To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Alcohol use disorder (AUD) is clinically heterogeneous. We examine its potential genetic heterogeneity as a function of sex, age, clinical features and mode of ascertainment.
In the Swedish population born 1932–1995 (n = 5 829 952), we examined the genetic risk profiles for AUD, major depression (MD), anxiety disorders, bipolar disorder, drug use disorder (DUD), attention deficit-hyperactivity disorder (ADHD) and criminal behavior (CB) in 361 124 cases of AUD subdivided by sex, age at onset (AAO), recurrence, mode of ascertainment and medical complications. Family genetic risk scores (FGRS), calculated from 1st to 5th-degree relatives controlling of cohabitation, assesses genetic risk from phenotypes in the family, not from DNA variants.
FGRS profiles differed modestly across sex with all scores higher in females. Differences were more pronounced for AAO and recurrence with the FGRS for AUD, DUD, ADHD and CB substantially higher in cases with early AAO or high recurrence rates. Genetic profiles differed considerably by mode of ascertainment, with higher FGRS for AUD and most other disorders in patients seen in hospital v. primary care settings. Cases of AUD with medical complications had higher FGRS for AUD. AUD cases comorbid with MD and DUD had higher FGRS risk for AUD, but this genetic may be less specific given increases in FGRS for multiple other disorders.
From a genetic perspective, AUD differs substantially as a function of AAO, recurrence, mode of ascertainment and patterns of comorbidity, suggesting caution in cross-sample comparisons of AUD cohorts that differ in these features.
Antisociality across adolescence and young adulthood puts individuals at high risk of developing a variety of problems. Prior research has linked antisociality to autonomic nervous system and endocrinological functioning. However, there is large heterogeneity in antisocial behaviors, and these neurobiological measures are rarely studied conjointly, limited to small specific studies with narrow age ranges, and yield mixed findings due to the type of behavior examined.
We harmonized data from 1489 participants (9–27 years, 67% male), from six heterogeneous samples. In the resulting dataset, we tested relations between distinct dimensions of antisociality and heart rate, pre-ejection period (PEP), respiratory sinus arrhythmia, respiration rate, skin conductance levels, testosterone, basal cortisol, and the cortisol awakening response (CAR), and test the role of age throughout adolescence and young adulthood.
Three dimensions of antisociality were uncovered: ‘callous-unemotional (CU)/manipulative traits’, ‘intentional aggression/conduct’, and ‘reactivity/impulsivity/irritability’. Shorter PEPs and higher testosterone were related to CU/manipulative traits, and a higher CAR is related to both CU/manipulative traits and intentional aggression/conduct. These effects were stable across age.
Across a heterogeneous sample and consistent across development, the CAR may be a valuable measure to link to CU/manipulative traits and intentional aggression, while sympathetic arousal and testosterone are additionally valuable to understand CU/manipulative traits. Together, these findings deepen our understanding of the fundamental mechanisms underlying different components of antisociality. Finally, we illustrate the potential of using current statistical techniques for combining multiple datasets to draw robust conclusions about biobehavioral associations.
It has been well established that depressive disorders including perinatal depression are very heterogeneous, which partly explain the ineffectiveness of available treatments for many patients. Recent innovations in data science can help elucidate the nature of perinatal depression especially the heterogeneity in its presentation.
The present study aime to elucidate heterogeneous subtypes of PND and assess the effectiveness of a multicomponent cognitive behavioral therapy (CBT) across heterogenous subtypes of PND.
This study was conducted in 2005 in two rural areas of Rawalpindi, Pakistan. Out of a total of 3,898 women, 903 pregnant women were identifed with PND (using DSM-IV) and randomly assigned to intervention and control group. Baseline assessments included interviewer admininstered Hamilton Depression Scale (HDS) and social risk factors. Follow-up assessments were conducted at 6 months and 12 months post-intervention. Principle component analysis was run to reduce dimensionality of the HDS. Two step cluster analysis was then run to elucidate subtypes of PND using the dimensional scores. Thereafter, effectiveness of CBT was compared across these subtypes of PND using multilevel modelling.
