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Breaking cycles of risk: The mitigating role of maternal working memory in associations among socioeconomic status, early caregiving, and children's working memory

Published online by Cambridge University Press:  20 December 2016

Jennifer H. Suor ,
Melissa L. Sturge-Apple  and
Michael A. Skibo
Jennifer H. Suor*
Affiliation:
University of Rochester
Melissa L. Sturge-Apple
Affiliation:
University of Rochester
Michael A. Skibo
Affiliation:
Westchester Community College
*
Address correspondence and reprint requests to: Jennifer H. Suor, Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY 14627; E-mail: [email protected].
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Abstract

Previous research has documented socioeconomic-related disparities in children's working memory; however, the putative proximal caregiving mechanisms that underlie these effects are less known. The present study sought to examine whether the effects of early family socioeconomic status on children's working memory were mediated through experiences of caregiving, specifically maternal harsh discipline and responsiveness. Utilizing a psychobiological framework of parenting, the present study also tested whether maternal working memory moderated the initial paths between the family socioeconomic context and maternal harsh discipline and responsiveness in the mediation model. The sample included 185 socioeconomically diverse mother–child dyads assessed when children were 3.5 and 5 years old. Results demonstrated that maternal harsh discipline was a unique mediator of the relation between early experiences of family socioeconomic adversity and lower working memory outcomes in children. Individual differences in maternal working memory emerged as a potent individual difference factor that specifically moderated the mediating influence of harsh discipline within low socioeconomic contexts. The findings have implications for early risk processes underlying deficits in child working memory outcomes and potential targets for parent–child interventions.

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Issue 4 , October 2017 , pp. 1133 - 1147
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

This research was supported by National Institute of Nursing Research Grant R21 NR010857-01. We are much appreciative of the mothers and children who participated in this project and gave generously of their time. We also thank the staff on the project, including Katie Kao, Michael Fittoria, Samantha Spivey, and Caryn Stark.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.Google Scholar
Alloway, T. P., & Alloway, R. G. (2010). Investigating the predictive role of working memory and IQ in academic attainment. Journal of Experimental Child Psychology, 106, 20–29.Google Scholar
Arnsten, A. F. (2015). Stress weakens prefrontal networks: Molecular insults to higher cognition. Nature Neuroscience, 18, 1376–1385.Google Scholar
Arnsten, A. F., & Goldman-Rakic, P. S. (1998). Noise stress impairs prefrontal cortical cognitive function in monkeys: Evidence for a hyperdopaminergic mechanism. Archives of General Psychiatry, 55, 362–368.Google Scholar
Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Review Neuroscience, 4, 829–839.Google Scholar
Barrett, J., & Fleming, A. S. (2011). Annual research review: All mothers are not created equal: Neural and psychobiological perspectives on mothering and the importance of individual differences. Journal of Child Psychology and Psychiatry, 52, 368–397.Google Scholar
Bechara, A., & Martin, E. M. (2004). Impaired decision-making related to working memory deficits in individuals with substance addictions. Neuropsychology, 18, 152.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908.Google Scholar
Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238–246.Google Scholar
Berch, D. B., Kirkorian, R., & Huha, E. M. (1998). The Corsi block-tapping task: Methodological and theoretical considerations. Brain and Cognition, 38, 317–338.Google Scholar
