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Background Male infants are more prone to health problems and developmental delays than female infants. Objectives On the basis of theories of gender differences in brain development and social relationships, we explored associations between testosterone and cortisol levels with infant cognitive, motor, and language development (“infant development”) in very low birth weight (VLBW) infants, controlling for mother–infant interactions, characteristics of mothers and infants, and days of saliva collection after birth. Methods A total of 62 mother–VLBW infant pairs were recruited from the newborn intensive care unit of a tertiary medical center in the Southeast United States. Data were collected through infant medical record review, biochemical measurement, observation of mother–infant interactions, and standard questionnaires. Infant development was assessed at 6 months corrected age (CA), and mother–infant interactions were observed at 3 and 6 months CA. Results General linear regression with separate analyses for each infant gender showed that high testosterone levels were positively associated with language development of male infants after controlling for mother–infant interactions and other covariates, whereas high cortisol levels were negatively associated with motor development of female infants after controlling for mother–infant interactions. Conclusions Steroid hormonal levels may well be more fundamental factors for assessing infant development than infant gender or mother–infant interactions at 6 months CA.

Background: Investigators addressing nursing research are faced increasingly with the need to analyze data that involve variables of mixed types and are characterized by complex nonlinearity and interactions. Tree-based methods, also called recursive partitioning, are gaining popularity in various fields. In addition to efficiency and flexibility in handling multifaceted data, tree-based methods offer ease of interpretation. Objectives: The aims of this study were to introduce tree-based methods, discuss their advantages and pitfalls in application, and describe their potential use in nursing research. Method: In this article, (a) an introduction to tree-structured methods is presented, (b) the technique is illustrated via quality of life (QOL) data collected in the Breast Cancer Education Intervention study, and (c) implications for their potential use in nursing research are discussed. Discussion: As illustrated by the QOL analysis example, tree methods generate interesting and easily understood findings that cannot be uncovered via traditional linear regression analysis. The expanding breadth and complexity of nursing research may entail the use of new tools to improve efficiency and gain new insights. In certain situations, tree-based methods offer an attractive approach that help address such needs.