Learn 2 Learn: Enriching Student Success Through Metacognitive School-Based Intervention - A Developmental Perspective

Metacognition is the awareness and comprehension of one’s own way of thinking. It is one of three components of self-regulated learning, the other two being cognition and motivation. Self-regulated learning and metacognitive skill have been found to enhance student learning and achievement (Joseph, 2009). This research study examined the effect of metacognitive training on the self-regulation and academic performance of middle-school students in a social studies classroom. Experimental intervention sessions for sixth and eighth grade children were designed and executed to enrich metacognitive skills and were modeled after Ambrose et al.’s (2010) five-step model of metacognition. Two randomly assigned classes from both the sixth and eighth grades functioned as the experimental group, receiving metacognitive interventions called Learn 2 Learn, while another two randomly assigned classes in both grade levels acted as the control groups (Know How 2-HI School or College Knowledge), receiving information on educational transitions and/or career pathways. Students’ levels of metacognition and motivation were measured with pre- and post- quantitative and qualitative assessments. Additionally, student performance was assessed based on student grades from the first, second, and third marking periods. Contrary to predictions, there was no intervention effect on students’ metacognition found from the quantitative measure of metacognition or student grades, although there was a significant intervention effect and a significant intervention by time by grade level interaction for the qualitative measure of metacognition. All measures of metacognition were positively correlated with grades. In addition, it was found that sixth grade students consistently had higher levels of metacognition, motivation, and academic performance than did the eighth grade students. This study hoped to chart any developmental changes in metacognition between lower- and upper-middle school students

Effect of Internet-Based Cognitive Behavioral Humanistic and Interpersonal Training vs Internet-Based General Health Education on Adolescent Depression in Primary Care

Importance: Although 13% to 20% of American adolescents experience a depressive episode annually, no scalable primary care model for adolescent depression prevention is currently available. Objective: To study whether competent adulthood transition with cognitive behavioral humanistic and interpersonal training (CATCH-IT) lowers the hazard for depression in at-risk adolescents identified in primary care, as compared with a general health education (HE) attention control. Design, Setting, and Participants: This multicenter, randomized clinical trial, a phase 3 single-blind study, compares CATCH-IT with HE. Participants were enrolled from 2012 to 2016 and assessed at 2, 6, 12, 18, and 24 months postrandomization in a primary care setting. Eligible adolescents were aged 13 to 18 years with subsyndromal depression and/or history of depression and no current depression diagnosis or treatment. Of 2250 adolescents screened for eligibility, 446 participants completed the baseline interview, and 369 were randomized into CATCH-IT (n = 193) and HE (n = 176). Interventions: The internet-based intervention, CATCH-IT, is a 20-module (15 adolescent modules and 5 parent modules) online psychoeducation course that includes a parent program, supported by 3 motivational interviews. Main Outcomes and Measures: Time to event for depressive episode; depressive symptoms at 6 months. Results: Of 369 participants (mean [SD] age, 15.4 [1.5] years; 251 women [68%]) included in this trial, 193 were randomized into CATCH-IT and 176 into HE. Among these participants, 28% had both a past episode and subsyndromal depression; 12% had a past episode only, 59% had subsyndromal depression only, and 1% had borderline subsyndromal depression. The outcome of time to event favored CATCH-IT but was not significant with intention-to-treat analyses (unadjusted hazard ratio [HR], 0.59; 95% CI, 0.27-1.29; P = .18; adjusted HR, 0.53; 95% CI, 0.23-1.23; P = .14). Adolescents with higher baseline Center for Epidemiologic Studies Depression scale (CES-D ) scores showed a significantly stronger effect of CATCH-IT on time to event relative to those with lower baseline scores (HR 0.82; 95% CI, 0.67-0.99; P = .04). For example, the hazard ratio for a CES-D score of 15 was 0.20 (95% CI, 0.05-0.77), compared with a hazard ratio of 1.44 (95% CI, 0.41-5.03) for a CES-D score of 5. In both CATCH-IT and HE groups, depression symptoms declined and functional scores increased. Conclusions and Relevance: For preventing depressive episodes CATCH-IT may be better than HE for at-risk adolescents with subsyndromal depression. Also CATCH-IT may be a scalable approach to prevent depressive episodes in adolescents in primary care

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Effect of Internet-Based Cognitive Behavioral Humanistic and Interpersonal Training vs Internet-Based General Health Education on Adolescent Depression in Primary Care: A Randomized Clinical Trial

