Designing Socially Assistive Robots for Perinatal Depression Screening

Insights and Ethical Considerations from Two Exploratory Studies

Datos Bibliográficos

ID22190877
AutoresMengyu Zhong (0000-0002-6740-1111, Uppsala University), Lux Miranda (0000-0002-8238-8111, Uppsala University), Fotios C Papadopoulos (0000-0002-8692-3652, Uppsala University), Katie Winkle (0000-0002-3309-3552, Uppsala University), Alkistis Skalkidou (0000-0002-4935-7532, Uppsala University), Ginevra Castellano (0000-0002-2841-6791, Uppsala University)
Año2026
Volumen15
Número3
Páginas1-31
Fecha de publicación2026-05-31
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaACM Transactions on Human-Robot Interaction (JOURNAL)
Identificadores de la revistaISSN: 2573-9522 • E-ISSN: 2573-9522
EditorialAssociation for Computing Machinery (ACM) (PUBLISHER)
DOI10.1145/3797257
OpenAlexW7130424872
IdiomaEN
Referencias citadas48

Perinatal depression (PND) is a common mental health disorder associated with childbirth, which has high societal costs affecting up to 10% of individuals during pregnancy or postpartum. Whilst socially assistive robots (SARs) have recently proven to be useful tools in mental healthcare, and our previous work has investigated different stakeholders’ perspectives on SARs in PND screening through interview studies, gaps remain in understanding how primary users (i.e., prospective patients) perceive and interact with such technologies. In this article, we use a participatory design methodology with semi-structured interviews of women in Sweden with previous experience of PND to explore the roles that SARs could play in addressing PND challenges and identify design factors for SARs in PND screening. We design and evaluate in a user study a robot prototype in two new interaction contexts for SARs with different levels of human oversight. The results show that SARs are welcomed by most participants, who appreciated the potentially faster assessment process and felt more comfortable opening up with a robot versus a human clinician. However, we found that there is no single solution that fits all, as other participants preferred the flexibility of self-reported digital surveys or interaction with a human clinician. Moreover, results show that transparency and human oversight are crucial requirements to consider when implementing robot-delivered PND screening questionnaires and diagnostic interviews. We reflect on ethical considerations, provide design recommendations and urge HRI designers to carefully consider whom SARs benefit, whom they may not, and which safeguarding factors are necessary to prevent potential negative outcomes

Exploratory research · Human–robot interaction · Mental health · Participatory design · Qualitative research · Robot · Safeguarding · Digital Mental Health Interventions · Maternal Mental Health During Pregnancy and Postpartum · Mobile Health and mHealth Applications