Mobile applications and physical activity registers: user portraying study

ˑ: 

PhD, Associate Professor O.G. Zhigareva1
PhD A.L. Yurchenko1
S.V. Skrygin1
M.V. Goryacheva1
1Financial University under the Government of the Russian Federation, Moscow

Keywords: physical activity, healthy lifestyle, mobile applications, training, population groups.

           Background. Modern meaning of physical activity refers primarily to the individual physical progress agenda with its determination, knowledgebase, habitual sporting/ physical education practices and healthy lifestyle. Physical activity in the context of the study was interpreted as the muscular activity for the individual physical fitness for job responsibilities and everyday life. As for the physical activity style, it was defined as the individual physical activity within a certain timeframe [2].

The growing interest in the origin and formation of physical activity stimulation models – viewed as the genuine component of a developed society – is understandable, and the modern pedagogical science logically comes up with the questions about their genesis, designs and functions [4].

It should be mentioned that the physical activity level is rated by calorific values and some other rates – with a sedentary job, e.g., claiming less than 2000 and about 3000 calories per day from women and men, respectively. These proportions give an idea of how the individual physical activity and diets shall be planned and managed [3, p. 62].

The World Health Organization (WHO) recommends a daily individual moderate-to-high-intensity physical activity of at least 60 minutes per day for the 5-17 year-olds; whilst the 18-64 adults and seniors are recommended to assign 150+ minutes a week for moderate intensity aerobic practices or 75+ minutes a week for high-intensity aerobic practices; with the same recommendation applicable to the 65+ age groups plus balancing and flexibility exercises. A special emphasis is made on the modern mobile fitness application tools and other relevant physical activity facilitating gadgets. Studies of the market of fitness applications including the daily physical activity recording and analyzing tools rank this market among the fastest growing ones [1, 5, 6, 8].

Objective of the study was to portray an average user of a mobile application who appreciates the short- and long-term benefits of the gadgets for the individual physical activity projects.

Methods and structure of the study. The study analyzed, among other things, popularity of the modern special social networks including Nike + Training Club, Runtastic, RunKeeper, Strava, Fitbit etc., with the users classified into the 13-17, 18-24, 25-34, 35-54 and 55+ age and gender groups.

Results and discussion. The study of a user community showed that the lifetime of a physical activity /fitness application is on average 2 times longer than of the other applications, with the user communities dominated by women: see Figure 1). Male users were found to prefer the least demanding applications – like  the gambling ones, for instance [4].

Figure 1. Gender stratification of the physical activity / fitness application user community, %

As for age groups, the user community is dominated by the 35-54 year old women followed with a small margin by the 25-34 year old women group: see Figure 2.

Figure 2. Age stratification of the physical activity / fitness application user community, %

It should be noted that the actual motivations of the 18-24 year old women (who are more proficient in the modern mobile technologies and dedicated to various applications) for the physical activity are still unclear at this juncture. On the whole, we analyzed a three-year-long physical activity of more than five hundred physical activity / fitness applications  (Nike + Training Club, Runtastic, RunKeeper, Strava, Fitbit etc.) using gender groups aged 18 to 54 years: see Tables 1, 2.

As demonstrated by the study data, women made progress of the three-year physical activity in the distances, calories, workouts and ascents, with the physical activity intensity being variable. The men’s group test data were more controversial. Thus the ascents, workouts, distances, average paces and total training times were found to fall by the end of the third year, with the male trainees reluctant to count the calorific demands.

Table 1. Physical activity progress: women’s group

Year 1

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Women

Distance, km

2,91

2,83

2,78

2,93

Average pace, min/km

6:37

6:29

6:27

6:16

Calories

206

301

217

331

Ascent, m

18

12

15

16

Training days

-

3

7

38

Total time

00:19:15

00:54:04

02:24.22

13:21.41

Year 2

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Women

Distance, km

5,04

5,81

4,86

4,98

Average pace, min/km

6:00

6:18

6:02

6:11

Calories

363

517

407

476

Ascent, m

12

18

16

18

Training days

-

2

8

31

Total time

00:30:18

01:14:04

04:49.32

15:52.12

Year 3

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Women

Distance, km

8,72

8,16

8,52

8,81

Average pace, min/km

6:26

6:24

6:18

6:12

Calories

629

586

611

627

Ascent, m

29

33

31

34

Training days

-

2

5

51

Total time

00:56:13

01:44:01

04:20.02

20:16.38

 

Table 2. Physical activity progress: men’s group

Year 1

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Men

Distance, km

5,22 

4,19 

4,19 

4,72 

Average pace, min/km

4.56 

5,14 

5,14 

5,01 

Calories

401

422 

422 

408 

Ascent, m

193 

164 

164 

166 

Training days

2

44

Total time

00:25:48 

00:52.17 

00:52.17 

18:56.47 

Year 2

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Men

Distance, km

2,17

4,56

5,1

5,32

Average pace, min/km

2.42

5,13

5.21

5,22

Calories

124

213

223

201

Ascent, m

3

7

21

23

Training days

-

5

19

173

Total time

00:05:51

00:31.14

05:02.05

45:34.41

Year 3

18-54 y.o.

