Research Article Critique

Predictors of Postpartum Depression

Postpartum depression (PPD) is moderate to a severe depressive episode that occurs a few weeks after a woman has given birth. Its prevalence increases during the first three months after delivery and continues for over a year. Approximately 13 percent of women who have given birth, experience the condition, which is associated with high maternal mortality and morbidity as well as pervasive impacts on the cognitive, behavioral, and emotional development of children (Gaillard, Strat, & Mandelbrot, 2014). Unfortunately,PPD has no single cause and is often associated with a combination of various physical and emotional factors (“Postpartum Depression Facts,” n.d). In light of this, Predictors of Postpartum Depression article seeks to unveil the underlying causes behind the condition. Based on research carried out at the prenatal care unit at the University Obstetrics Clinic, the study examines specific socio-demographic and clinical risk factors associated with postpartum depression. The purpose of this paper is to review and analyze the Predictors of Postpartum Depression to come up with a summarized review of the underlying causes of PPD.

Research Question

Postpartum depression is significantly common among the health problems that cause considerable impact and stress on families and society. PPD occurs at the same time as infant development and learning, leading to cognitive, behavioral, and emotional problems in the development of children whose mother has PPD. As it is, there has no definite cause of PPD, in spite of several studies attempting to unveil the causes. The purpose of the survey is to examine several socio-demographic factors, clinical risk behaviors, medical illness prior the pregnancy, history of depression, and birth outcomes to understand the risk factors of PPD.

Research Design

The research design used in the study is the survey research methods narrowed down to the use of questionnaires, which encompasses measurement procedures that involve posing questions to the respondents. In the article, the study materials were issued to women attending prenatal clinics at the University Obstetrics Clinic between 2004 and 2011. Among the designs of research, the authors utilized the model due to its convenience in data collection. Due to the large number of people the survey targeted, the survey research design presented a better option for data gathering and general description of the population. Compared to other methods, studies provide a high level of general capabilities in representing big data. Similarly, the process is relatively cheap as compared to other methods since researchers only need to pay for the survey questionnaires. Apart from the strengths of the study design, inflexibility can be seen as a weakness and strength at the same time, considering that the survey and method cannot be changed during the entire process of gathering data. A major weakness that the authors may have encountered was when dealing with controversial issues as they are not ideal for such. For instance, it may have been hard for respondents to recall fully pre-pregnancy illness, or open up about drug use and domestic violence.

Study Sample

The entire sample for screening was 3,039 women who were at four or eight months pregnant. Out of the total number, 1,515 women were not included in the analysis as the lacked postpartum assessment – a majority of them attended clinics near their homes instead of the high-risk obstetrics clinic at the University. Eighty-four were not considered because they only filled the 8-month questionnaire and there were no questions about medical history, and 17 were left out because they did not have data on birth outcomes. The study was only left with 1,423 women for data analysis, evaluation, and recording of findings. To assess whether the number of participants was adequate as compared to the research question we compute the expected number of women who should have enrolled in the study to ensure a 95 percent confidence interval was achieved assuming the margin error was no more than 5 percent.

n_i = {p(1-p) + p(1-p)} (^Z/_E)² = {0.13(1-0.12) + 0.13(1-0.12)}(^1.96/_0.05)² = 347.6

According to the above calculation, a sample size of 348 pregnant women would ensure that the 95 percent confidence interval for the predictors of postpartum depression would be achieved. The large sample size allowed the use of full screening sample and a wide range of predictor variables.

Data Collection Methods

The authors used questionnaires as their data collection methods, which were distributed by the clinical staff to the pregnant women who visited the clinics in their 4^th or 8^th month of pregnancy. During the data gathering process, the women were requested for their written consent to link their medical records with survey results as per the medical ethics. Nevertheless, because of the nature of the busy obstetrics clinic, the clinical staff were not able to get all the questionnaires completed.

Limitations of the Study

According to Katon, Russo & Gavin (2014), the study was only carried out from one clinic located in one geographical region in the United States. As such, it would be hard to use the research findings to generalize the predictors of postpartum depression since such factors could only be present in the geographical area and not in other places. Similarly, the questionnaire sought to evaluate the association of alcohol to postpartum depression. By concluding that less alcohol during pregnancy is associated with high risk of PPD reflects missing gaps in the questionnaire, as only a minority was identified with alcohol use and only a few with abuse or dependency. Another thing is, by using the 6-week PPD screening, the study may have missed PPD developed within the three-month period.

Research Findings

From the research, it is clear that, women with depressive symptoms during pregnancy and use anti-depressants, which is a high risk of PPD. Other predictors of postpartum depression included younger age, smoking, less alcohol consumption and the presence of psychosocial stressors. Women who had diabetes before pregnancy were also at a higher risk of getting PPD. The research findings emphasize that depressive symptoms were the strongest risk factors of PPD. Similarly, younger women who were exposed to smoking, or were unemployed were also at a higher danger of developing PPD. Based on the mode of study and where data was gathered, the results of the survey can be defined as credible.

Summary

It is clear that postpartum depression is highly prevalent within three months after delivery, and although previous research has not been exhaustive on factors associated with the condition, it is clear that depressive symptoms before pregnancy are one of the major causes. Other factors have also been related to PPD but at a lower risk. Attention to these factors may help nurses in evidence-based practice, where primary care during pregnancy can be tailored to focus on women who display signs of depression and come up with a way of managing the condition before it gets out of hand.

References

“Postpartum Depression Facts.” (n.d). National Institute of Mental Health. Retrieved from: https://www.nimh.nih.gov/health/publications/postpartum-depression-facts/index.shtml

Gaillard, A., Strat, Y., L., Mandelbrot, L., Keita, H., & Dubertret, C. (2014). Predictors of postpartum depression: Prospective study of 264 women followed during pregnancy and postpartum. Psychiatry Research, 215(2), pp. 341-346.

Katon, W., Russo, J., & Gavin, A. (2014). Predictors of Postpartum Depression. Journal of Women’s Health, 23(9), pp. 753-759.