Becoming Partners: A School-Based Group Intervention for Families of Young Children Who Are Disruptive

Abstract A multiple family discussion group program was implemented and evaluated by school counselors working with families of young children referred by their teachers for aggression and attention problems. The logic guiding construction of the program and the program's unique aspects are described. Outcome data revealed that the program was effective in reducing the children's hyperactive, defiant, and aggressive behavior and improving the parents' management skills. The advantages of school counselors conducting this program are discussed. School counselors often find themselves working with young children like Tim who demonstrate disruptive behavior and attention difficulties in school. These children are often overactive, inattentive, and demonstrate noncompliance, impulsivity, limited self-control, and an impaired ability to interact appropriately with adults and peers. These behaviors often result in academic difficulties, increased risk for rejection by their peers, and stigmatization as problem children by school staff Research on the causes of noncompliance and aggression in children reveal that in addition to differences in temperament that may contribute to their noncompliance, 4 children who are aggressive and disruptive at school often experience harsh inconsistent parenting at home (Brannigan, Gemmell, Pevalin, & Wade, 2002). Moreover, a number of studies report how the challenge of raising a difficult child (e.g. who is unpredictable, irritable, and unresponsive) often elicits a series of increasingly harsh parenting-child interactions that not only increase the levels of parental stress and guilt and diminish a sense of parenting competence, but also create a mutually coercive cycle of interaction (Johnson & Reader, 2002). Without appropriate, consistent parenting for these temperamentally difficult children, early behavior problems escalate to more severe problems and age-appropriate social competencies fail to emerge (Miller, 1998). Our program targets parents/families of primary grade children (e.g. first and second grade) whose child has been identified as demonstrating classroom conduct/behavior problems by their classroom teacher. There are several reasons for targeting this age range. First, teachers complain of problems in these children of noncompliance, limited self-control, and poor relations with peers. Second, these children are at increased risk for rejection by their peers. Third, a significant number of children who become chronically antisocial and delinquent first exhibit conduct problems during the preschool and early school years. We hoped that intervention with the families of disruptive primary school age children could help these parents teach their 7 children to behave appropriately before the child's behaviors resulted in peer rejection, well-established negative reputations, school problems, and academic failure

Becoming Partners: A School-Based Group Intervention for Families of Young Children Who Are Disruptive

A multiple family discussion group program was implemented and evaluated by school counselors working with families of young children referred by their teachers for aggression and attention problems. The logic guiding construction of the program and the program’s unique aspects are described. Outcome data revealed that the program was effective in reducing the children’s hyperactive, defiant, and aggressive behavior and improving the parents’ management skills. The advantages of school counselors conducting this program are discussed

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.