Importance: Although 13% to 20% of American adolescents experience a depressive episode annually, no scalable primary care model for adolescent depression prevention is currently available. Objective: To study whether competent adulthood transition with cognitive behavioral humanistic and interpersonal training (CATCH-IT) lowers the hazard for depression in at-risk adolescents identified in primary care, as compared with a general health education (HE) attention control. Design, Setting, and Participants: This multicenter, randomized clinical trial, a phase 3 single-blind study, compares CATCH-IT with HE. Participants were enrolled from 2012 to 2016 and assessed at 2, 6, 12, 18, and 24 months postrandomization in a primary care setting. Eligible adolescents were aged 13 to 18 years with subsyndromal depression and/or history of depression and no current depression diagnosis or treatment. Of 2250 adolescents screened for eligibility, 446 participants completed the baseline interview, and 369 were randomized into CATCH-IT (n = 193) and HE (n = 176). Interventions: The internet-based intervention, CATCH-IT, is a 20-module (15 adolescent modules and 5 parent modules) online psychoeducation course that includes a parent program, supported by 3 motivational interviews. Main Outcomes and Measures: Time to event for depressive episode; depressive symptoms at 6 months. Results: Of 369 participants (mean [SD] age, 15.4 [1.5] years; 251 women [68%]) included in this trial, 193 were randomized into CATCH-IT and 176 into HE. Among these participants, 28% had both a past episode and subsyndromal depression; 12% had a past episode only, 59% had subsyndromal depression only, and 1% had borderline subsyndromal depression. The outcome of time to event favored CATCH-IT but was not significant with intention-to-treat analyses (unadjusted hazard ratio [HR], 0.59; 95% CI, 0.27-1.29; P =.18; adjusted HR, 0.53; 95% CI, 0.23-1.23; P =.14). Adolescents with higher baseline Center for Epidemiologic Studies Depression scale (CES-D10) scores showed a significantly stronger effect of CATCH-IT on time to event relative to those with lower baseline scores (HR 0.82; 95% CI, 0.67-0.99; P =.04). For example, the hazard ratio for a CES-D10score of 15 was 0.20 (95% CI, 0.05-0.77), compared with a hazard ratio of 1.44 (95% CI, 0.41-5.03) for a CES-D10score of 5. In both CATCH-IT and HE groups, depression symptoms declined and functional scores increased. Conclusions and Relevance: For preventing depressive episodes CATCH-IT may be better than HE for at-risk adolescents with subsyndromal depression. Also CATCH-IT may be a scalable approach to prevent depressive episodes in adolescents in primary care. Trial Registration: ClinicalTrials.gov Identifier: NCT01893749</p

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program.

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828 = 53 and nrs505922 = 59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p = 1.32 x 10-199), and thrombosis ORrs505922 1.33, p = 2.2 x10-265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10-191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10-12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10-23, lupus OR 0.84, p = 3.97 x 10-06. PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10-13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.We are grateful to the Host Genetic Initiative for making their data publicly available (full acknowledgements can be found here: https://www.covid19hg.org/acknowledgements/). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award #MVP035. This research was also supported by additional Department of Veterans Affairs awards grant #MVP001. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. Full acknowledgements for the VA Million Veteran Program COVID-19 Science Initiative can be found in the supplementary methods. C.G. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 754490 – MINDED project. A.G., P.B. and A.R.L. are funded by the Member States of the European Molecular Biology Laboratory (EMBL). I.B.- H. received funding from Open Targets (grant agreement OTAR-044). The Fenland Study (10.22025/2017.10.101.00001) is funded by the Medical Research Council (MC_UU_12015/1); we are grateful to all the volunteers and to the General Practitioners and practice staff for assistance with recruitment; we thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams; we further acknowledge support for genomics from the Medical Research Council (MC_PC_13046); proteomic measurements were supported and governed by a collaboration agreement between the University of Cambridge and Somalogic. J.E.P. is supported by UKRI Innovation Fellowship at Health Data Research UK (MR/S004068/2). L.R., N.H. and C.L. are supported by the Swedish Research Council. E.A. was supported by the EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart grant n° 116074 and by the British Heart Foundation Programme Grant RG/18/13/33946. We thank Dr. Angela Wood for feedback on statistical analyses used in the paper. We thank the INTERVAL Study investigators, co-ordination team and the epidemiology field, data and laboratory teams, which were supported by core funding from the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014) [The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care], and the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the Department of Health and Social Care (England), the Chief Scientist Office of the Scottish Government Health and Social Care Directorates, the Health and Social Care Research and Development Division (Welsh Government), the Public Health Agency (Northern Ireland), the British Heart Foundation, and Wellcome. J.D. holds a British Heart Foundation Professorship and a National Institute for Health Research Senior Investigator Awar