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Predictors of postpartum stress

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  • Chich‐Hsiu Hung
  • Chia‐Ju Lin
  • Joel Stocker
  • Ching‐Yun Yu

Abstract

Aim. To predict important factors in women’s postpartum stress. Background. The transition to motherhood is often accompanied by stress, but research on predictors of postpartum stress is scant. Design. A cross‐sectional survey was used in the study. Methods. Proportional stratified quota sampling based on births at 11 registered general hospitals and seven specialty clinics in the Kaohsiung area of southern Taiwan was used to obtain a high degree of representation. Eight hundred and fifty‐nine women participated in the study within six weeks postpartum. The Hung postpartum stress scale, the social support scale and the 12‐item Chinese Health Questionnaire were used in this study. Results. Women with minor psychiatric morbidity, one or two children, junior college educational level, formula feeding for their infants, preference for an infant boy and a low level of social support were important predictors for women’s postpartum stress. Conclusion. Our findings provide information and data for service planning and community care for the prevention and amelioration of postpartum stress. Relevance to clinical practice. Postpartum women face a constellation of factors that could put them at risk for high levels of postpartum stress. Postpartum stress could significantly negatively impact women’s health status. Nursing interventions should be tailored to decrease women’s postpartum stress as a means of promoting postpartum women’s pursuit of well‐being.

Suggested Citation

  • Chich‐Hsiu Hung & Chia‐Ju Lin & Joel Stocker & Ching‐Yun Yu, 2011. "Predictors of postpartum stress," Journal of Clinical Nursing, John Wiley & Sons, vol. 20(5‐6), pages 666-674, March.
  • Handle: RePEc:wly:jocnur:v:20:y:2011:i:5-6:p:666-674
    DOI: 10.1111/j.1365-2702.2010.03555.x
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    Cited by:

    1. Zhang, Chi & Managi, Shunsuke, 2020. "Functional social support and maternal stress: A study on the 2017 paid parental leave reform in Japan," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 153-172.

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