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This handbook introduces the reader to the thought-provoking research on the neural foundations of human intelligence. Written for undergraduate or graduate students, practitioners, and researchers in psychology, cognitive neuroscience, and related fields, the chapters summarize research emerging from the rapidly developing neuroscience literature on human intelligence. The volume focusses on theoretical innovation and recent advances in the measurement, modelling, and characterization of the neurobiology of intelligence differences, especially from brain imaging studies. It summarizes fundamental issues in the characterization and measurement of general intelligence, and surveys multidisciplinary research consortia and large-scale data repositories for the study of general intelligence. A systematic review of neuroimaging methods for studying intelligence is provided, including structural and diffusion-weighted MRI techniques, functional MRI methods, and spectroscopic imaging of metabolic markers of intelligence.
We discuss whole-child development, learning, and thriving through a dynamic systems theory lens that focuses on the United States and includes an analysis of historical challenges in the American public education system, including inequitable resources, opportunities, and outcomes. To transform US education systems, developmental and learning scientists, educators, policymakers, parents, and communities must apply the knowledge they have today to 1. challenge the assumptions and goals that drove the design of the current US education system, 2. articulate a revised, comprehensive definition of whole-child development, learning, and thriving that accepts rather than simplifies how human beings develop, 3. create a profound paradigm shift in how the purpose of education is described in the context of social, cultural, and political forces, including the impacts of race, privilege, and bias and 4. describe a new dynamic 'language' for measurement of both the academic competencies and the full set of 21st century skills.
This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care.
Methods
We searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted.
Results
Twelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3–4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3–4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions.
Conclusions
When adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression.
A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls.
Methods
This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate.
Results
ES-SCZ was associated with the GAF dimensions in patients (symptom: B = −1.53, p-value = 0.001; disability: B = −1.44, p-value = 0.001), siblings (symptom: B = −3.07, p-value < 0.001; disability: B = −2.52, p-value < 0.001), and healthy controls (symptom: B = −1.50, p-value < 0.001; disability: B = −1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group.
Conclusions
Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management.
Investigate an outbreak of coronavirus disease 2019 (COVID-19) among operating room staff utilizing contact tracing, mass testing for severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and environmental sampling.
Operating room staff with positive SARS-CoV-2 molecular testing.
Methods:
Epidemiologic and environmental investigations were conducted including contact tracing, environmental surveys, and sampling and review of the operating room schedule for staff-to-staff, staff-to-patient, and patient-to-staff SARS-CoV-2 transmission.
Results:
In total, 24 healthcare personnel (HCP) tested positive for SARS-CoV-2, including nurses (29%), surgical technologists (25%), and surgical residents (16%). Moreover, 19 HCP (79%) reported having used a communal area, most commonly break rooms (75%). Overall, 20 HCP (83%) reported symptomatic disease. In total, 72 environmental samples were collected from communal areas for SARS-CoV-2 genomic testing; none was positive. Furthermore, 236 surgical cases were reviewed for transmission: 213 (90%) had negative preoperative SARS-CoV-2 testing, 21 (9%) had a positive test on or before the date of surgery, and 2 (<1%) did not have a preoperative test performed. In addition, 40 patients underwent postoperative testing (mean, 13 days to postoperative testing), and 2 returned positive results. Neither of these 2 cases was linked to our outbreak.
Conclusions:
Complacency in infection control practices among staff during peak community transmission of SARS-CoV-2 is believed to have driven staff-to-staff transmission. Prompt identification of the outbreak led to rapid interventions, ultimately allowing for uninterrupted surgical service.
To describe a pilot project infection prevention and control (IPC) assessment conducted in skilled nursing facilities (SNFs) in New York State (NYS) during a pivotal 2-week period when the region became the nation’s epicenter for coronavirus disease 2019 (COVID-19).
Design:
A telephone and video assessment of IPC measures in SNFs at high risk or experiencing COVID-19 activity.
Participants:
SNFs in 14 New York counties, including New York City.
Intervention:
A 3-component remote IPC assessment: (1) screening tool; (2) telephone IPC checklist; and (3) COVID-19 video IPC assessment (ie, “COVIDeo”).
Results:
In total, 92 SNFs completed the IPC screening tool and checklist: 52 (57%) were conducted as part COVID-19 investigations, and 40 (43%) were proactive prevention-based assessments. Among the 40 proactive assessments, 14 (35%) identified suspected or confirmed COVID-19 cases. COVIDeo was performed in 26 (28%) of 92 assessments and provided observations that other tools would have missed: personal protective equipment (PPE) that was not easily accessible, redundant, or improperly donned, doffed, or stored and specific challenges implementing IPC in specialty populations. The IPC assessments took ∼1 hour each and reached an estimated 4 times as many SNFs as on-site visits in a similar time frame.
Conclusions:
Remote IPC assessments by telephone and video were timely and feasible methods of assessing the extent to which IPC interventions had been implemented in a vulnerable setting and to disseminate real-time recommendations. Remote assessments are now being implemented across New York State and in various healthcare facility types. Similar methods have been adapted nationally by the Centers for Disease Control and Prevention.