Hasil untuk "Social pathology. Social and public welfare. Criminology"

Amanda Jones, Maria Fjellfeldt, Ulla-Karin Schön

To enhance user participation in the complex setting of coordinating support, more knowledge is needed about strategies designed to improve user involvement. This study aimed to explore staff perceptions of barriers and facilitators during the implementation process of the innovation shared decision-making (SDM) in coordinated individual planning (CIP) within the comorbidity field of practice. A mixed methods approach was used, involving the collection and analysis of questionnaire data at two time points, followed by individual and focus group interviews. Data were collected from staff working in social services and healthcare. The data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR), focusing on the domains of innovation, inner setting, and individuals involved. Barriers to implementation included among others, perceptions of high workloads, a lack of relational connections between staff from different units, and staff ambiguity regarding user participation. Facilitators included circumstances such as experience with the innovation, a focus on user participation, and the presence of functional collaboration between staff from different organizations prior to implementation. Overall, the findings highlight the importance of relational connections both between users and staff and among staff from different units during the implementation process of SDM in a collaborative setting like CIP.

Felipe Haleyson Ribeiro Dos Santos, Edson Ronaldo Guarido Filho

Este artigo tem como objetivo revisar a literatura sobre desempenho em organizações policiais. A pesquisa foi realizada em bases de dados de artigos científicos, que foram catalogados e, posteriormente, por meio do método inOrdinatio, foram classificados e selecionados para análise. O escopo teórico pretendido é identificar como tem sido estudado o desempenho nas organizações policiais. Após aprofundar a análise, e com foco na gestão, foi possível classificar os artigos em três níveis: individual, que trata o desempenho sob a perspectiva do indivíduo policial (incluindo fatores atrelados à satisfação, iniciativa, motivação, liderança e ao sentimento de justiça); organizacional, que considera o desempenho sob a perspectiva de indicadores supraindividuais; e institucional, que está ancorado na legitimidade como forma de avaliar o desempenho. Não foram encontrados estudos que abordassem a relação de desempenho entre os níveis, o que pode ser visto como sugestão para novas pesquisas.

Marie Peretti-Ndiaye

Paul Welfordsson, Anna-Karin Danielsson, Anette Søgaard Nielsen et al.

Abstract Background Alcohol screening and brief interventions (SBI) are effective strategies to reduce hazardous alcohol use in healthcare settings but are implemented inconsistently in cardiology practice. There is a need to understand factors associated with alcohol prevention practices in clinical cardiology to bridge this evidence-practice gap. The aim of this study was to investigate factors associated with SBI practices in cardiology. Methods Multi-centre cross-sectional study. We surveyed clinicians at cardiology services in 12 regions across Sweden. The outcome was participants’ tendency to initiate SBI. Predictor variables included perceived importance of alcohol screening, level of comfort discussing alcohol habits with patients, perceived reliability of self-reported alcohol habits, and perceived competence for screening and brief interventions. Analyses included Wilcoxon signed-rank tests and ordinal logistic regression models. Results In total, 692 clinicians participated in the survey (nurses = 55%; doctors = 19%; assistant nurses = 22%). Perceived importance of screening was not significantly associated with initiating SBI (OR = 1.55, 95%CI = 0.75–3.20). However, greater comfort when discussing alcohol habits was strongly associated with participants’ tendency to initiate SBI (OR = 4.06, 95%CI = 2.62–6.30) in maximally-adjusted models. Competence with screening (OR = 1.65, 95%CI = 1.06–2.56) and brief interventions (OR = 1.93, 95%CI = 1.30–2.85), and perceived reliability of self-reported alcohol habits (OR = 1.54, 95%CI = 1.12–2.13) were also positively associated with initiating SBI. While most (> 95%) participants considered it important that cardiology patients are asked about their alcohol habits, just 27% indicated that they often or always initiate SBI (z = 21.88, p < .001). Conclusions Many cardiology clinicians in Sweden view alcohol screening as important, but these views are frequently not aligned with self-reported clinical practice. Findings highlight a need to empower clinicians to initiate conversations about alcohol use with their patients and for improved training to support SBI implementation. Promising strategies may include creating workflows that normalize discussions around alcohol use and clinician training that focuses on challenging stereotypes associated with alcohol use disorder.

