Postpartum Depression: Statistics and Methods of Diagnosis Essay

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The postpartum disorder, which is best known as one related to pregnancy, might be compounded by prenatal anxiety, prenatal depression, postpartum depression, or even panic attacks.

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Shulman (2018) states that 10-20% of new mothers suffered from postpartum depression (PDD).

Up to 40-60% of adolescent mothers and approximately 50% of those with low income experienced postpartum depression (Shulman, 2018).

Only 15 % of them seek treatment for postpartum depression, while others continue to suffer from such symptoms of any depressive disorder as fatigue, irritability, low energy, sleepiness.

According to DelLisle (2018), about 103 women out of 1000 suffer PDD, and most of them are not recorded.

Moreover, not all providers can recognize the signs of PDD timely and provide a woman with appropriate care and education on the issue (Marques, 2018).

Lack of PDD screening may cause potential negative consequences for a mother as well as for a child.

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The research (Haelle, 2018) has shown that the children of mothers with PDD are at high risk of developmental delays, sleep problems, acquiring mental health conditions, lower IQ. Mothers, in turn, might stop breastfeeding earlier.

The following tools for screening PPD can be used: the Patient Health Questionnaire (PHQ) and the Edinburgh Postpartum Depression Scale (EPDS) incorporated into the data management systems utilized at healthcare facilities.

The incorporation of the screening tools into the existing electronic medical support system has proved to lead to positive outcomes for both mothers and children (van der Zee-van den Berg et al., 2016). Women completed the questionnaires during their regular visits, and the data was incorporated into the electronic medical support system. The system sent reminders to clinicians, so the decision-making process was facilitated. The integration of the questionnaires that have proved their efficiency into data management systems can be an effective evidence-based informatics tool. The system may analyze the results of the questionnaires and trace the negative trends in each case. If a woman displays the occurrence of some depressive symptoms, the system will send reminders and guidelines to physicians to take the necessary actions based on a set of scenarios.

References

DeLisle, G. P. (2018). Forum Italicum. Web.

Haelle, T. (2018). Pediatric News. Web.

Marques, R., Monteiro, F., Canavarro, M. C., & Fonseca, A. (2018). The role of emotion regulation difficulties in the relationship between attachment representations and depressive and anxiety symptoms in the postpartum period. Journal of Affective Disorders, pp: 7-11. Web.

Shulman, B., Royce, D., Deirdre, R., Breau, G., Sadowski, I., & Misri, S. (2018). Feasibility of a Mindfulness-Based Cognitive Therapy Group Intervention as an Adjunctive Treatment for Postpartum Depression and Anxiety. Journal of Affective Disorders, pp: 4-9. Web.

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Van der Zee-van den Berg, A. I., Boere-Boonekamp, M. M., IJzerman, M. J., Haasnoot-Smallegange, R. M. E., & Reijneveld, S. A. (2016). Screening for postpartum depression in well-baby care settings: A systematic review. Maternal and Child Health Journal, 21(1), 9-20. Web.

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IvyPanda. (2022) 'Postpartum Depression: Statistics and Methods of Diagnosis'. 13 February.

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IvyPanda. 2022. "Postpartum Depression: Statistics and Methods of Diagnosis." February 13, 2022. https://ivypanda.com/essays/postpartum-depression-treatment-study/.

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IvyPanda. "Postpartum Depression: Statistics and Methods of Diagnosis." February 13, 2022. https://ivypanda.com/essays/postpartum-depression-treatment-study/.

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