The birth of a child often causes a serious emotional imbalance on a mother due to a mix of joy, anxiety and fear coming with parenthood. In some cases, the fear and anxiety can escalate to serious depression. Postpartum depression occurs to about 10% of all new mothers. It may limit them from performing normal activities and socializing with their social circles. Postpartum depression chips in weeks after giving birth though in some women it may start long before giving birth. If a woman is specifically highly insecure, anxious and moody during pregnancy, postpartum depression may chip in. Katon, Russo and Gavin (2014) conducted a study to examine socio demographic factors, pregnancy-associated psychosocial stress and depression, health risk behaviors, pre-pregnancy medical and psychiatric illness, pregnancy related illnesses, and birth outcomes as risk factors for postpartum depression (PDD).
This summary shall focus on the study questions and the methods which have been used to test the predictors. A prospective cohort study was conducted with the sample constituting women in the fourth to eighth months of their pregnancy. Hierarchical logistic regression was used in the analysis of to examine predictors of postpartum depression. The sample size was 1,423. The women who participated in the study were in a university based high risk obstetrics clinic. A questionnaire was used in the interviewing process to establish whether there were concrete grounds to conclude that there were symptoms of postpartum depression. In the conclusions section, the study established that women who were predisposed to factors such as anxiety were more prone to PDD. Young women who were unemployed were more likely to experience PDD. Women who were abusing various drugs were also predisposed to depression as compared to those who were not abusing any drug. Such women were more likely to be under the use of antidepressants to prepare them ahead of the childbearing process. The study also investigated the role of psychosocial stress in triggering postpartum depression. Pre-pregnancy related diseases were also found to play a significant role in PDD. Women who had diabetes and neurologic conditions were found to be more predisposed to PDD as compared to those who did not have these conditions. The study, therefore, identified specific socio-demographic and clinical risk factors which can be integrated into the prenatal management practices to ensure that women being prepared to undergo childbearing process are free from depression hence achieving right emotional state to manage their fears and anxiety.
The title outlines the subject of the study. Postpartum depression is a popular topic which can be tackled from various approaches. Katon, Russo & Gavin (2014), target its predictors. Their target population can be questioned. Factors can trigger postpartum depression before birth or by factors after birth. In this study, all 1,423 participants were in their fourth to eight months of their pregnancy which may present biased information. The bias may be founded on the fact that there were no predictors in women after giving birth. The process exposes the mother to anxiety and tosses her to an identity crisis while trying to fit into motherhood. If for instance the new mother is subjected to emotional torture by those closely related to her, postpartum depression may be experienced.
According to Thurgood, Avery and Williamson (2009), some distinctions such as postpartum psychosis and postpartum traumatic stress disorder can break the attachment between the mother and the child triggering feelings of helplessness on the side of the mother. In some of these cases, the feelings maybe triggered if the mother was initially so attached to the child but later realizes she cannot provide the child with the life she wanted. In a situation where the mother breaks up with the father immediately after birth, postpartum depression can be experienced. Pregnancy after rape are also characterized by such scenarios where the mother may fail to own up the pregnancy and develop an attachment to the child. Katon, Russo and Gavin (2014), therefore presented a slightly hollow argument since they did not consider predictors which could have occurred after birth. However, they present a concrete argument supported by empirical evidence which can be employed in any clinical setting to offer insight on PDD, its predictors and consequentially management approaches which can be employed.
This is a quantitative research. Data is collected and analyzed to test the proposed hypotheses. A correlational research design was employed in the study. In psychological based studies, correlational research designs allow the researcher to isolate and manipulate an independent variable and hence observe its effect on a dependent variable. The environment can be controlled to ensure that the factors are monitored and manipulated as much as possible. In this study, the sample size (1,423) is sufficient to provide enough data for a correlational research. Presence of different predictors is used as a variable to establish whether they play any role in predisposing the new mothers to PDD. Some of the variables (factors) discussed in the study include unemployment, drug abuse, neurological disorders and other medical conditions before childbirth. The variables can be manipulated considering that the researchers can compare the results between mothers who are exposed to them and the results on those who are not exposed. A continuous PHQ-9 severity measure was used as an independent variable.
Hypotheses given sought to test the role of different predictors in PDD. In the study, a total number of sampled participants were 3,039 though the ones whose data was included in the study were compared with the 1,616 whose data was not included. This therefore helped in the creation of non-response prosperity scores with the baseline variables being the factors identified above (demographics, depression, pregnancy variables and medical conditions). Univariate analysis was conducted on the data collected.
The analytical process employed in the study can be used to correlate data and provide enough information to test the given hypotheses. The hypotheses were aimed at exploring a specific niche where the researchers could manipulate variables to get the factual information required for the study (Ranjit, 2014). Therefore, as far as the confines of the study and the hypotheses being tested are of concern, the study achieved its goals. The research design employed is popular in psychological research considering that majority of the study often involve making observations and getting information from questionnaires filled in by respondents (Kothari, Kumar, & Uusitalo, 2014). The questionnaires were developed having open and closed-ended questions which would give insight on the state of the mothers and the experiences they had experienced in the period preceding the pregnancy and the one succeeding conception.
The authors only focused on prenatal analysis hence the results could be biased. It was important to consider predictors after giving birth such as loss of attachment with a child which may be possible in cases of marital problems.
The study established that younger age, unemployment, antenatal depressive symptoms, psychosocial stressors, physical illnesses such as diabetes and drug abuse acted as independent predictors to PDD. Considering the methodology employed in the study, the results can be adopted since the empirical approach employed is not devoid as compared to the guidelines of social research.
1. Katon, W., Russo, J. & Gavin, A. (2014). Predictors of Postpartum Depression. Journal of Women’s Health, 23(9), 753-759.
2. Kothari, C., Kumar, R., & Uusitalo, O. (2014). Research Methodology. New Age International. https://doi.org/http://18.104.22.168:8080/jspui/bitstream/123456789/2574/1/Research%2 0Methodology.pdf
3. Ranjit, K. (2014). Research methodology a step-by-step guide for beginners. Sage. https://doi.org/10.1177/1362361315580442
4. Thurgood, S., Avery, D. M. & Williamson, L. (2009). Postpartum Depression (PDD). American Journal of Clinical Medicine, 6(2), 17-22.