Physical activity is a crucial factor in the primary and secondary prevention of cardiovascular diseases. Large prospective cohort studies have shown that cardiovascular risk factors identified in childhood are predictive of adult cardiovascular risk [1, 2]. The American Heart Association (AHA) guidelines state that ‘school-age youth should participate every day in 60 minutes or more of moderate to vigorous physical activity that is enjoyable and developmentally appropriate [3].
Sadly, these targets are not being met. In a study of data collected from 105 countries, including Ireland, only 20% of 13–15-year-olds reached the target [4]. Although these figures are a commendable start, there are still many gaps in data collection and monitoring of youth physical activity, particularly in home and family settings, variable school settings, active play, quality of recreational facilities, sport settings and transport surveillance. These gaps are compounded by a lack of government funding for essential infrastructure for national physical activity programmes, enabling coordinated data collection and sharing [5]. Self-reporting is unreliable as a monitoring tool for children [6], although it is helpful as a motivational tool. The measurement error is of a particular concern due to issues of recall and less work has been undertaken to identify and, if needed, develop suitable tools. The use of objective motion sensors such as accelerometers which provide more precise estimates of activity has now been shown to be valid and reliable [7, 8]. With the advent of the internet forty years ago, technology has pervaded every aspect of life. Schools now use e-boards to access educational material online. It is certain that technology is here to stay and that it will likely continue to filter into our lives and those of our children. Smartphone users worldwide topped 1.75 billion in 2014 [9], and while most children do not own their mobile phone, in an American study, 57% of parents reported that they had downloaded apps for their children’s use [10]. Technology has often been cited as one of the main reasons for sedentary behavior; however, there are other factors which also influence a child’s activity levels such as parental behavior, peers, urban/rural setting, proximity of services and amenities, infrastructure for safe physical commuting, education and sports policies [11]. To assume that technology is the sole reason for poor performance in this area would be short-sighted. Figure 1 shows an overview of child’s activity level factors.
An overview of child’s activity level factors.
Apps have become increasingly significant as education tools. Over 80% of the top-selling paid apps in the Tunes Store target the children’s Education category, which is growing [12]. A report published for The Joan Ganz Centre at Sesame Workshop, New York, in 2012 states that ‘the percentage of apps for children has risen in every age category, accompanied by a decrease in apps for adults. Media convergence has excellent potential for delivering educational content, allowing for multi-platform educational initiatives that were never before possible and enabling a 360-degree approach toward educating and reaching children [12]. The ideal scenario is when the apps accessible to children are of high quality as educational/motivational tools. This implies that the app content should be of a standard set by appropriate professional bodies and that the apps are engaging and motivating to the child as set out by appropriate education standards.
The use of e-media as an educational tool and its impact on society is a relatively new but growing area of research, as seen by multiple publications on the subject within the last five years. Only a small number of studies have examined the content of children’s mobile apps for health. These have been small studies and often focus mainly on Apple apps. Firstly, some looked at adherence to the American expert recommendations to prevent and treat obesity [13, 14, 15, 16, 17]. Mobile applications do not appear to be standard interventions in most childhood obesity programmes that are unsurprising given the lack of regulations or standards in children’s technology. These studies also concluded that the apps assessed did not adhere closely to guidelines or strategies recommended by expert organizations [15, 16]. Secondly, some studies have examined the content of children’s apps for behavior change techniques. Their findings are that these apps do not use all the behavioral change techniques available to them [16, 17, 18, 19].
An expert or statutory framework for analyzing children’s apps is lacking, which is likely contributing to the dearth of research into the quality of children’s apps. Furthermore, quantitative and research into children’s apps available for cardiovascular disease prevention is sparse. Another drawback for app researchers is that technology is changing so rapidly that by the time studies such as these are published, new offerings are coming to market. For this reason, a policy of structured data collection and focused research groups should be implemented so that health professionals have an opportunity to influence the future development of apps relating to children’s health.
