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De Fruyt and De Clercq (this volume) and Sellbom (this volume) raise important issues surrounding the use of a five-factor model (FFM) of personality to conceptualize, assess, and diagnose personality disorder including how one includes a measure of impairment, the level of abstraction that is optimal (domains vs. facets), and the need for the development of formal test manuals, normative data, and means for identifying non-credible responding. In this response, the authors note their agreement with De Fruyt and De Clercq regarding the importance of assessing impairment but note that (a) it is already included to a large degree in the assessment of pathological FFM traits and (b) that they would prefer an approach that focuses explicitly on difficulties in occupational and social functioning. As to Sellbom’s comments suggesting that further work is necessary with regard to the development of test manuals, normative databases, and measures of valid responding – the authors agree and note some of the obstacles including the need for funding for the collection of normative data (and what consensus as to the kind – clinical only; community only; both) and development of test manuals. As to measures of credible responding, they note that many of these exist already for the family of FFM PD scales that they helped create and are aware of similar efforts for other popular measures of pathological traits.
The use of dimensional personality traits with explicit ties to general or normative personality has gone mainstream with instantiation in the most recent version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the soon to be released 11th revision of the International Classification of Diseases (ICD-11). Much of the theoretical and empirical work that supports the transition to dimensional trait-based models of personality disorder has used the prominent five-factor model of personality to do so, which suggests that five basic dimensions capture much of the important and reliable personality variance: neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. This chapter reviews this literature and demonstrates how general and pathological five-factor models of personality are parsimonious, valid, and useful. The authors believe that the use of such models for the diagnosis of personality disorder represents a much needed and empirically supported movement to integrate normative and pathological personality.
Address the future of innovative reproductive technologies with experts in the fields of IVF, fertility preservation and laboratory advances. This essential resource examines the changing roles of IVF, and moves beyond the basics of reproductive medicine. This book introduces the optimization of care, to improve patient outcomes, whilst facing ethical challenges that accompany new technologies, and applying the patient-centered care model to improve both patient and staff retention. By showcasing the future of the field in terms of clinical practice and innovative laboratory technologies, this guide will support clinics worldwide to provide high-quality customer experience, maintaining a competitive edge, following increasing standardization of clinical and laboratory protocols. This invaluable guide features chapters on patient evaluation, predictive modelling, advances in pharmacology, and laboratories of the future. Written by research and clinical leaders from around the world, it describes ground-breaking innovative treatments and technologies, encompassing the care model in a holistic way.
Residential mobility during upbringing, and especially adolescence, is associated with multiple negative mental health outcomes. However, whether associations are confounded by unmeasured familial factors, including genetic liability, is unclear.
We used a population-based case–cohort study to assess whether polygenic risk scores (PRSs) for schizophrenia, bipolar disorder and major depression were associated with mobility from ages 10–14 years, and whether PRS and parental history of mental disorder together explained associations between mobility and each disorder.
Information on cases (n = 4207 schizophrenia, n = 1402 bipolar disorder, n = 18 215 major depression) and a random population sample (n = 17 582), born 1981–1997, was linked between Danish civil and psychiatric registries. Genome-wide data were obtained from the Danish Neonatal Screening Biobank and PRSs were calculated based on results of separate, large meta-analyses.
PRSs for schizophrenia and major depression were weakly associated with moving once (odds ratio 1.07, 95% CI 1.00–1.16; and odds ratio 1.10, 95% CI 1.04–1.17, respectively), but not twice or three or more times. Mobility was positively associated with each disorder, with more moves associated with greater risk. Adjustment for PRS produced slight reductions in the magnitude of associations. Adjustment for PRS and parental history of mental disorder together reduced estimates by 5–11%. In fully adjusted models mobility was associated with all three disorders; hazard ratios ranged from 1.33 (95% CI 1.08–1.62; one move and bipolar disorder) to 3.05 (95% CI 1.92–4.86; three or more moves and bipolar disorder).
Associations of mobility with schizophrenia, bipolar disorder and depression do not appear to be attributable to genetic liability as measured here. Potential familial confounding of mobility associations may be predominantly environmental in nature.
Heart disease is the leading cause of death in schizophrenia. However, there has been little research directly examining cardiac function in schizophrenia.
To investigate cardiac structure and function in individuals with schizophrenia using cardiac magnetic resonance imaging (CMR) after excluding medical and metabolic comorbidity.
In total, 80 participants underwent CMR to determine biventricular volumes and function and measures of blood pressure, physical activity and glycated haemoglobin levels. Individuals with schizophrenia (‘patients’) and controls were matched for age, gender, ethnicity and body surface area.
Patients had significantly smaller indexed left ventricular (LV) end-diastolic volume (effect size d = −0.82, P = 0.001), LV end-systolic volume (d = −0.58, P = 0.02), LV stroke volume (d = −0.85, P = 0.001), right ventricular (RV) end-diastolic volume (d = −0.79, P = 0.002), RV end-systolic volume (d = −0.58, P = 0.02), and RV stroke volume (d = −0.87, P = 0.001) but unaltered ejection fractions relative to controls. LV concentricity (d = 0.73, P = 0.003) and septal thickness (d = 1.13, P < 0.001) were significantly larger in the patients. Mean concentricity in patients was above the reference range. The findings were largely unchanged after adjusting for smoking and/or exercise levels and were independent of medication dose and duration.
Individuals with schizophrenia show evidence of concentric cardiac remodelling compared with healthy controls of a similar age, gender, ethnicity, body surface area and blood pressure, and independent of smoking and activity levels. This could be contributing to the excess cardiovascular mortality observed in schizophrenia. Future studies should investigate the contribution of antipsychotic medication to these changes.
