Hostname: page-component-6766d58669-vgfm9 Total loading time: 0 Render date: 2026-05-25T02:56:43.071Z Has data issue: false hasContentIssue false
  • English
  • Français

Contextual risks, child problem-solving profiles, and socioemotional functioning: Testing the specialization hypothesis

Published online by Cambridge University Press:  13 December 2021

Zhi Li Open the ORCID record for Zhi Li [Opens in a new window] ,
Melissa L. Sturge-Apple Open the ORCID record for Melissa L. Sturge-Apple [Opens in a new window]  and
Patrick T. Davies Open the ORCID record for Patrick T. Davies [Opens in a new window]
Zhi Li*
Affiliation:
School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
Melissa L. Sturge-Apple
Affiliation:
Department of Psychology, University of Rochester & Mt. Hope Family Center, Rochester, NY, United States
Patrick T. Davies
Affiliation:
Department of Psychology, University of Rochester, Rochester, NY, United States
*
Corresponding author: Zhi Li, email: zhi.li@pku.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

Guided by the evolutionary perspective and specialization hypothesis, this multi-method (behavioral observation, questionnaire) longitudinal study adopted a person-centered approach to explore children’s problem-solving skills within different contexts. Participants were 235 young children (M age = 2.97 years at the first measurement occasion) and their parents assessed in two measurement occasions spaced one year apart. Latent profile analyses revealed four unique problem-solving profiles, capturing variability in children’s performance, and observed engagement in abstract vs. reward-oriented (RO) problem-solving tasks at wave one. The four profiles included: (a) a high-abstract-high-RO, (b) a high-abstract-low-RO, (c) a low-abstract-high-RO, and (d) a low-abstract-low-RO classes. Contextual risks within and outside families during wave one, including greater neighborhood crime, impoverishment, and observed lower maternal sensitivity were linked to the elevated likelihood for children from the two profiles with low-abstract problem-solving, particularly those from the low-abstract-high-RO problem-solving profile. Furthermore, child problem-solving profiles were linked to meaningful differences in their socioemotional functioning one year later. The present finding has important implications in revealing the heterogeneity in child problem-solving within different contexts that responded differently to contextual risks. In addition, this study advanced the understanding of the developmental implications of child problem-solving capacity.