Principle component analysis revealed a four component solution for the Hamilton depression rating scale. Using these dimensional scores, cluster analysis (average silhouette= 0.5) revealed a parsimonius four cluster soultion of participants with mild PND symptoms (n=326); predominant sleep problems (n=311) c) predominant atypical symptoms (n=80) and d) comorbid depressive and anxiety symptoms (n=186). CBT yielded moderate effect sizes across all these subtypes of PND (cohen’s d > 0.8).
Multicomponent CBT is effective across hetergeneous presentations of PND.
The field of psychopathology is in a transformative phase, and is witnessing a renewed surge of interest in theoretical models of mental disorders. While many interesting proposals are competing for attention in the literature, they tend to focus narrowly on the proximate level of analysis and lack a broader understanding of biological function. In this paper, we present an integrative framework for mental disorders built on concepts from life history theory, and describe a taxonomy of mental disorders based on its principles, the fast–slow–defense model (FSD). The FSD integrates psychopathology with normative individual differences in personality and behavior, and allows researchers to draw principled distinctions between broad clusters of disorders, as well as identify functional subtypes within current diagnostic categories. Simulation work demonstrates that the model can explain the large-scale structure of comorbidity, including the apparent emergence of a general “p factor” of psychopathology. A life history approach also provides novel integrative insights into the role of environmental risk/protective factors and the developmental trajectories of various disorders.
Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics.
This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample.
We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients.
Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms.
Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.
This paper examines the associations between social participation and individual life satisfaction among older adults. It specifically considers the diversity of the practices and social inequalities among this population. For analyses, we used a large survey of individuals of 65 years and older conducted in 2011 in Switzerland (N = 2,727). The first set of linear regression analyses examines Diener's Satisfaction with Life Scale and its association with various indicators of social participation. While the second set of logistic regression addresses the issue of social inequalities by evaluating the impacts of gender, age group, region and education on social participation indicators that are significantly associated with the satisfaction with life score. Our results stressed the importance of combining multiple forms of participation for life satisfaction and shows that some forms are particularly meaningful: in particular, the involvement in associations, visitation of family or visitation of friends/acquaintances and church attendance. When inequalities among older adults are considered, having rich and varied social participation, being involved in associations and maintaining private sociability with non-kin appear more elitist. While institutionalised and/or private sociability types of participation appear particularly significant for older adults’ life satisfaction, the most traditional integration forms – i.e. family and religions – are crucial for the more vulnerable. Implications for active ageing was equally discussed as well.
Religion and politics are connected. They have been used at various times to promote ethnic sentiments and provincial agendas, all of which end up tearing apart the country's economy and political stability. Religion remains a vibrant tool for political manipulation and the mobilization of electorates. The chapter argues that politics must not be over-determined by religion if the country wants to live in peace and develop.
Huang and Mendoza’s introduction to the fourth volume of Asian American Literatures in Transition offers a refresher on Lisa Lowe’s formative critical work, Immigrant Acts (1996), published at the beginning of the time period covered in this volume. The authors reframe Lowe’s terms “heterogeneity,” “hybridity,” and “multiplicity” within several watershed moments affecting Asian Americans and other groups in the USA: including the Defense of Marriage Act (1996), the September 11 attacks, the decriminalization of sodomy (2003), the COVID pandemic, and the Black Lives Matter movement. While many of these events exacerbated the vulnerability and precarity of some Asian American groups, the turbulence of the time fueled the Asian American literary imagination as writers in this period drew on more representational strategies for their literary experimentations than in previous periods. This volume covers precisely these tensions: artistic proliferations in the face of injustice, recognition in the face of social erasures, innovation in the face of neoliberal white supremacy’s monopoly on wealth and violence.