Bickel, W. K., Yi, R., Landes, R. D., Hill, P. F., & Baxter, C. (2011). Remember the future: Working memory training decreases delay discounting among stimulant addicts. Biological Psychiatry, 69, 260–265.Google Scholar
Blair, C., Granger, D. A., Willoughby, M., Mills-Koonce, R., Cox, M., Greenberg, M. T., … Fortunato, C. K. (2011). Salivary cortisol mediates effects of poverty and parenting on executive functions in early childhood. Child Development, 82, 1970–1984.CrossRefGoogle ScholarPubMed
Bridgett, D. J., Oddi, K. B., Laake, L. M., Murdock, K. W., & Bachmann, M. N. (2013). Integrating and differentiating aspects of self-regulation: Effortful control, executive functioning, and links to negative affectivity. Emotion, 13, 47–63.Google Scholar
Brooks-Gunn, J., & Duncan, G. J. (1997). The effects of poverty on children. Future of Children, 7, 55–71.Google Scholar
Bull, R., Espy, K., & Wiebe, S. A. (2008). Short-term memory, working memory, and executive functioning in preschoolers: Longitudinal predictors of mathematical achievement at age 7 years. Developmental Neuropsychology, 33, 205–228.CrossRefGoogle ScholarPubMed
Carlson, S. M. (2003). Executive function in context: Development, measurement, theory, and experience. Monographs of the Society for Research in Child Development, 68, 138–151.CrossRefGoogle ScholarPubMed
Carlson, S. M., Moses, L. J., & Breton, C. (2002). How specific is the relation between executive function and theory of mind? Contributions of inhibitory control and working memory. Infant and Child Development, 11, 73–92.Google Scholar
Chang, L., Schwartz, D., Dodge, K. A., & McBride-Chang, C. (2003). Harsh parenting in relation to child emotion regulation and aggression. Journal of Family Psychology, 17, 598–606.CrossRefGoogle ScholarPubMed
Chico, E., Gonzalez, A., Ali, N., Steiner, M., & Fleming, A. S. (2014). Executive function and mothering: Challenges faced by teenage mothers. Developmental Psychobiology, 56, 1027–1035.Google Scholar
Cicchetti, D. (2002). The impact of social experience on neurobiological systems: Illustration from a constructivist view of child maltreatment. Cognitive Development, 17, 1407–1428.Google Scholar
Cicchetti, D., & Curtis, W. (2005). An event-related potential study of the processing of affective facial expressions in young children who experienced maltreatment during the first year of life. Development and Psychopathology, 17, 641–677.Google Scholar
Cicchetti, D., & Rogosch, F. A. (2009). Adaptive coping under conditions of extreme stress: Multilevel influences on the determinants of resilience in maltreated children. New Directions for Child and Adolescent Development, 124, 47–59.CrossRefGoogle Scholar
Conger, R. D., Conger, K. J., & Martin, M. J. (2010). Socioeconomic status, family processes, and individual development. Journal of Marriage and Family, 72, 685–704.CrossRefGoogle ScholarPubMed
Davidov, M., & Grusec, J. E. (2006). Untangling the links of parental responsiveness to distress and warmth to child outcomes. Child Development, 77, 44–58.Google Scholar
Davies, P. T., & Cicchetti, D. (2014). How and why does the 5-HTTLPR gene moderate associations between maternal unresponsiveness and children's disruptive problems? Child Development, 85, 484–500.Google Scholar
Davis, R. N., & Nolen-Hoeksema, S. (2000). Cognitive inflexibility among ruminators and nonruminators. Cognitive Therapy and Research, 24, 699–711.CrossRefGoogle Scholar
Dearing, E., McCartney, K., & Taylor, B. A. (2001). Change in family income-to-needs matters more for children with less. Child Development, 72, 1779–1793.Google Scholar
Deater-Deckard, K., Sewell, M. D., Petrill, S. A., & Thompson, L. A. (2010). Maternal working memory and reactive negativity in parenting. Psychological Science, 21, 75–79.Google Scholar
De Bellis, M. D. (2001). Developmental traumatology: The psychobiological development of maltreated children and its implications for research, treatment, and policy. Development and Psychopathology, 13, 539–564.Google Scholar