In order to identify relevant research, electronic databases were searched from inception to 2021, including The Cochrane Database, Prospero, and Campbell Collaboration, OVID: Medline, PsychINFO, CINNAHL, EmBase. Walkabouts, PediaFit Pilot Project, myBigO. Key search terms used were combinations of mobile applications, physical activity, web-based applications, electronic resources, exergames, exercise, fitness, sport, children, paediatric, education and monitoring. Grey literature was also searched using a variety of sources including The Health Technology Assessment agencies, Euroscan, HealthPACT, Open Grey database, Canadian Agency for Drugs and Technology in Health, Directory of Open Access Repositories, Social Science Research Network, Web of Science, and the World Catalogue database. Searches of the internet were also carried out using Google Scholar, Mozilla Firefox and Google Chrome.
The web-based and mobile electronic resources were identified through searches of commercial stores (Apple iPhone/iPad, GooglePlay and Microsoft). In this study the ‘Participants’ are synonymous with ‘Applications’. The applications were purchased if necessary and downloaded onto the researcher’s personal laptop computer and/or smartphone devices. Both Apple and Android devices were used to maximise the application selection possibilities.
The criteria for inclusion were web-based or mobile applications for physical activity/active games/sport/ fitness/ health for children from 2 to 12 years of age; apps whose detail included words such as ‘kids’, ‘children’, ‘everyone can do it’, ‘play’, ‘exercise’, ‘dance’, ‘sport’; and PEGI (Pan European Gaming Information) rating 3+. Apps were excluded for the following reasons: language was not English; they were not targeting children or families; not targeting physical activity/ physical fitness/ exercise; age rating 12+; content (e.g. language, images) clearly aimed at an adult audience; commercial marketing content only (e.g. for a private gym); virtual game only with no physical activity component in spite of claims otherwise in description; anatomy education tools.
The outcome variables were two-fold: 1) Frequency of variables occurring in apps, expressed as a percentage of the total number of apps. E.g. 13% advocated 60 minutes exercise per day. 2) Quality score: Each app was assigned a score using the evaluation forms in Tables 2 and 3. Table 2 scores were derived from the guidelines on physical activity and monitoring capability. Table 3 sets out educational criteria. In each category variables were given a score of 1 or 0 based on the presence or absence of the desired feature. In the category ‘Intensity’ Scores of 0, 1, or 2 were assigned for ‘low’, ‘moderate’ and ‘vigorous’ intensity respectively. ‘Picture Quality’ was scored 0, 1, or 2 for ‘poor’, ‘fair’ and ‘good’ respectively. Other variables included in the score were Duration, Intensity, Muscle strengthening, Flexibility, Bone strengthening, Monitoring capability, Lifestyle advice, No Advertisements (Ads), Sound (appropriate sound/text/image balance), Text Limited to age (Text Limited), Text supported by Image and/or Sound (Text Image/Sound), Special Needs, Ease of Use, Picture Quality, Assessment features, Responsiveness, Recording capability, Motivational features. A descriptive analysis of the overall findings for each indicator was also carried out.
Three search strategies for identifying suitable applications for study were used: First search strategy – Guide for Parents: This involved scrolling through sub-categories of the family/kids section as per store recommendation and guide to parents. Second search strategy – Store search engine: This search was done through the general search function of the stores using a combination of the following search terms (keys were paired): ‘kids’, ‘children’, ‘exercise’, ‘fitness’, ‘physical activity’, ‘exergames’, ‘aerobic’, ‘heart’, ‘cardiovascular’, ‘health’, ‘lifestyle’ and ‘healthy living’. Third Search Strategy – Google Search Engine: A search was carried out on the general Google search engine using a combination of the following key search terms ‘kids’, ‘children’, ‘exercise’, ‘fitness’, ‘physical activity’, ‘exergames’, ‘aerobic’, ‘heart’, ‘cardiovascular’, ‘health’, ‘lifestyle’ and ‘healthy living’.
