indices were the χ2 /df ratio, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean squared residual (SRMR). The findings of this meta-analytic review indicate that the B-ESEM model fit is superior to the fit of reference models. Furthermore, the results suggest that model fit is sensitive to sample size, item number, and the number of specific and general factors in a model.

Chromatographic-Based Platforms as New Avenues for Scientific Progress and Sustainability.

Chromatography was born approximately one century ago and has undergone outstanding technological improvements in innovation, research, and development since then that has made it fundamental to advances in knowledge at different levels, with a relevant impact on the well-being and health of individuals. Chromatography boosted a comprehensive and deeper understanding of the complexity and diversity of human-environment interactions and systems, how these interactions affect our life, and the several societal challenges we are currently facing, namely those related to the sustainability of our planet and the future generations. From the life sciences, which allowed us to identify endogenous metabolites relevant to disease mechanisms, to the OMICS field, nanotechnology, clinical and forensic analysis, drug discovery, environment, and "foodprint", among others, the wide range of applications of today's chromatographic techniques is impressive. This is fueled by a great variability of powerful chromatographic instruments currently available, with very high sensitivity, resolution, and identification capacity, that provide a strong basis for an analytical platform able to support the challenging demands of the postgenomic and post COVID-19 eras. Within this context, this review aims to address the great utility of chromatography in helping to cope with several societal-based challenges, such as the characterization of disease and/or physiological status, and the response to current agri-food industry challenges of food safety and sustainability, or the monitoring of environmental contamination. These are increasingly important challenges considering the climate changes, the tons of food waste produced every day, and the exponential growth of the human population. In this context, the principles governing the separation mechanisms in chromatography as well the different types and chromatographic techniques will be described. In addition, the major achievements and the most important technological advances will be also highlighted. Finally, a set of studies was selected in order to evince the importance of different chromatographic analyses to understand processes or create fundamental information in the response to current societal challenges.

Multidimensional soil salinity data mining and evaluation from different satellites.

Soil salinization, a common land degradation mode, restricts the ecological environment and is a global issue due to climate change. Accurately, quickly and effectively monitoring soil salinity is critical for governmental institutions that develop hazard prevention and mitigation strategies. Remote sensing (RS) technology provides a viable alternative to traditional field work due to its large area coverage, abundant spectral information and nearly constant observations. Key issues in RS-based soil salinity monitoring include the lack of both data-mining techniques for obtaining spectral band information and comprehensive considerations of synergies among different spectra. The main objective of this study was to provide in-depth explorations of data mining and integration algorithms from different satellites to multidimensionally evaluate soil salinity models. The Ebinur Lake Wetland Reserve (Xinjiang Province, China) was selected as a case study. First, ground-measured visible and near infrared (VIS-NIR) spectral data were combined with the RS band to simulate Landsat 8 (L8) and Sentinel 2 (S2) and 3 (S3) data. Second, one-dimensional RS bands and 15 soil salinity and vegetation indices were selected, and 15 spectral data transformations (reciprocal, differential, absorbance, etc.) were obtained. Two- and three-dimensional spectral indices were constructed, and the response relationships between different spectral indices and soil electrical conductivity (EC) were comprehensively explored. Finally, an integrated multidimensional algorithm was used to estimate soil salinity in high-performance models for the three satellites. The results showed that all data-mining-based model combinations performed well for all satellites (R2 > 0.80). However, with multidimensional model combinations, S3 presented the highest predictive capability (R2 = 0.89, RMSE = 2.57 mS·cm-1, RPD = 2.05), followed by S2 (R2 = 0.86, RMSE = 2.71 mS·cm-1, RPD = 1.90) and L8 (R2 = 0.85, RMSE = 2.84 mS·cm-1, RPD = 1.87). Therefore, data mining with integration algorithms in model combinations performs significantly better than previous models and could be considered a promising method for obtaining improved results from soil salinity susceptibility models in similar cases.

Treatments of Differential Item Functioning: A Comparison of Four Methods.

Test fairness is critical to the validity of group comparisons involving gender, ethnicities, culture, or treatment conditions. Detection of differential item functioning (DIF) is one component of efforts to ensure test fairness. The current study compared four treatments for items that have been identified as showing DIF: deleting, ignoring, multiple-group modeling, and modeling DIF as a secondary dimension. Results of this study provide indications about which approach could be applied for items showing DIF for a wide range of testing environments requiring reliable treatment.

Rotate and Project: Measurement of the Intended Concept with Unidimensional Item Response Theory from Multidimensional Ordinal Items.

What to do when item response data are multidimensional but a unidimensional model is preferred in terms of statistical simplicity and ease of interpretability? The projection method for the compensatory logistic multidimensional item response model for dichotomous data leads to a two parameter logistic model with local item dependence. Despite the local item dependence, the model is unidimensional for many practical purposes. Here, Ip's projection method is generalized to the case of the graded response model for polytomous variables, extending the applicability of the method to Likert-type response formats. A secondary aim of the paper is the study of rotation techniques intended for use prior to projection. In contrast to rotations aiming at a simple structure of factor loadings, the proposed techniques increase the variance explained before or after projection, facilitate the interpretation of the projected dimension by variants of target rotations or a mix of both. The method is illustrated with an application to the Highly Sensitive Person Scale and R code is provided.