Scholar Commons - Institutional Repository of the University of South Carolina
Not a member yet
34867 research outputs found
Sort by
From Victimization to Offense: A Scoping Review of Attachment Theory and Social Learning Theory in Explaining Hypersexual Behaviors in Male Sexual Offenders with Histories of Childhood Sexual Abuse
Full text linkThe association between childhood sexual abuse (CSA) and hypersexual behaviors in both juvenile and adult male sexual offenders has been investigated; however, a clear theoretical framework explaining this connection remains debated. This review aims to evaluate which theoretical frameworks—such as Social Learning Theory and Attachment Theory—best explain the link between CSA and hypersexuality in male sexual offenders. A systematic search and analysis of existing literature was conducted, including studies on the psychological, behavioral, and developmental impacts of CSA on hypersexual behaviors. Both Social Learning Theory and Attachment Theory were critically assessed, particularly focusing on the pathways from victimization to offending behavior and the links between hypersexuality, recidivism, and mental health outcomes in male sexual offenders. The findings suggest that while multiple frameworks offer insights, Attachment Theory provides a robust explanation of how childhood victimization leads to the internalization of deviant sexual behaviors and impaired interpersonal relationships in young adulthood. In contrast, Social Learning Theory emphasizes the role of modeled behaviors and environmental reinforcements in shaping these deviant sexual behaviors. CSA is shown to be a significant factor in both hypersexual behaviors and sexual offending, with traumatic experiences shaping long-term behavioral patterns. This review highlights the importance of adopting an integrated theoretical framework to better explain the complex relationship between CSA and sexual offending behaviors
A Reliable and Efficient Detection Pipeline for Rodent Ultrasonic Vocalizations
Full text linkAnalyzing ultrasonic vocalizations (USVs) is crucial for understanding rodents\u27 affective states and social behaviors, but the manual analysis is time-consuming and prone to errors. Automated USV detection systems have been developed to address these challenges. Yet, these systems often rely on machine learning and fail to generalize effectively to new datasets. To tackle these shortcomings, we introduce ContourUSV, an efficient automated system for detecting USVs from audio recordings. Our pipeline includes spectrogram generation, cleaning, pre-processing, contour detection, post-processing, and evaluation against manual annotations. To ensure robustness and reliability, we compared ContourUSV with three state-of-the-art systems using an existing open-access USV dataset (USVSEG) and a second dataset we are releasing publicly along with this paper. On average, across the two datasets, ContourUSV outperformed the other three systems with a 1.51× improvement in precision, 1.17× in recall, 1.80× in F1 score, and 1.49× in specificity while achieving an average speedup of 117.07×
The Federal Trade Commission, Germany, and Non-Compete Agreements: An Analysis of the Federal Trade Commission\u27s Proposed Ban on Non-Compete Agreements and a Comparison to German Non-Compete Law
No full textScaling Laws of Political Regime Dynamics: Stability of Democracies and Autocracies in the Twentieth Century
No full textIn light of the current rise of authoritarian regimes and the anti-liberal tendencies in some established democracies, understanding the dynamic and statistical properties of political regimes is of critical importance. Despite their relevance, a comprehensive quantitative assessment of these dynamics on a historical scale remains largely unexplored, and the notion that democratization is an irreversible process has gone mostly unchallenged. This study provides a rigorous and quantitative analysis of political regimes worldwide by examining changes in freedoms of expression, association and electoral quality throughout the twentieth century. Utilizing the multidimensional V-Dem dataset, which covers over 170 countries across more than a century, alongside tools from statistical physics, we demonstrate that historical political regime dynamics follow a scaling law, which is a hallmark of diffusion. We identify three distinct dynamical regimes in the data: super-diffusive behaviour in destabilizing autocracies, random-walk dynamics in hybrid regimes and sub-diffusive behaviour in democracies and stable autocracies. Using these results, we also offer a novel perspective on the propensity of civil conflict
Exploring Socio-Psychological Drivers and Pathways of Sustainable Fashion Consumption
