Meta-analysis of the predictive factors of postpartum fatigue
Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with...
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Veröffentlicht in: | Applied nursing research 2017-08, Vol.36, p.122-127 |
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description | Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes.
We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes.
Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (rrange=0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (rrange=0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (rrange=0.50+) for depression.
Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue.
•Nearly 64% of new mothers are affected by fatigue during the postpartum period.•Education level, age, postpartum hemorrhage, infection, and child-care difficulties had a small effect on predicting PPF.•Physiological illness, sleeping and breastfeeding problems, stress and anxiety had a medium effect on predicting PPF.•Depression had the largest effect on predicting PPF. |
doi_str_mv | 10.1016/j.apnr.2017.06.010 |
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We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes.
Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (rrange=0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (rrange=0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (rrange=0.50+) for depression.
Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue.
•Nearly 64% of new mothers are affected by fatigue during the postpartum period.•Education level, age, postpartum hemorrhage, infection, and child-care difficulties had a small effect on predicting PPF.•Physiological illness, sleeping and breastfeeding problems, stress and anxiety had a medium effect on predicting PPF.•Depression had the largest effect on predicting PPF.</description><identifier>ISSN: 0897-1897</identifier><identifier>EISSN: 1532-8201</identifier><identifier>DOI: 10.1016/j.apnr.2017.06.010</identifier><identifier>PMID: 28720232</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Depression, Postpartum - psychology ; Fatigue ; Fatigue - psychology ; Female ; Humans ; Infant, Newborn ; Mother-Child Relations - psychology ; Mothers - psychology ; Nursing ; Postnatal ; Postnatal fatigue ; Postpartum ; Postpartum fatigue ; Predictive factors ; Predictive Value of Tests ; Pregnancy ; Reproducibility of Results ; Risk Assessment</subject><ispartof>Applied nursing research, 2017-08, Vol.36, p.122-127</ispartof><rights>2017 Elsevier Inc.</rights><rights>Copyright © 2017 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-f9aff35636590d708353871b09160c15bf2dfdc1f2856ffbed0766da1368e9803</citedby><cites>FETCH-LOGICAL-c422t-f9aff35636590d708353871b09160c15bf2dfdc1f2856ffbed0766da1368e9803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.apnr.2017.06.010$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28720232$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Badr, Hanan A.</creatorcontrib><creatorcontrib>Zauszniewski, Jaclene A.</creatorcontrib><title>Meta-analysis of the predictive factors of postpartum fatigue</title><title>Applied nursing research</title><addtitle>Appl Nurs Res</addtitle><description>Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes.
We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes.
Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (rrange=0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (rrange=0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (rrange=0.50+) for depression.
Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue.
•Nearly 64% of new mothers are affected by fatigue during the postpartum period.•Education level, age, postpartum hemorrhage, infection, and child-care difficulties had a small effect on predicting PPF.•Physiological illness, sleeping and breastfeeding problems, stress and anxiety had a medium effect on predicting PPF.•Depression had the largest effect on predicting PPF.</description><subject>Adult</subject><subject>Depression, Postpartum - psychology</subject><subject>Fatigue</subject><subject>Fatigue - psychology</subject><subject>Female</subject><subject>Humans</subject><subject>Infant, Newborn</subject><subject>Mother-Child Relations - psychology</subject><subject>Mothers - psychology</subject><subject>Nursing</subject><subject>Postnatal</subject><subject>Postnatal fatigue</subject><subject>Postpartum</subject><subject>Postpartum fatigue</subject><subject>Predictive factors</subject><subject>Predictive Value of Tests</subject><subject>Pregnancy</subject><subject>Reproducibility of Results</subject><subject>Risk Assessment</subject><issn>0897-1897</issn><issn>1532-8201</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE9LAzEQxYMoWqtfwIP06GXXmaSb3QU9SPEfVLzoOaTZiaa03TXJFvrtTW316GUG3rz3YH6MXSDkCCiv57nuVj7ngGUOMgeEAzbAQvCsStohG0BVlxmmccJOQ5gDII4lHLMTXpUcuOADdvtCUWd6pReb4MKotaP4SaPOU-NMdGsaWW1i638uXRtip33sl0mN7qOnM3Zk9SLQ-X4P2fvD_dvkKZu-Pj5P7qaZGXMeM1tra0UhhSxqaEqoRCGqEmdQowSDxczyxjYGLa8Kae2MGiilbDQKWVFdgRiyq11v59uvnkJUSxcMLRZ6RW0fFNYcRI0lF8nKd1bj2xA8WdV5t9R-oxDUFpuaqy02tcWmQKqELYUu9_39bEnNX-SXUzLc7AyUvlw78ioYRyuTMHkyUTWt-6__G00EfZE</recordid><startdate>201708</startdate><enddate>201708</enddate><creator>Badr, Hanan A.</creator><creator>Zauszniewski, Jaclene A.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>201708</creationdate><title>Meta-analysis of the predictive factors of postpartum fatigue</title><author>Badr, Hanan A. ; Zauszniewski, Jaclene A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-f9aff35636590d708353871b09160c15bf2dfdc1f2856ffbed0766da1368e9803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Depression, Postpartum - psychology</topic><topic>Fatigue</topic><topic>Fatigue - psychology</topic><topic>Female</topic><topic>Humans</topic><topic>Infant, Newborn</topic><topic>Mother-Child Relations - psychology</topic><topic>Mothers - psychology</topic><topic>Nursing</topic><topic>Postnatal</topic><topic>Postnatal fatigue</topic><topic>Postpartum</topic><topic>Postpartum fatigue</topic><topic>Predictive factors</topic><topic>Predictive Value of Tests</topic><topic>Pregnancy</topic><topic>Reproducibility of Results</topic><topic>Risk Assessment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Badr, Hanan A.</creatorcontrib><creatorcontrib>Zauszniewski, Jaclene A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Applied nursing research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Badr, Hanan A.</au><au>Zauszniewski, Jaclene A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Meta-analysis of the predictive factors of postpartum fatigue</atitle><jtitle>Applied nursing research</jtitle><addtitle>Appl Nurs Res</addtitle><date>2017-08</date><risdate>2017</risdate><volume>36</volume><spage>122</spage><epage>127</epage><pages>122-127</pages><issn>0897-1897</issn><eissn>1532-8201</eissn><abstract>Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes.
We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes.
Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (rrange=0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (rrange=0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (rrange=0.50+) for depression.
Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue.
•Nearly 64% of new mothers are affected by fatigue during the postpartum period.•Education level, age, postpartum hemorrhage, infection, and child-care difficulties had a small effect on predicting PPF.•Physiological illness, sleeping and breastfeeding problems, stress and anxiety had a medium effect on predicting PPF.•Depression had the largest effect on predicting PPF.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>28720232</pmid><doi>10.1016/j.apnr.2017.06.010</doi><tpages>6</tpages></addata></record> |
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subjects | Adult Depression, Postpartum - psychology Fatigue Fatigue - psychology Female Humans Infant, Newborn Mother-Child Relations - psychology Mothers - psychology Nursing Postnatal Postnatal fatigue Postpartum Postpartum fatigue Predictive factors Predictive Value of Tests Pregnancy Reproducibility of Results Risk Assessment |
title | Meta-analysis of the predictive factors of postpartum fatigue |
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