Acceptability of digital health solutions and AI: qualitative interviews with perimenopausal women experiencing health inequalities.

Objectives: Exploring the acceptability of digital health and artificial intelligence (AI) to perimenopausal women experiencing health inequalities. Setting: We recruited five community leaders representing organisations which support women who experience health inequalities, across the UK. Leaders represented ethnic minority-focused groups as well as groups representing broader disadvantage such as menopause or wellness groups based in areas of deprivation and domestic abuse support groups and were chosen to represent the experience of women in perimenopause who also experienced health inequalities. Data were collected from 84 women via five different community leaders and seven community groups in 24 qualitative datasets, which included 14 focus groups and 10 individual interviews. Inclusion criteria included experience of peri-menopause and membership within the designated group. Women who were beyond their last menstrual period were included to reflect on their experiences during peri-menopause as well as those actively experiencing symptoms. Analysis used the Theoretical Framework of Acceptability domains that influence the acceptability of health interventions. Results: Perimenopausal women expressed fear and distrust towards AI digital health interventions, particularly due to concerns about data privacy and lack of trust of representation of their racial and ethnic backgrounds. AI-driven solutions in women's health faced scepticism due to their perceived lack of relevance and effectiveness. Conclusion: Addressing issues of representation and improving trust in AI technologies are essential to enhance trust, improve engagement and reduce digital health inequalities.