Diamond, A. (2006). The early development of executive functions. In Bialystock, E. & Craik, F. I. M. (Eds.), The early development of executive functions. Lifespan cognition: Mechanisms of change (pp. 70–95). Oxford: Oxford University Press.Google Scholar
Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children 4 to 12 years old. Science, 333, 959–964.Google Scholar
Diamond, A., Prevor, M., Callender, G., & Druin, D. (1997). Prefrontal cortex cognitive deficits in children treated early and continuously for PKU. Monographs of the Society for Research in Child Development, 62, 1–208.Google Scholar
Dix, T. (1991). The affective organization of parenting: Adaptive and maladaptive processes. Psychological Bulletin, 110, 3–25.Google Scholar
Doan, S. N., & Evans, G. W. (2011). Maternal responsiveness moderates the relationship between allostatic load and working memory. Development and Psychopathology, 23, 873–880.Google Scholar
Enders, C. K. (2001). The impact of nonnormality on full information maximum likelihood estimation for structural equation models with missing data. Psychological Methods, 6, 352–370.Google Scholar
Evans, G. W., & Schamberg, M. A. (2009). Childhood poverty, chronic stress, and adult working memory. Proceedings of the National Academy of Sciences, 106, 6545–6549.Google Scholar
Farah, M. J., Shera, D. M., Savage, J. H., Betancourt, L. M., Gianetta, J. M., Brodskey, N. L., … Hurt, H. (2006). Childhood poverty: Specific associations with neurocognitive development. Brain Research, 1110, 166–174.Google Scholar
Fay-Stammbach, T., Hawes, D. J., & Meredith, P. (2014). Parenting Influences on executive function in early childhood: A review. Child Development Perspectives, 8, 258–264.Google Scholar
Fox, N. A., & Calkins, S. D. (2003). The development of self-control of emotion: Intrinsic and extrinsic influences. Motivation and Emotion, 27, 7–26.Google Scholar
Garon, N., Bryson, S. E., & Smith, I. M. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134, 31–60.Google Scholar
Gonzalez, A., Jenkins, J. M., Steiner, M., & Fleming, A. S. (2012). Maternal early life experiences and parenting: The mediating role of cortisol and executive function. Journal of the American Academy of Child & Adolescent Psychiatry, 51, 673–682.Google Scholar
Grenard, J. L., Ames, S. L., Wiers, R. W., Thush, C., Sussman, S., & Stacy, A. W. (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors, 22, 426.Google Scholar
Grusec, J. E., & Davidov, M. (2010). Integrating different theoretical perspectives on socialization theory and research: A domain-specific approach. Child Development, 81, 687–709.Google Scholar
Hackman, D. A., Betancourt, L. M., Gallop, R., Romer, D., Brodsky, N. L., Hurt, H., & Farah, M. L. (2014). Mapping the trajectory of socioeconomic disparity in working memory: Parental and neighborhood factors. Child Development, 85, 1433–1445.Google Scholar
Hackman, D. A., Farah, M. L., & Meaney, M. J. (2010). Socioeconomic status and the brain: Mechanistic insights from human and animal research. Nature Review Neuroscience, 11, 651–659.Google Scholar
Hester, R., & Garavan, H. (2005). Working memory and executive function: The influence of content and load on the control of attention. Memory & Cognition, 33, 221–233.Google Scholar
Hinson, J. M., Jameson, T. L., & Whitney, P. (2003). Impulsive decision making and working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 298–306.Google Scholar
Hofmann, W., Friese, M., & Roefs, A. (2009). Three ways to resist temptation: The independent contributions of executive attention, inhibitory control, and affect regulation to the impulse control of eating behavior. Journal of Experimental Social Psychology, 45, 431–435.Google Scholar
Hofmann, W., Friese, M., Schmeichel, B. J., & Baddeley, A. D. (2011). Working memory and self-regulation. In Vohs, K. D. & Baumeister, R. F. (Eds.), Handbook of self-regulation: Research, theory, and applications (2nd ed., pp. 204–225). New York: Guilford Press.Google Scholar
