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The organisational dynamics of integrating neurology services in an NHS hospital trust: A systems psychodynamic perspective
Full text linkBackground: The factors driving NHS integration are captured in the Neurology patient population, characterised by increased life expectancy, alongside high incidence of complex, degenerative, and long-term conditions. Organisational change is a requirement of integration, with the potential to undermine clinical care. Merger is introduced as an existing form of integration, where relational understanding has been subjugated. Literature Review: Research addressing professional views of organisational merger in NHS hospital trusts was systematically identified. A line of argument synthesis illustrates the distal influence of politics and place, borne out locally in assimilation, loss, and pragmatic progress. Aims: To explore what could be learned about a local integration from a psychodynamic method of observation, and to hypothesise unconscious aspects of integration relevant to wider UK health systems. Method: A philosophical and epistemological position consistent with the unconscious aspects of change in a public institution are set out in detail. This conceptual frame is operationalised into a three phase method of observation. Data generated from 6 in depth observations and reflective groups was analysed in line with reflective thematic analysis. Results: A rigid hierarchy underpinned anxiety at uncertain boundaries, indicating the task and structure of integration split off painful feelings. Systemic demands to quantify integration were hypothesised to obscure the painful task of caring for patients with degenerative conditions. These defensive structures also appeared liable to semi-sudden collapse, risking the sudden return and contagion of disavowed feelings. Conclusions: The capacity to flexibly contain painful feeling states is denatured by marketised competition and pressures to evidence quality. Associative forms of enquiry offer a means of integrating feeling states into the process of organisational change in the NHS. This form of knowledge is essential to integrate local systems, but is threatened by cycles of top down re-organisation, reverting power to the centre
Competing ferromagnetic and antiferromagnetic phases on the frustrated Ising honeycomb lattice
Full text linkWe investigate the frustrated J₁–J₂–J₃ Ising model on the honeycomb lattice, featuring first- and second-neighbor ferromagnetic couplings (J₁>0 and J₂>0) and third-neighbor antiferromagnetic interactions (J₃<0). Using the cluster mean-field method, we analyze the phase transitions in the regime 1/2<J₂/J₁≤1, where ferromagnetic and antiferromagnetic phases compete. Our results reveal that near the strongly frustrated limit J₃/J₁=−1, the system exhibits order-by-disorder state selection, tricritical and bicritical behavior, critical endpoints, and two successive phase transitions. The ferromagnetic–paramagnetic transition remains second order across the entire interaction range, whereas the antiferromagnetic–paramagnetic boundary shows a richer behavior, including both first- and second-order transitions as well as tricriticality. Increasing the second-neighbor coupling J₂/J₁ narrows the range of J₃/J₁ where first-order antiferromagnetic–paramagnetic transitions occur; beyond a certain threshold, only second-order order–disorder transitions persist. Consequently, the tricritical point shifts toward J₃/J₁≈−1 as J₂/J₁ increases, culminating in a bicritical point where the antiferromagnetic, ferromagnetic, and paramagnetic phases meet
A Gender Gap in Attitudes Towards Monetary Policy? The Case of Satisfaction with the Bank of England
Full text linkThis article investigates the existence and extent of a gender gap in satisfaction with the Bank of England’s performance in controlling inflation. Descriptive data and previous research report gender gaps in attitudes towards monetary institutions and outcomes. Much of this research, however, disregards potential biases arising from women’s lower propensity to express an opinion, and to answer ‘don’t know’ instead. Using the Bank of England’s Inflation Attitudes survey (2001–2025), and modelling selection into substantive answers, I find a statistically significant – yet, substantively small and not persistent – gender gap in satisfaction with the Bank of England. This gender gap remains after controlling for inflation perception and monetary knowledge. I also find that women do not overestimate inflation, and they do not seem to ‘punish’ more harshly the Bank for high inflation or deflation. Therefore, variance in this gender gap can be attributed to a different propensity to report ‘extreme’ opinions, and to different reactions to high inflation or deflation. These findings highlight gendered dimensions for the understanding of monetary institutions and finance, contributing to the literature on satisfaction with the performance of institutions
Network reorganisation reveals somato-motor transition from segregation to integration during tonic pain
