286 research outputs found

    Recognition of Face Identity and Emotion in Expressive Specific Language Impairment

    Get PDF
    Objective: To study face and emotion recognition in children with mostly expressive specific language impairment (SLI-E). Subjects and Methods: A test movie to study perception and recognition of faces and mimic-gestural expression was applied to 24 children diagnosed as suffering from SLI-E and an age-matched control group of normally developing children. Results: Compared to a normal control group, the SLI-E children scored significantly worse in both the face and expression recognition tasks with a preponderant effect on emotion recognition. The performance of the SLI-E group could not be explained by reduced attention during the test session. Conclusion: We conclude that SLI-E is associated with a deficiency in decoding non-verbal emotional facial and gestural information, which might lead to profound and persistent problems in social interaction and development. Copyright (C) 2012 S. Karger AG, Base

    Prediction of 7-year psychopathology from mother-infant joint attention behaviours: a nested case–control study

    Get PDF
    <br>Background: To investigate whether later diagnosis of psychiatric disorder can be predicted from analysis of mother-infant joint attention (JA) behaviours in social-communicative interaction at 12 months.</br> <br>Method: Using data from a large contemporary birth cohort, we examined 159 videos of a mother-infant interaction for joint attention behaviour when children were aged one year, sampled from within the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Fifty-three of the videos involved infants who were later considered to have a psychiatric disorder at seven years and 106 were same aged controls. Psychopathologies included in the case group were disruptive behaviour disorders, oppositional-conduct disorder, attention-deficit/hyperactivity disorder, pervasive development disorder, anxiety and depressive disorders. Psychiatric diagnoses were obtained using the Development and Wellbeing Assessment when the children were seven years old.</br> <br>Results: None of the three JA behaviours (shared look rate, shared attention rate and shared attention intensity) showed a significant association with the primary outcome of case–control status. Only shared look rate predicted any of the exploratory sub-diagnosis outcomes and was found to be positively associated with later oppositional-conduct disorders (OR [95% CI]: 1.5 [1.0, 2.3]; p = 0.041).</br><br>Conclusions: JA behaviours did not, in general, predict later psychopathology. However, shared look was positively associated with later oppositional-conduct disorders. This suggests that some features of JA may be early markers of later psychopathology. Further investigation will be required to determine whether any JA behaviours can be used to screen for families in need of intervention.</br&gt

    Depression and Anxiety Change from Adolescence to Adulthood in Individuals with and without Language Impairment

    Get PDF
    This prospective longitudinal study aims to determine patterns and predictors of change in depression and anxiety from adolescence to adulthood in individuals with language impairment (LI). Individuals with LI originally recruited at age 7 years and a comparison group of age-matched peers (AMPs) were followed from adolescence (16 years) to adulthood (24 years). We determine patterns of change in depression and anxiety using the Child Manifest Anxiety Scale-Revised (CMAS-R) and Short Moods and Feelings Questionnaire (SMFQ). In addition to examining associations with gender, verbal and nonverbal skills, we use a time-varying variable to investigate relationships between depression and anxiety symptoms and transitions in educational/employment circumstances. The results show that anxiety was higher in participants with LI than age matched peers and remained so from adolescence to adulthood. Individuals with LI had higher levels of depression symptoms than did AMPs at 16 years. Levels in those with LI decreased post-compulsory schooling but rose again by 24 years of age. Those who left compulsory school provision (regardless of school type) for more choice-driven college but who were not in full-time employment or study by 24 years of age were more likely to show this depression pathway. Verbal and nonverbal skills were not predictive of this pattern of depression over time. The typical female vulnerability for depression and anxiety was observed for AMPs but not for individuals with LI. These findings have implications for service provision, career/employment advice and support for individuals with a history of LI during different transitions from adolescence to adulthood

    The effects of changes in the order of verbal labels and numerical values on children's scores on attitude and rating scales

    Get PDF
    Research with adults has shown that variations in verbal labels and numerical scale values on rating scales can affect the responses given. However, few studies have been conducted with children. The study aimed to examine potential differences in children’s responses to Likert-type rating scales according to their anchor points and scale direction, and to see whether or not such differences were stable over time. 130 British children, aged 9 to 11, completed six sets of Likert-type rating scales, presented in four different ways varying the position of positive labels and numerical values. The results showed, both initially and 8-12 weeks later, that presenting a positive label or a high score on the left of a scale led to significantly higher mean scores than did the other variations. These findings indicate that different arrangements of rating scales can produce different results which has clear implications for the administration of scales with children

