Characteristics of multi-behavioural lifestyle interventions in university students to improve overall health: a scoping review.

University students are a key population group for early preventive interventions to mitigate the risk of developing non-communicable diseases (NCD) later in life, as during this transitional period, unhealthy lifestyle behaviours are often adopted.1–3 There is increasing evidence that lifestyle risk factors seldom occur in isolation.4,5 As a result, it has been suggested that addressing multiple rather than single behaviours may be more effective in improving health.2 This reasoning has been widely adopted, and since 2010, there has been a surge in multi-behavioural intervention studies, defined as interventions addressing two or more lifestyle risk factors.6 Despite this growth, accumulating evidence suggests that multi-behavioural interventions may not be as effective as initially anticipated. A systematic review by Meader et al. (2017) found that most multi-behavioural interventions conducted among general adult populations focused on addressing lifestyle behaviours simultaneously through education and skills-based approaches, resulting in only modest improvements in behaviour.7 In this review, only about a fifth of studies focused on university students. Streram et al. (2025) assessed the effectiveness of lifestyle interventions to improve both general and mental health among university students and found that multi-behavioural interventions were less effective than those targeting single behaviours.8 However, studies that did not report both general and mental health outcomes were excluded, potentially excluding interventions with a primary focus on behavioural or physical health. Furthermore, a shift in research priorities can be observed between the periods covered by these reviews. In Meader et al. (2017), nearly half of the studies focused exclusively on diet and physical activity, while fewer included alcohol and smoking, and none addressed sleep.7 In contrast, Streram et al. (2025) reported that sleep was targeted in 41% of studies, similar to diet (41%) and physical activity (46%) and alcohol use was also more frequently addressed compared to what was reported by Meader et al. (2017) (32% versus 23%).8 Taken together, the existing evidence does not necessarily indicate that multi-behavioural interventions are ineffective, but rather reveals substantial heterogeneity in targeted behaviours, intervention design and outcome selection. University students represented a minority of participants in an earlier review, and a more recent review applied restrictive inclusion criteria that have excluded relevant non-mental health-oriented interventions. Consequently, the current evidence base remains fragmented and can be better characterised, limiting meaningful synthesis and interpretation. Importantly, this heterogeneity poses particular challenges for translating existing evidence to low-resource university settings, where institutional capacity, health service infrastructure, and student health priorities may differ substantially from those in high-income contexts. Given the anticipated variability in intervention characteristics, outcomes and contextual settings, a systematic review is considered premature. Thus, a scoping review is deemed more appropriate to map the extent, nature, and characteristics of multi-behavioural lifestyle interventions among university students, to identify gaps, and to inform the design, adaptation, and evaluation of contextually appropriate and scalable interventions. Aim To map and describe the characteristics of multi-behavioural lifestyle interventions conducted among university students. Objectives 1. To map and describe the characteristics of multi-behavioural (2 modifiable risk factors) lifestyle interventions conducted among university students using the Template for Intervention Description and Replication (TIDIeR) checklist. 2. To identify and describe the modifiable lifestyle risk factors most frequently targeted by these interventions. 3. To summarise the types of health outcome measures used across included studies. 4. To identify and describe the most commonly used intervention components across included studies. 5. To identify gaps in intervention reporting and content relevant to the design and adaptation of scalable interventions in low-resource university settings.