Prenatal nursing intervention studies published in Korean nursing journals: a scoping review.
Seo Yun KimHae Won KimPublished in: Korean journal of women health nursing (2020)
The purpose of this study was to describe prenatal nursing intervention studies on pregnant women and their families published in Korean nursing journals to identify research trends and to analyze the characteristics of intervention studies. This scoping review was conducted using Arksey and O'Malley's framework. We identified a research question and searched six domestic electronic databases for relevant articles. Forty-five references that met the inclusion and exclusion criteria were finally selected. We extracted the data using an analytic framework, and then collated and summarized the characteristics of the intervention studies. The most frequently used research designs were non-randomized controlled trials (91.1%), and only a few studies applied a specific theoretical framework (24.4%). The participants were mainly pregnant women only (64.4%) during the third trimester (35.6%) of pregnancy. Prenatal education was the most common type of intervention (48.9%), followed by complementary therapy (37.8%) and psychosocial support programs (13.3%). The most commonly used outcome variables were drawn from the psychological domain (44.5%), although distinct types of outcome variables-especially from the psychological and physical domains-were used to measure the effectiveness of different types of prenatal interventions. This review suggests that further prenatal nursing intervention studies in Korea should expand the study participants to include pregnant women's family members, high-risk and vulnerable groups, and women throughout entire pregnancy. Furthermore, it is necessary to develop integrative prenatal nursing interventions that promote family support and participation by facilitating partnerships among women, families, and nurses before, during, and after pregnancy.
Keyphrases
- pregnant women
- pregnancy outcomes
- randomized controlled trial
- mental health
- healthcare
- case control
- quality improvement
- physical activity
- preterm birth
- systematic review
- type diabetes
- clinical trial
- big data
- meta analyses
- stem cells
- polycystic ovary syndrome
- machine learning
- depressive symptoms
- electronic health record
- cell therapy
- deep learning