    Cumulative Risk, Cumulative Outcome: A 20-Year Longitudinal Study

    Get PDF
    Cumulative risk (CR) models provide some of the most robust findings in the developmental literature, predicting numerous and varied outcomes. Typically, however, these outcomes are predicted one at a time, across different samples, using concurrent designs, longitudinal designs of short duration, or retrospective designs. We predicted that a single CR index, applied within a single sample, would prospectively predict diverse outcomes, i.e., depression, intelligence, school dropout, arrest, smoking, and physical disease from childhood to adulthood. Further, we predicted that number of risk factors would predict number of adverse outcomes (cumulative outcome; CO). We also predicted that early CR (assessed at age 5/6) explains variance in CO above and beyond that explained by subsequent risk (assessed at ages 12/13 and 19/20). The sample consisted of 284 individuals, 48% of whom were diagnosed with a speech/language disorder. Cumulative risk, assessed at 5/6-, 12/13-, and 19/ 20-years-old, predicted aforementioned outcomes at age 25/26 in every instance. Furthermore, number of risk factors was positively associated with number of negative outcomes. Finally, early risk accounted for variance beyond that explained by later risk in the prediction of CO. We discuss these findings in terms of five criteria posed by these data, positing a mediated net of adversity- model, suggesting that CR may increase some central integrative factor, simultaneously augmenting risk across cognitive, quality of life, psychiatric and physical health outcomes.div_PaS1. Rutter M. Family, area and school influences in the genesis of conduct disorders. In: Hersov LA, Berger M, Shaffer D, editors. Aggression and Anti-social Behavior in Childhood and Adolescence. Oxford: Pergamon; 1978. p. 95-113. 2. Appleyard K, Egeland B, van Dulmen MHM, Sroufe LA. When more is not better: The role of cumulative risk in child behavior outcomes. J Child Psychol Psychiatry. 2005; 46: 235-245. doi: 10.1111/j.1469- 7610.2004.00351.x PMID: 15755300 3. Deater-Deckard K, Dodge KA, Bates JE, Pettit GS. Multiple-risk factors in the development of externalizing behavior problems: Group and individual differences. Dev Psychopathol. 1998; 10: 469-493. doi: 10.1017/S0954579498001709 PMID: 9741678 4. Evans GW, Li D, Whipple SS. Cumulative risk and child development. Psychol Bull. 2013; 139: 1342- 1396. doi: 10.1037/a0031808 PMID: 23566018 5. Sameroff AJ, Rosenblum T. Identifying risk and protective factors for healthy child development. In: Clarke-Stewart A, Dunn J, editors. Families Count: Effects on Child and Adolescent Development. New York, New York: Cambridge University Press; 2006. p. 53-76. 6. Sameroff AJ, Seifer R, Baldwin A, Baldwin C. Stability of intelligence from preschool to adolescence: The influence of social and family risk factors. Child Dev. 1987; 64: 80-97. doi: 10.1111/j.1467-8624. 1993.tb02896.x 7. Sameroff AJ, Seifer R, Barocas R, Zax M, Greenspan S. Intelligence quotient scores of 4-year-old children: Social-environmental risk factors. Pediatrics. 1987; 79: 343-350. PMID: 3822634 8. Laucht M, Esser G, Schmidt MH. Developmental outcome of infants born with biological and psychosocial risks. J Child Psychol Psychiatry. 1997; 38: 843-853. doi: 10.1111/j.1469-7610.1997.tb01602.x PMID: 9363583 9. Simmons RG, Burgeson R, Carlton-Ford S, Blyth DA. The impact of cumulative change in early adolescence. Child Dev. 1987; 58: 1220-1234. doi: 10.2307/1130616 PMID: 3665641 10. Barocas R, Seifer R, Sameroff AJ, Andrews TA, Croft RT, Ostrow E. Social and interpersonal determinants of developmental risk. Dev Psychol. 1991; 27: 479-488. doi: 10.1037//0012-1649.27.3.479 11. Evans GW. A multimethodological analysis of cumulative risk and allostatic load among rural children. Dev Psychol. 