Supplementary 2 - Literature Review Search Strategy

Preeclampsia is a form of gestational hypertension that usually appears after the 20th week of pregnancy. Evidence suggests that low-dose aspirin (LDA) effectively prevents the onset of preeclampsia, but the uptake rate remains low. This scoping review aims to synthesize and integrate existing knowledge domains relevant to factors which influence women’s medication decisions during pregnancy, and to develop a causal explanation for at-risk women’s LDA uptake decisions. We introduced systems thinking to map the variables and develop causal loops to show variable interactions and causal explanations guided by the Theory of Planned Behavior. We extracted 64 variables, grouped into provider- (n=19), patient- (n=39), and system-level (n=7) factors. By identifying variable interactions, we built a theory to explain various causal pathways leading to LDA treatment uptake. Mapping the variables and supporting the relationships of these variables with theories and concepts increases our study’s generalizability to medication decisions for other pregnancy complications.

Publication Details

Journal
Stanford Digital Repository
Published
2024-12-18
DOI
https://doi.org/10.25740/zj395jx5411
Primary Topic
Protist diversity and phylogeny
Type
article
Field-Weighted Citation Impact
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article

Supplementary 2 - Literature Review Search Strategy

Stanford Digital Repository
Protist diversity and phylogeny
article

Supplementary 2 - Literature Review Search Strategy

article en

Abstract

Preeclampsia is a form of gestational hypertension that usually appears after the 20th week of pregnancy. Evidence suggests that low-dose aspirin (LDA) effectively prevents the onset of preeclampsia, but the uptake rate remains low. This scoping review aims to synthesize and integrate existing knowledge domains relevant to factors which influence women’s medication decisions during pregnancy, and to develop a causal explanation for at-risk women’s LDA uptake decisions. We introduced systems thinking to map the variables and develop causal loops to show variable interactions and causal explanations guided by the Theory of Planned Behavior. We extracted 64 variables, grouped into provider- (n=19), patient- (n=39), and system-level (n=7) factors. By identifying variable interactions, we built a theory to explain various causal pathways leading to LDA treatment uptake. Mapping the variables and supporting the relationships of these variables with theories and concepts increases our study’s generalizability to medication decisions for other pregnancy complications.

Stanford Digital Repository
Good health and well-being
Openalex Percentile: Top 60%
Protist diversity and phylogeny
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