The role of social support, being present and self-kindness in university student well-being

ABSTRACT

Poor well-being in university students is a serious concern. Using self-kindness – an attitude of understanding and benevolence in times of adversity or failure – may be key to enabling students to maintain well-being despite the pressures inherent to their student role. This study aimed to test a theoretically guided model of how self-kindness, along with the ability to be in the present moment and the experience of receiving social support, contribute to well-being in university students. Participants were 6195 university students who completed a web-based survey. Structural equation modelling analyses confirmed our hypotheses, showing that: (a) receiving social support is important to the capacity for self-kindness both directly and indirectly through the ability to ‘be present’; and (b) the relationship between social support and well-being is partially mediated by the practices of self-kindness and being present. Overall, the model explained 39% of the variance in student well-being. These findings have implications for our understanding of well-being in university students, as well as the importance of considering self-kindness, on its own, as a target for intervention.

KEYWORDS:

• Mental health
• well-being
• self-kindness
• mindfulness
• social support

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Helen M. Stallman is a Clinical Psychologist and specialist in the development and evaluation of interventions aimed to improve mental health and well-being in university students. The quality and impact of her work has been recognised with a number of awards.

Jeneva L. Ohan is a Senior Lecturer and Psychologist, with expertise in child development, child psychopathology and stigma.

Belinda Chiera is a Senior Lecturer in Statistics at the School of Information Technology and Mathematical Sciences, University of South Australia. She has over 16 years’ experience in applying statistical analysis techniques including working with very large data sets for government, industry and addressing complex social analytics.