2003; 39: 924-933. doi: 10.1037/0012-1649.39.5.924 PMID: 12952404 12. Evans GW, Kim P, Ting AH, Tesher HB, Shannis D. Cumulative risk, maternal responsiveness, and allostatic load among young adolescents. Dev Psychol. 2007; 43: 341-351. doi: 10.1037/0012-1649. 43.2.341 PMID: 17352543 13. Newcomb MD, Maddahian E, Bentler PM. Risk factors for drug use among adolescents: Concurrent and longitudinal analyses. Am J Public Health. 2007; 76: 525-531. doi: 10.2105/AJPH.76.5.525 14. Larson K, Russ SA, Crall JJ, Halfon N. Influence of multiple social risks on children's health. Pediatrics. 2008; 121: 337-344. doi: 10.1542/peds.2007-0447 PMID: 18245425 15. Gest SD, Reed GM, Masten AS. Measuring developmental changes in exposure to adversity: A life chart and rating scale approach. Dev Psychopathol. 1999; 11: 171-192. doi: 10.1017/ S095457949900200.x PMID: 10208361 16. Garbarino J, Kostelny K. The effects of political violence on Palestinian children's behavior problems: A risk accumulation model. Child Dev. 1996; 67: 33-45. doi: 10.2307/1131684 PMID: 8605832 17. Schoon I, Bynner J, Joshi H, Parsons S, Wiggins RD, Sacker A. The influence of context, timing, and duration of risk experiences for the passage from childhood to midadulthood. Child Dev. 2002; 73: 1486-1504. doi: 10.1111/1467-8624.00485 PMID: 12361314 18. Beitchman JH, Wilson B, Brownlie EB, Walters H, Lancee W. Long-term consistency in speech/language profiles: I. Developmental and academic outcomes. J Am Acad Child Adolesc Psychiatry. 1996; 35: 804-814. doi: 10.1097/00004583-199606000-00021 PMID: 8682762 Cumulative Risk, Cumulative Outcome PLOS ONE | DOI:10.1371/journal.pone.0127650 June 1, 2015 13 / 16 19. Beitchman JH, Wilson B, Johnson CJ, Atkinson L, Young A, Adlaf E, et al. Fourteen-year follow-up of speech/language-impaired and control children: Psychiatric outcome. J Am Acad Child Adolesc Psychiatry. 2001; 40: 75-82. doi: 10.1097/00004583-200101000-00019 PMID: 11195567 20. Snow P, Powell M. Developmental language disorders and adolescent risk: A public-health advocacy role for speech pathologists? Int J Speech Lang Pathol. 2004; 6: 221-229. doi: 10.1080/ 14417040400010132 21. Coie JD, Watt NF, West SG, Hawkins JD, Asarnow JR, Markman HJ, et al. The science of prevention. A conceptual framework and some directions for a national research program. Am Psychol. 1993; 48: 1013-1022. doi: 10.1037/0003-066X.48.10.1013 PMID: 8256874 22. Beitchman JH, Nair R, Clegg M, Patel PG, Ferguson B, Pressman E, et al. Prevalence of speech and language disorders in 5-year-old kindergarten children in the Ottawa-Carleton region. J Speech Hear Disord. 1986; 51: 98-110. PMID: 3702369 23. Beitchman JH, Nair R, Clegg M, Ferguson B, Patel PG. Prevalence of psychiatric disorders in children with speech and language disorders. J Am Acad Child Psychiatry. 1986; 25: 528-535. doi: 10.1016/ S0002-7138(10)60013-1 PMID: 3489024 25. Beitchman JH, Lancee W, Brownlie EB, Inglis A, Wild J, Mathews R, et al. Seven-year follow-up of speech/language-impaired and control children: Speech/language stability and outcome. J Am Acad Child Adolesc Psychiatry. 1994; 33: 1322-1330. doi: 10.1097/00004583-199411000-00015 PMID: 7995800 26. Bankson NW. Bankson Language Screening Test. Baltimore University Press; 1977. 27. Carrow E. Screening Test for Auditory Comprehension of Language. 5th ed. Boston: Teaching Resources Corporation; 1973. 28. Pendergast K, Dickey SE, Selmar JW, Soder AL. Photo Articulation Test. Danville, IL: Interstate; 1969. 29. Dunn LM, Dunn LM. Peabody Picture Vocabulary Test-Revised. Circle Pines, MN: American Guidance Service; 1981. 30. Newcomer PL, Hammill DD. Test of Language Development. Austin, TX: Empiric Press; 1977. 31. Hammill DD, Newcomer PL. Test of Language Development-Intermediate. Austin, TX: Pro-Ed; 1988. 32. Hammill DD, Brown V, Larsen S, Wiederholt J. Test of Adolescent/Adult Language-3. Austin, TX: Pro-Ed; 1994. PMID: 17172782 33. Goldman R, Fristoe M, Woodcock RW. Goldman-Fristoe-Woodcock Auditory Memory Tests. Circle Pine, MN: American Guidance Service; 1974. 