Development of a New Antenatal Measure to Predict Postpartum Depression
by Jenkins, Danielle D., Psy.D., GEORGE FOX UNIVERSITY, 2012, 125 pages; 3501336

Abstract:

Postpartum depression is 1 of the most common pregnancy complications, yet many women feel too ashamed to get help. It is important to study postpartum depression so that it can more easily be detected, more quickly treated, and that the stigma around this illness can be reduced. Early detection is vital to prevent complications for the infant, mother, and beyond. The first hypothesis of this study was that some identified antenatal factors would be more predictive of postpartum depression than other factors. Those factors were then used to construct the Measurement of Motherhood Stress – Second Edition (MOMS-II). The second hypothesis was that as the number of risk factors increase, then the score on the Edinburgh Postnatal Depression Scale (EPDS) and Patient Health Questionnaire-9 (PHQ-9) would rise. Statements were created using risk factors identified in the literature and were added to a Likert-type scale to create the 33 item screener, Measurement of Motherhood Stress (MOMS; Jenkins, DePierre, Wilson, & Thurston, 2011). The MOMS, the EPDS, and the PHQ-9 were given to 160 pregnant women. Following the birth of the child, the EPDS and PHQ-9 were re-administered to 86 participants and results were collected. Item analysis was then performed on the MOMS. Thirteen items were stronger predictors of postpartum depression and were used to create a 10-item revised MOMS scale. Additionally, as predicted, the more stressors endorsed on the MOMS, the higher the depression scores on the EPDS and the PHQ-9. This study highlights the utility of an antenatal screener for postpartum depression as an important piece in the early detection and treatment of postpartum depression.

 
AdviserNancy Thurston
SchoolGEORGE FOX UNIVERSITY
SourceDAI/B 73-07(E), p. , Mar 2012
Source TypeDissertation
SubjectsObstetrics and gynecology; Developmental psychology; Clinical psychology; Quantitative psychology and psychometrics
Publication Number3501336
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