We looked for adherence to the EU Physical Activity Guidelines (2008) for optimal health and future disease prevention, the AHA guidelines (2014) for cardiovascular and non-communicable disease prevention[2, 3] and the National Guidelines for Physical Activity for Ireland (2009). The recommendations are 60 minutes physical activity daily, moderate/vigorous intensity physical activity, muscle strengthening, flexibility and bone-strengthening exercises 3 times a week. Intensity of exercise was based on the ESC guidelines which state that for the young a moderate intensity physical activity would correspond to an absolute energy expenditure of ~ 4.8 – 7.1 metabolic equivalents (METs), and vigorous intensity activity would correspond to an absolute energy expenditure of ~ 7.2 – 10.1 METs. Activities within the app were assigned an intensity level based on the Compendium of Metabolic Equivalent Tables (2000) (Appendix 1). This study also assessed the apps for the presence of any monitoring tools including accelerometer as these provide important user feedback, which is important for motivational and educational purposes. A quantitative evaluation form was used to record the data (Appendix 2). Quality Characteristics for Educational Applications were collected based on the British Educational and Communications Technology Agency (BECTA) published quality principles for digital learning resources, 2007 (Appendix 3). As there is no universally accepted validated tool for assessing mobile applications for children, an adapted qualitative evaluation form (Appendix 4) was prepared from literature research sources and based on BECTA principles for the purpose of this study. In order to reduce bias in the study, consumer ratings from the app stores and from Common Sense Media (CSM) a not-for-profit organisation which reviews media for children were also collected.
The applications themselves may be mentioned in the study but the data recorded was anonymised and only used for the purpose of analysis. Conclusions drawn were of a general nature rather than a criticism of any individual company. No individual application was named other than the highest ranked in the analysis and information gathered in the study was generalised in the discussion so that any risk of defamation was avoided.
A score was allocated to each of the criteria and summed to an overall score. Descriptives of each variable were presented as a percentage, and for the overall score described by its standard deviation, mean and median. All recording of data was electronic on a laptop computer and placed on a Microsoft Excel file. Data were described and visualised using Microsoft Excel and IBM/SPSS v20. Figure 2 provides an overview of the assessment methods used. Comprehensive analysis performed in our study assessed the qualitative and quantitative outcomes of the mobile and web-based applications available in the market.
An overview of the assessment methods used.
The purpose of this study was to determine whether or not the tools as mentioned earlier provide accurate and appropriate advice on physical activity for children as set out by the EU Physical Activity Guidelines (2008) [20] for optimal health and future disease prevention, the American Heart Association guidelines (2014) [3] for cardiovascular and non-communicable disease prevention and the National Guidelines for Physical Activity for Ireland (2009) [21]. This particular study also evaluates the quality of the monitoring tools available to children in terms of physical activity and exercise engagement and the appropriateness of the electronic tools for children in terms of content and design. The apps were assessed as learning tools using the criteria set out in the methods section.
The main objective was to identify any gaps in relation to adherence to the guidelines, monitoring capability and quality as educational tools of these apps. We have proposed a set of novel adapted qualitative evaluation criteria. The findings of this qualitative evaluation can be used to make guideline-based recommendations for the development of new web-based technologies for health. We believe that this study will add to the research into the content of mobile applications for children’s health and education and will identify what gaps exist between what is available and what the ideal standards should be.
In total 4000 apps were reviewed from Google Play, iTunes and Microsoft stores collectively using three search strategies. The three search strategies were necessary as strategy 1, which is recommended to parents by the stores to ensure age- appropriate content resulted in only 11 appropriate apps out of 2000. Strategy 2 resulted in 32 suitable apps out of 2110 and Strategy 3 unearthed 3 apps which belonged to the stores but had not been detected despite the comprehensive search. A total of 46 applications fulfilled the inclusion/exclusion criteria. Out of these 46 applications, there were 13 applications from Google store (28%), 27 from iTunes (59%) and 3 from Microsoft (7%) and a further 3 apps from these stores were discovered via the general Google search engine (7%). 13 (38%) of these apps were yoga applications. The total number of apps suitable for inclusion was 46.