34. Johnson CJ, Taback N, Escobar M, Wilson B, Beitchman JH. Local norming of the test of adolescent/ adult language-3 in the Ottawa speech and language study. J Speech Lang Hear Res. 1999; 42: 761- 766. PMID: 10391638 35. Johnson CJ, Lam I, Wang M, Beitchman JH, Young A, Escobar M, et al. Fourteen-year follow-up of children with and without speech/language impairments: Speech/language stability and outcomes. J Speech Lang Hear Res. 1999; 42: 744-760. PMID: 10391637 36. Beitchman JH, Douglas L, Wilson B, Johnson C, Young A, Atkinson L, et al. Adolescent substance use disorders: findings from a 14-year follow-up of speech/language-impaired and control children. J Clin Child Psychol. 1999; 28: 312-321. doi: 10.1207/S15374424jccp280303 PMID: 10446680 37. Blishen BR. The 1981 [nineteen hundred and eighty-one] socioeconomic index for occupations in Canada. Can Rev Sociol Anthropol. 1987; 24: 465-488. 38. Bumpass LL, Rindfuss RR, Janosik RB. Age and marital status at first birth and the pace of subsequent fertility. Demography. 1978; 15: 75-86. PMID: 631400 39. Martinez G, Daniels K, Chandra A. Fertility of men and women aged 15-44 years in the United States: National survey of family growth, 2006-2010. Hyattsville, MD: National Center for Health Statistics Reports. 2012; 51: 1-28. 40. Luster T, McAdoo HP. Factors related to the achievement and adjustment of young African American children. Child Dev. 1994; 65: 1080-1094. doi: 10.2307/1131306 PMID: 7956466 41. Lundberg U. On the psychobiology of stress and health. In: Svenson O, Maule AJ, editors. Time Pressure and Stress in Human Judgment and Decision Making. New York, NY: Plenum; 1993. p. 41-53. 42. Rutter M, Quinton D. Psychiatric disorder-ecological factors and concepts of causation. In: McGurk, editor. Ecological Factors in Human Development. Amsterdam: Noord-Holland; 1977. p. 173-187. 43. Canada S, Division CO. 1981 Census population [Canada] public use microdata file (PUMF): Household and family file. Ottawa, Ontario: Statistics Canada; 2011. 44. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas. 1977; 1: 385.401. doi: 10.1177/014662167700100306 45. Blanz B, Schmidt MH, Esser G. Familial adversities and child psychiatric disorders. J Child Psychol Psychiatry. 1991; 32: 939.950. doi: 10.1111/j.1469-7610.1991.tb01921.x PMID: 1744197 46. Cairney J, Boyle M, Offord DR, Racine Y. Stress, social support and depression in single and married mothers. Soc Psychiatry Psychiatr Epidemiol. 2003; 38: 442.449. doi: 10.1007/s00127-003-0661-0 PMID: 12910340 47. Locke HJ, Wallace KM. Short marital-adjustment and prediction tests: Their reliability and validity. Marriage Fam Living. 1959; 21: 251.255. 48. O'Leary KD, Turkewitz H. Methodological errors in marital and child treatment research. J Consult Clin Psychol. 1978; 46: 747.758. doi: 10.1037/0022-006X.46.4.747 PMID: 670519 49. Ackerman BP, Brown ED, Izard CE. The relations between contextual risk, earned income, and the school adjustment of children from economically disadvantaged families. Dev Psychol. 2004; 40: 204. 216. doi: 10.1037/0012-1649.40.2.204 PMID: 14979761 50. Fergusson DM, Lynskey MT. Suicide attempts and suicidal ideation in a birth cohort of 16-year-old New Zealanders. J Am Acad Child Adolesc Psychiatry. 1995; 34: 1308.1317. doi: 10.1097/00004583- 199510000-00016 PMID: 7592268 51. Fergusson DM, Lynskey MT. Adolescent resiliency to family adversity. J Child Psychol Psychiatry. 1996; 37: 281.292. doi: 10.1111/j.1469-7610.1996.tb01405.x PMID: 8707911 52. Wechsler D. WAIS-III Administration and Scoring Manual. San Antonio, TX: The Psychological Corporation; 1997. PMID: 17904332 53. Tellegen A, Briggs PF. Old wine in new skins: Grouping Wechsler subtests into new scales. J Consult Psychol. 1967; 31: 499.506. doi: 10.1037/h0024963 PMID: 6075979 54. Atkinson L, Yoshida G. A BASIC program for evaluating subtest combination short forms. Edu Psychol Meas. 1989; 49: 141.143. 