Full text linkThe sustained nature of tonic pain makes it a useful experimental analogue for studying the prolonged neural processing involved in chronic pain. However, research is yet to identify its consistent and generalisable biomarkers. Here, we analysed electroencephalography data recorded in 36 volunteers during 5-minute sessions of noxious hot and innocuous warm water immersion using network-based statistics and graph theory-based analysis. Our results revealed a brain-wide reorganisation of functional connectivity during tonic pain, marked by a global shift from segregation to integration. This shift was characterised by a transition from intra- to internetwork communication, with the Somato-Motor (SomMot) network playing a pivotal role. During innocuous warmth, the SomMot network exhibited significantly higher functional specialisation for localised sensory processing. During noxious heat, however, it shifted to an integrative coordinator, a finding reinforced by a significant discrepancy in global clustering coefficient when intranetwork connections were excluded. We also found that psychological traits modulated global network inferences (GNIs) in distinct, clinically relevant ways: pain catastrophising was positively associated with network segregation and integration during pain, whereas anxiety was negatively associated with segregation and integration during innocuous warmth. Notably, a machine learning model using these GNIs achieved 86% accuracy in classifying noxious heat from innocuous warmth. Together, our findings elucidate the transformation from segregated processing to integrated network dynamics induced by tonic pain, characterised by a transition in the SomMot network functioning as an integrator. Critically, global network inferences may serve as valuable predictors of pain experiences, highlighting their translational potential in pain neuroscience
Social Influence and Carbon Dioxide Mitigation
Full text linkWe investigate the potential of social influence to increase people’s willingness to mitigate their carbon impact. In a large-scale online experiment consisting of two waves of data collection participants are given the choice to spend any share of a 10 GBP endowment on mitigation. If a wave-1 participant is told that their (anonymized) choice will be observed by a wave-2 participant before that participant makes their choice, then the wave-1 participant’s willingness to mitigate (WTM) increases by about 17%. This is not the case if their choice is observed by the wave-2 participant after that participant has already made their choice, which demonstrates that it is indeed the possibility of influence and not only observability that matters. Increasing influence at the extensive margin, i.e. increasing the number of wave-2 participants observing the choice, does not increase WTM. We also elicit beliefs and find that most participants overestimate how much influence they have
On the relationship between government subsidies, ESG performance and the stock market
Full text linkThis thesis examines the interactions between government subsidies, firms’ environmental, social, and governance (ESG) performance, and stock market reactions. It focuses on how ESG-related subsidies influence corporate behaviour and investor perceptions, subsequently impacting stock market outcomes. Chapter I provides an overview and introduces the research objectives of the thesis. Chapter II demonstrates that higher ESG subsidies lead to significant improvements in firms’ ESG performance, particularly after the Paris Agreement. These improvements are more pronounced among larger firms and state-owned enterprises (SOEs) compared to their counterparts. Chapter III employs event study methodology to illustrate that positive stock market reactions to ESG subsidy policy announcements are predominantly observed among firms with robust ESG standings, highlighting investor preferences for sustainable practices. The market impact of ESG subsidies intensifies post-Paris Agreement; however, SOEs experience relatively weaker effects than non-SOEs.Chapter IV introduces Institutional Social Responsibility Concentration (ISRC), showing that stocks receiving larger allocations from socially responsible mutual funds tend to achieve higher future returns, driven by enhanced ESG performance and greater market stability. This relationship further strengthens following the Paris Agreement, underscoring the global shift toward sustainability. Chapter V concludes the thesis and outlines potential directions for future research. Collectively, this work contributes to the sustainable finance literature and provides valuable insights for policymakers, investors, and stakeholders committed to advancing corporate sustainability
The biopsychosocial model of depersonalisation and derealisation: an updated framework