A new carbon isotope record for two high-latitude sedimentary successions that span the Jurassic–Cretaceous boundary interval in the Sverdrup Basin of Arctic Canada is presented. This study, combined with other published Arctic data, shows a large negative isotopic excursion of organic carbon (δ13Corg) of 4‰ (V-PDB) and to a minimum of −30.7‰ in the probable middle Volgian Stage. This is followed by a return to less negative values of c. −27‰. A smaller positive excursion in the Valanginian Stage of c. 2‰, reaching maximum values of −24.6‰, is related to the Weissert Event. The Volgian isotopic trends are consistent with other high-latitude records but do not appear in δ13Ccarb records of Tethyan Tithonian strata. In the absence of any obvious definitive cause for the depleted δ13Corg anomaly, we suggest several possible contributing factors. The Sverdrup Basin and other Arctic areas may have experienced compositional evolution away from open-marine δ13C values during the Volgian Age due to low global or large-scale regional sea levels, and later become effectively coupled to global oceans by Valanginian time when sea level rose. A geologically sudden increase in volcanism may have caused the large negative δ13Corg values seen in the Arctic Volgian records but the lack of precise geochronological age control for the Jurassic–Cretaceous boundary precludes direct comparison with potentially coincident events, such as the Shatsky Rise. This study offers improved correlation constraints and a refined C-isotope curve for the Boreal region throughout latest Jurassic and earliest Cretaceous time.
To develop and validate the Discrepancy-based Evidence for Loss of Thinking Abilities (DELTA) score. The DELTA score characterizes the strength of evidence for cognitive decline on a continuous spectrum using well-established psychometric principles for improving detection of cognitive changes.
DELTA score development used neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (two tests each from Memory, Executive Function, and Language domains). We derived regression-based normative reference scores using age, gender, years of education, and word-reading ability from robust cognitively normal ADNI participants. Discrepancies between predicted and observed scores were used for calculating the DELTA score (range 0–15). We validated DELTA scores primarily against longitudinal Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Functional Activities Questionnaire (FAQ) scores (baseline assessment through Year 3) using linear mixed models and secondarily against cross-sectional Alzheimer’s biomarkers.
There were 1359 ADNI participants with calculable baseline DELTA scores (age 73.7 ± 7.1 years, 55.4% female, 100% white/Caucasian). Higher baseline DELTA scores (stronger evidence of cognitive decline) predicted higher baseline CDR-SOB (ΔR2 = .318) and faster rates of CDR-SOB increase over time (ΔR2 = .209). Longitudinal changes in DELTA scores tracked closely and in the same direction as CDR-SOB scores (fixed and random effects of mean + mean-centered DELTA, ΔR2 > .7). Results were similar for FAQ scores. High DELTA scores predicted higher PET-Aβ SUVr (ρ = 324), higher CSF-pTau/CSF-Aβ ratio (ρ = .460), and demonstrated PPV > .9 for positive Alzheimer’s disease biomarker classification.
Data support initial development and validation of the DELTA score through its associations with longitudinal functional changes and Alzheimer’s biomarkers. We provide several considerations for future research and include an automated scoring program for clinical use.
Aging is often associated with a progressive decline of cognitive functions, due in part to the susceptibility of specific brain regions to stressors of aging. However, chronological age is a poor predictor of cognition. Cognitive decline is variable in terms of onset and progression, suggesting that biological age, due to differences in biological mechanisms that regulate vulnerability, is a better predictor of cognitive decline. As with humans, animal models exhibit variability in age-related cognitive decline, and this variability has been employed to determine biomarkers and mechanisms of cognitive impairment. Based on these animal models, theories of age-related cognitive decline have evolved. Recent work has focused on senescent physiology, rather than cell death associated with neurodegenerative disease. The results suggest that age-related alterations in redox stress modify Ca2+ regulation to alter learning and memory mechanisms, as well as signaling cascades from the synapse to the nucleus. Furthermore, the stressors of aging, senescent physiology, and environmental factors interact with epigenetic mechanisms contributing variability in gene transcription, resulting in variability in resiliency, onset, and the progression of the aging phenotype.
Cyberpsychological research suggests that we are increasingly merging with our technology (Parsons, 2017; see also Chapter 3). Director of engineering at Google and chancellor of Singularity University, Ray Kurzweil (2010) has gone so far as predicting that, by the 2020s, we will have reverse-engineered the entire brain. Predictions abound related to the potential impact of nanobots on our consciousness, but we are still a long way from transhumanist imaginations about upgrading our brains with implantable computer chips.
The effortlessly available online knowledgebase found in the Internet has essentially succeeded other media in terms of acquiring knowledge for daily life. In this digital age, persons in Western industrialized countries are progressively exhibiting themselves online and communicating with others in disembodied contexts that span time and space.
On Thursday, July 26, 2018, Facebook experienced the largest single-day drop in value in Wall Street history. On that day, Facebook’s market value plummeted by more than $100 billion (down 19 percent). Why did this happen? While part of this reflects declining growth in users and revenue, a good deal of the loss can be attributed to Facebook’s years of privacy lapses. Facebook’s principal approach to revenue generation violates the ethical principle of privacy.
In this chapter, there is an emphasis on describing some of the ethical concerns that may arise from research, clinical applications, and even personal use of virtual reality and related technologies. Throughout, there will be attempts to offer straightforward recommendations for optimal outcomes and minimal risks.
In developed countries, older adult populations are multiplying at a notable rate due to enhanced healthcare, technological access, and enriched living conditions (Bleakley et al., 2015). In fact, there are some projections suggesting that, in the next few decades, a fifth of the US population will be sixty-five years of age or older (Blazer, Maslow, & Eden, 2012; Jacobsen et al., 2011).