Showing papers by "City University London published in 2021"

Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Abstract: Importance Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures Patient Health Questionnaire–9 (PHQ-9) scores. Results Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, −0.8; 95% CI, −1.4 to −0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.

Capturing Causal Complexity: Heuristics for Configurational Theorizing

Abstract: Management scholars study phenomena marked by complex interdependencies where multiple explanatory factors combine to bring about an outcome of interest. Yet, theorizing about causal complexity can prove challenging for the correlational theorizing that is predominant in the field of management, given its “net effects thinking” that emphasizes the unique contribution of individual explanatory factors. In contrast, configurational theories and thinking are well-suited to explaining causally complex phenomena. In this article, we seek to advance configurational theorizing by providing a model of the configurational theorizing process which consists of three iterative stages—scoping, linking and naming. In each stage, we develop and offer several heuristics aimed at stimulating configurational theorizing. That is, these theorizing heuristics are intended to help scholars discover configurations of explanatory factors, probe the connections among these factors, and articulate the orchestrating themes that underpin their coherence. We conclude with a discussion of how configurational theorizing advances theory development in the field of management and organizations, and beyond.

Mapping the NFT revolution: market trends, trade networks, and visual features.

Abstract: Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when their market has experienced record sales, but little is known about the overall structure and evolution of its market. Here, we analyse data concerning 6.1 million trades of 4.7 million NFTs between June 23, 2017 and April 27, 2021, obtained primarily from Ethereum and WAX blockchains. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. Finally, we investigate the predictability of NFT sales using simple machine learning algorithms and find that sale history and, secondarily, visual features are good predictors for price. We anticipate that these findings will stimulate further research on NFT production, adoption, and trading in different contexts.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Abstract: Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Managing Change, Creativity and Innovation

Abstract: I would urge anyone with an interest in managing organisations, whether they be students or practising managers, to buy this book" - Bernard Burnes, Professor of Organisational Change, Manchester Business School, University of Manchester "Change is truly the one constant in business. As such, the ability to manage change and its drivers of innovation and creativity is essential. Thankfully, Andriopoulos and Dawson offer an exceptional treatise on this domain, insightful and engaging. I encourage management students at all levels to explore this work" - Marianne W. Lewis, Director of Kolodzik Business Scholars, University of Cincinnati Managing Change, Creativity and Innovation brings together comprehensive aspects of change management and creativity management, providing management and HR students with an accessible and wide-ranging resource for study, debate and inspiration. Balancing theory with practice, this book looks at the human side of managing change and creativity, treating them as interdependent aspects of management and organizations. Topics include: - Historical overview of business practice and theory - Understanding creativity and change - Managing individuals, teams and nurturing creativity - The creative economy and future of organizations Features include: - Coverage of all the important recent research in the field - Real-life topical case studies taken from the Financial Times - Interactive resources at the end of each chapter, including questions, exercises, topics for debate, recommended reading and web resources

A historical perspective of explainable Artificial Intelligence

Abstract: Explainability in Artificial Intelligence (AI) has been revived as a topic of active research by the need of conveying safety and trust to users in the “how” and “why” of automated decision‐making in different applications such as autonomous driving, medical diagnosis, or banking and finance. While explainability in AI has recently received significant attention, the origins of this line of work go back several decades to when AI systems were mainly developed as (knowledge‐based) expert systems. Since then, the definition, understanding, and implementation of explainability have been picked up in several lines of research work, namely, expert systems, machine learning, recommender systems, and in approaches to neural‐symbolic learning and reasoning, mostly happening during different periods of AI history. In this article, we present a historical perspective of Explainable Artificial Intelligence. We discuss how explainability was mainly conceived in the past, how it is understood in the present and, how it might be understood in the future. We conclude the article by proposing criteria for explanations that we believe will play a crucial role in the development of human‐understandable explainable systems.

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. Conclusions and Relevance In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Supply Chain Management for Extreme Conditions: Research Opportunities

Abstract: Large companies were concerned about their supply chains with environmental and social sustainability and disruption from natural disasters, conflict, and trade disagreements even before the advent of Covid-19. The additional challenges presented by Covid-19 in 2020 are “extreme” in being distinct from supply chain risk in that not just particular companies, but also entire societies are affected. Therefore, it is appropriate to rethink supply chain management (SCM) for research and practice to cope with extreme conditions, now and in the future, whether due to pandemics, war, climate change, or biodiversity collapse. In this essay, we first present the widespread challenges, along with some of the responses. We then list research opportunities for supply chain management in extreme conditions. These opportunities pertain to retailers’ survival in the face of highly successful e-commerce giants and the mixed use of robots and human workers. There are also opportunities to share supply-chain capacity in distribution and coopetition regarding medically necessary items such as anti-virals or vaccines. The growing role of government in supporting business, including the creation of industry commons, also presents avenues for further research.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Abstract: Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

(Un)Sustainability and Organization Studies: Towards a Radical Engagement:

Abstract: In this essay, we trace the evolution of the field of sustainability in management and organization studies and narrate its epistemological twists and turns. Concerned by the current trajectory tha...