No full textThis study explores social and psychological factors influencing the intention to purchase sustainable fashion products. Integrating self-congruity theory, self-completion theory, and Theory of Planned Behaviour, this study proposed a dual-path model of socio-psychological variables essential for shaping consumer attitudes towards sustainable consumption and subsequent purchase intention. Additionally, the moderating role of sustainable brand awareness in the link between attitude and intention and the effect of affordability on purchase intentions were tested. Data were collected from 278 US fashion consumers through an online survey, and PLS-SEM was used for the analyses. Results show that self-identity drives self-expressive benefits, while environmental awareness positively influences environmental concern and consumer attitudes towards sustainable fashion consumption. Additionally, subjective norms and affordability are strong predictors of purchase intentions. Furthermore, the moderating effect of sustainable brand awareness in the attitude-intention relationship is statistically significant. These findings expand our understanding of fashion consumers\u27 intention to purchase sustainable products and offer valuable guidance for businesses seeking to effectively communicate their sustainable efforts, strengthen branding and boost potential sales
Investing in the Development of the Next Generation of MCH Leaders
No full textThe public health landscape is constantly evolving to address the strengths and needs of the community. Training for the public health workforce is leading the way, establishing an ecosystem approach that integrates individuals within social, political, and environmental contexts to promote health equity within a framework of social justice. One area of public health that is innovatively preparing the next generation of leaders is maternal and child health (MCH). In the United States, key indicators of health disparities within MCH remain stagnant, highlighting the need for training programs that develop future MCH professionals from diverse backgrounds. These professionals will deliver culturally and linguistically appropriate services for an increasingly underserved and underrepresented population, both in the US and around the world. The MCH Leadership, Education, and Advancement in Undergraduate Pathways (LEAP) training program provides coordinated opportunities for undergraduate students, faculty, agencies, organizations, and communities to work together for developing the future MCH public health workforce. Effective and respectful leadership development in MCH requires investment in fundamental educational, research, and community-engaged practice-based skill sets cultivated in undergraduate programs. Currently, six funded programs in the MCH LEAP portfolio share a collective mission to train undergraduates who have historically had a minimal presence to become MCH leaders of tomorrow. These programs also make changes to organizational structures that reflect the geographic and demographic representation of their communities. Mixed-methods evaluations, encompassing both qualitative and quantitative approaches, illustrate the MCH LEAP training program’s effectiveness in introducing and developing the competencies for the next generation of the MCH workforce
Writing Loss, Culture and Change: Deindustrialisation and Community Writers’ Groups In Glasgow
No full textCharacterising the Relationship Between Body Mass Index and Lung Cancer Using Causal Inference Methods
No full textBackground: Lung cancer is the leading cause of cancer-related deaths in the U.S. Simultaneously, the U.S. is grappling with a growing obesity epidemic, a major risk factor for several cancers and metabolic disorders, including diabetes mellitus, which is associated with an increased risk of cancer in various organs. However, research on the relationship between body mass index (BMI) and lung cancer has generated conflicting results. Studies using measured BMI (either objectively measured or self-reported) suggest that lower BMI is inversely associated with lung cancer risk. In contrast some of the more recent Mendelian randomization (MR) studies, which use genetically proxied BMI, suggest increased BMI may be associated with increased lung cancer risk. However, MR studies face uncertainties due to potential pleiotropic effects, and lack of strong correlation with measured BMI. No previous systematic reviews and meta-analyses on this topic have included MR studies. Further, due to lingering concerns that uncontrolled confounding may explain the inverse association observed between measured BMI and lung cancer makes it important to investigate the association between BMI and lung cancer using marginal structural models (MSMs) and causal mediation analysis, because these methods specifically