Qiqi Qiang

Understanding how emotions diffuse through social networks is central to computational social science. Recently, large language models (LLMs) have been increasingly used to simulate social media interactions, raising the question of whether LLM-generated data can realistically reproduce emotion diffusion patterns observed in real online communities. In this study, we conduct a systematic comparison between emotion diffusion in real-world social graphs and in LLM-simulated interaction networks. We construct diffusion graphs from Reddit discussion data and compare them with synthetic social graphs generated through LLM-driven conversational simulations. Emotion states are inferred using established sentiment analysis pipelines, and both real and simulated graphs are analyzed from structural, behavioral, and predictive perspectives. Our results reveal substantial structural and dynamic discrepancies between real and simulated diffusion processes. Real-world emotion diffusion exhibits dense connectivity, repeated interactions, sentiment shifts, and emergent community structures, whereas LLM-simulated graphs largely consist of isolated linear chains with monotonic emotional trajectories. These structural limitations significantly affect downstream tasks such as graph-based emotion prediction, leading to reduced emotional diversity and class imbalance in simulated settings. Our findings highlight current limitations of LLM-based social simulation in capturing the interactive complexity and emotional heterogeneity of real social networks. This work provides empirical evidence for the cautious use of LLM-generated data in social science research and suggests directions for improving future simulation frameworks.

T. Modie-Moroka, T. Malinga, M. Dube

Violence against women (VAW) and violence against the Earth (VAE) have always shared a unique and complex association yet to be explored. The fields of VAW and VAE have evolved in separate routes, with divergent theoretical foundations but with little integration. While the impact of VAW has received much attention over the years, relatively little thought has gone into the intersections. Drawing parallels between society’s treatment of the physical and natural environment and its treatment of women, this paper will pull in insights to broaden and clarify the way VAW has been conceptualized, its association with the physical and natural environment (Mother Earth), and the constructs and the commitments that flow from them. In this paper, we formulate, cast, and present an expanded understanding of the relationship between violence against the physical and the natural environment and VAW. The article, an offshoot of our conceptualization on the inter-linkages between VAW and VAE, is being submitted for interpretation and application. 

Junchi Yao, Hongjie Zhang, Jie Ou et al.

In the context where social media emerges as a pivotal platform for social movements and shaping public opinion, accurately simulating and predicting the dynamics of user opinions is of significant importance. Such insights are vital for understanding social phenomena, informing policy decisions, and guiding public opinion. Unfortunately, traditional algorithms based on idealized models and disregarding social data often fail to capture the complexity and nuance of real-world social interactions. This study proposes the Fusing Dynamics Equation-Large Language Model (FDE-LLM) algorithm. This innovative approach aligns the actions and evolution of opinions in Large Language Models (LLMs) with the real-world data on social networks. The FDE-LLM devides users into two roles: opinion leaders and followers. Opinion leaders use LLM for role-playing and employ Cellular Automata(CA) to constrain opinion changes. In contrast, opinion followers are integrated into a dynamic system that combines the CA model with the Susceptible-Infectious-Recovered (SIR) model. This innovative design significantly improves the accuracy of the simulation. Our experiments utilized four real-world datasets from Weibo. The result demonstrates that the FDE-LLM significantly outperforms traditional Agent-Based Modeling (ABM) algorithms and LLM-based algorithms. Additionally, our algorithm accurately simulates the decay and recovery of opinions over time, underscoring LLMs potential to revolutionize the understanding of social media dynamics.

Miguel Angel Cano Paños

For more than forty years, Spain has been confronted with internal terrorism, of an ethno-nationalist nature, deployed by the terrorist organization ETA. Their armed struggle, which caused more than 850 fatalities, had as its objective the independence of the Basque Country, Navarre, as well as a part of the so-called French Basque Country. It was especially during the 1970s, 1980s and 1990s when the police forces deployed in the so-called “Northern Zone” were exposed not only to the possibility of suffering a terrorist attack, but also to the rejection and animosity of a large part of the Basque a Navarrese population, which considered the police as an “occupation force”. This gave rise to the concept of “Northern Syndrome”, which referred, above all, to the psychological consequences that this omnipresent terror and rejection in their daily lives produced in both the police officers and their families. Based on these considerations, the objective of the present work is to analyse said psycho-pathological construct. To this end, the author of this paper has conducted a total of 25 interviews with police officers and relatives who were stationed in the Basque Country and Navarra during the so-called “years of lead”. As will be seen, practically all of the individuals interviewed affirm not only the existence of said Syndrome, but also having suffered from it during their stay in the North and, in some cases, also currently.

