Dataset Information

Gender Differences in Individual Dishonesty Profiles.

ABSTRACT: Dishonesty has an enormous impact on all aspects of our society. It causes huge financial losses annually, so efforts to understand dishonest behavior have increased. However, one of the main questions yet to be answered is whether dishonesty varies according to gender. Do men behave more dishonestly than women? Although the literature points to a yes, there is still no consensus on the matter. We examined gender differences in dishonesty in a large sample (N = 2,452) using a model recently developed by Pascual-Ezama et al. It is a variation of the classic die-under-the-cup task. It enabled us to identify individual dishonesty profiles and look for gender differences between them. The results show that the men were more prone to behave dishonestly than women with small rewards, who seem satisfied without maximizing the potential reward. However, the differences vanished when there was no reward. The men also showed more radical dishonest behavior than the women. The results also suggest that gender differences might be shaped by factors other than gender.

SUBMITTER: Munoz Garcia A

PROVIDER: S-EPMC8703141 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Gender Differences in Individual Dishonesty Profiles.

Muñoz García Adrián A Gil-Gómez de Liaño Beatriz B Pascual-Ezama David D

Frontiers in psychology 20211210

Dishonesty has an enormous impact on all aspects of our society. It causes huge financial losses annually, so efforts to understand dishonest behavior have increased. However, one of the main questions yet to be answered is whether dishonesty varies according to gender. Do men behave more dishonestly than women? Although the literature points to a yes, there is still no consensus on the matter. We examined gender differences in dishonesty in a large sample (<i>N</i> = 2,452) using a model recent ...[more]

PMID: 34955957

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Project description:BACKGROUND: Cardiovascular disease (CVD) incidence, complications and burden differ markedly between women and men. Although there is variation in the distribution of lifestyle factors between the genders, they do not fully explain the differences in CVD incidence and suggest the existence of gender-specific genetic risk factors. We aimed to estimate whether the genetic risk profiles of coronary heart disease (CHD), ischemic stroke and the composite end-point of CVD differ between the genders. METHODOLOGY/PRINCIPAL FINDINGS: We studied in two Finnish population cohorts, using the case-cohort design the association between common variation in 46 candidate genes and CHD, ischemic stroke, CVD, and CVD-related quantitative risk factors. We analyzed men and women jointly and also conducted genotype-gender interaction analysis. Several allelic variants conferred disease risk for men and women jointly, including rs1801020 in coagulation factor XII (HR = 1.31 (1.08-1.60) for CVD, uncorrected p = 0.006 multiplicative model). Variant rs11673407 in the fucosyltransferase 3 gene was strongly associated with waist/hip ratio (uncorrected p = 0.00005) in joint analysis. In interaction analysis we found statistical evidence of variant-gender interaction conferring risk of CHD and CVD: rs3742264 in the carboxypeptidase B2 gene, p(interaction) = 0.009 for CHD, and rs2774279 in the upstream stimulatory factor 1 gene, p(interaction) = 0.007 for CHD and CVD, showed strong association in women but not in men, while rs2069840 in interleukin 6 gene, p(interaction) = 0.004 for CVD, showed strong association in men but not in women (uncorrected p-values). Also, two variants in the selenoprotein S gene conferred risk for ischemic stroke in women, p(interaction) = 0.003 and 0.007. Importantly, we identified a larger number of gender-specific effects for women than for men. CONCLUSIONS/SIGNIFICANCE: A false discovery rate analysis suggests that we may expect half of the reported findings for combined gender analysis to be true positives, while at least third of the reported genotype-gender interaction results are true positives. The asymmetry in positive findings between the genders could imply that genetic risk loci for CVD are more readily detectable in women, while for men they are more confounded by environmental/lifestyle risk factors. The possible differences in genetic risk profiles between the genders should be addressed in more detail in genetic studies of CVD, and more focus on female CVD risk is also warranted in genome-wide association studies.

Project description:PurposeThere are discrepancies in mental health treatment outcomes between ethnic groups, which may differ between genders. NHS Talking Therapies for anxiety and depression provide evidence-based psychological therapies for common mental disorders. This study examines the intersection between ethnicity and gender as factors associated with psychological treatment outcomes. Aims were to explore by gender: (1) differences in psychological treatment outcomes for minoritized ethnic people compared to White-British people, (2) whether differences are observed when controlling for clinical and socio-demographic factors associated with outcomes, and (3) whether organization-level factors moderate differences in outcomes between ethnic groups.MethodsPatient data from eight NHS Talking Therapies for anxiety and depression services (n = 98,063) was used to explore associations between ethnicity and outcomes, using logistic regression. Stratified subsamples were used to separately explore factors associated with outcomes for males and females.ResultsIn adjusted analyses, Asian (OR = 0.82 [95% CI 0.78; 0.87], p < .001, 'Other' (OR = 0.79 [95%CI 0.72-0.87], p < .001) and White-other (0.93 [95%CI 0.89-0.97], p < .001) ethnic groups were less likely to reliably recover than White-British people. Asian (OR = 1.48 [95% CI 1.35-1.62], p < .001), Mixed (OR = 1.18 [95% CI 1.05-1.34], p = .008), 'Other' (OR = 1.60 [95% CI 1.38-1.84], p < .001) and White-other (OR = 1.18 [95% CI 1.09-1.28], p < .001) groups were more likely to experience a reliable deterioration in symptoms. Poorer outcomes for these groups were consistent across genders. There was some evidence of interactions between ethnic groups and organization-level factors impacting outcomes, but findings were limited.ConclusionsAcross genders, Asian, 'Other' and White-other groups experienced worse treatment outcomes across several measures in adjusted models. Reducing waiting times or offering more treatment sessions might lead to increased engagement and reduced drop-out for some patient groups.

Dataset Information

Gender Differences in Individual Dishonesty Profiles.

Publications

Gender Differences in Individual Dishonesty Profiles.

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