# Exercise as it relates to Disease/The role of psychological predictors and physical activity apps in promoting physical activity during the Covid-19 lockdown in Australia

This is a critical appraisal from the research article "Promoting physical activity during the COVID-19 lockdown in Australia: The roles of psychological predictors and commercial physical activity apps" by Jasmine M. Peterson, Eva Kemps, Lucy K. Lewis, Ivanka Prichard.
This is an assignment for the unit; Health, Disease and Exercise at the University of Canberra, Semester 2, 2021.

## What is the background to this research?

For over 18 months, Australia has experienced very unprecedented times due to the many effects that the COVID- 19 lockdown has had on our lives. Physical activity has been shown to have many physical and mental health benefits, creating great concern that the COVID 19 lockdown negatively impacts engagement in physical activity. The outbreak in not only Australia but internationally, holds public health concerns due to the stay at home orders creating adverse outcomes, increasing the populations sedentary behaviour. In April 2021, Sport Australia released National and State data about participation in sport and active recreation. In 2020, 63.9% of the population above the age of 15 participated in sport and active recreation. Due to the impacts this lockdown has on the population’s involvement in physical activity, particularly in community sport and recreation, innovative approaches need to be made to improve engagement in physical activity and keeping people connected.

## Where is the research from?

Jasmine M. Peterson, Eva Kemps, Lucy K. Lewis and Ivanka Prichard conducted a nationwide survey following the initial lockdown which concluded in May 2020. Their research took place at Flinders University in Adelaide in the Caring Futures Institute (college of nursing and health sciences, SHAPE research centre and Psychology, College of education. The research was supported by a COVID-19 Agility Research Grant from the Caring Futures Institute, College of Nursing & Health Sciences, Flinders University. The authors declare that there were no conflicts of interest (financial or personal relationships) that may have influenced their research.

## What kind of research was this?

The study was an observational design in which participants were selected from a pre-existing database. Participants were asked to respond in an online survey.

## What did the research involve?

A final sample of 408 participants were used out of 471 initial respondents in which all participants provided informed consent electronically with ethical approval granted by the University’s social and behavioural research ethics committee. The data was collected through the Qualtrics platform from June to July in 2020 with participants assessed on physical activity, mental health and physical activity app use during lockdown.
Through the survey, various things were assessed among participants, these included:
* Physical activity- Participants self- reported the physical activity they participated in during lockdown in which they recorded what type of activity (e.g. running), frequency and duration. Total physical activity was calculated by multiplying the frequency of each activity by its duration.
* Perceived change in physical activity - there were 6 response options in which the options ranged from ‘much more active than usual to ceased physical activity altogether’, these responses were then categorised into increased, no change or decreased.
* Social support- the use of The 'Social Support for Exercise Behaviours Scale' enabled the assessment of perceived social support for physical activity from family or friends during lockdown, provided on a 5-point Likert scale from 1 (never) to 5 (very often).
* Physical activity efficacy - The 'Physical Activity Self-Efficacy Scale' was used to measure perceived self- efficacy. This scale helps determine how certain, from 1 (very uncertain) to 4 (very certain) that an individual believes they are able to participate in physical activity when faced with difficulties (e.g. depressed or lacking energy).
* Behavioural regulation motives - The '19-item Behavioural Regulation in Exercise Questionnaire' (BREQ-2) was used to assess self-determined motivation among participants during the lockdown.
* Mental Health - The 'Depression, Anxiety and Stress Scales' (DASS-21) was used to measure participants mental health during the COVID-19 lockdown. The items were rated on a 4-point Likert Scale from 0 (Did not apply to me) to 3 (Applied to me very much). Severity ratings were then recorded according the DASS sub-scale (normal to extremely severe).
* Use of commercial physical activity apps - Participants recorded whether they had used a physical activity app that was able to track their physical activity, therefore needing to specify the app (e.g. Fitbit).
* Engagement with app - specific communities - Using a 6-point Likert scale from 0 (never) to 5 (very often), participants specified how often they engaged with members of the app community in various forms.
* Engagement with social network platforms - Participants reported their engagement in social media platforms related to physical activity using a series of Likert scales, ranging from never (0) to very often (5).

## What were the basic results?

Of the 408 participants, a large percentage (53.4%) reported a decrease in physical activity, 23.8% reported an increase and the remaining 22.8% reported no change. The main forms of physical activity the participants engaged in were walking (43.5%), running (19%), home workouts (16.1%), yoga / pilates (6%), cycling (5.6%) and strength training (3.1%).The physical activity that participants engaged in (min/ week) varied significantly according to age, BMI and location. 51.2% of participants used a commercial physical activity app, the most frequently used apps were Strava (23%), Fitbit (16.3%) and Garmin (10%). Almost all participants using these apps (82.8%), reported engagement with the app - specific community or social media platforms relating to physical activity and exercise.