A review of geothermal energy-driven hydrogen production systems

Abstract: This paper presents a review of hydrogen production systems using geothermal energy, showing the importance and potential of this technology in addition to the main obstacles facing this domain. The effect of several parameters was taken into consideration, such as geothermal fluid temperature, water electrolysis temperature, working fluid, and type of power cycle. The different types of geothermal power plants were also compared, namely, flash, binary, flash-binary, recuperative, regenerative, and organic Rankine flash cycles. This study covers a wide range of investigations regarding hydrogen production rate, hydrogen production cost, energetic efficiency, exergetic efficiency, exergetic cost, and electricity generated. Hydrogen production rate is one of the most important mentioned parameters in which it was found to vary from 5.439 kg/h to 13958 kg/h. Multigeneration systems have shown great potential to enhance the overall system’s efficiency, leading to reduced production costs. The integration of another energy source was found to be interesting in geothermal-driven hydrogen production systems. This would promote the adoption of multigeneration system as well as increasing the geothermal fluid’s temperature before entering the power cycle.

A Business Model View of Strategy

Abstract: We argue that while the business model construct may not be entirely new, it can still provide a novel lens, complementary to Resource Based View and Market Positioning, to develop new theoretical insights in strategy. We propose that the consideration of interdependencies among the activities of a business model provides such a lens. We show that by starting strategy development with interdependencies among activities, we can: (i) develop new insights on how to build superior strategies; and (ii) explain company performance variance especially when heterogeneity in resources and capabilities is not strong and barriers to imitation are weak. Overall, we propose that a promising research avenue for the business model literature is to integrate complexity theory with demand-side and supply-side theories of strategy to generate more nuanced insights on what activities to connect and how to develop superior interdependencies among activities that can form the basis of superior strategies.

The impact of the COVID-19 pandemic on the mental health and well-being of children and young people.

Abstract: The COVID-19 pandemic has had an enormous impact across the world. In this discussion paper, we examine the effect that lockdown has had on the mental health and well-being of children and young people. We write from a UK perspective in the light of the international evidence. Many of the discussion points raised resonate globally. We discuss how these issues can be dealt with and set out potential solutions as we emerge from this global crisis.

Innovations in earthquake risk reduction for resilience: recent advances and challenges

Abstract: The Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR) highlights the importance of scientific research, supporting the ‘availability and application of science and technology to decision making’ in disaster risk reduction (DRR). Science and technology can play a crucial role in the world’s ability to reduce casualties, physical damage, and interruption to critical infrastructure due to natural hazards and their complex interactions. The SFDRR encourages better access to technological innovations combined with increased DRR investments in developing cost-effective approaches and tackling global challenges. To this aim, it is essential to link multi- and interdisciplinary research and technological innovations with policy and engineering/DRR practice. To share knowledge and promote discussion on recent advances, challenges, and future directions on ‘Innovations in Earthquake Risk Reduction for Resilience’, a group of experts from academia and industry met in London, UK, in July 2019. The workshop focused on both cutting-edge ‘soft’ (e.g., novel modelling methods/frameworks, early warning systems, disaster financing and parametric insurance) and ‘hard’ (e.g., novel structural systems/devices for new structures and retrofitting of existing structures, sensors) risk-reduction strategies for the enhancement of structural and infrastructural earthquake safety and resilience. The workshop highlighted emerging trends and lessons from recent earthquake events and pinpointed critical issues for future research and policy interventions. This paper summarises some of the key aspects identified and discussed during the workshop to inform other researchers worldwide and extend the conversation to a broader audience, with the ultimate aim of driving change in how seismic risk is quantified and mitigated.

Public debt and economic growth: panel data evidence for Asian countries

Abstract: This study examines the relationship between public debt on both short and long-run economic growth, in a panel of selected Asian countries for the period of 1980–2012 We employ several econometrics methods: pooled mean group, mean group, dynamic fixed effects and also allow for common correlated effects The impact of a change in public debt is also analysed using asymmetric panel ARDL method Our results indicate that an increase in government debt is negatively associated with economic growth in both the short and long-run

Critical Essay: The reconciliation of fraternal twins: Integrating the psychological and sociological approaches to ‘micro’ corporate social responsibility

Abstract: Aguinis and Glavas’ call for a deeper understanding of the microfoundations of corporate social responsibility has spurred a growing number of empirical micro-CSR (corporate social responsibility) ...