address this issue. Aims: The aims of this study were: (1) to conduct a systematic review and meta-analysis on the association between BMI and lung cancer risk; (2) to determine the association between BMI and lung cancer risk analyzing data from a prospective cohort study using causal inference methods (MSMs) and compare with the results generated analyzing the data using the more routinely used Cox-proportional Hazards (Cox-PH) model; and (3) in the same cohort study to examine the direct and indirect effects of smoking on lung cancer, with BMI as a mediator, and the direct and indirect effects of BMI on lung cancer, with diabetes mellitus as a mediator. Methods: For Aim 1, a systematic review and meta-analysis synthesized the available evidence on the association between BMI and lung cancer risk, including studies that used measured/self-reported BMI and studies that used genetically proxied BMI (MR studies). We searched PUBMED, CINAHL, Embase, and Web of Science for cohort and nested case-control studies published until August 31, 2024. Two independent reviewers screened articles for eligibility, conducted data extraction and quality assessments for included papers, and resolved discrepancies through discussion. Meta-analyses using random-effects models estimated pooled relative risks (RRs) and odds ratios (ORs) with 95% confidence intervals (CIs). Dose-response analyses evaluated the relationship between increasing BMI and lung cancer risk, and E-values were calculated to assess the potential influence of unmeasured confounding. Aim 2 was a prospective cohort study using data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. The study population was comprised of 120,863 participants aged 55-74 years, who were recruited and followed-up from1993-2009. The data were analyzed to examine the association between BMI and lung cancer risk using causal inference methods (MSMs) and compared with results from Cox-PH models. BMI was measured at baseline and earlier life stages (ages 20 and 50), and BMI trajectories were also evaluated. Participants\u27 self-reported smoking history, demographic factors, family history of lung cancer, and lifestyle behaviors were collected. Both MSMs and Cox-PH models with inverse probability of treatment and censoring weights accounted for time-varying confounders. Covariates included sex, education, race, occupation, comorbidities, cigarette smoking, dietary intake, and physical activity. Sensitivity analyses excluded participants with short follow-ups and included diabetes as an additional covariate. Aim 3 was also a prospective cohort study using data from the PLCO Cancer Screening Trial. We performed causal mediation analysis to investigate the direct and indirect effects of smoking on lung cancer with BMI as a mediator, and the effects of BMI on lung cancer mediated by diabetes mellitus. Analyses was focused on baseline smoking status, with BMI and diabetes mellitus as mediators. Lung cancer incidence was the primary outcome. Cox-PH models were used to calculate hazard ratios (HRs) with 95% CIs for direct and indirect effects. The CAUSALMED procedure in SAS (version 9.4) estimated natural direct and indirect effects, adjusting for potential confounders such as sex, education, occupation, family history of lung cancer, second-hand smoke exposure, and physical activity. Results: Aim 1: A total of 45 studies (40 studies that measured BMI or used self-reported BMI and 5 MR studies) met the inclusion criteria. Meta-analysis of studies with measured/self-reported BMI (n=40) indicated that each 1 kg/m² increase in BMI was associated with a 4% reduction in lung cancer risk (RR: 0.96; 95% CI: 0.95–0.97). Higher BMI (overweight and obesity) was inversely associated with lung cancer risk (RR: 0.79; 95% CI: 0.74–0.83), while underweight individuals had a significantly higher risk (RR: 1.43; 95% CI: 1.25–1.64). Overall dose-response analyses revealed a non-linear inverse association between BMI and lung cancer. E-values suggested that strong unmeasured confounding would be required to nullify the observed associations between measured/self-reported BMI and lung cancer. MR studies (n=5) showed a non-significant increase in lung cancer risk with each 1 kg/m² increase in genetically predicted BMI (OR: 1.05; 95% CI: 0.99–1.12). Aim 2: Baseline BMI was inversely associated with lung cancer risk across both MSMs and Cox-PH models. Among the never smokers, overweight and obese individuals had lower lung cancer risk compared to normal-weight never smokers. Among the current and former smokers, within all the smoking strata lung cancer risk decreased with increasing BMI, with the MSM model showing consistently stronger inverse HRs compared to the Cox-PH model. While the Cox-PH model suggested uncertainty with wide confidence intervals, the