In rapidly growing and high-burden urban centres, identifying tuberculosis (TB) transmission hotspots and understanding the potential impact of interventions can inform future control and prevention strategies. Using data on local demography, TB reports and patient reporting patterns in Dhaka South City Corporation (DSCC) and Dhaka North City Corporation (DNCC), Bangladesh, between 2010 and 2017, we developed maps of TB reporting rates across wards in DSCC and DNCC and identified wards with high rates of reported TB (i.e. ‘hotspots’) in DSCC and DNCC. We developed ward-level transmission models and estimated the potential epidemiological impact of three TB interventions: active case finding (ACF), mass preventive therapy (PT) and a combination of ACF and PT, implemented either citywide or targeted to high-incidence hotspots. There was substantial geographic heterogeneity in the estimated TB incidence in both DSCC and DNCC: incidence in the highest-incidence wards was over ten times higher than in the lowest-incidence wards in each city corporation. ACF, PT and combined ACF plus PT delivered to 10% of the population reduced TB incidence by a projected 7%–9%, 13%–15% and 19%–23% over five years, respectively. Targeting TB hotspots increased the projected reduction in TB incidence achieved by each intervention 1.4- to 1.8-fold. The geographical pattern of TB notifications suggests high levels of ongoing TB transmission in DSCC and DNCC, with substantial heterogeneity at the ward level. Interventions that reduce transmission are likely to be highly effective and incorporating notification data at the local level can further improve intervention efficiency.
Dietary interventions did not prevent depression onset nor reduced depressive symptoms in a large multi-center randomized controlled depression prevention study (MooDFOOD) involving overweight adults with subsyndromal depressive symptoms. We conducted follow-up analyses to investigate whether dietary interventions differ in their effects on depressive symptom profiles (mood/cognition; somatic; atypical, energy-related).
Baseline, 3-, 6-, and 12-month follow-up data from MooDFOOD were used (n = 933). Participants received (1) placebo supplements, (2) food-related behavioral activation (F-BA) therapy with placebo supplements, (3) multi-nutrient supplements (omega-3 fatty acids and a multi-vitamin), or (4) F-BA therapy with multi-nutrient supplements. Depressive symptom profiles were based on the Inventory of Depressive Symptomatology.
F-BA therapy was significantly associated with decreased severity of the somatic (B = −0.03, p = 0.014, d = −0.10) and energy-related (B = −0.08, p = 0.001, d = −0.13), but not with the mood/cognition symptom profile, whereas multi-nutrient supplementation was significantly associated with increased severity of the mood/cognition (B = 0.05, p = 0.022, d = 0.09) and the energy-related (B = 0.07, p = 0.002, d = 0.12) but not with the somatic symptom profile.
Differentiating depressive symptom profiles indicated that food-related behavioral interventions are most beneficial to alleviate somatic symptoms and symptoms of the atypical, energy-related profile linked to an immuno-metabolic form of depression, although effect sizes were small. Multi-nutrient supplements are not indicated to reduce depressive symptom profiles. These findings show that attention to clinical heterogeneity in depression is of importance when studying dietary interventions.
This chapter explores the submerged yet generative relationship of influence between the poetries of Louis MacNeice (1907-63) and Seamus Heaney (1939-2013) – two major Northern Irish poets of very different backgrounds and primary aesthetic dispositions. Notwithstanding their respective signature identifications with modernity, flux and hybridity on the one hand and tradition, continuity and community on the other, the chapter proposes that Heaney turns to MacNeice in order to seek out new directions for his own growth as artist. The chapter centrally argues that these two poets share a common concern with renewing the relationship between immutable reality and the alterity of dream-life. In consequence, their engagements with territorial conflict lead both poets to open vital space for non-conformity with the totalizing logic of enforced national destiny. Within this space, MacNeice and Heaney offer a linked vision of creativity renewed rather than foreclosed through recognizing human frailty in the face of mortality.