Keywords

contextual risksproblem-solvingsocioemotional functioning

Information

Type
Regular Article
Information
Development and Psychopathology , Volume 35 , Issue 3 , August 2023 , pp. 1421 - 1433
Check for updates
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Albow, J.C., Measelle, J.R., Kraemer, H.C., Harrington, R., Luby, L., & Smider, N. (1999). The MacArthur three-city outcome study: Evaluating multi-informant measures of young children’s symptomatology. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 1580–2590. https://doi.org/10.1097/00004583-199912000-00020 Google Scholar
Ashley, J., & Tomasello, M. (1998). Cooperative problem-solving and teaching in preschoolers. Social Development, 7, 143–163. https://doi.org/10.1111/1467-9507.00059 CrossRefGoogle Scholar
Belsky, J., Pasco Fearon, R.M., & Bell, B. (2007). Parenting, attention and externalizing problems: Testing mediation longitudinally, repeatedly and reciprocally. Journal of Child Psychology and Psychiatry, 48, 1233–1242. https://doi.org/10.1111/j.1469-7610.2007.01807.x CrossRefGoogle Scholar
Belsky, J., Schlomer, G.L., & Ellis, B.J. (2012). Beyond cumulative risk: Distinguishing harshness and unpredictability as determinants of parenting and early life history strategy. Developmental Psychology, 48, 662–673. https://doi.org/10.1037/a0024454 CrossRefGoogle Scholar
Belsky, J., Steinberg, L., & Draper, P. (1991). Childhood experience, interpersonal development, and reproductive strategy: An evolutionary theory of socialization. Child Development, 62, 647–670. https://doi.org/10.1111/j.1467-8624.1991.tb01558.x CrossRefGoogle Scholar
Bolck, A., Croon, M., & Hagenaars, J. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12, 3–27. https://doi.org/10.1093/pan/mph001 CrossRefGoogle Scholar
Bronfenbrenner, U., & Morris, P.A. (2006). The bioecological model of human development. In Damon, W. & Lerner, R.M. (Eds.), Handbook of Child Psychology, Vol. 1: Theoretical Models of Human Development (6th ed., pp. 793–828). New York: Wiley.Google Scholar
Brooks-Gunn, J., & Duncan, G.J. (1997). The effects of poverty on children. The Future of Children, 55–71. https://doi.org/10.2307/1602387 CrossRefGoogle Scholar
Brown, E.D., Seyler, M.D., Knorr, A.M., Garnett, M.L., & Laurenceau, J.P. (2016). Daily poverty-related stress and coping: Associations with child learned helplessness. Family Relations, 65, 591–602. https://doi.org/10.1111/fare.12217 CrossRefGoogle Scholar
Bruchhage, M.M., Ngo, G.C., Schneider, N., D’Sa, V., & Deoni, S.C. (2020). Functional connectivity correlates of infant and early childhood cognitive development. Brain Structure and Function, 225, 669–681. https://doi.org/10.1007/s00429-020-02027-4 CrossRefGoogle Scholar
Caughy, M.O.B., Hayslett-McCall, K.L., & O’Campo, P.J. (2007). No neighborhood is an island: Incorporating distal neighborhood effects into multilevel studies of child developmental competence. Health & Place, 13, 788–798. https://doi.org/10.1016/j.healthplace.2007.01.006 CrossRefGoogle Scholar
Caughy, M.O.B., & O’campo, P.J. (2006). Neighborhood poverty, social capital, and the cognitive development of African American preschoolers. American Journal of Community Psychology, 37, 141–154. https://doi.org/10.1007/s10464-005-9001-8 CrossRefGoogle Scholar
Dennis, T.A., Cole, P.M., Wiggins, C.N., Cohen, L.H., & Zalewski, M. (2009). The functional organization of preschool-age children’s emotion expressions and actions in challenging situations. Emotion, 9, 520–530. https://doi.org/10.1037/a0016514 CrossRefGoogle Scholar
Dennison, M.J., Rosen, M.L., Sambrook, K.A., Jenness, J.L., Sheridan, M.A., & McLaughlin, K.A. (2019). Differential associations of distinct forms of childhood adversity with neurobehavioral measures of reward processing: A developmental pathway to depression. Child Development, 90, e96–e113. https://doi.org/10.1111/cdev.13011 CrossRefGoogle Scholar