MSM highlighted a clearer trend with greater statistical precision, particularly among current smokers, with lung cancer risk decreasing as BMI increased. These findings remained consistent when considering BMI at ages 20 and 50. Sensitivity analyses excluding the first year and the first five years of follow-up, as well as including diabetes as a covariate, did not significantly change the results. Aim 3: Among 142,245 participants, current smokers with more than 45 years of smoking history had a 32-fold higher lung cancer risk compared to never smokers (HR: 32.08; 95% CI: 27.42–36.74). The controlled direct effect was slightly lower (HR: 30.30; 95% CI: 25.84–34.75). The natural indirect effect of BMI was positive among current smokers, particularly those with longer smoking histories, indicating a modest increase in lung cancer risk mediated by BMI. In contrast, former smokers had an inverse or null indirect effect. For BMI and lung cancer, an inverse association was observed, with each 1 kg/m² increase in BMI linked to a 2% decrease in lung cancer risk (HR: 0.98; 95% CI: 0.96–0.99). The mediation effect of diabetes mellitus on this association was not statistically significant (HR: 1.000; 95% CI: 0.999–1.003). Conclusion: This research program offers insights into the controversial relationship between BMI and lung cancer risk. Aim 1, the systematic review and meta-analysis, provides strong, consistent evidence from studies using measured or self-reported BMI that higher BMI is inversely associated with lung cancer risk. In contrast, MR studies did not show a significant association between BMI and lung cancer, though the summary OR was in the direction of increased risk. Aim 2, an analysis within the PLCO cohort using MSMs, further confirmed an inverse association between BMI and lung cancer risk. In Aim 3, causal mediation analysis demonstrated that BMI positively mediates the relationship between smoking and lung cancer risk in current smokers, while it shows an inverse or null mediation effect in former smokers. Diabetes mellitus does not significantly mediate the BMI-lung cancer association. The findings of this dissertation project indicate a potential causal inverse relationship between BMI and lung cancer, supported by temporality, strength of association (including dose-response relationship), consistency, and biological plausibility. This relationship is evident across subgroups (i.e.: gender, histological subtypes and BMI measurement technique) and smoking statuses, with biological mechanisms like reduced carcinogen-DNA adducts and oxidative DNA damage providing further support, though additional research is needed. Future studies should incorporate other indices of body fat, such as central obesity measures (e.g., waist-to-hip ratio, waist circumference), to better understand risk factors and biological mechanisms. Further research employing sophisticated body composition tools, such as imaging technologies, alongside molecular techniques like metabolomics, could provide deeper insights into the biological mechanisms at play
Intimate Partner Violence in Post-Conflict Communities: The Case of Peru
No full textIntimate partner violence (IPV) is a major public health issue worldwide and the most common type of violence experienced by women. In the last decade, a growing number of studies have evidenced that situations of civil conflict, post-conflict, and displacement can significantly exacerbate IPV and increase the likelihood of experiencing IPV later in life. This study expands on the literature by taking a Geographic Information System (GIS) mapping approach to understand how civil conflict violence in Peru (1980-2000) is associated with IPV rates in the country, 4 years (2004) and 19 years (2019) after the conflict. Study results evidence the latent legacy that the 20-year civil conflict has on levels of IPV rates in the country, even 4 years and 19 years after the conflict ended. In 2004, provinces with Medium Conflict Exposure are predicted to score .20 points higher than provinces with No Conflict Exposure in terms of IPV rates (p \u3c 0.01). In 2019, provinces with Medium Conflict Exposure are predicted to score .14 points higher than provinces with No Conflict Exposure (p \u3c 0.01). This study adds to the increasing body of literature regarding conflict exposure and IPV and can motivate social work researchers to use spatial statistical analysis to understand social problems such as IPV when conducting studies with an ecological framework
Utilization of Psychedelic Substances and Unmet Need for Mental Health Services in the United States: A Nationally Representative Study
