The effects of yoga on student mental health: A pragmatic randomized controlled study.
University students in Norway experience double the symptom burden than that of the general population (Shot 2014). A school settings is demonstrated to be especially effective in terms of implementing mental health interventions (Jane-Llopis 2005). Moreover, policy makers (Jane-Llopis 2005) and global civil society (Patton et al 2016) highlight the importance of improving the mental health of young adults as it will generate positive effects among them, with carry over-effects into future generations (Patton et al 2016). Yoga, a physical and mental practice, may be one appealing option – it is increasing in popularity, available, relatively cheap, and associated with few risks.
To our knowledge, Pascoe and Bauer (2016) is the only solid systematic review on yoga and students. Although they suggest that yoga may reduce symptoms of distress and increase well-being, they conclude that this evidence is preliminary and needs to be explored further due to limitations with methodology as well as lack of follow-ups. This study will explore whether yoga can reduce student distress, both psychological and physiological, as well as other measures and co-determinants of mental health such as well-being and sleep. In order to assess the cost-effectiveness of yoga, we choose to include, not only a post-intervention, but also a a three month follow-up assessment.
Participants will be recruited from universities and colleges in the Oslo area. We will include students above the age of 18, without any serious mental health diagnosis or life crisis the past year. Participants have to be enrolled to an exam before and after the study within the same degree, and should not have practiced yoga systematically during the past six months.
The intervention group will be offered to practice yoga at “HiYoga” (a local yoga center) 1,25 hr two times a week for 12 weeks with a certified yoga alliance instructor. The yoga course is based on Ashtanga Vinyasa Yoga and will contain a mix of asana (physical yoga exercises), pranayama (breathing exercises) and meditation. The students will also learn about specific yamas and niyamas from yoga philosophy.
The control group will be on a waitlist, and will be asked to refrain from all yoga practices.
Our aim is to capture student mental health by assessing both psychological and physiological distress as well as two well-being measures, and have them fill in one sleep and one mindfulness questionnaire. Moreover, we aim to explore whether the effects may last beyond the yoga course period, by adding a 3 month follow-up to post-intervention measurements.
The hypothesis is that yoga decreases psychological and physiological distress and improves well-being, sleep and mindfulness both at post-test and follow-up.
Measurements and outcomes
The primary outcome, psychological distress, is measured by Hopkins Symptom Checklist (HSCL-25).
Secondary outcomes will be (1) Heart Rate Variability (HRV), measured through a nocturnal HRV test on Polar V800 watches, (2) well-being, measured with Satisfaction With Life Scale (SWLS) and Warwick-Edinburgh Mental Well-being Scale (WEMWBS), (3) mindfulness with Mindful Attention Assessment Scale (MAAS), (4) sleep with the Bergen Insomnia Scale (BIS) and (5) self reported exam grades.
Based on the standard deviation from a previous study of HSCL-25 (SD=0.33) (Strand et al fra 2003), a total sample of 150 participants would provide 80 % power (two-side α=0.05) to detect an effect of d=0.40 for change in HSCL-25 (corresponding to a 0.13 points difference on the HSCL-25) including both post-intervention and follow-up in the same analysis. Taking into account the possibility of a 25 % drop-out rate, 200 participates (100 in each group) will be recruited to the study.
Randomisation and masking
The participants will be randomised to intervention or control-group using an online randomisation tool. All data will be saved in order to reduce the risk of interference. The statistician will be blinded to group.
We are planning to analyse the data using a a linear mixed model, using the software IBM SPSS 25.0. We will compare the intervention and the control group on mean score on the primary and secondary outcomes at both postintervetnion and et follow-up, adjusting for possible group differences in baseline score of each outcome. The use of linear mixed models can handle values missing at random if the participant has a valid value on either post-intervention and follow-up. For participants who dropped out after randomization, multiple imputation of missing values will be used in order to provide an intention-to-treat analysis.
The study will be executed in two rounds. We aim at randomisation and baseline assessment for round one in January 2017 and for round two in August 2017, depending on HiYoga’s schedule, and when the pulse watches arrive.
Baseline (T1) will be assessed before the intervention in week o, post-intervention (T2) in week 12, and follow-up (T3) in week 24.
- Tiril: Responsible for agreements, recruitment to group and to the study, creation of material including consent form, attendance lists and injuries overview, randomisation, logistics with participants and HiYoga, assessments, writing first draft, formalities to Lancet application
- Jonny: Responsible for ethics committee application and the HRV analyses
- Gunvor: Responsible for questionnaires
- Pål: Responsible for results chapters and appendix
- Sandra: Responsible for literature search
- Arild: Overall coordination
Patton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, et al. Our future: a Lancet commission on adolescent health and wellbeing. Lancet. 2016; 387 (10036): 2423-78.
Jane-Llopis E, Barry MM. What makes mental health promotion effective? Promotion and education. 2005; 12 (2:suppl): 47-54.
Studentenes Helse og Trivselsundersøkelse (SHoT) 2014. http://www.studentvelferd.no/dokumenter/2014/09/SHoT-2014_Rapport_.pdf
Pascoe MC, Bauer IE. A systematic review of randomised control trials on the effects of yoga on stress measures and mood. J Psychiatr Res. 2015;68:270-82.