App use, physical activity and healthy lifestyle: a cross sectional study

Benefits of physical activity have often been studied and include improved health and reduced mortality rates [1‐3]. However, actually becoming physically active is a challenge for many. In the Netherlands research shows that 41 % percent of all adults do not comply with the Dutch Public Health Physical Activity Guideline (at least 30 min of moderate to vigorous physical activity during at least 5 days of the week) [4]. Moreover, only 20 % of Dutch adults meet the Strenuous Intensity Physical Activity Guideline of at least three times a week 20 min of vigorous exercise [4]. Physical inactivity is a growing public health concern in the Netherlands as well as in other Western countries. Significant health problems such as increased morbidity and mortality attributable to cardiovascular disease, diabetes, cancers and increased risk of depression may arise if the amount of physical activity in the general population does not increase [5‐9].

There is need for innovative ways to promote physical activity and a healthy lifestyle. One promising development is the use of smartphones during exercise. Use of mobile applications (apps) may be a powerful tool to encourage physical activity and health [10, 11]. Apps are accessible, have a large reach, and have multiple functionalities, such as interactive possibilities and feedback opportunities [12, 13]. Although more than 17,000 health and fitness apps have been developed and are available for the public [12], the literature considering the relationship of app use and health and physical activity is scarce.

However, preliminary evidence is promising [11, 14, 15]. Two reviews and one meta-analysis demonstrated positive effects of mobile phone interventions, interventions with mobile technology, and interventions with remote and web interventions in healthy, inactive and overweight individuals [11, 14, 15]. The mobile phone interventions were often combined with additional education, self-reporting of frequency and type of use of the program or telephone calls. The positive effects of these interventions included increased physical activity (expressed by total time, number of occasions of physical activity and energy expenditure), cardiovascular fitness and reduced overweight [11, 14, 15]. Small to moderate effect sizes were reported [14, 15]. Nevertheless, in these three reviews few interventions were included that used apps. Moreover, in some studies additional interventions were provided next to the mobile phone and app interventions, therefore based on those studies no conclusions can be drawn regarding to the isolated effects of apps on physical activity. Another recent review demonstrated modest effects of app based interventions on physical activity expressed by step count [16]. It should be noted that the apps were often combined with external pedometers, small sample sizes were included, small increases in step counts and a short duration of interventions was presented [16]. However, a recent study has shown promising results of the isolated effect of app use [17]. This study demonstrated that use of a Web-based app on lifestyle indicators decreased weight and increased physical activity of people [17]. Moreover, app users presented a higher chance to maintain a healthy lifestyle [17]. In summary, few studies have examined the effect of app use on changes in physical activity and health.

In recreational running the use of apps is high and emerging and several apps have been developed to assist individuals in their running exercise. Previous research has shown that recreational running or participation in a running mass event could also be a potential health and physical activity promoting activity [18‐20]; Chatton and Kayser showed that participants in a 16 km run were more active than the general population and better in shape [18]. Additionally, in the preparation for a 5 and a 10 km run participants increased physical activity [19, 20]. A majority of participants train in preparation for running events; some of them exercise individually and some of them in a running group [21, 22]. Potentially, app use could assist runners to increase motivation, to increase activity level and set goals during the preparation for a running event. Perhaps the use of apps could assist runners to increase running physical activity and to live and feel healthier. Therefore, the aim of this study was to determine the relationship between the use of apps and changes in physical activity and health and lifestyle behaviour of short and long distance runners. More specific, we were interested in training volume, alcohol intake, smoking behaviour, and lifestyle (e.g. weight loss and eating behaviour).

Of all invited runners 4307 (28 %) agreed to participate in the survey, of which 2838 runners participated in the 16 km and 1341 in the 6.4 km. Table 1 presents the subject characteristics of male and female 16 and 6.4 km runners. Hundred-twelve participants participated in both distances and 507 participants reported too much missing values and were therefore excluded. The type of apps used by participants is shown in Fig. 1. Most participants used Runkeeper (44.4 %) in their preparation. The category ‘other apps” was the second largest app type chosen by participants (16.9 %), these were the apps that were not mentioned in the answer options.

Our main finding was that app use was positively related to RPA, feeling healthier, changing lifestyle and self-image. Also, use of apps was positively related to stimulating others to become active. Moreover, app use in 16 km runners was positively related to feeling more energetic, eating healthier and maintaining the sport behaviour. The odds ratios ranged from 1.24 to 1.89. Additionally, for RPA the explained variance was 41 % and 38 % for 16 km and 6.4 km respectively. These findings are of high importance considering that for app users the weekly training volume prior to the preparation phase was lower than non-app users.

These results corroborate with the findings of other studies, in which app use seemed to have increased physical activity and a healthy lifestyle [11, 14‐17]. In contrast to those studies, the focus in this study was on mobile app use only. It should be noted that we did not analyse the effect of app use, but we examined the use of mobile apps in relation to physical activity, perceived health and self-image. This relationship between app use and perceived health and self-image in the preparation of a running event has not been considered in previous studies. Analysing this relationship is relevant, since it provides insight in innovative and accessible ways to encourage physical activity and a healthier life.

