Nudging university students to counselling and mental health (CMH) services: staff perspectives on the implementation of a proactive wellbeing analytics intervention

The volume of university students disclosing mental health difficulties is increasing, yet the proportion who access help is lower than expected. University counselling and mental health (CMH) teams are seeking new ways of working with data to ensure services are accessible, timely and effective. Qualitative data were collected via a focus group to explore CMH staff's perceptions on the implementation of a well-being analytics project at a UK university that aimed to improve service uptake by earlier identification of students at-risk and tailored signposting. Data were analysed using the Normalisation Process Theory alongside the RE-AIM evaluation framework. Staff expressed how the approach was unique in identifying students who would typically remain unseen or would be unlikely to self-refer otherwise. We recommend that future analytics projects should consider separate but interlinked roles for data analysis and student support, and highlight the importance of preparing teams for the proactive identification of students at-risk.