Doom, J.R., Vanzomeren-Dohm, A.A., & Simpson, J.A. (2016). Early unpredictability predicts increased adolescent externalizing behaviors and substance use: A life history perspective. Development and psychopathology, 28, 1505–1516. https://doi.org/10.1017%2FS0954579415001169 CrossRefGoogle Scholar
Ellis, B.J., Bianchi, J., Griskevicius, V., & Frankenhuis, W.E. (2017). Beyond risk and protective factors: An adaptation-based approach to resilience. Perspectives on Psychological Science, 12, 561–587. https://doi.org/10.1177%2F1745691617693054 CrossRefGoogle Scholar
Ellis, B.J., Figueredo, A.J., Brumbach, B.H., & Schlomer, G.L. (2009). Fundamental dimensions of environmental risk. Human Nature, 20, 204–268. https://doi.org/10.1007/s12110-009-9063-7 CrossRefGoogle Scholar
Evans, G.W., Li, D., & Whipple, S.S. (2013). Cumulative risk and child development. Psychological Bulletin, 139, 1342–1396. https://doi.org/10.1037/a0031808 CrossRefGoogle Scholar
Frankenhuis, W.E., & de Weerth, C. (2013). Does early-life exposure to stress shape or impair cognition? Current Directions in Psychological Science, 22, 407–412. https://doi.org/10.1177%2F0963721413484324 CrossRefGoogle Scholar
Frankenhuis, W.E., Panchanathan, K., & Nettle, D. (2016). Cognition in harsh and unpredictable environments. Current Opinion in Psychology, 7, 76–80. https://doi.org/10.1016/j.copsyc.2015.08.011 CrossRefGoogle Scholar
Frankenhuis, W.E., Roelofs, M.F.A., & de Vries, S.A. (2018). Does exposure to psychosocial adversity enhance deception detection ability? Evolutionary Behavioral Sciences, 12, 218–229. https://doi.org/10.1037/ebs0000103 CrossRefGoogle Scholar
Frankenhuis, W.E., Young, E.S., & Ellis, B.J. (2020). The hidden talents approach: Theoretical and methodological challenges. Trends in Cognitive Sciences, 24, 569–581. https://doi.org/10.1016/j.tics.2020.03.007 CrossRefGoogle Scholar
Griskevicius, V., Tybur, J.M., Delton, A.W., & Robertson, T.E. (2011). The influence of mortality and socioeconomic status on risk and delayed rewards: A life history theory approach. Journal of Personality and Social Psychology, 100, 1015–1026. https://doi.org/10.1037/a0022403 CrossRefGoogle Scholar
Hagenaars, J.A., & McCutcheon, A.L. (Eds.). (2002). Applied Latent Class Analysis. New York: Cambridge University Press.CrossRefGoogle Scholar
Harries, K. (2006). Property crimes and violence in United States: An analysis of the influence of population density. International Journal of Criminal Justice Sciences, 1, 24–33.Google Scholar
Humphreys, K.L., Lee, S.S., Telzer, E.H., Gabard-Durnam, L.J., Goff, B., Flannery, J., & Tottenham, N. (2015). Exploration—Exploitation strategy is dependent on early experience. Developmental Psychobiology, 57, 313–321. https://doi.org/10.1002/dev.21293 CrossRefGoogle Scholar
Kirby, D., Coyle, K., & Gould, J.B. (2001). Manifestations of poverty and birthrates among young teenagers in California zip code areas. Family Planning Perspectives, 63–69. https://doi.org/10.2307/2673751 CrossRefGoogle Scholar
Knight, E.D., Smith, J.S., Martin, L., Lewis, T., & LONGSCAN Investigators. (2008). Measures for Assessment of Functioning and Outcomes in Longitudinal Research on Child Abuse. Vol. 3: Early Adolescence (Ages 12–14). Ithaca, NY: Cornell University.Google Scholar
Lanza, S.T., & Rhoades, B.L. (2013). Latent class analysis: An alternative perspective on subgroup analysis in prevention and treatment. Prevention Science, 14, 157–168. https://doi.org/10.1007%2Fs11121-011-0201-1 CrossRefGoogle Scholar
Lauritsen, J.L. (1994). Explaining race and gender differences in adolescent sexual behavior. Social Forces, 72, 859–883. https://doi.org/10.1093/sf/72.3.859 CrossRefGoogle Scholar
Li, Z., Liu, S., Hartman, S., & Belsky, J. (2018). Interactive effects of early-life income harshness and unpredictability on children’s socioemotional and academic functioning in kindergarten and adolescence. Developmental Psychology, 54, 2101–2112. https://doi.org/10.1037/dev0000601 CrossRefGoogle Scholar
