Date of Completion


Document Type

Honors College Thesis



Thesis Type

Honors College, College of Arts and Science Honors

First Advisor

Hugh Garavan


The effect of maternal state on infant development in utero has been an important topic of research; however, maternal social support has not been well defined as a factor in infant outcomes. The COVID-19 pandemic provided an opportunity to study widespread changes in social support in perinatal women. In an effort to better understand the relationship between perinatal maternal social support and infant temperament and development, this study analyzed data from the COVID-19 and Perinatal Experiences (COPE) study, including ten measures of social support from the Medical Outcomes Study (MOS) Social Support Survey and COPE-IS survey, three measures of infant temperament from the Infant Behavior Questionnaire-Revised, and five measures of infant development from the Ages and Stages Questionnaire, Third Edition. The main hypothesis was that increased maternal social support during the perinatal period would be associated with a decrease in infant negative affect at twelve months of age. Linear regressions were run predicting infant negative affect from maternal social support, as well as predicting other measures of infant temperament and development. Maternal social network support and a specific measure of emotional/informational support significantly predicted infant negative affect approximately one year later. Additionally, the relationship appeared to be specific to social support measured early in the perinatal period. No other relationships were found between maternal social support and infant temperament or development. Overall, these findings promote perinatal maternal social support as an important factor in the development of infant temperament (specifically negative affect), with emotional support appearing to have the greatest individual influence.


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Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.