Gender-related variables for health research
TL;DR: A gender assessment tool for use in clinical and population research, including large-scale health surveys involving diverse Western populations, and an important step toward developing more comprehensive and precise survey-based measures of gender in relation to health are developed.
Abstract: In this paper, we argue for Gender as a Sociocultural Variable (GASV) as a complement to Sex as a Biological Variable (SABV). Sex (biology) and gender (sociocultural behaviors and attitudes) interact to influence health and disease processes across the lifespan—which is currently playing out in the COVID-19 pandemic. This study develops a gender assessment tool—the Stanford Gender-Related Variables for Health Research—for use in clinical and population research, including large-scale health surveys involving diverse Western populations. While analyzing sex as a biological variable is widely mandated, gender as a sociocultural variable is not, largely because the field lacks quantitative tools for analyzing the influence of gender on health outcomes. We conducted a comprehensive review of English-language measures of gender from 1975 to 2015 to identify variables across three domains: gender norms, gender-related traits, and gender relations. This yielded 11 variables tested with 44 items in three US cross-sectional survey populations: two internet-based (N = 2051; N = 2135) and a patient-research registry (N = 489), conducted between May 2017 and January 2018. Exploratory and confirmatory factor analyses reduced 11 constructs to 7 gender-related variables: caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination. Regression analyses, adjusted for age, ethnicity, income, education, sex assigned at birth, and self-reported gender identity, identified associations between these gender-related variables and self-rated general health, physical and mental health, and health-risk behaviors. Our new instrument represents an important step toward developing more comprehensive and precise survey-based measures of gender in relation to health. Our questionnaire is designed to shed light on how specific gender-related behaviors and attitudes contribute to health and disease processes, irrespective of—or in addition to—biological sex and self-reported gender identity. Use of these gender-related variables in experimental studies, such as clinical trials, may also help us understand if gender factors play an important role as treatment-effect modifiers and would thus need to be further considered in treatment decision-making.
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TL;DR: In this article, a large cohort of healthcare workers participating in the Italian vaccination campaign against SARS-CoV-2 has been studied to establish the impact of sex and gender on vaccination coverage using the Gender Impact Assessment approach.
43 citations
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TL;DR: In this article, the authors review the use of both carrots and sticks (requirements) developed to motivate researchers and the entire scientific research enterprise to consider sex and gender influences on health and in science.
Abstract: To improve the outcomes of research and medicine, government-based international research funding agencies have implemented various types of policies and mechanisms with respect to sex as a biological variable and gender as a sociocultural factor. After the 1990s, the US National Institutes of Health (NIH), the Canadian Institute for Health Research (CIHR), and the European Commission (EC) began 1) requesting that applicants address sex and gender considerations in grant proposals and 2) offering resources to help the scientific community integrate sex and gender into biomedical research. Although, it is too early to analyze data on the success of all of the policies and mechanisms implemented, here we review the use of both carrots (incentives) and sticks (requirements) developed to motivate researchers and the entire scientific research enterprise to consider sex and gender influences on health and in science. The NIH focused on sex as a biological variable (SABV) aligned with an initiative to enhance reproducibility through rigor and transparency; CIHR instituted a sex- and gender-based analysis (SGBA) policy; and the EC required the integration of the "gender dimension", which incorporates sex, gender, and intersectional analysis into research and innovation. Other global efforts are briefly summarized. Although we are still learning what works, we share lessons learned to improve the integration of sex and gender considerations into research. In conjunction with refining and expanding the policies of funding agencies and mechanisms, private funders/philanthropic groups, editors of peer-reviewed journals, academic institutions, professional organizations, ethics boards, healthcare systems, and industry also need to make concerted efforts to integrate sex and gender into research, and we all must bridge across silos to promote system-wide solutions throughout the biomedical enterprise. For example, policies that encourage researchers to disaggregate data by sex and gender, the development of tools to better measure gender effects, or policies similar to SABV and/or SGBA adopted by private funders would accelerate progress. Uptake, accountability for, and a critical appraisal of sex and gender throughout the biomedical enterprise will be crucial to achieving the goal of relevant, reproducible, replicable, and responsible science that will lead to better evidence-based personalized care for all, but especially for women.
40 citations
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TL;DR: In this paper, the authors describe prominent authorship positions held by women and the overall percentage of women co-authoring manuscripts submitted during the covid-19 pandemic compared with the previous two years.
Abstract: Objective To describe prominent authorship positions held by women and the overall percentage of women co-authoring manuscripts submitted during the covid-19 pandemic compared with the previous two years. Design Cross sectional study. Setting Nine specialist and two large general medical journals. Population Authors of research manuscripts submitted between 1 January 2018 and 31 May 2021. Main outcome measures Primary outcome: first author’s gender. Secondary outcomes: last and corresponding authors’ gender; number (percentage) of women on authorship byline in “pre-pandemic” period (1 January 2018 to 31 December 2019) and in “covid-19” and “non-covid-19” manuscripts during pandemic. Results A total of 63 259 manuscripts were included. The number of female first, last, and corresponding authors respectively were 1313 (37.1%), 996 (27.9%), and 1119 (31.1%) for covid-19 manuscripts (lowest values in Jan-May 2020: 230 (29.4%), 165 (21.1%), and 185 (22.9%)), compared with 8583 (44.9%), 6118 (31.2%), and 7273 (37.3%) for pandemic non-covid-19 manuscripts and 12 724 (46.0%), 8923 (31.4%), and 10 981 (38.9%) for pre-pandemic manuscripts. The adjusted odds ratio of having a female first author in covid-19 manuscripts was Conclusions Women have been underrepresented as co-authors and in prominent authorship positions in covid-19 research, and this gender disparity needs to be corrected by those involved in academic promotion and awarding of research grants. Women attained some prominent authorship positions equally or more frequently than before the pandemic on non-covid-19 related manuscripts submitted at some time points during the pandemic.