55. Caraballo RS, Maurer KR, Giovino GA, Pechacek TF, Mowery PD, Richter PA, et al. Racial and ethnic differences in serum cotinine levels of cigarette smokers: Third national health and nutrition examination survey, 1988.1991. JAMA. 1998; 280: 135.139. doi: 10.1001/jama.280.2.135 PMID: 9669785 56. Brenner ND, Collins JL, Kann L, Warren CW, Williams BI. Reliability of the youth risk behavior survey questionnaire. Am J Epidemiol. 1995; 141: 575.580. PMID: 7900725 57. Freier M, Bell RM, Ellickson PL. Do teens tell the truth? The validity of self-reported tobacco use by adolescents. Santa Monica, California; 1991. 58. Perez-Stable EJ, Benowitz NL, Marin G. Is serum cotinine a better measure of cigarette smoking than self-report? Prev Med. 1995; 24: 171.179. doi: 10.1006/pmed.1995.1031 PMID: 7597020 59. Bjartveit K, Tverdal A. Health consequences of smoking 1.4 cigarettes per day. Tob Control. 2005; 14: 315.320. doi: 10.1136/tc.2005.011932 PMID: 16183982 60. Babinski LM, Hartsough CS, Lambert NM. A comparison of self_]report of criminal involvement and official arrest records. Aggress Behav. 2001; 27: 44.54. doi: 10.1002/1098-2337(20010101/31)27:1 61. Kroner DG, Mills JF, Morgan RD. Underreporting of crime-related content and the prediction of criminal recidivism among violent offenders. Psychol Serv. 2007; 4: 85.95. doi: 10.1037/1541-1559.4.2.85 62. Collins LM, Schafer JL, Kam C-M. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Methods. 2001; 6: 330.351. doi: 10.1037/1082-989X.6.4.330 PMID: 11778676 63. Graham JW, Olchowski AE, Gilreath TD. How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci. 2007; 8: 206.213. doi: 10.1007/s11121-007-0070- 9 PMID: 17549635 64. Schafer JL, Graham JW. Missing data: Our view of the state of the art. Psychol Methods. 2002; 7: 147. 177. doi: 10.1037/1082-989X.7.2.147 PMID: 12090408 65. Little RJA. A test of missing completely at random for multivariate data with missing values. J Am Stat Assoc. 1988; 83: 1198.1202. 66. Atkinson L. Strategic decisions: Life history, interpersonal relations, intergenerational neurobiology, and ethics in parenting and development. Parenting. 2012; 12: 185.191. doi: 10.1080/15295192.2012. 683356 67. Cicchetti D, Toth SL. The past achievements and future promises of developmental psychopathology: The coming of age of a discipline. J Child Psychol Psychiatry. 2009; 50: 16-25. doi: 10.1111/j.1469- 7610.2008.01979.x PMID: 19175810 68. Jack DC. Silencing the self: Women and depression. 1991. 69. Snyder H. Juvenile arrests, 2000. Juvenile Justice Bulletin. Washington, DC: Office of Juvenile Justice and Delinquency Prevention; 2002. 70. Coxe S, West SG, Aiken LS. The analysis of count data: A gentle introduction to Poisson regression and its alternatives. J Pers Assess. 2009; 91: 121-136. doi: 10.1080/00223890802634175 PMID: 19205933 71. Tabachnick BG, Fidell LS. Using multivariate statistics. Boston, Mass.: Pearson/Allyn and Bacon; 2001. 72. Williams S, Anderson J, McGee R, Silva PA. Risk factors for behavioral and emotional disorder in preadolescent children. J Am Acad Child Adolesc Psychiatry. 1990; 29: 413-419. doi: 10.1097/00004583- 199005000-00013 PMID: 2347839 73. Abelson RP. A variance explanation paradox: When a little is a lot. Psychol Bull. 1995; 97: 129-133. doi: 10.1037/0033-2909.97.1.129 74. McCartney K, Rosenthal R. Effect size, practical importance, and social policy for children. Child Dev. 2000; 71: 173-180. PMID: 10836571 75. Prentice DA, Miller DT. When small effects are impressive. Psychol Bull. 1992; 112: 160-164. doi: 10. 1037//0033-2909.112.1.160 76. Rosenthal R, Rubin DB.A simple general purpose display of magnitude of experimental effect. J Edu Psychol. 1983; 74: 166-169. doi: 10.1037/0022-0663.74.2.166 77. Steering Committee of the Physicians' Health Study Research Group. Findings from the aspirin component of the ongoing Physician's Health Study. New England Journal of Medicine. 