Conectar
Large language model tools are increasingly used in higher education, offering opportunities to support self-directed learning. In nursing education, course-specific AI virtual tutors may provide contextualised support while addressing concerns about content accuracy and alignment; yet empirical evidence remains limited.
This study evaluated the use and perceived impact of a co-designed AI-powered virtual tutor embedded in a graduate-level Master of Nursing (MN) course. We explored how students used the tutor, their perceptions of benefits and limitations, and its influence on learning and engagement.
A pilot study using a mixed-methods explanatory sequential design was employed. The tutor was trained on course-specific materials and integrated into the institutional learning management system. Data included anonymised usage logs and user interactions coded using Bloom's Taxonomy of Educational Objectives, post-course surveys assessing AI self-efficacy, usability, and learning impact, and semi-structured interviews with students and teaching assistants (TAs). Quantitative and qualitative strands were integrated through a joint display.
A total of 651 interactions by individuals within a group of ~120 MN students were logged. Interactions peaked in evenings and around assignment deadlines. Most interactions reflected lower-order education processes, with more application and analysis later in the course. Eleven participants completed surveys; students reported high AI self-efficacy and moderate tutor use. Perceived usefulness was mixed, but most reported the tutor enhanced both lower- and higher-level learning and recommended its future use. Interviews revealed that students valued the tutor's immediacy and course-specific accuracy, while TAs noted efficiency gains. Reported challenges included usability issues, scope limitations, privacy concerns, and risk of over-reliance on the tool.
A co-designed AI virtual tutor was feasible and valued for contextual relevance, though perceived usefulness was variable. Findings support responsible, pedagogically integrated use of AI tutors in graduate nursing education.
Postpartum psychosis is a psychiatric emergency that occurs following childbirth. Women are often cared for in general psychiatric units or in psychiatric Mother and Baby units. Postpartum psychosis is associated with a significant risk of relapse. There is a need to explore how women perceive care to understand what works well or needs further improvement.
This review aimed to explore women's experiences of care and support for postpartum psychosis.
A systematic review using meta-ethnographic methods was conducted.
Comprehensive searches were conducted between 4 March 2024 and 4 March 2025 on five databases (CINAHL, EMBASE, MEDLINE, PsycINFO and Web of Science). Backward and forward chain searching was also undertaken.
Critical appraisal was conducted following screening. Reciprocal and refutational translation were used to form the synthesis, and a line of argument was developed. The eMERGe reporting guidelines were used.
Fifteen studies were included within this synthesis. All the studies were conducted in high income countries and included 235 women. Three main themes were developed. ‘Navigating the unknown’ explored women's perceptions of postpartum psychosis as a less well-known condition, and their informational needs. ‘The double-edged sword of care’ found that there were helpful elements of formal mental health care, but that accessing care was sometimes traumatic, stigmatising and conflicting to women's identities. ‘Seeking consolation and recovery’ explored women's need for psychological support and experiences of peer support.
The findings of this review highlighted women's needs in respect to informational support, medication support, psychological support and in-patient care settings. Mother and baby units were strongly preferred by women.
The findings highlighted a need for specialised care for postpartum psychosis.
There were no patient or public contributions.
Prospero (CRD42024515712)
FreshRSS