Full text linkDepersonalisation (DP) and derealisation (DR) are dissociative phenomena involving detachment from the self (DP) or the external world (DR). Although relatively common, they remain under-researched, with existing studies largely limited to small clinical samples. This thesis adopts a biopsychosocial framework to investigate their development, maintenance, and severity. Chapter 1 reviews literature on DPDR, focusing on adverse childhood experiences (ACEs) and associated biological processes. The definition of ACEs was broadened beyond abuse and neglect to include household instability, emphasising the need to assess both individual ACE types and cumulative ACE clusters. The importance of distinguishing between DP and DR, and of considering secondary factors influencing DPDR, is highlighted. Using participant data from the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 7,906), Chapter 2 examines ACEs in the first 11 years as predictors of DP and DR at ages 12, 17, and 24. Potential mediators (attachment, depression, anxiety, and perseverative cognition) are tested. Longitudinal analyses suggest ACEs are associated with DPDR from adolescence through to adulthood. Chapter 3 explores biological mechanisms, assessing whether interleukin-6 (IL-6) and C-reactive protein (CRP) predict DP and DR and mediate ACE–DPDR links. Sex, ethnicity, and social position are also examined as confounders. Longitudinal analyses demonstrated that CRP predicted DR over time, and IL-6 predicted DP. Chapter 4 investigates maintenance processes through thematic analysis of 368 self-help forum posts, identifying reactivation and persistence themes. Chapter 5 evaluates whether DPDR severity follows a dose-response relationship with ACEs and compares trait rumination with hyper-reflexivity as potential cognitive processes associated with DPDR. Quantitative analyses further tested maintenance themes identified qualitatively. Taken together, findings indicated that DP and DR may have distinct aetiologies: DP is strongly predicted by diverse ACEs and childhood IL-6, while DR is linked to selective ACEs and CRP dysregulation over time. Anxiety, depression, perseverative cognition, and rumination did not mediate ACE–DPDR relationships, while hyper-reflexivity emerged as a key feature of DPDR. Maintenance of DPDR appears driven by dysregulation of core systems, cognitive triggers, and environmental reactivity, helping explain their persistence
Building Better Than We Know: Maintenance, Eye Movements, and Social Trust
No full textObjective: To determine if remediating images of poorly maintained residential properties increases social trust and identify which aspects of the built environment participants attend to when making social decisions.
Methods: Using a within-subject design and a multilevel approach to analysis, participant’s eye movements and attitudinal states were recorded as they were presented with a series of static images of residential properties. These residential properties were chosen from areas which are categorised as being among the most deprived according to the English Index of Multiple Deprivation. The images then had the salient aspects of physical disorder corrected using digital imaging software. The resulting experimental stimuli were presented in both ‘original/unmaintained’ and ‘manipulated/maintained’ conditions to each participant along with a question regarding social trust.
Results: Images of residential properties in the maintained condition were associated with higher social trust scores (likelihood ratio test χ² (1) = 548.13, p < .001). Images of residential properties in the unmaintained condition were associated with longer dwell durations (likelihood ratio test χ² (1) = 329.46, p < .001).
Conclusions: These findings suggest that the visual component of maintenance interventions may contribute to their effectiveness by shaping initial social trust perceptions
Disentangled Multimodal Spatiotemporal Learning for Hybrid EEG-fNIRS Brain-Computer Interface
Full text linkThe hybrid EEG-fNIRS Brain-computer interface (BCI) combines the high temporal resolution of electroencephalography (EEG) with the high spatial resolution of functional near-infrared spectroscopy (fNIRS) to enable comprehensive brain activity detection. However, integrating these modalities to obtain highly discriminative features remains challenging. Most existing methods fail to effectively capture the spatiotemporal coupling features and correlations between EEG and fNIRS signals. Furthermore, these methods adopt a holistic learning paradigm for the representation of each modality, leading to unrefined and redundant multimodal representations. To address these challenges, we propose a disentangled multimodal spatiotemporal learning (DMSL) method for hybrid EEG-fNIRS BCI systems, which simultaneously performs multimodal spatiotemporal coupling and disentangled representation learning within a unified framework. Specifically, DMSL utilizes a compact convolutional module with one-dimensional temporal and spatial convolution layers to extract complex spatiotemporal patterns from each modality and introduces a multimodal attention interaction module to comprehensively capture the inter-modality correlations, enhancing the representations for each modality. Subsequently, DMSL designs an adaptive multi-branch graph convolutional module based on reconstructed channels to effectively capture the spatiotemporal coupling features, incorporating modality consistency and disparity constraints to disentangle common and modality-specific representations for each modality. These disentangled representations are finally adaptively fused to perform different task predictions. The proposed DMSL demonstrates state-of-the-art performance on publicly available datasets for mental arithmetic, motor imagery, and emotion recognition tasks, exceeding the best baselines by 2.34%, 0.59%, and 1.47%, respectively. These results demonstrate the effectiveness of DMSL in improving EEG-fNIRS decoding and its strong generalization ability in BCI applications