Out of the 46 applications that fulfilled the search criteria, six apps (13%) advocated 60 minutes or more of physical activity/exercise daily. Out of these six apps, four fulfilled the criteria of moderate to vigorous physical activity in addition to the duration of 60 minutes daily. Five of these apps involved exercise which encompassed muscle strengthening and flexibility training, while four included bone strengthening activities. Four (9%) of the applications contained healthy lifestyle advice on any topic including diet as part of the content.
Of the 46 applications, 23 (50%) encouraged low intensity activities, 12 (26%) involved moderate intensity activity and 11 (24%) encouraged vigorous intensity activities. Therefore, 50% of the apps analysed involved moderate to vigorous intensity activities as per the guidelines.
35 out of 46 (76%) apps encouraged activity which would lead to muscle strengthening, 24 (52%) encouraged activities which would increase bone strength and 33 (72%) included flexibility activities for children.
Nine out of 46 (20%) of the applications had monitoring capability. This was mainly through monitoring the play levels reached, time spent on the app, videos watched, scores achieved and self-recording features. Four apps (9%) used accelerometry to record the child’s actual movements. In these, progress through these apps was directly linked to the child’s movements.
7% (3) of the apps featured advertising. The balance of sound with pictures and text was considered adequate in 89% (41) of the apps. The written text was age appropriate in 30 apps (65%) and would be difficult for children to read or understand in 16 (35%) apps. However, the majority of the text in the apps (44 or 96%) was supported by images or audio to help children to understand and follow instructions. Special educational needs were only addressed in 7% (3) of the apps. Most of the apps (38 or 83%) were deemed easy to use and were user-friendly. The picture quality was graded as poor, moderate and good in seven, three and 36 apps respectively.
Performance assessment capability was only present in 13 (28%) apps. Six apps (13%) used scoring systems to assess performance and four (9%) assessed performance using a timer feature. It was noted that 38 (83%) apps were considered visually stimulating and motivational with features such as new levels to unlock, and prizes to be won. Of these motivational features, extra scores or collectables were present in 26 (57%) apps. Forty-two (91%) of the apps also encouraged creativity and/or collaboration. Finally, the majority of the apps were developed commercially (42 or 91%) rather than by academic institutions or governmental agencies. The apps developed by the academic institutions showed higher sumscores in comparison to the commercially developed apps (Figure 3).
Boxplot of the apps developed by the academic institutions showed higher sum scores in comparison to the commercially developed apps.
The frequency of variables is presented in Table 1. A sum score was calculated for all variables listed to assess the overall quality of apps as in Table 2.
Table 1
Frequencies and percentages (%) of variables present in Applications (n = 46).
VARIABLES | INDICATORS | FREQUENCY | PERCENT (%) |
---|---|---|---|
Duration of Activity 60 minutes | No | 40 | 87 |
Yes | 6 | 13 | |
Intensity | Low (<4.8 METS) | 23 | 50 |
Moderate (4.8–7.1 METS) | 12 | 26 | |
Vigorous (7.2–10.1 METS) | 11 | 24 | |
Muscle strengthening | No | 11 | 24 |
Yes | 35 | 76 | |
Flexibility | No | 13 | 28 |
Yes | 33 | 72 | |
Bone strengthening | No | 22 | 48 |
Yes | 24 | 52 | |
Monitoring | No | 37 | 80 |
Yes | 9 | 20 | |
No Advertisements | Yes | 3 | 7 |
No | 43 | 93 | |
Sound balanced
with images and text |
No | 5 | 11 |
Yes | 41 | 89 | |
Text age-appropriate | No | 16 | 35 |
Yes | 30 | 65 | |
Text supported
by images or audio |
No | 2 | 4 |
Yes | 44 | 96 | |
Special Educational Needs features | No | 43 | 93 |
Yes | 3 | 7 | |
Easy to use | No | 8 | 17 |
Yes | 38 | 83 | |
Picture Quality | Poor | 7 | 15 |
Moderate | 3 | 7 | |
Good | 36 | 78 | |
Assessment capability | No | 33 | 72 |
Yes | 13 | 28 | |
Responsive | No | 10 | 22 |
Yes | 36 | 78 | |
Recording capability | No | 34 | 74 |
Yes | 12 | 26 | |
Motivational features | No | 20 | 43 |
Yes | 26 | 57 | |
Table 2
Variables for data analysis showing scoring system.
