Preconception health influences the risk of pregnancy-related complications, subsequently impacting the short- and long-term health of women. This study assessed pregnancy intention and the preconception health of Australian women. Using cross-sectional data from the Australian Longitudinal Study on Women's Health, regression analyses found that the intention to become pregnant was significantly associated with higher body mass index (BMI). There was 'No association was found between pregnancy intention and meeting recommendations for fruit, vegetables, or physical activity. The intention to become pregnant does not foster optimal health behaviors among young Australian women.
This study investigates whether total factor productivity (TFP) promotes environmental sustainability and examines the moderating and mediating roles of financial development in shaping this relationship. Using balanced panel data for 92 countries from 2000 to 2023, the analysis employs dynamic two-step Generalised Method of Moments (GMM), Lewbel's 2SLS, and panel threshold regression techniques to address endogeneity and capture nonlinear dynamics. Environmental degradation is measured using the ecological footprint and CO2 emissions. The findings indicate that productivity growth significantly reduces environmental degradation by improving resource-use efficiency and fostering cleaner production processes. Financial development and financial institutions further strengthen this effect by facilitating investment in green technologies and sustainable infrastructure. However, financial markets exhibit mixed environmental impacts, reflecting short-term profit incentives. Threshold estimations reveal that TFP initially intensifies environmental pressure at low levels of financial development but becomes environmentally beneficial once critical financial thresholds are surpassed. The mediation analysis identifies energy efficiency as the dominant transmission channel through which TFP reduces environmental degradation, while industrial expansion partially offsets these gains. Additional channels include technological innovation and trade openness, though their mediating roles are relatively modest. Overall, the results highlight the importance of well-developed and well-regulated financial systems in converting productivity gains into environmental benefits. The study provides policy-relevant insights for designing integrated productivity, financial, and environmental strategies to support sustainable development.
This study explores the progression of artificial intelligence (AI) systems through the lens of complexity theory, challenging conventional linear projections of advancement toward artificial general intelligence (AGI). We posit the existence of critical points, akin to phase transitions, where increasing system complexity may not lead to greater capability, but rather to performance plateaus or instability. To investigate this hypothesis, we used agent-based modelling (ABM) to simulate the evolution of AI systems, using evaluation benchmark performances as a proxy for complexity. Our simulations modeled the possible characteristics that systems could exhibit when crossing a critical threshold, transitioning from predictable improvement to a regime of erratic, volatile behavior. Practically, we introduced and validated a methodology for detecting these simulated critical transitions algorithmically. We proposed a heuristic Stochastic Gradient Descent-based approach and compared it with established CUmulative SUM (CUSUM) and Lyapunov exponent techniques, to show that different signatures of instability—from abrupt shifts to gradual volatility ramps—can be identified. We contextualized these findings with real-world phenomena, arguing that the empirically observed —“Jagged Capability Frontier” in large language models (LLMs) illustrates the kind of nonlinear performance boundaries that could be sharply accentuated by the onset of criticality. This research contributes not only a novel theoretical framework for understanding potential limits to AI scaling but also a practical, validated methodology for monitoring the systemic stability of AI systems, offering a new dimension to AGI evaluation and safety.
Purpose Women’s career progression in healthcare continues to lag men’s, particularly at senior leadership levels, limiting organizational performance and weakening leadership pipelines. This study applies Conservation of Resources (COR) theory’s positive gains cycle to examine how supportive organizational environments and human resource management practices can accelerate women’s advancement from early career stages to senior leadership. Design/methodology/approach Using a social constructivist approach, we conducted 30 in-depth interviews with Australian healthcare leaders (20 female and 10 male) across multiple organizational levels. Thematic analysis identified the resources and interactions that enable sustained leadership progression for women. Findings Four interconnected resources, including supportive work environments, supportive communities, a resolute mindset and dynamic authenticity, were identified as drivers of career progression. External support, including flexible policies, inclusive promotion systems, mentorship and leadership visibility, fosters internal strengths such as resilience, self-efficacy and adaptive leadership capacity. These resources interact to create reinforcing gain spirals, enabling women to navigate challenges and sustain advancement through strategic reinvestment. Practical implications The “Success is Contagious” framework provides HRM strategies for strengthening leadership pipelines, such as building robust support systems, fostering professional networks and designing development pathways that encourage authentic leadership. Originality/value This study extends COR theory by showing how organizational resources can initiate and sustain positive resource spirals in women’s leadership progression. It offers evidence-based strategies for human resources and senior leaders to design systems that align organizational context with individual agency, ensuring long-term leadership capacity in healthcare.
Abusive supervision (AS) is an antiproductive behavior that significantly affects operational efficiency and employee performance, but its precise impact mechanism remains poorly understood. This study aimed to quantify the differential impact of active versus passive AS on construction workers' work efficiency and verify the mediating role of cognitive states. Utilizing electroencephalogram (EEG) feature extraction integrated with cognitive science, we exposed 25 construction worker participants to randomized scenarios simulating active AS, passive AS, and control conditions. Behavioral performance data and cognitive state indicators were systematically collected and analyzed. AS significantly reduced work efficiency, with active AS having a greater impact than passive AS. AS was negatively correlated with attention and valence index, but positively correlated with mental fatigue. The adoption of EEG technology introduced a novel methodological approach to construction AS research, and this study empirically reveals the pathway through which AS impairs work efficiency via cognitive impairment. It provides a scientific foundation for developing targeted interventions to mitigate AS's adverse effects on construction worker productivity.
