Background: The global challenge of nursing student dropout is widely studied. However, literature review regarding concrete identification of students at risk of dropping out is lacking.

Aim: To identify and describe existing tools used in identifying undergraduate bachelor-level nursing students at risk of dropping out and the ability of these tools to identify at-risk students.

Design: Mixed-methods systematic review.

Data sources: Five databases, CINAHL (EBSCOhost), MEDLINE (PubMed), ERIC (EBSCOhost), Scopus and Web of Science, were searched in July 2024 and reference lists screened.

Review methods: The review was conducted following the JBI mixed-methods systematic review methodology. Studies describing concrete tools to identify individual bachelor-level nursing students at risk of dropping out were included, without temporal limits. Eligible studies were assessed with JBI Critical Appraisal tools. Convergent integrated approach was followed to synthesize data. In total, 12 studies were included.

Results: Fourteen tools for identifying at-risk nursing students were found, most of them being questionnaires. The tools covered different content areas for dropout-risk identification, ranging from single-area to broad coverage. The tool's ability to identify was examined either as the ability to predict actual or intended dropout, warning signals, or to differentiate at-risk and not-at-risk students, or was not directly measured. Student-registry-based tools seemed to have stronger evidence of their capability compared to questionnaires, yet did not cover a student's personal, emotional or life-situation factors related to dropout, accessible via questionnaires.

Conclusions: Currently, when no tool seems to be superior to another, educators and administrators exploring possibilities to implement these tools need to consider and possibly compromise between predictive accuracy and thoroughness. Further studies are needed to determine the appropriate balance between the objective and subjective factors when developing a valid and reliable tool with the ability to predict either intention or actual dropout of nursing students.