# Drivers and barriers of acceptance of eHealth interventions in postpartum mental health care: a cross-sectional study

## TL;DR

This study explores how women accept eHealth tools for postpartum mental health, finding that those with mental health issues show high acceptance.

## Contribution

The study identifies specific drivers and barriers to eHealth acceptance in postpartum women using the UTAUT model.

## Key findings

- 68.21% of women showed high acceptance of eHealth interventions for postpartum mental health.
- Women with mental illness or postpartum depression reported significantly higher acceptance.
- The extended UTAUT model explained 59.82% of the variance in acceptance.

## Abstract

Postpartum mental health problems are common in women. Screening practice and treatment options are less common, which is a possible threat to health of mothers and children. eHealth interventions might bridge the gap but few validated programs are available. For developing relevant tools, an assessment of user behavior is a relevant step. Users’ acceptance of eHealth interventions can be examined via the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

A cross-sectional study was conducted between October 2022 and June 2023. Acceptance, sociodemographic, medical, psychometric, and eHealth data were assessed. This study included 453 women who had experienced pregnancy. Multiple hierarchical regression analysis and group comparisons (t-tests, ANOVA) were conducted.

High acceptance of eHealth interventions in postpartum mental health care was reported by 68.21% (n = 309) of women. Acceptance was significantly higher in women affected by mental illness, t(395) = -4.72, padj < 0.001, d = 0.50, and with postpartum depression (present or past), t(395) = -4.54, padj < 0.001, d = 0.46. Significant predictors of acceptance were Perceived support during pregnancy (β = − 0.15, p = .009), Quality of life (β = − 0.13, p = .022), Postpartum depression (β = 0.40, p = .001), Digital confidence (β = 0.18, p = .002), and the UTAUT predictors Effort expectancy (β = 0.10, p = .037), Performance expectancy (β = 0.50, p < .001) and Social influence (β = 0.25, p < .001). The extended UTAUT model was able to explain 59.82% of variance in acceptance.

This study provides valuable insights into user behavior of women who experienced pregnancy. High acceptance towards eHealth interventions in postpartum mental health care and identified drivers and barriers should be taken into account when implementing tailored eHealth interventions for this vulnerable target group. Specifically women with mental health issues report high acceptance and should therefore be addressed in a targeted manner.

The online version contains supplementary material available at 10.1186/s12889-025-25297-1.