Little, R.J. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202. https://doi.org/10.1080/01621459.1988.10478722 CrossRefGoogle Scholar
Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778. https://doi.org/10.1093/biomet/88.3.767 CrossRefGoogle Scholar
Lugo-Gil, J., & Tamis-LeMonda, C.S. (2008). Family resources and parenting quality: Links to children’s cognitive development across the first 3 years. Child Development, 79, 1065–1085. https://doi.org/10.1111/j.1467-8624.2008.01176.x CrossRefGoogle Scholar
Manly, J.T., Oshri, A., Lynch, M., Herzog, M., & Wortel, S. (2013). Child neglect and the development of externalizing behavior problems: Associations with maternal drug dependence and neighborhood crime. Child Maltreatment, 18, 17–29. https://doi.org/10.1177%2F1077559512464119 CrossRefGoogle Scholar
Martin, A., Ryan, R.M., & Brooks-Gunn, J. (2013). Longitudinal associations among interest, persistence, supportive parenting, and achievement in early childhood. Early Childhood Research Quarterly, 28, 658–667. https://doi.org/10.1016/j.ecresq.2013.05.003 CrossRefGoogle Scholar
McCoy, D.C., Connors, M.C., Morris, P.A., Yoshikawa, H., & Friedman-Krauss, A.H. (2015). Neighborhood economic disadvantage and children’s cognitive and social-emotional development: Exploring Head Start classroom quality as a mediating mechanism. Early Childhood Research Quarterly, 32, 150–159. https://doi.org/10.1016/j.ecresq.2015.04.003 CrossRefGoogle Scholar
Metcalfe, L.A., Harvey, E.A., & Laws, H.B. (2013). The longitudinal relation between academic/cognitive skills and externalizing behavior problems in preschool children. Journal of educational psychology, 105, 881–894. https://doi.org/10.1037/a0032624 CrossRefGoogle Scholar
Minh, A., Muhajarine, N., Janus, M., Brownell, M., & Guhn, M. (2017). A review of neighborhood effects and early child development: How, where, and for whom, do neighborhoods matter? Health & Place, 46, 155–174. https://doi.org/10.1016/j.healthplace.2017.04.012 CrossRefGoogle Scholar
Mittal, C., Griskevicius, V., Simpson, J.A., Sung, S., & Young, E.S. (2015). Cognitive adaptations to stressful environments: When childhood adversity enhances adult executive function. Journal of Personality and Social Psychology, 109, 604–621. https://doi.org/10.1037/pspi0000028 CrossRefGoogle Scholar
Morgan, P.L., Farkas, G., Tufis, P.A., & Sperling, R.A. (2008). Are reading and behavior problems risk factors for each other? Journal of Learning Disabilities, 41, 417–436. https://doi.org/10.1177%2F0022219408321123 CrossRefGoogle Scholar
Muthén, L.K., & Muthén, B.O. (1998–2011). Mplus User’s Guide (6th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
Nweze, T., Nwoke, M.B., Nwufo, J.I., Aniekwu, R.I., & Lange, F. (2020). Working for the future: parentally deprived Nigerian Children have enhanced working memory ability. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.13241 Google Scholar
Quinlan, R.J. (2007). Human parental effort and environmental risk. Proceedings of the Royal Society B: Biological Sciences, 274, 121–125. https://doi.org/10.1098/rspb.2006.3690 CrossRefGoogle Scholar
Raby, K.L., Roisman, G.I., Fraley, R.C., & Simpson, J.A. (2015). The enduring predictive significance of early maternal sensitivity: Social and academic competence through age 32 years. Child Development, 86, 695–708. https://doi.org/10.1111/cdev.12325 CrossRefGoogle Scholar
Ruff, H.A., Capozzoli, M., & Weissberg, R. (1998). Age, individuality, and context as factors in sustained visual attention during the preschool years. Developmental Psychology, 34, 454–464. https://doi.org/10.1037/0012-1649.34.3.454.CrossRefGoogle Scholar
Ryan, R.M., Martin, A., & Brooks-Gunn, J. (2006). Is one good parent good enough? Patterns of mother and father parenting and child cognitive outcomes at 24 and 36 months. Parenting, 6, 211–228. https://doi.org/10.1080/15295192.2006.9681306 CrossRefGoogle Scholar