Period

 

 

Trainings

First training

Week 1, average

Month 1, average

Yearly total, average

Мужчины

Distance, km

8.58

8,11

7,91

7,88

Average pace, min/km

4.40

5.12

5.21

5.27

Calories

567

611

587

593

Ascent, m

71

101

121

117

Training days

-

2

7

98

Total time

00:40:04

01:21.28

04:39.51

65:21.03

 

Conclusion. The study data and analyses made it possible to portray the modern physical activity / fitness application user community as dominated by the 18-54 year old individuals of the both genders dedicated to a healthy lifestyle and fashionable technological innovations and fairly proficient in these applications – which they find useful for their health agendas.

References

  1. Al Ayubi S.U., Parmanto B, Branch R., Ding D.A. Persuasive and Social mHealth Application for Physical Activity: A Usability and Feasibility Study. JMIR mHealth uHealth 2014; / [Electronic resource] 2(2):e25 Available at: http://mhealth.jmir.org/2014/2/e25/ doi:10.2196/mhealth.2902 PMID:25099928 (date of access: 09.06.2019).
  2. Weiner E.N., Kastyunin S.A. Brief Encyclopedic Dictionary. Adaptive physical education. Litagent Flinta, 2003. 145 p.
  3. Global recommendations on physical activity for health. WHO [Electronic resource] Available at: https://www.who.int/dietphysicalactivity/factsheet_recommendations/ru/ (data obrascheniya: 07.06.2019).
  4. Sarason-Kahn J. California Health Foundation. How smartphones are changing healthcare system for consumers and suppliers. [Electronic resource] Available at: https://www.chcf.org/wp-content/uploads/2017/12/PDF-How Smartphones Changing Health Care, (date of access 09.06.2019).
  5. Yurchenko A.L., Zhigareva O.G.., Anurov V.L., Sidorov A.S. Physical education system evolution in Russian statehood establishment period. Teoriya i praktika fiz. kultury, 2018. no. 4.
  6. Moore S.C., Lee I.M., Weiderpass E. et al. Association of physical activity in free time with a risk of developing 26 types of cancer in 1.44 million adults. [Electronic resource] JAMA Intern Med. 2016 June 1176 (6): 816-25. doi: 10.1001 / jamainternmed.2016.1548. (date of access: 09.06.2019).
  7. Sarasohn-Kahn J. California Health Care Foundation. How Smartphones Are Changing Health Care for Consumers and Providers [Electronic resource] Available at: https://www.chcf.org/wp-content/uploads/2017/12/PDF-How Smartphones Changing Health Care. (date of access: 09.06.2019)
  8. Andryushchenko L.B., Bodrov I.M., Zaytsev V.A., Buyanova T.V. Esteck complex application for age-specific functionality tests. Theory and Practice of Physical Culture. 2018. no. 9. p. 5.

Corresponding author: oksz70@mail.ru

Abstract

Modern meaning of physical activity refers primarily to the individual physical progress agenda with its determination, knowledgebase, habitual sporting/ physical education practices and healthy lifestyle. Physical activity in the context of the study was interpreted as the muscular activity for the individual physical fitness for job responsibilities and everyday life. As for the physical activity style, it was defined as the individual physical activity within a certain timeframe. Lately many physical activity registration gadgets has been increasingly used to capture and store the physical activity data arrays, with the users’ access to the training system design and management data significantly improved year to year. Such data and support is provided by many special social groups including Nike + Training Club, Runtastic, RunKeeper, Strava, Fitbit etc. Many users of such applications may freely share the training data and analyze their progress in the individual physical activity projects with communal support. At the same time, the progress rating and analyzing practices are still not that popular in a few traditional user groups which we would classify be gender and age. We analyzed the gender- and age-specific group progress in the individual physical activity projects in the 13-17, 18-24, 25-34, 35-54 and 55+ age groups. Objective of the study was to portray an average user of a mobile application who appreciates the short- and long-term benefits of the gadgets for the individual physical activity projects. The study data and analyses may be helpful for the personnel of the physical education and sport service companies, runner's club coaches, and for the relevant mobile gadgets marketing specialists.