Our study plans to quantify the effect of higher temperatures on different critical Turkish health outcomes mainly to chart future developments and to identify locations in Turkey that may be potential vulnerable hotspots. The general structure of the temperature mortality function was estimated with different fixed-level effects, with a specific focus on the mortality effect of maximum apparent temperature. Regional models were fitted to pinpoint the thresholds where the temperature–mortality relation changes, thus investigating whether the thresholds are determined nationally or regionally. The future patterns were estimated by extrapolating from future temperature trends: analyzing possible future mortality trends under the restricting assumption of minimal acclimation. Using the fixed effect regression structure, social and developmental variables acting as heat effect modifiers were also identified. In the largest dataset, the initial fixed effect regression specification supports the hypothesis summarized by the U-shaped relationship between temperature and mortality. This is a first corroboration for Turkish climate and health research. In addition, intermediation effects were substantiated for the level of urbanization and population density, and the human development and health development within provinces. Regional heterogeneity is substantiated by the mortality–temperature relationship and the significant threshold deviations from the national average.
Autism spectrum disorder (autism) is a heterogeneous group of neurodevelopmental conditions characterized by early childhood-onset impairments in communication and social interaction alongside restricted and repetitive behaviors and interests. This review summarizes recent developments in human genetics research in autism, complemented by epigenetic and transcriptomic findings. The clinical heterogeneity of autism is mirrored by a complex genetic architecture involving several types of common and rare variants, ranging from point mutations to large copy number variants, and either inherited or spontaneous (de novo). More than 100 risk genes have been implicated by rare, often de novo, potentially damaging mutations in highly constrained genes. These account for substantial individual risk but a small proportion of the population risk. In contrast, most of the genetic risk is attributable to common inherited variants acting en masse, each individually with small effects. Studies have identified a handful of robustly associated common variants. Different risk genes converge on the same mechanisms, such as gene regulation and synaptic connectivity. These mechanisms are also implicated by genes that are epigenetically and transcriptionally dysregulated in autism. Major challenges to understanding the biological mechanisms include substantial phenotypic heterogeneity, large locus heterogeneity, variable penetrance, and widespread pleiotropy. Considerable increases in sample sizes are needed to better understand the hundreds or thousands of common and rare genetic variants involved. Future research should integrate common and rare variant research, multi-omics data including genomics, epigenomics, and transcriptomics, and refined phenotype assessment with multidimensional and longitudinal measures.
The symptoms of obsessive−compulsive disorder (OCD) are highly heterogeneous and it is unclear what is the optimal way to conceptualize this heterogeneity. This study aimed to establish a comprehensive symptom structure model of OCD across the lifespan using factor and network analytic techniques.
A large multinational cohort of well-characterized children, adolescents, and adults diagnosed with OCD (N = 1366) participated in the study. All completed the Dimensional Yale-Brown Obsessive−Compulsive Scale, which contains an expanded checklist of 87 distinct OCD symptoms. Exploratory and confirmatory factor analysis were used to outline empirically supported symptom dimensions, and interconnections among the resulting dimensions were established using network analysis. Associations between dimensions and sociodemographic and clinical variables were explored using structural equation modeling (SEM).
Thirteen first-order symptom dimensions emerged that could be parsimoniously reduced to eight broad dimensions, which were valid across the lifespan: Disturbing Thoughts, Incompleteness, Contamination, Hoarding, Transformation, Body Focus, Superstition, and Loss/Separation. A general OCD factor could be included in the final factor model without a significant decline in model fit according to most fit indices. Network analysis showed that Incompleteness and Disturbing Thoughts were most central (i.e. had most unique interconnections with other dimensions). SEM showed that the eight broad dimensions were differentially related to sociodemographic and clinical variables.
Future research will need to establish if this expanded hierarchical and multidimensional model can help improve our understanding of the etiology, neurobiology and treatment of OCD.
