Perspectives, preferences and needs regarding early prediction of preeclampsia in Dutch pregnant women: A qualitative study
Background: To improve early risk-identification in pregnancy, research on prediction models for common pregnancy complications is ongoing. Therefore, it was the aim of this study to explore pregnant women's perceptions, preferences and needs regarding prediction models for first trimester screening for common pregnancy complications, such as preeclampsia, to support future implementation. Method: Ten focus groups (of which five with primiparous and five with multiparous women) were conducted (n = 45). Six focus groups were conducted in urban regions and four in rural regions. All focus group... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2017 |
Schlagwörter: | Attitudes / Need / Preeclampsia / Preferences / Qualitative research / Screening |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26678029 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://repub.eur.nl/pub/95629 |
Background: To improve early risk-identification in pregnancy, research on prediction models for common pregnancy complications is ongoing. Therefore, it was the aim of this study to explore pregnant women's perceptions, preferences and needs regarding prediction models for first trimester screening for common pregnancy complications, such as preeclampsia, to support future implementation. Method: Ten focus groups (of which five with primiparous and five with multiparous women) were conducted (n = 45). Six focus groups were conducted in urban regions and four in rural regions. All focus group discussions were audio taped and NVIVO was used in order to facilitate the thematic analysis conducted by the researchers. Results: Women in this study had a positive attitude towards first trimester screening for preeclampsia using prediction models. Reassurance when determined as low-risk was a major need for using the test. Self-monitoring, early recognition and intensive monitoring were considered benefits of using prediction models in case of a high-