Although most results were comparable for 16 and 6.4 km runners, a few differences were found. In 16 km runners, app use was related to eating healthier, feeling more energetic and a higher chance to maintain sport behaviour. The relationships between app use and these variables did not reach significance level in the 6.4 km runners. The “fun run” character of the 6.4 km may be a first explanation for the differences found. Compared to the 16 km run, participation in a 6.4 km run may not require a long preparation phase and lifestyle changes. In addition, we found that in the training phase most 16 km runners trained 10–20 km per week (37.3 %) and 20–30 km per week (27.3 %), whereas the largest part of 6.4 km runners trained 5–10 km per week (42.0 %) and 10–20 km per week (26.3 %). Thus another possible explanation might be that the differences in weekly training distance of 16 and 6.4 km runners combined with a shorter preparation resulted in the inconsistent findings. Previous literature has shown that running improves aerobic fitness and cardiovascular function at rest [26]. In a review, a fairly strong dose–response relationship between weekly training volume and cardiorespiratory fitness was shown for inactive and healthy middle aged and elderly people [27]. This may explain why the physical fitness of the 16 km runners increased more compared to 6.4 km runners, resulting in a higher perceived energy level. Potentially, there is a link between weekly training volume and eating behaviour as well. To support this suggestion, Williams et al. showed that a larger weekly running distance promoted a healthier eating pattern [28]. In addition, in that study a relationship was found between weekly running distance and years spend in running, which might provide an explanation for our finding that app use was related to a higher chance to maintain the physical activity of the longer distance runners compared to the shorter distance runners.

Previous studies have shown that participating in running events can encourage physical activity [26, 29]. However, maintaining an active lifestyle is difficult for many [30]. Moreover, the gap between intention for being physically active and actually being active is large [31]. In many of behaviour change models, such as the Fogg behaviour model and the attitude, social influence and efficacy (ASE) model, the behavioural intention is assumed to be most important in changing behaviour [32, 33]. It would be interesting to determine the impact of an app on behaviour determinants such as self-efficacy, attitude and social influence. In addition, given that behaviour change theories (BCTs) are often relatively absent in apps, it would be valuable to find out which of these theories are taken into account in the app [34].

This study showed that the intention to maintain the running behaviour was higher for the app users, therefore app use may assist in decreasing drop-out of running and encouraging physical activity. This is a very interesting finding, since apps were more often used by overweight participants and the participants in the 6.4 km run (who trained less often). For these two groups physical activity may need to be encouraged. Furthermore, a very interesting finding was that app users more often encouraged others to engage in running compared to non-app users. This could be explained by the fact that some apps contain features to interact with others, such as following and supporting their activities [13]. This interaction combined with the use of social media might motivate others to be more active [35]. These findings suggest that the use of mobile apps can contribute to the promotion of running and prevention of drop-out. Our findings may be related to the new phenomenon of quantified self, which means that people are measuring their health conditions via wearables [36]. This new trend may actually be an underlying element in the findings of this study.

Furthermore, when we look at practical implications, we suggest that app use could be an additional stimulus to the training program, because it provides an easy and accessible tool to promote physical activity and a healthy lifestyle. Given that the use of smart phones increases [37, 38], a large amount of individuals can be reached with health and fitness apps. Sport organizations and employers may therefore recommend the use of apps in the preparation of a running event. For instance, large recreational running events often include a business run, in which business teams can compete. The use of apps may encourage employers to train more and live healthier. This data shows that app use is related to increased physical activity and improved health. Moreover, frequency of app use is higher in inexperienced and overweight participants. We could hypothesize that these group of runners have some comparable characteristics as inactive individuals. Therefore, our results could potentially be transferred to inactive individuals.

Some limitations of this study need to be addressed. At first, a self-reported, non-validated survey was used. Second, a causality between app use and the outcome variables cannot be determined. It remains unclear what would be the cause and what would be the result; did app use increase physical activity or did physical activity encourage app use. The involvement of other underlying causes should be considered as well. Randomized controlled studies need to be performed to determine a causal relationship. The third limitation was that several types of apps were included. The most used app was Runkeeper, but also a number of other apps were used. It would be interesting to find out why people choose certain apps and which features make an app popular. Apps differ in their features and may differ in their effectiveness as well. Therefore, the possibility that the relationships found might be different for each app has to be kept in mind, because the way apps present information and provide feedback differs. As a fourth limitation low explained variances for app use in relation to most of the health and lifestyle outcomes were found. Therefore we have to keep in mind that other factors, such as psychological factors, contributed to the runner’s lifestyle and self-image as well. At last, this study included individuals that were already active and motivated to participate to a running event. However, considering the problem of increased inactivity, it would be even more interesting to conduct research on potential of app use in promoting a healthy lifestyle in inactive individuals including long-term consequences. Further research is needed to determine which features would need to be included in such an app.

In conclusion, our results showed that recreational runners who used an app are more likely to be more physically active and feel and live healthier. These results suggest that use of mobile apps has a beneficial role in the preparation of a running event, as it promotes health. Further research is now needed to determine a causal relationship between app use and physical and health related outcomes. More specific, a randomized controlled trial (RCT) needs to be developed and conducted. For instance, the effect of one app such as Runkeeper could be examined on weekly training distance and lifestyle. Another example would be to develop and evaluate a physical activity and health promotion app in a group of inactive individuals. To gain insight in long-term effects, a follow-up survey should be included as well.