Chapter Three, “Crowds and Transformation,” synthesizes concepts of self-recovery, play, and collective intellect to explore what transformative tools and practices crowds were developing (in modernist fictional worlds) in order to identify and represent themselves, or to have as tactical weapons during their conflicts with elite authority. Conventional identity is creatively reworked by disarticulated performances such as Clarissa’s or the unnamed Captain in The Secret Sharer. The chapter maps mechanisms that produce modernity’s porous and transmissible social mind, exemplified in readings of Jacob’s Room and “Ithaca,” for example. Historical examples of street demonstrations and popular movements in the first decades of the twentieth century in England and Ireland are compared with readings of the permeable and suggestible crowds of “Wandering Rocks” and Wyndham Lewis’ writings, to differentiate what the book identifies as rising crowds from Lewis’ crowds of “extinction.” Finally, the chapter transitions to the concept of crowdedness as an ethical experience.
The large-scale structure of the Earth can be extracted with seismic tomography, but the finer scales of variation within the Earth lie beyond any capacity for direct imaging. Nevertheless, the scattered wavefield produced by small-scale heterogeneity contains important information on structure. We consider the representation of variations in Earth structure on scales from the global to the regional, and discuss ways in which numerical simulations and inversions can exploit data with differing station density to provide maximum resolution of structure. We contrast deterministic and stochastic (parametric) representations of heterogeneity, and examine the way in which ensemble results can be exploited for Earth structure that is time invariant. We also consider the way that effective media, with simpler structure, can be extracted from complex models by the process of wavespeed upscaling
Exploiting Seismic Waveforms introduces a range of recent developments in seismology including the application of correlation techniques, understanding of multi-scale heterogeneity and the extraction of structure and source information by seismic waveform inversion. It provides a full treatment of correlation methods for seismic noise and event signals, and develops inverse methods for both sources and structure. Higher frequency components of seismograms are frequently neglected, or removed by filtering, but they contain information about seismic structure on scales that cannot be revealed by seismic tomography. Sufficient computational resources are now available for waveform inversion for 3-D structure to be a practical procedure and this book describes suitable algorithms and examples reflecting current best practice. Intended for students and researchers in seismology, this book provides a physical understanding of seismic waveforms and the way that different aspects of the seismic wavefield are revealed by the way that seismic data are handled.
In March 2020, the government of the United Kingdom advised all people aged 70 and above to self-isolate stringently for a minimum of 12 weeks in response to COVID-19. The British Society of Gerontology criticised the government for ignoring individual differences, deeming the approach ageist. Former British Geriatrics Society president David Oliver contested accusations of ageism, arguing that the approach was pragmatic discrimination based on epidemiological evidence. This debate catalyses core gerontological tensions regarding ageism, discrimination, categorisation and heterogeneity. A critical realist perspective reveals that both the government and gerontology are struggling to negotiate these irresolvable tensions. Contrary to the binary debate, age-based isolation simultaneously represents pragmatic discrimination and value-driven ageism. However, it does so partly because it relies on a chronologic epistemology that positions age as a potent biosocial axis of meaningful difference, thereby reflecting gerontology's own ageism. The ethical purism of gerontological accusations of ageism is thus somewhat misplaced, potentially obscuring an opportunity for reflection on value-laden engagements with age in social research.
Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results.
Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes.
The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased.
SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.
We develop a model of strategic network formation of collaborations to analyze the consequences of an understudied but consequential form of heterogeneity: differences between actors in the form of their production functions. We also address how this interacts with resource heterogeneity, as a way to measure the impact actors have as potential partners on a collaborative project. Some actors (e.g., start-up firms) may exhibit increasing returns to their investment into collaboration projects, while others (e.g., established firms) may face decreasing returns. Our model provides insights into how actor heterogeneity can help explain well-observed collaboration patterns. We show that if there is a direct relation between increasing returns and resources, start-ups exclude mature firms and networks become segregated by types of production function, portraying dominant group architectures. On the other hand, if there is an inverse relation between increasing returns and resources, networks portray core-periphery architectures, where the mature firms form a core and start-ups with low-resources link to them.