Medicine and Health

Preferences for and intention to use an app for premenstrual mental health symptoms using the Health Behaviour Model (HBM)

E. L. Funnell, N. A. Martin-key, et al.

Discover how online insights illuminate preferences for premenstrual mental health apps! This research, conducted by Erin L. Funnell and colleagues, reveals the significant factors influencing the intention to use these crucial tools, focusing on user desires and perceived barriers. Don't miss out on their findings that aim to enhance app development and engagement.

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Playback language: English

Index

Abstract

This study investigated preferences for and factors influencing the intention to use an app for premenstrual mental health symptoms. An online survey of 530 UK participants (mean age 35.85) whose mental health was affected by their menstrual cycle was conducted. Symptom monitoring and psychoeducation were the most desired app features. Structural equation modeling (SEM) using the Health Belief Model (HBM) showed that cues to action, perceived barriers, perceived severity, and perceived benefits significantly predicted intention to use. The findings highlight the importance of app co-design, healthcare professional endorsement, clear communication of therapeutic benefits, and addressing user concerns regarding digital comfort, privacy, and app quality.

Publisher

npj Women's Health

Published On

May 24, 2024

Authors

Erin L. Funnell, Nayra A. Martin-Key, Jiri Benacek, Benedetta Spadaro, Sabine Bahn

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