Sarah Pemberton, Stephanie Kewley, Leona Mydlowski

Comprehensive and multi-disciplinary public health approaches are necessary to prevent sexual re-offending. However, criminal justice solutions continue to dominate and the arrangement in England and Wales is no exception. The introduction of the Multi-Agency Public Protection Arrangements (MAPPA) in 2003 brought together the work of the police, prison and probation services in order to manage violent and sexual offenders. This paper focuses specifically on the work of the specialist police officers who are tasked under MAPPA with the Management of Sexual or Violent Offenders (MOSOVO) and whether or not they can assist desistance in those who have been convicted of a sexual offence. We argue that the risk-based, highly politicized model of public protection that MOSOVO staff operate within creates tensions more likely to hinder than facilitate desistance. As indicated by findings in an independent review of the police’s management of registered sex offenders (2023), successful desistance journeys are found in people who are supported by formal agents who actively promote hope and optimism and convey a belief that the person attempting desistance can change. In conclusion, we recommend that MOSOVO staff be willing and resourced to help individuals with sexual convictions develop a non-offending lifestyle and identity and support them in achieving this goal, which requires the provision of comprehensive support beyond risk management.

Ulene Schiller, Marianne Strydom, Antoinette Lombard et al.

Worldwide, children in the care of the state constitute one of the most vulnerable groups in society. They are often not heard, or their views not respected in matters concerning them. This is incongruent with the Declaration of the Rights of the Child (1959) as well as the United Nations Convention on the Rights of the Child (UN, 1989). Guided by a conceptual framework of child participation theory, this article analyses South African legislation and policies to determine how and when child participation is being promoted. Findings indicate that providing information to children on how to participate meaningfully is the key for effective child participation and that practical guidelines should be developed.

Yasuko Kawahata

The study of Opinion Dynamics, which explores how individual opinions and beliefs evolve and how societal consensus is formed, has been examined across social science, physics, and mathematics. Historically based on statistical physics models like the Ising model, recent research integrates quantum information theory concepts, such as Graph States, Stabilizer States, and Toric Codes. These quantum approaches offer fresh perspectives for analyzing complex relationships and interactions in opinion formation, such as modeling local interactions, using topological features for error resistance, and applying quantum mechanics for deeper insights into opinion polarization and entanglement. However, these applications face challenges in complexity, interpretation, and empirical validation. Quantum concepts are abstract and not easily translated into social science contexts, and direct observation of social opinion processes differs significantly from quantum experiments, leading to a gap between theoretical models and real-world applicability. Despite its potential, the practical use of the Toric Code Hamiltonian in Opinion Dynamics requires further exploration and research.

Julie Jiang, Luca Luceri, Joseph B. Walther et al.

Online hate messaging is a pervasive issue plaguing the well-being of social media users. This research empirically investigates a novel theory positing that online hate may be driven primarily by the pursuit of social approval rather than a direct desire to harm the targets. Results show that toxicity is homophilous in users' social networks and that a user's propensity for hostility can be predicted by their social networks. We also illustrate how receiving greater or fewer social engagements in the form of likes, retweets, quotes, and replies affects a user's subsequent toxicity. We establish a clear connection between receiving social approval signals and increases in subsequent toxicity. Being retweeted plays a particularly prominent role in escalating toxicity. Results also show that not receiving expected levels of social approval leads to decreased toxicity. We discuss the important implications of our research and opportunities to combat online hate.

Zitai Qiu, Jia Wu, Jian Yang et al.

