SAFE: an eHealth intervention for women experiencing intimate partner violence - study protocol for a randomized...

Area of Science:

• Public Health
• Digital Health
• Psychology

Background:

• Intimate partner violence (IPV) affects a significant portion of women globally, yet many face barriers to disclosing abuse or seeking help.
• eHealth interventions offer a promising, accessible, and anonymous alternative to traditional support services for IPV survivors.
• The SAFE project in the Netherlands is developing and evaluating an eHealth intervention for female victims of IPV.

Purpose of the Study:

• To evaluate the effectiveness of the SAFE eHealth intervention for female victims of intimate partner violence.
• To assess the impact of the intervention on users' self-efficacy.
• To understand user experiences and website utilization through a process evaluation.

Main Methods:

• A randomized controlled trial with a two-arm parallel design comparing an intervention group with enhanced eHealth features against a control group with static information.
• Quantitative data collection via questionnaires at multiple time points (baseline, 3, 6, 12 months), with self-efficacy (General Self-Efficacy scale) as the primary outcome at 6 months.
• A mixed-methods process evaluation incorporating website analytics, web evaluation questionnaires, and qualitative interviews to explore user experiences.

Main Results:

• eHealth interventions demonstrate potential for broad reach among women experiencing IPV.
• Internet-based designs can effectively reduce barriers to accessing support and encourage help-seeking behaviors.
• The study aims to provide real-world user data through an open feasibility study.

Conclusions:

• eHealth interventions hold significant potential to support women experiencing intimate partner violence.
• The accessibility and anonymity of eHealth can lower barriers to help-seeking, potentially reducing delays in protective actions.
• Further evaluation through feasibility studies will provide insights into real-world application and user data.