Background <p>Pregnancy is a specific period that requires important nutrients for fetal growth and development. This study aims to review previous empirical studies that examine the determinants of healthy behavior during pregnancy, especially the studies that use HBM, SCT, or TPB framework. More specifically, this study develops a comprehensive conceptual model based on findings from previous studies to obtain a model with high predictive ability.</p> Methods <p>This study reviews 61 selected journal articles obtained from the Scopus and Web of Science databases and selected using the PRISMA method. The analysis includes trend analysis and analysis of findings. The analysis methods used are bibliometric analysis and content analysis.</p> Results <p>The analysis shows that research on this topic began in 1999. Although relatively low, there has been a growth in researchers’ interest in this topic. Most of the previous research used survey designs and cross-sectional data collection. Compared to HBM and SCT, TPB or its extension is more widely used to explain healthy behavior during pregnancy. Furthermore, the healthy behaviors that focus on researchers’ attention are quite diverse, which can then be categorized into six types of behavior. Analysis of previous research findings shows that healthy behavior in pregnant women is influenced by many factors.</p> Conclusions <p>A conceptual model to explain these behaviors has been developed based on these findings involving 11 variables.</p> Originality/value <p>This study is the first to integrate the three models (HBM, SCT, and TPB) to explain healthy behaviors during pregnancy.</p> Implications <p>This study can be used to develop intervention strategies to increase awareness and actively encourage pregnant women to adopt healthy lifestyles and habits for their health and that of their babies. However, this model needs to be tested empirically in various contexts to ensure its predictive power and stability.</p>

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Healthy behavior of pregnant women: review and integrated model conceptualization

  • Erry Yudhya Mulyani,
  • Tri Rakhmawati,
  • Sih Damayanti,
  • Agung Mulyo Widodo,
  • Anugrah Novianti,
  • Harlinda Syofyan,
  • Idrus Jus’at,
  • Sik Sumaedi

摘要

Background

Pregnancy is a specific period that requires important nutrients for fetal growth and development. This study aims to review previous empirical studies that examine the determinants of healthy behavior during pregnancy, especially the studies that use HBM, SCT, or TPB framework. More specifically, this study develops a comprehensive conceptual model based on findings from previous studies to obtain a model with high predictive ability.

Methods

This study reviews 61 selected journal articles obtained from the Scopus and Web of Science databases and selected using the PRISMA method. The analysis includes trend analysis and analysis of findings. The analysis methods used are bibliometric analysis and content analysis.

Results

The analysis shows that research on this topic began in 1999. Although relatively low, there has been a growth in researchers’ interest in this topic. Most of the previous research used survey designs and cross-sectional data collection. Compared to HBM and SCT, TPB or its extension is more widely used to explain healthy behavior during pregnancy. Furthermore, the healthy behaviors that focus on researchers’ attention are quite diverse, which can then be categorized into six types of behavior. Analysis of previous research findings shows that healthy behavior in pregnant women is influenced by many factors.

Conclusions

A conceptual model to explain these behaviors has been developed based on these findings involving 11 variables.

Originality/value

This study is the first to integrate the three models (HBM, SCT, and TPB) to explain healthy behaviors during pregnancy.

Implications

This study can be used to develop intervention strategies to increase awareness and actively encourage pregnant women to adopt healthy lifestyles and habits for their health and that of their babies. However, this model needs to be tested empirically in various contexts to ensure its predictive power and stability.