Social events reflect the dynamics of society and, here, natural disasters and emergencies receive significant attention. The timely detection of these events can provide organisations and individuals with valuable information to reduce or avoid losses. However, due to the complex heterogeneities of the content and structure of social media, existing models can only learn limited information; large amounts of semantic and structural information are ignored. In addition, due to high labour costs, it is rare for social media datasets to include high-quality labels, which also makes it challenging for models to learn information from social media. In this study, we propose two hyperbolic graph representation-based methods for detecting social events from heterogeneous social media environments. For cases where a dataset has labels, we designed a Hyperbolic Social Event Detection (HSED) model that converts complex social information into a unified social message graph. This model addresses the heterogeneity of social media, and, with this graph, the information in social media can be used to capture structural information based on the properties of hyperbolic space. For cases where the dataset is unlabelled, we designed an Unsupervised Hyperbolic Social Event Detection (UHSED). This model is based on the HSED model but includes graph contrastive learning to make it work in unlabelled scenarios. Extensive experiments demonstrate the superiority of the proposed approaches.

Anna Cheng, Ryan Badolato, Andrew Segoshi et al.

Abstract Background Extended-release buprenorphine (XRB) offers a novel approach to sustained monthly treatment for people who use opioids in criminal justice settings (CJS). This study explores the experiences of adults receiving XRB as a jail-to-community treatment. Methods and findings In-depth qualitative interviews were conducted among adult participants with opioid use disorder (OUD; n  = 16) who were recently released from NYC jails and maintained on XRB after switching from daily sublingual buprenorphine (SLB). Interviews elaborated on the acceptability and barriers and facilitators of XRB treatment pre- and post-release. Interviews were audio recorded, transcribed, and analyzed for content related to factors influencing XRB treatment uptake and community reentry. Important themes were grouped into systems, medication, and patient-level factors. Key systems-level factors influencing initiation of XRB in jail included an alternative to perceived stigmatization and privacy concerns associated with daily in-jail SLB administration and less concerns with buprenorphine diversion. In-jail peer networks positively influenced participant adoption of XRB. XRB satisfaction was attributed to reduced in-jail clinic and medication administration visits, perceived efficacy and blockade effects upon the use of heroin/fentanyl following release, and averting the risk of criminal activities to fund opioid use. Barriers to retention included post-injection withdrawal symptoms and cravings attributed to perceived suboptimal medication dosing, injection site pain, and lack of in-jail provider information about the medication. Conclusion Participants were generally favorable to XRB initiation in jail and retention post-release. Further studies are needed to address factors influencing access to XRB in criminal justice settings, including stigma, ensuring patient privacy following initiation on XRB, and patient-, provider-, and correctional staff education pertaining to XRB. Trial Registration ClinicalTrials.gov Identified: NCT03604159.

Arnav Kapoor, Dipanwita Guhathakurta, Mehul Mathur et al.

NFT or Non-Fungible Token is a token that certifies a digital asset to be unique. A wide range of assets including, digital art, music, tweets, memes, are being sold as NFTs. NFT-related content has been widely shared on social media sites such as Twitter. We aim to understand the dominant factors that influence NFT asset valuation. Towards this objective, we create a first-of-its-kind dataset linking Twitter and OpenSea (the largest NFT marketplace) to capture social media profiles and linked NFT assets. Our dataset contains 245,159 tweets posted by 17,155 unique users, directly linking 62,997 NFT assets on OpenSea worth 19 Million USD. We have made the dataset public. We analyze the growth of NFTs, characterize the Twitter users promoting NFT assets, and gauge the impact of Twitter features on the virality of an NFT. Further, we investigate the effectiveness of different social media and NFT platform features by experimenting with multiple machine learning and deep learning models to predict an asset's value. Our results show that social media features improve the accuracy by 6% over baseline models that use only NFT platform features. Among social media features, count of user membership lists, number of likes and retweets are important features.

