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23. Cultural narratives, social norms, and psychological stigma : a study of mental health help-seeking behavior in Peshawar, PakistanDaraz Umar, Štefan Bojnec, Younas Khan, Zakir Hussain, 2025, izvirni znanstveni članek Opis: Introduction: Mental health stigma remains a major barrier to accessing psychiatric care worldwide, with pronounced effects in culturally traditional societies such as Peshawar, Pakistan. In the Pashtun cultural context, the code of Pashtunwali—an honor-based system—shapes social attitudes and behaviors, potentially influencing mental health help-seeking patterns. This study examines how cultural narratives, social norms, and stigma interact to affect help-seeking behavior in this sociocultural setting. Methods: A cross-sectional survey was conducted among a stratified random sample of 400 adults aged 19 years and above in Peshawar. Data were collected using culturally validated instruments, including the Mental Illness Stigma Scale (MISS) and a Social Norms Scale. Bivariate analyses employed simple linear regression and binary logistic regression to examine individual relationships between variables. Multivariate analyses, including multiple linear regression and Structural Equation Modeling (SEM), were used to assess combined effects and mediation pathways. Results: Cultural narratives had a positive impact on help-seeking behavior, explaining 42% of its variance. Stigma showed a significant negative association, decreasing help-seeking likelihood by 26% for each unit increase. Social norms demonstrated a positive association with help-seeking behavior and indirectly reduced stigma. Collectively, these variables accounted for 68% of the variance in help-seeking likelihood. Discussion: The findings highlight the pivotal role of culturally resonant narratives and supportive social norms rooted in Pashtunwali in improving mental health service utilization. Addressing stigma while reinforcing positive cultural frameworks can substantially enhance help-seeking behavior in Peshawar and similar sociocultural contexts.
Ključne besede: cultural narratives, mental health stigma, social norms, psychiatric help, structural equation modeling (SEM)
Objavljeno v RUP: 28.08.2025; Ogledov: 665; Prenosov: 7
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24. Exploring the drivers of farm sustained participation in agri‑environmental programmesŠtefan Bojnec, Imre Fertő, 2025, izvirni znanstveni članek Opis: This paper examines the socioeconomic and institutional determinants influencing sustained participation in Agri-Environmental Climate Schemes (AECS), drawing on comprehensive panel data from Slovenian farms covering the period 2014–2021. Using discrete-time hazard models and nonparametric duration analysis, we identify economic resilience—characterised by larger farm size, income diversification, and prior participation—as a significant driver of prolonged AECS engagement. Conversely, greater dependence on market-based income is negatively correlated with long-term participation, highlighting inherent trade-offs between short-term economic gains and sustained ecological commitments. Additionally, educational attainment exhibits a modest yet positive association, emphasising the importance of knowledge dissemination and capacity building in facilitating the responsible use and sustained environmental protection. Our findings underscore the necessity for context-specific policy designs, advocating diversified financial incentives, robust extension services, and market-aligned strategies to effectively integrate agricultural productivity with environmental sustainability.
Ključne besede: agri-environmental climate scheme management, farm corporate social responsibility, sustainable farm production adoption, selection model, duration analysis, discrete-time models
Objavljeno v RUP: 28.08.2025; Ogledov: 468; Prenosov: 7
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30. AI automation and technologies within industries across Europe : current size and expected growthAna Grdović Gnip, 2025, objavljeni povzetek znanstvenega prispevka na konferenci Opis: This paper examines the current landscape of artificial intelligence (AI) automation and technologies across various industries in Europe, utilizing descriptive statistics derived from Eurostat data. By analyzing the proportions of AI adoption within key sectors, the aim is to provide a comprehensive overview of the present state of AI integration in European industries. This is relevant from the perspective of its possible economic effects. The existing litareture that focuses on the effects of automation technologies on employment is rather inconsistent and inconclusive (Filippi et al, 2023). According to Bowles (2014) 54 % of European workers are at risk of substitution (by applying the occupation-based approach), while according to Pouliakas (2018) only 13.9 % of workers will face a risk higher than 70 % (by applying the task-based approach). Moreover, McGuinness et al 2021, show how 16 % of adult European workers have recently experienced a skills-displacing technological change, i.e., some changes in the use of technologies (e.g., machinery and ICT systems) in the last five years and thus concludes that several of their skills will become outdated in the next five years. Josten and Lordan (2020) predicted that by 47% of European jobs will be automatable (of which 35% are fully automatable), while 40% of them are not expected to be automated. Anyhow, the probability of automation varies considerably across industries. The service sector is generally less threatened by automation (Pajarinen et al, 2015), no matter the fact that wholesale and retail trade have a high probability of automation (Nedeloska and Quintini, 2018). Several studies conclude that (besides services) industries with a low probability of automation (lower than 40 %) include: education, health and social work, arts, sport and entertainment, management, business and finance, public administration and public utility services (Illessy et al, 2021, Yamashita nad Cummins, 2021; among others). Furthermore, this paper explores projected growth trajectories for AI usage, highlighting anticipated advancements and the potential for increased efficiency and innovation. Basically, an independent survey conducted in 2024 by the German Reichelt elektronics on the current status and potential of technologies (such as AI, ML, big data, robotics and IoT) and their use in European industrial companies shows that many European companies in the industrial sector (60%) believe that production will be fully automated in five years’ time. In addition, more than two thirds of the European industry (68%) consider automation to be essential in order to remain competitive. Therefore this paper also discusses the challenges and hurdles that may impede the widespread adoption of AI technologies, including regulatory, ethical, and infrastructural considerations, while seeking to understand the dynamics of AI implementation in Europe and its implications for future economic development.
Ključne besede: automation, AI technologies, productivity, Europe
Objavljeno v RUP: 28.08.2025; Ogledov: 626; Prenosov: 8
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