Rydell, A.M., Berlin, L., & Bohlin, G. (2003). Emotionality, emotion regulation, and adaptation among 5-to 8-year-old children. Emotion, 3, 30–47. https://doi.org/10.1037/1528-3542.3.1.30 CrossRefGoogle Scholar
Sheridan, M.A., McLaughlin, K.A., Winter, W., Fox, N., Zeanah, C., & Nelson, C.A. (2018). Early deprivation disruption of associative learning is a developmental pathway to depression and social problems. Nature Communications, 9, 1–8. https://doi.org/10.1038/s41467-018-04381-8 CrossRefGoogle Scholar
Sturge-Apple, M.L., Davies, P.T., Cicchetti, D., Hentges, R.F., & Coe, J.L. (2017). Family instability and children’s effortful control in the context of poverty: Sometimes a bird in the hand is worth two in the bush. Development and Psychopathology, 29, 685–696. https://doi.org/10.1017/S0954579416000407 CrossRefGoogle Scholar
Suor, J.H., Sturge-Apple, M.L., Davies, P.T., & Cicchetti, D. (2017). A life history approach to delineating how harsh environments and hawk temperament traits differentially shape children’s problem-solving skills. Journal of Child Psychology and Psychiatry, 58, 902–909. https://doi.org/10.1111/jcpp.12718 CrossRefGoogle Scholar
Tamis-LeMonda, C.S., Briggs, R.D., McClowry, S.G., & Snow, D.L. (2009). Maternal control and sensitivity, child gender, and maternal education in relation to children’s behavioral outcomes in African American families. Journal of Applied Developmental Psychology, 30, 321–331. https://doi.org/10.1016/j.appdev.2008.12.018 CrossRefGoogle Scholar
Tamis-LeMonda, C.S., Shannon, J.D., Cabrera, N.J., & Lamb, M.E. (2004). Fathers and mothers at play with their 2-and 3-year-olds: Contributions to language and cognitive development. Child Development, 75, 1806–1820. https://doi.org/10.1111/j.1467-8624.2004.00818.x CrossRefGoogle Scholar
Tein, J.Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling: A Multidisciplinary Journal, 20, 640–657. https://doi.org/10.1080%2F10705511.2013.824781 CrossRefGoogle Scholar
Tucker-Drob, E.M., & Harden, K.P. (2012). Early childhood cognitive development and parental cognitive stimulation: Evidence for reciprocal gene–environment transactions. Developmental Science, 15, 250–259. https://doi.org/10.1111/j.1467-7687.2011.01121.x CrossRefGoogle Scholar
Vermunt, J.K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450–469. https://doi.org/10.1093/pan/mpq025 CrossRefGoogle Scholar
Wang, F., Christ, S.L., Mills-Koonce, W.R., Garrett-Peters, P., & Cox, M.J. (2013). Association between maternal sensitivity and externalizing behavior from preschool to preadolescence. Journal of Applied Developmental Psychology, 34, 89–100. https://doi.org/10.1016/j.appdev.2012.11.003 CrossRefGoogle Scholar
Wieland, N., Green, S., Ellingsen, R., & Baker, B. L. (2014). Parent–child problem solving in families of children with or without intellectual disability. Journal of Intellectual Disability Research, 58, 17–30. https://doi.org/10.1111/jir.12009 CrossRefGoogle ScholarPubMed
Wechsler, D. (2002). Wechsler Preschool and Primary Scale of Intelligence (3rd edn). San Antonio, TX: Psychological Corporation.Google Scholar
Wilson, M., & Daly, M. (1997). Life expectancy, economic inequality, homicide, and reproductive timing in Chicago neighbourhoods. BMJ, 314, 1271. https://doi.org/10.1136/bmj.314.7089.1271 CrossRefGoogle Scholar
Young, E.S., Griskevicius, V., Simpson, J.A., Waters, T.E., & Mittal, C. (2018). Can an unpredictable childhood environment enhance working memory? Testing the sensitized-specialization hypothesis. Journal of Personality and Social Psychology, 114, 891–908. https://doi.org/10.1037/pspi0000124 CrossRefGoogle Scholar
Zadeh, Z.Y., Farnia, F., & Ungerleider, C. (2010). How home enrichment mediates the relationship between maternal education and children’s achievement in reading and math. Early Education and Development, 21, 568–594. https://doi.org/10.1080/10409280903118424 CrossRefGoogle Scholar
Supplementary material: File

Li et al. supplementary material

Li et al. supplementary material

Download Li et al. supplementary material(File)
File 97.5 KB