1988; 318: 262-264. PMID: 3275899 78. Kagan J, Moss HA. Birth to Maturity: A Study in Psychological Development. American Psychological Asociation; 1962. 79. O'Connor TG. The persistent effects of early experiences on psychological development. In: Cicchetti D, Cohen DJ, editors. Developmental Psychopathology, 3: Risk, Disorder, and Adaptation. 2nd ed. Hoboken, NJ: John Wiley & Sons;2006. p. 202-234. 80. Rutter M. Isle of wight revisited: Twenty-five years of child psychiatric epidemiology. J Am Acad Child Adolesc Psychiatry. 1989; 28: 633-653. doi: 10.1097/00004583-198909000-00001 PMID: 2676960 81. Garmezy N, Masten AS. Chronic adversities. In: Rutter M, Hersov LA, Taylor E, editors. Child and Adolescent Psychiatry: Modern Approaches. Oxford: Blackwell Scientific Publications;1994. p. 191-208. 82. Masten AS, Coatsworth JD. The development of competence in favorable and unfavorable environments: Lessons from research on successful children. Am Psychol. 1998; 53: 205-220. doi: 10.1037/ 0003-066X.53.2.205 PMID: 9491748 83. McEwen BS. Allostasis and allostatic load: implications for neuropsychopharmacology. Neuropsychopharmacology. 2000; 22: 108-124. doi: 10.1016/S0893-133X(99)00129-3 PMID: 10649824 84. Teicher MH, Andersen SL, Polcari A, Anderson CM, Navalta CP, Kim DM. The neurobiological consequences of early stress and childhood maltreatment. Neurosci Behav Rev. 2003; 27: 33-44. doi: 10. 1016/S0149-7634(03)00007-1 85. Ptek R, Ku_elov H, Stefano GB. Dopamine D4 receptor gene DRD4 and its associaton with psychiatric disorders. Med Sci Monit. 2011; 17: RA215. PMID: 21873960 86. Thompson RA. Early attachment and later development. In: Cassidy J, Shaver P, editors. Handbook of Attachment: Theory, Research, and Clinical Applications. New York: Guilford; 2008. p. 348-365. 87. Fraley CR. Attachment stability from infancy to adulthood: Meta-analysis and dynamic modeling of developmental mechanism. Pers Soc PsycholRev. 2002; 6: 123-151. 88. Pinquart M, Feussner C, Ahnert L. Meta-analytic evidence for stability in attachments from infancy to early adulthood. Attach Hum Dev. 2013; 15: 189-218. doi: 10.1080/14616734.2013.746257 PMID: 2321066510pub3913pub

    Genetics of callous-unemotional behavior in children

    Get PDF
    Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase β€˜missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU

    Effects of Language Context on Ratings of Shy and Unsociable Behaviors in English Language Learning Children

    Get PDF
    Purpose The primary goal of this study was to explore the effect of the language context on the socially withdrawn behaviors of school aged-children who are English Language Learners (ELLs) from middle to high SES backgrounds. This is one of the first studies to address the frequently confused concepts of shyness and unsociability as independent constructs within the ELL population. This study also investigated the feasibility of an experimental parent and child questionnaire that examines shyness and unsociability across native and English speaking contexts. Method Children and parents (34 ELL and 37 native English speaking) were administered an experimental questionnaire examining shy and unsociable behavior in native language and English-speaking contexts. Results Parents and children from the ELL group reported significantly higher ratings of shy behavior in English versus native language contexts, whereas unsociable ratings did not differ across language contexts. Conclusions Shyness and unsociability are distinguishable behaviors in ELL children and these constructs should be considered when examining withdrawal. Additionally, examining ELL children’s behavior across language contexts provides a valuable method for investigating language influenced behavioral problems. This study demonstrates the need for service providers to evaluate behavior across subtype and language context before pathologizing withdrawal in ELL children
    • …
    corecore