## What conclusions can we take from this research?

The results concluded in this study are consistent with various other studies that have been completed in both non-pandemic and pandemic times. A study completed by E.S Anderson- Bill et al. in 2011 (non-pandemic) looked at ‘Social Cognitive Determinants of Nutrition and Physical Activity Among Web-Health Users Enrolling in an Online Intervention: The Influence of Social Support, Self-Efficacy, Outcome Expectations, and Self-Regulation’. The results found in Andersons study during non-pandemic times, are consistent with the results found in this current study. Although the results indicated a negative correlation between physical activity and mental health, this suggests that mental health plays an important role in the engagement of physical activity during lockdown no matter what. To increase the efficacy of this study, rather than having participants self-record their physical activity levels, activity monitors could be used to accurately represent their engagement in exercise as self-recorded results could create error in measure as participants may under or overestimate their physical activity.

## Practical advice

During a pandemic, it can be difficult to find motivation to get out of bed, let alone get outside and move your body but this has proven to greatly improve overall health and wellbeing. By targeting social support, self-efficacy and independent motivation, this will essentially help improve physical activity levels during the pandemic and overall wellbeing. In order to support this, physical activity apps should be encouraged among populations as this creates an innovative approach to improving motivation towards physical activity during these unprecedented times. Most importantly, it is hoped that by improving motivation and self- efficacy towards exercise that this will greatly benefit mental health outcomes.

## Further information/resources

For further information and help regarding benefits of physical activity and recommended apps/ resources to help you stay active, follow these links:
https://www.nia.nih.gov/health/infographics/5-tips-help-you-stay-motivated-exercise
https://www.health.gov.au/news/health-alerts/novel-coronavirus-2019-ncov-health-alert/ongoing-support-during-coronavirus-covid-19/exercising-and-staying-active-during-coronavirus-covid-19-restrictions
Apps to search for in the app store (available on iOS and android):
- Nike training club
- Couch to 5k
- Strava
- FitBit coach
- Daily Yoga
- Headspace

## References

* 1 2 3 4 5 6 7 8 9 10 11 12 Jasmine M. Peterson, Eva Kemps, Lucy K. Lewis, Ivanka Prichard. Promoting physical activity during the COVID-19 lockdown in Australia: The roles of psychological predictors and commercial physical activity apps. Psychology of Sport and Exercise, 2021 (56)
* ↑ Horesh Dor-Haim, Sara Katzburg, Polla Revach, Hagai Levine & Sharon Barak. The impact of COVID-19 lockdown on physical activity and weight gain among active adult population in Israel: a cross-sectional study. BMC Public Health 21, 1521 (2021)
* 1 2 Sports NSW. Participation in sport and active recreation, 2021. https://www.sport.nsw.gov.au/participation-sport-and-active-recreation
* 1 2 I. Prichard and M. Tiggemann. Relations among exercise type, self-objectification, and body image in the fitness centre environment: The role of reasons for exercise. Psychology of Sport and Exercise, 9 (6) (2008), pp. 855-866.
* ↑ R. Stanton, Q.G. To, S. Khalesi, S.L. Williams, S.J. Alley, T.L. Thwaite et al. Depression, anxiety and stress during COVID-19: Associations with changes in physical activity, sleep, tobacco and alcohol use in Australian adults. International Journal of Environmental Research and Public Health, 17 (11) (2020), p. 4065
* ↑ J.F. Sallis, R.M. Grossman, R.B. Pinski, T.L. Patterson and P.R. Nader. The development of scales to measure social support for diet and exercise behaviours. Preventive. Medicine, 16 (6) (1987), pp. 825-836.
* 1 2 R. Schwarzer and B. Renner. Health-specific self-efficacy scales, Vol. 14, Freie Universität Berlin (2009), p. 2009
* ↑ D. Markland and V. Tobin. A modification to the behavioural regulation in exercise questionnaire to include an assessment of amotivation. Journal of Sport & Exercise Psychology, 26 (2) (2004), pp. 191-196.
* 1 2 3 P.F. Lovibond and S.H. Lovibond. The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the beck depression and anxiety inventories. Behaviour Research and Therapy, 33 (3) (1995), pp. 335-343
* ↑ J.M. Petersen, E. Kemps, L.K. Lewis and I. Prichard. Associations between commercial app use and physical activity: Cross-sectional study. Journal of Medical Internet Research, 22 (6) (2020), Article e17152
* ↑ E.S. Anderson-Bill, R.A. Winett and J.R. Wojcik. Social cognitive determinants of nutrition and physical activity among web-health users enrolling in an online intervention: The influence of social support, self-efficacy, outcome expectations, and self-regulation. Journal of Medical Internet Research, 13 (1) (2011), p. e28