Basileal Imana, Aleksandra Korolova, John Heidemann

Social media platforms curate access to information and opportunities, and so play a critical role in shaping public discourse today. The opaque nature of the algorithms these platforms use to curate content raises societal questions. Prior studies have used black-box methods to show that these algorithms can lead to biased or discriminatory outcomes. However, existing auditing methods face fundamental limitations because they function independent of the platforms. Concerns of potential harm have prompted proposal of legislation in both the U.S. and the E.U. to mandate a new form of auditing where vetted external researchers get privileged access to social media platforms. Unfortunately, to date there have been no concrete technical proposals to provide such auditing, because auditing at scale risks disclosure of users' private data and platforms' proprietary algorithms. We propose a new method for platform-supported auditing that can meet the goals of the proposed legislation. Our first contribution is to enumerate the challenges of existing auditing methods to implement these policies at scale. Second, we suggest that limited, privileged access to relevance estimators is the key to enabling generalizable platform-supported auditing by external researchers. Third, we show platform-supported auditing need not risk user privacy nor disclosure of platforms' business interests by proposing an auditing framework that protects against these risks. For a particular fairness metric, we show that ensuring privacy imposes only a small constant factor increase (6.34x as an upper bound, and 4x for typical parameters) in the number of samples required for accurate auditing. Our technical contributions, combined with ongoing legal and policy efforts, can enable public oversight into how social media platforms affect individuals and society by moving past the privacy-vs-transparency hurdle.

Filipo Sharevski, Amy Devine, Emma Pieroni et al.

In this paper we investigate what folk models of misinformation exist through semi-structured interviews with a sample of 235 social media users. Work on social media misinformation does not investigate how ordinary users - the target of misinformation - deal with it; rather, the focus is mostly on the anxiety, tensions, or divisions misinformation creates. Studying the aspects of creation, diffusion and amplification also overlooks how misinformation is internalized by users on social media and thus is quick to prescribe "inoculation" strategies for the presumed lack of immunity to misinformation. How users grapple with social media content to develop "natural immunity" as a precursor to misinformation resilience remains an open question. We have identified at least five folk models that conceptualize misinformation as either: political (counter)argumentation, out-of-context narratives, inherently fallacious information, external propaganda, or simply entertainment. We use the rich conceptualizations embodied in these folk models to uncover how social media users minimize adverse reactions to misinformation encounters in their everyday lives.

Ziv Epstein, Hause Lin, Gordon Pennycook et al.

Unlike traditional media, social media typically provides quantified metrics of how many users have engaged with each piece of content. Some have argued that the presence of these cues promotes the spread of misinformation. Here we investigate the causal effect of social cues on users' engagement with social media posts. We conducted an experiment with N=628 Americans on a custom-built newsfeed interface where we systematically varied the presence and strength of social cues. We find that when cues are shown, indicating that a larger number of others have engaged with a post, users were more likely to share and like that post. Furthermore, relative to a control without social cues, the presence of social cues increased the sharing of true relative to false news. The presence of social cues also makes it more difficult to precisely predict how popular any given post would be. Together, our results suggest that -- instead of distracting users or causing them to share low-quality news -- social cues may, in certain circumstances, actually boost truth discernment and reduce the sharing of misinformation. Our work suggests that social cues play important roles in shaping users' attention and engagement on social media, and platforms should understand the effects of different cues before making changes to what cues are displayed and how.

Tania Arrieta Hernandez

This article examines the changing landscape of public service provision in the UK during austerity. Austerity is presented through the notions of retrenchment, decentralisation and shifts in governance. The analysis shows that retrenchment and decentralisation eroded the capacity of public institutions to protect the provision of vital public services. This is revealed through the reduced provision of non-statutory services and the reinforcement of inequalities in service provision. Shifts in governance have led to mixed outcomes in the quality of services. This article also addresses how austerity influenced many of the problems observed in service provision during the COVID-19 pandemic. Vital public services in the UK faced the pandemic with a diminished resource base, heightened inequalities and significant fragmentation in service provision.

Idalina Maria Freitas Lima Santiago

Este artigo problematiza a violência de gênero vivenciada pelas usuárias das Unidades de Saúde da Família (USF), do Sistema Único de Saúde (SUS), e o atendimento prestado por este serviço no combate de tais violências. Busca apontar os marcadores sociais das usuárias que passaram por violência de gênero; tipificar as violências de gênero vivenciadas por essas mulheres; identificar os procedimentos tomados por elas para enfrentar essas violências; analisar o atendimento das USF no combate à violência de gênero. Trata-se de pesquisa analítico-descritiva e abordagem quanti-qualitativa, envolvendo as cidades de João Pessoa, Campina Grande, Cajazeiras e Patos, na Paraíba. A amostra é constituída por 600 usuárias e 21 profissionais de saúde. As USF investigadas não se constituem espaços de interlocução com as mulheres violentadas, não efetivando o referenciamento para a Rede de Atendimento.