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Related Experiment Videos

Some controls control too much.

Nora S Newcombe1

  • 1Psychology Department, Temple University, Philadelphia, PA 19122-6085, USA. newcombe@temple.edu

Child Development
|August 27, 2003
PubMed
Summary
This summary is machine-generated.

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Statistical controls in research risk creating unrealistic scenarios. This study suggests the negative effects of time in child care may be overestimated due to unexamined links with family income and maternal depression.

Area of Science:

  • Child Development
  • Developmental Psychology
  • Socioeconomic Factors in Early Childhood

Background:

  • Researchers often use statistical controls to isolate variables.
  • This method can lead to studying artificial scenarios and drawing inaccurate conclusions.
  • The National Institute of Child Health and Human Development (NICHD) Early Child Care Research Network studied time in child care.

Purpose of the Study:

  • To evaluate the potential overestimation of negative effects associated with time in child care.
  • To examine the influence of confounding variables like family income and maternal depression.
  • To assess the validity of statistical controls in early childhood research.

Main Methods:

  • Analysis of data from the NICHD Early Child Care Research Network.

Related Experiment Videos

  • Statistical control for family income and maternal depression.
  • Examination of indirect causal pathways linked to child care use.

    • Main Results:

    • Controlling for family income and maternal depression may overestimate negative effects of child care duration.
    • Maternal employment, linked to child care use, influences income and maternal depression.
    • These linked factors impact children's socioemotional adjustment, suggesting complex interactions.

    Conclusions:

    • The negative impacts of time in child care may be overstated when not accounting for mediating factors.
    • Statistical controls can obscure real-world causal pathways in family and child development research.
    • Future research should consider complex, interconnected factors for accurate policy conclusions.