No full textIntroduction: Unmet need for mental health services—when an individual experiences mental health symptoms and perceives a need for treatment but does not receive services—is a growing problem in the U.S. Nearly half (49%) of 59.3 million adults aged 18 or older with a mental health disorder do not receive needed mental health treatment (Substance Abuse and Mental Health Services Administration, 2023). Unmet need has been linked to several access barriers including accessibility of services, affordability, and acceptability or the stigma associated with mental health treatment. Experiencing these barriers to treatment can lead some individuals to seek alternative forms of treatment. Recently, as the media has reported positive effects of psychedelics to treat mental health conditions, illicit use of these substances has increased. Although research of psychedelics use outside of the clinical setting remains understudied, there is evidence to suggest that psychedelics are being used for self-medication, sometimes referred to as ‘microdosing’ or ‘macrodosing’. However, these studies are often smaller survey studies conducted via online recruitment, and lacking a representative sample. The purpose of this study is to provide nationally representative information on psychedelic use trends and their relationship to unmet need, as well as factors that may affect their use like access barriers and mental health diagnoses. Methods: This is a quantitative, cross-sectional study using secondary data from the 2015-2019 National Survey on Drug Use and Health (NSDUH). Multivariable logistic regressions were used to examine the relationship between past-year psychedelic use and unmet need, receipt of mental health treatment, access barriers, and Major Depressive Disorder (MDD) and psychedelic use. Interaction terms and marginal effects were used to assess the moderating effect of unmet need on the relationship between past-year MDD and psychedelic use. Demographic information collected in the NSDUH was used as covariates for the adjusted logistic regressions. Results: In both the unadjusted and adjusted results, those with unmet need for mental health services in the past year are more likely to have use psychedelics in the past year compared to those who did not report unmet need (OR 3.17; 95% CI 2.98-3.37 and aOR 2.41; 95% CI 2.25-2.57, respectively). Additionally, marginal effects were calculated and determined receipt of formal treatment weakened the association between perceived unmet need for mental health treatment and past-year psychedelic use. When examining access barriers, only the affordability barrier had significant findings. For both the unadjusted and adjusted models, individuals who indicated they could not afford the cost of mental health treatment as their reason for not receiving services were more likely to have used psychedelics in the past year (OR 1.28: 95% CI 1.14-1.43 and aOR 1.26: 95% CI 1.11-1.41, respectively). Similar positive associations were discovered between past-year MDE and past-year psychedelic use. The unadjusted odds of having used psychedelics in the past year if an individual also experienced past-year depression is 2.89 (95% CI 1.73-3.07). The association persisted after adjusting for sociodemographic covariates (aOR 1.66; 95% CI 1.55-1.79). After calculating marginal effects for the moderating effect of past-year depression, results suggest its presence was associated with higher odds of psychedelic use only when there was no unmet need (0.021 versus 0.012). On the other hand, depression did not add much to the odds of psychedelic use if the participant had unmet need (0.0256 versus 0.0259). Conclusion: This is the first nationally representative study to examine the relationship between unmet need and related factors to the illicit use of psychedelic substances. Across all studies, a significant, positive association was found between past-year psychedelic use and unmet need, affordability barriers, and depression. The implications of this research are important as the legalization of these substances, for either medical use or, in some states’ case, recreational use nears. While this study cannot determine causal links, it has important preliminary findings towards answer whether individuals with unmet mental health care needs may be substituting evidence-based care with psychedelic use outside of a clinical setting. Understanding these relationships and related factors are an imperative step to further research. Details of unmet need and psychedelic use can better inform policymakers as they decide how psychedelics might be made available to the public and how to direct the development of safety regulations. Further research should focus on prospective longitudinal studies that utilize repeated standardized measures with the intention of informing public policy surrounding the safe and effective implementation of these substances at mental health treatment