Hofmann, W., Gschwendner, T., Friese, M., Wiers, R. W., & Schmitt, M. (2008). Working memory capacity and self-regulatory behavior: Toward an individual differences perspective on behavior determination by automatic versus controlled processes. Journal of Personality and Social Psychology, 95, 962.Google Scholar
Hofmann, W., Rauch, W., & Gawronski, B. (2007). And deplete us not into temptation: Automatic attitudes, dietary restraint, and self-regulatory resources as determinants of eating behavior. Journal of Experimental Social Psychology, 43, 497–504.Google Scholar
Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16, 174–180.Google Scholar
Holmes, J., Gathercole, S. E., & Dunning, D. L. (2009). Adaptive training leads to sustained enhancement of poor working memory in children. Developmental Science, 12, F9–F15.Google Scholar
Hughes, C. (1998). Finding your marbles: Does preschoolers’ strategic behavior predict later understanding of mind? Developmental Psychology, 34, 1326–1339.Google Scholar
Hughes, C., & Ensor, R. (2005). Executive function and theory of mind in 2 year olds: A family affair? Developmental Neuropsychology, 28, 645–668.Google Scholar
Hume, T. (2012). PathSpan (Version 1.2) [Computer software]. Retrieved from http://itunes.apple.com Google Scholar
Joormann, J., & Gotlib, I. H. (2008). Updating the contents of working memory in depression: Interference from irrelevant negative material. Journal of Abnormal Psychology, 117, 182.Google Scholar
Khurana, A., Romer, D., Betancourt, L. M., Brodsky, N. L., Giannetta, J. M., & Hurt, H. (2012). Early adolescent sexual debut: The mediating role of working memory ability, sensation seeking, and impulsivity. Developmental Psychology, 48, 1416–1428.Google Scholar
Khurana, A., Romer, D., Betancourt, L. M., Brodsky, N. L., Giannetta, J. M., & Hurt, H. (2013). Working memory ability predicts trajectories of early alcohol use in adolescents: The mediational role of impulsivity. Addiction, 108, 506–515.Google Scholar
Khurana, A., Romer, D., Betancourt, L. M., Brodsky, N. L., Giannetta, J. M., & Hurt, H. (2015). Stronger working memory reduces sexual risk taking in adolescents, even after controlling for parental influences. Child Development, 86, 1125–1141.Google Scholar
Knight, E. D., Smith, J. B., Martin, L. M., 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). Chapel Hill, NC: University of North Carolina at Chapel Hill, Injury Prevention Research Center. Retrieved from http://www.iprc.unc.edu/longscan Google Scholar
LeFevre, J. A., Fast, L., Skwarchuk, S. L., Smith-Chant, B. L., Bisanz, J., Kamawar, D., & Penner-Wilger, M. (2010). Pathways to mathematics: Longitudinal predictors of performance. Child Development, 81, 1753–1767.Google Scholar
Lengua, L. J., & Kovacs, E. A. (2005). Bidirectional associations between temperament and parenting and the prediction of adjustment problems in middle childhood. Journal of Applied Developmental Psychology, 26, 21–38.Google Scholar
Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202.Google Scholar
Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). On the merits of orthogonalizing powered and product terms: Implications for modeling latent variable interactions. Structural Equation Modeling, 13, 479–519.Google Scholar
MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, 384–389.Google Scholar
Melby, J. N., & Conger, R. D. (2001). The Iowa family interaction rating scales: Instrument summary. In Kerig, P. K. & Lindahl, K. M. (Eds.), Family observational coding systems: Resources for systemic research (pp. 33–58). Mahwah, NJ: Erlbaum.Google Scholar
Mileva-Seitz, V., & Fleming, A. S. (2011). How mothers are born: A psychobiological analysis of mothering. In Booth, A., McHale, S. M., & Landale, N. S. (Eds.), Biosocial foundations of family processes (pp. 3–34). New York: Springer.Google Scholar
Murphy, B. L., Arnsten, A. F., Goldman-Rakic, P. S., & Roth, R. H. (1996). Increased dopamine turnover in the prefrontal cortex impairs spatial working memory performance in rats and monkeys. Proceedings of the National Academy of Sciences, 93, 1325–1329.Google Scholar