24 citations
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TL;DR: This article sets out these areas and argues for more precise operationalization of sex- and gender-related factors in health research and policy initiatives in order to advance these varied agendas in mutually supportive ways.
Abstract: Including sex and gender considerations in health research is considered essential by many funders and is very useful for policy makers, program developers, clinicians, consumers and other end users. While longstanding confusions and conflations of terminology in the sex and gender field are well documented, newer conceptual confusions and conflations continue to emerge. Contemporary social demands for improved health and equity, as well as increased interest in precision healthcare and medicine, have made obvious the need for sex and gender science, sex and gender-based analyses (SGBA+), considerations of intersectionality, and equity, diversity and inclusion initiatives (EDI) to broaden representation among participants and diversify research agendas. But without a shared and precise understanding of these conceptual areas, fields of study, and approaches and their inter-relationships, more conflation and confusion can occur. This article sets out these areas and argues for more precise operationalization of sex- and gender-related factors in health research and policy initiatives in order to advance these varied agendas in mutually supportive ways.
18 citations
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TL;DR: In this article, a multidimensional sex/gender concept was developed as a theoretically grounded starting point for the operationalization of sex and gender in quantitative (environmental) health research.
Abstract: There is a growing awareness about the need to comprehensively integrate sex and gender into health research in order to enhance the validity and significance of research results. An in-depth consideration of differential exposures and vulnerability is lacking, especially within environmental risk assessment. Thus, the interdisciplinary team of the collaborative research project INGER (integrating gender into environmental health research) aimed to develop a multidimensional sex/gender concept as a theoretically grounded starting point for the operationalization of sex and gender in quantitative (environmental) health research. The iterative development process was based on gender theoretical and health science approaches and was inspired by previously published concepts or models of sex- and gender-related dimensions. The INGER sex/gender concept fulfills the four theoretically established prerequisites for comprehensively investigating sex and gender aspects in population health research: multidimensionality, variety, embodiment, and intersectionality. The theoretical foundation of INGER’s multidimensional sex/gender concept will be laid out, as well as recent sex/gender conceptualization developments in health sciences. In conclusion, by building upon the latest state of research of several disciplines, the conceptual framework will significantly contribute to integrating gender theoretical concepts into (environmental) health research, improving the validity of research and, thus, supporting the promotion of health equity in the long term.
18 citations
References
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TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...
76,383 citations
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TL;DR: In this article, structural equation models with latent variables are defined, critiqued, and illustrated, and an overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence.
Abstract: Criteria for evaluating structural equation models with latent variables are defined, critiqued, and illustrated. An overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence. Model assessment is considered to be a complex process mixing statistical criteria with philosophical, historical, and theoretical elements. Inevitably the process entails some attempt at a reconcilation between so-called objective and subjective norms.
19,160 citations
"Gender-related variables for health..." refers methods in this paper
...ρ was computed using James Gaskin’s “Validity master tool” [76], and following conventional criteria [77], we considered values > 0....
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TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
Abstract: Factor analysis, path analysis, structural equation modeling, and related multivariate statistical methods are based on maximum likelihood or generalized least squares estimation developed for covariance structure models. Large-sample theory provides a chi-square goodness-of-fit test for comparing a model against a general alternative model based on correlated variables. This model comparison is insufficient for model evaluation: In large samples virtually any model tends to be rejected as inadequate, and in small samples various competing models, if evaluated, might be equally acceptable. A general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models. Use of the null model in the context of a procedure that sequentially evaluates the statistical necessity of various sets of parameters places statistical methods in covariance structure analysis into a more complete framework. The concepts of ideal models and pseudo chi-square tests are introduced, and their roles in hypothesis testing are developed. The importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models is also emphasized. Normed and nonnormed fit indices are developed and illustrated.
16,420 citations
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TL;DR: In this paper, the authors examined the change in the goodness-of-fit index (GFI) when cross-group constraints are imposed on a measurement model and found that the change was independent of both model complexity and sample size.
Abstract: Measurement invariance is usually tested using Multigroup Confirmatory Factor Analysis, which examines the change in the goodness-of-fit index (GFI) when cross-group constraints are imposed on a measurement model. Although many studies have examined the properties of GFI as indicators of overall model fit for single-group data, there have been none to date that examine how GFIs change when between-group constraints are added to a measurement model. The lack of a consensus about what constitutes significant GFI differences places limits on measurement invariance testing. We examine 20 GFIs based on the minimum fit function. A simulation under the two-group situation was used to examine changes in the GFIs (ΔGFIs) when invariance constraints were added. Based on the results, we recommend using Δcomparative fit index, ΔGamma hat, and ΔMcDonald's Noncentrality Index to evaluate measurement invariance. These three ΔGFIs are independent of both model complexity and sample size, and are not correlated with the o...
10,597 citations
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26 Apr 1990TL;DR: In this article, a strategy for redesigning jobs to reduce unnecessary stress and improve productivity and job satisfaction is proposed, which is based on the concept of job redesigning and re-designing.
Abstract: Suggests a strategy for redesigning jobs to reduce unnecessary stress and improve productivity and job satisfaction.
8,329 citations
"Gender-related variables for health..." refers methods in this paper
...The first four items were adapted from Karasek and Theorell [55]; the last two were developed by the authors....
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Trending Questions (2)
What are the variables used in this research?
The variables used in this research are caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination.
How many esg related variables?
The paper does not mention any ESG (Environmental, Social, and Governance) related variables. The paper is about gender-related variables for health research.