Implementation, adoption and perceptions of telemental health during the COVID-19 pandemic: a systematic review.

Abstract: BACKGROUND: Early in 2020, mental health services had to rapidly shift from face-to-face models of care to delivering the majority of treatments remotely (by video or phone call or occasionally messaging) due to the COVID-19 pandemic. This resulted in several challenges for staff and patients, but also in benefits such as convenience or increased access for people with impaired mobility or in rural areas. There is a need to understand the extent and impacts of telemental health implementation, and barriers and facilitators to its effective and acceptable use. This is relevant both to future emergency adoption of telemental health, and to debates on its future use in routine mental health care. OBJECTIVE: To investigate the adoption and impacts of telemental health approaches during the COVID-19 Pandemic, and facilitators and barriers to optimal implementation. METHODS: Four databases (PubMed, PsycINFO, CINAHL and Web of Science) were searched for primary research relating to remote working, mental health care, and the COVID-19 pandemic. Preprint servers were also searched. Results of studies were synthesised using framework synthesis. RESULTS: A total of 77 papers met our inclusion criteria. In most studies, the majority of contacts could be transferred to a remote form during the pandemic, and good acceptability to service users and clinicians tended to be reported, at least where the alternative to remote contacts was interrupting care. However, a range of impediments to dealing optimal care by this means were also identified. CONCLUSIONS: Implementation of telemental health allowed some continuing support to the majority of service users during the COVID-19 pandemic and has value in an emergency situation. However, not all service users can be reached by this means, and better evidence is now needed on long-term impacts on therapeutic relationships and quality of care, and on impacts on groups at risk of digital exclusion and how to mitigate these. CLINICALTRIAL:

A review of grout materials in geothermal energy applications

Abstract: Ground heat exchangers are surrounded by grout material, making it one of the most important components in geothermal energy applications since it significantly affects the system's thermal performance. The current study reviews the different types of grout materials and compares their thermophysical properties. The most critical parameter is the grout's thermal conductivity in which it always presents a proportional relation with the system's efficiency. Numerous factors are involved in this review to ascertain theier impact on the grouts’ performance such as flowability, shrinkage, moisture content, freezing, heat capacity, strength, permeability, solubility and thermal imbalance. The different grouts compared are bentonite, cement, sand, graphite, controlled low-strength material, dolomite, and phase change materials. The literature shows that phase change materials are the best choices of grouting since they can provide high storage capacity, stability and temperature uniformity. The major problem of such materials is their low thermal conductivity. Thus, it is recommended to use composite phase change materials to enhance their thermal conductivity and increase the storage/retrieval rate.

Human migration: the big data perspective

Abstract: How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants.

Confucian business model canvas in the Asia Pacific: a Yin-Yang harmony cognition to value creation and innovation

Abstract: From an integrative view of paradox and culture, this research aims to elucidate the impact of cultural heterogeneity on the compositional structure of business models (BMs) in the Asia Pacific by ...

Implementation, adoption and perceptions of telemental health during the COVID-19 pandemic: a systematic review

Abstract: Background Early in 2020, mental health services had to rapidly shift from face-to-face models of care to delivering the majority of treatments remotely (by video or phone call or occasionally messaging) due to the COVID-19 pandemic. This resulted in several challenges for staff and patients, but also in benefits such as convenience or increased access for people with impaired mobility or in rural areas. There is a need to understand the extent and impacts of telemental health implementation, and barriers and facilitators to its effective and acceptable use. This is relevant both to future emergency adoption of telemental health, and to debates on its future use in routine mental health care. Objective To investigate the adoption and impacts of telemental health approaches during the COVID-19 Pandemic, and facilitators and barriers to optimal implementation. Methods Four databases (PubMed, PsycINFO, CINAHL and Web of Science) were searched for primary research relating to remote working, mental health care, and the COVID-19 pandemic. Preprint servers were also searched. Results of studies were synthesised using framework synthesis. Results A total of 77 papers met our inclusion criteria. In most studies, the majority of contacts could be transferred to a remote form during the pandemic, and good acceptability to service users and clinicians tended to be reported, at least where the alternative to remote contacts was interrupting care. However, a range of impediments to dealing optimal care by this means were also identified. Conclusions Implementation of telemental health allowed some continuing support to the majority of service users during the COVID-19 pandemic and has value in an emergency situation. However, not all service users can be reached by this means, and better evidence is now needed on long-term impacts on therapeutic relationships and quality of care, and on impacts on groups at risk of digital exclusion and how to mitigate these.