Noble, K. G., McCandliss, B. D., & Farah, M. J. (2007). Socioeconomic gradients predict individual differences in neurocognitive abilities. Developmental Science, 10, 464–480.Google Scholar
Noble, K. G., Norman, M. F., & Farah, M. L. (2005). Neurocognitive correlates of socioeconomic status in kindergarten children. Developmental Science, 8, 74–87.Google Scholar
Pagulayan, K. F., Busch, R. M., Medina, K. L., Bartok, J. A., & Krikorian, R. (2006). Developmental normative data for the Corsi-block tapping task. Journal of Clinical and Experimental Neuropsychology, 28, 1043–1052.Google Scholar
Pollak, S. D., Cicchetti, D., Klorman, R., & Brumaghim, J. T. (1997). Cognitive brain event-related potentials and emotion processing in maltreated children. Child Development, 68, 773–787.Google Scholar
Pollak, S. D., Klorman, R., Thatcher, J. E., & Cicchetti, D. (2001). P3b reflects maltreated children's reactions to facial displays of emotion. Psychophysiology, 38, 267–274.Google Scholar
Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437–448.Google Scholar
Putnam, S. P., & Rothbart, M. K. (2006). Development of short and very short forms of the Children's Behavior Questionnaire. Journal of Personality Assessment, 87, 102–112.Google Scholar
Rhoades, B. L., Greenberg, M. T., Lanza, S. T., & Blair, C. (2011). Demographic and familial predictors of early executive function development: Contribution of a person-centered perspective. Journal of Experimental Child Psychology, 108, 638–662.Google Scholar
Rothbart, M. K., Ahadi, S. A., Hershey, K. L., & Fisher, P. (2001). Investigations of temperament at 3–7 years: The Children's Behavior Questionnaire. Child Development, 72, 1394–1408.Google Scholar
Sarsour, K., Sheridan, M., Jutte, D., Nuru-Jeter, A., Hinsh, S., & Boyce, W. T. (2011). Family socioeconomic status and child executive functions: The roles of language, home environment, and single parenthood. Journal of the International Neuropsychological Society, 17, 120–132.Google Scholar
Sattler, J., & Ryan, J. (2009). Assessment with the WAIS–IV. LaMesa, CA: Jerome Sattler.Google Scholar
Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57, 1–10.Google Scholar
Siegle, G. J., Ghinassi, F., & Thase, M. E. (2007). Neurobehavioral therapies in the 21st century: Summary of an emerging field and an extended example of cognitive control training for depression. Cognitive Therapy and Research, 31, 235–262.Google Scholar
Steiger, J. H., & Lind, J. (1980). Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA.Google Scholar
Sturge-Apple, M. L., Suor, J. H., & Skibo, M. A. (2014). Maternal child-centered attributions and harsh discipline: The moderating role of maternal working memory across socioeconomic contexts. Journal of Family Psychology, 28, 645–654.Google Scholar
Thush, C., Wiers, R. W., Ames, S. L., Grenard, J. L., Sussman, S., & Stacy, A. W. (2008). Interactions between implicit and explicit cognition and working memory capacity in the prediction of alcohol use in at-risk adolescents. Drug and Alcohol Dependence, 94, 116–124.Google Scholar
Tofighi, D., & MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692–700.Google Scholar
US Department of Health and Human Services. (2012). 2012 Department of Health and Human Services poverty guidelines. Federal Register, 77, 4034–4035.Google Scholar
Waber, D. P., de Moor, C., Forbes, P. W., Almli, C. R., Botteron, K. N., Leonard, G., … Rumsey, J. (2007). The NIH MRI study of normal brain development: Performance of a population based sample of healthy children aged 6 to 18 years on neuropsychological battery. Journal of the International Neuropsychological Society, 13, 729–746.Google Scholar
Wechsler, D. (2002). Wechsler Preschool and Primary Scale of Intelligence (3rd ed.). San Antonio, TX: Psychological Corporation.Google Scholar
Wechsler, D. (2008). Wechsler Adult Intelligence Scale (4th ed.). San Antonio, TX: Pearson.Google Scholar
Wheaton, B. (1987). Assessment of fit in overidentified models with latent variables. Sociological Methods and Research, 16, 118–154.Google Scholar