VARIABLES | SCORE CRITERIA | SCORE VALUE | SCORE |
---|---|---|---|
Duration | ≤60 minutes daily | 0 | |
≥60 minutes daily | 1 | ||
Intensity | Low (≤4.7 METS) | 0 | |
Moderate (4.7 – 7.1 METS) | 1 | ||
Vigorous (7.2 – 10.1) | 2 | ||
Muscle strengthening | No | 0 | |
Yes | 1 | ||
Bone strengthening | No | 0 | |
Yes | 1 | ||
Flexibility | No | 0 | |
Yes | 1 | ||
Monitoring capability | No | 0 | |
Yes | 1 | ||
Lifestyle advice | No | 0 | |
Yes | 1 | ||
No Ads | No | 1 | |
Yes | 0 | ||
Sound (balance of sound, text and images) | No | 0 | |
Yes | 1 | ||
Text suitable for age | No | 0 | |
Yes | 1 | ||
Text Images (text supported by audio or images) | No | 0 | |
Yes | 1 | ||
Special Educational Needs | No | 0 | |
Yes | 1 | ||
Ease of use | No | 0 | |
Yes | 1 | ||
Picture quality | Poor | 0 | |
Fair | 1 | ||
Good | 2 | ||
Assessment capability | No | 0 | |
Yes | 1 | ||
Responsiveness | No | 0 | |
Yes | 1 | ||
Records progress | No | 0 | |
Yes | 1 | ||
Motivational (incentives) | No | 0 | |
Yes | 1 | ||
Total Score: | |||
The total score range was from 0 – 20. The sumscore showed that the quality of apps was reasonably adequate with mean score of 12, median 12, and standard deviation of 3.4. The quality of apps was also assessed based on the presence or absence of 60 minutes daily activity recommendation. The data shows better quality of apps which included the 60 minutes daily activity recommendation (Figure 4). PRISMA flow diagram is illustrated in Figure 5.
Boxplot of the score for apps with a duration more or less than 60 minutes.
PRISMA flow diagram.
The main finding of this study is that currently e-technology is not being used adequately or to its potential to prevent cardiovascular diseases in children and consequently to prevent future adult life epidemic. The results clearly show that the majority of children’s exercise apps are not meeting the standards for daily exercise as set out by the scientific guidelines [16, 17, 18, 19]. Appropriate, lifestyle advice for cardiovascular and other disease prevention is not included in the apps either for the parent or the child. Accelerometry is not often chosen by developers as a monitoring tool for these apps and although on the whole the quality of the apps as learning tools appears to be good, they are not being used to their full potential in terms of motivational features and health educational content [15, 16]. This study is relevant and timely in the current global environment where targets for physical activity in the scientific guidelines are not being met.
The data in this study revealed that to begin with, there is a paucity of children’s applications for the prevention of cardiovascular disease and promotion of cardiovascular health. The results show that despite using three search strategies encompassing all categories in the family and kids categories of the stores and using key search terms such as ‘kids’, ‘fitness’, ‘health’, ‘cardiovascular’, out of 4000 apps we only found 46 physical activity apps suitable for children’s cardiovascular health. We found that the search strategy that is recommended by the stores is to search categories via the family/kids sections. However, this led to only 11 suitable apps. Searching via a store’s search engine leads to mixed adult/child results some of which are inappropriate for children by virtue of subject matter or level of difficulty of content.
