About the Project
This research project intends to compare the influence of identical exercise modalities on the wellbeing of the performer in three different locations: urban (grey space), rural (green space) and beside water (blue space). The benefits of exercise are well documented and as such the British population is encouraged to be physically active. Running and cycling are examples of exercise that can be undertaken in grey and green spaces, and adjacent to blue spaces. Numerous studies have reported that the health and wellbeing benefits of being in, and around, blue spaces may be even greater than those found in green spaces (White et al., 2017; Kelly, 2018). These spaces are often free to access and therefore are potentially a good place to host physical activity interventions to improve health and wellbeing.
There are numerous descriptions of well-being within academic literature (Tabor & Yull., 2018; Pouw & McGregor., 2014; Dodge et al., 2012; Diener, Suh & Smith, 1999) however, it is still cited by scholars that well-being is ‘elusive’ (Bharara et al., 2019) and ‘heterogenous’ (Hausman, 2006). This may be due to the broad and multidimensional nature of well-being. As mental health issues increase (NHS Digital, 2018 [online]), so does interest in measuring well-being. Measurement tools can only be validated if they are underpinned by an explicit definition (MacKenzie, Podsakoff & Podsakoff, 2011). Wellbeing has been defined as, “The perception of an interaction between an individual’s positive feelings and external influences” (Gennings, Brown & Hewlett, 2021). This definition has been selected from a pool of definitions and is based on a sample of expert’s conceptualisations of wellbeing. For this proposed thesis, the external influence will be the environment.
This study will need to select an exercise modality that all participants can partake in, and then design identical routes in terms of distance and climb in three suitable target locations (grey, green, and blue). Participants will rate their enjoyment of the physical activity, for example, using the Physical Activity Enjoyment Scale (PACES) (Mullen et al., 2011). They will also rate their wellbeing before, during and after a prescribed physical activity programme in the three locations. A chapter of the thesis will be dedicated to reviewing wellbeing measurement scales prior to selecting the most appropriate. The PhD candidate can exercise their own free will in selecting any further parameters they may wish to measure, e.g., situational mindfulness (Yang, 2020) or the impact of using digital health technology to increase intrinsic motivation and self-determination (Lupton, 2020).
This PhD opportunity could suit candidates from a variety of backgrounds, including sport and exercise science, exercise and health psychology, sociology, and environmental geography. There is an opportunity to shape the project to suit the candidate’s background and interests.
Bharara, G., Duncan, S., Jarden, A., & Hinckson, E. (2019). A prototype analysis of New Zealand adolescents’ conceptualizations of wellbeing. International Journal of Wellbeing, 9(4)
Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological bulletin, 125(2), 276.
Dodge, R., Daly, A., Huyton, J., & Sanders, L. (2012). The challenge of defining wellbeing. International Journal of Wellbeing, 2(3), 222-235.
Gennings, E. K., Brown, H., & Hewlett, D. (2021). Constructing a definition: Adolescent wellbeing from the perspective of the child and expert. International Journal of Wellbeing, 11(1), 69-88.
Hausman, D. M. (2006). Valuing health. Philosophy & public affairs, 34(3), 246-274.
Kelly, C. (2018). ‘I Need the Sea and the Sea Needs Me’: Symbiotic coastal policy narratives for human wellbeing and sustainability in the UK. Marine Policy, 97, 223-231.
Lupton, D. (2020) ‘Better Understanding about what’s going on’: young Australians’ use of digital technologies for health and fitness. Sport, Education and Society, 25(1), 1-13.
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioral research: integrating new and existing techniques. MIS Quarterly, 35(2), 293-334.
Mullen, S.P., Olson, E.A., Phillips, S.M., Szabo, A.N., Wójcicki, T.R., Mailey, E.L., Gothe, N.P., Fanning, J.T., Kramer, A.F. and McAuley, E. (2011). Measuring enjoyment of physical activity in older adults: invariance of the physical activity enjoyment scale (paces) across groups and time. International Journal of Behavioral Nutrition and Physical Activity, 8(1), pp.1-9.
NHS Digital. (2018). Mental Health of Children and Young People in England, 2017. [online] Available: https://files.digital.nhs.uk/95/AC12EC/MHCYP%202017%20Multiple%20Conditions.pdf.
Pouw, N., & McGregor, A. (2014). An Economics of Wellbeing: What Would Economics Look Like if it were Focused on Human Wellbeing? IDS Working Paper, 436, 1-27
Tabor, D., & Yull, J. (2018). Personal Well-being in the UK: July 2017 to June 2018. Office for National Statistics. 1-12.
White, M. P., Pahl, S., Wheeler, B. W., Depledge, M. H., & Fleming, L. E. (2017). Natural environments and subjective wellbeing: Different types of exposure are associated with different aspects of wellbeing. Health & Place, 45, 77-84.
Yang, C.H. and Conroy, D.E. (2020). Mindfulness and physical activity: a systematic review and hierarchical model of mindfulness. International Journal of Sport and Exercise Psychology, 18(6), pp.794-817.