The applications for cardiovascular disease prevention were not specifically categorised and organised by cardiovascular disease or physical fitness. This means that suitable apps may be interspersed amongst a hundred other apps of various topics on any given results page. We found that search terms used by e-stores are very broad and generic in comparison to medical search terms which are very specific. For example, the term ‘exercise’ is often used as a title word or descriptive term for other educational apps such as ‘math’s exercises’, ‘lessons’, or ‘brain training’. Therefore, we found that using medical search terms in these stores led to a large number of irrelevant results. However, as multimedia companies move into the healthcare domain for patient health and activity monitoring, we may see a significant change in categorisation of apps by medical search terms.
Research into the content of children’s cardiovascular prevention apps is also sparse. Only a small number of studies have examined the content of children’s mobile apps for health [13, 14, 15, 16, 17]. Some have looked at adherence to the American expert recommendations for prevention and treatment of obesity [13, 14, 15, 16, 17] or assessed intervention programmes for the prevention and treatment of obesity and weight loss [22, 23, 24, 25, 26]. Mobile applications do not appear to be standard interventions in the majority of childhood obesity programmes which is unsurprising given the lack of regulations or standards in the area of children’s’ technology. These studies also concluded that the apps assessed did not adhere closely to guidelines or strategies as recommended by expert organisations [15, 16]. Interestingly, our research highlighted that the apps developed by academic groups contain information that is closer to the recommendations of health and education professional bodies. Other studies have examined the content of physical activity apps for the presence of behaviour change techniques. Their findings are that these apps do not use all of the behavioural change techniques available to them such as monitoring, intention formation, specific goal setting, review of goals and feedback on performance [16, 17, 27, 28, 29]. Research into physical activity apps have mostly focused on adult apps, measurement and behavioural techniques used [27, 30, 31, 32, 33, 34, 35, 36].
An expert or statutory framework for analysing children’s apps is lacking which is likely contributing to the dearth of research into the quality of children’s apps. Another drawback for app researchers is the fact that technology is changing so rapidly that by the time studies such as these are published new offerings are coming to market. The EU Physical Activity guidelines, and AHA guidelines for children are considered gold-standard recommendations for cardiovascular disease prevention and treatment and are formulated from evidence-based medicine. It appears that very few apps in this category are fulfilling all of the necessary variables for improved cardiovascular fitness as outlined by the professional health body guidelines. We found that only 6 of the 46 apps recommended physical activity for at least 60 minutes daily as per the current scientific guidelines for cardiovascular disease prevention in children. The intensity of exercise was noted to be 23 (50%), 12 (26%) and 11 (24%) in low (<4.8 METS), moderate (4.8-7.1 METS) and vigorous (7.2-10.1 METS) categories respectively. This means that 50% of the apps promoting physical activity in children are not promoting it at an intensity level which would improve cardiovascular fitness, resulting in a loss of all the other complementary benefits that would occur, such as reduced adiposity, reduced cholesterol and lower blood pressure. These benefits are especially important to a child who suffers from diabetes or obesity and may have already developed secondary effects of these conditions such as hypertension.
Most of the apps in this study promoted muscle strengthening activities (76%) however bone strengthening activities were only present in 52% of the apps indicating that weight-bearing activities through active play and games were not part of the content in 52% of the apps. 72% of the apps addressed flexibility training for children. Our study clearly reports that cardiovascular guidelines for prevention are not being published in apps for children’s health. We also found that lifestyle advice is only included in a low number of apps. In the context of cardiovascular disease prevention, lifestyle advice is important in order to influence and establish healthy habits early in the child’s life thus reducing modifiable risk factors later in life [37].
The majority of the applications that fulfilled the inclusion criteria were developed commercially and not by academic institutions. Out of the 6 apps which promoted daily physical activity the first ranked was AHA developed ‘NFL Play 60’. This app fulfilled all the criteria for cardiovascular health promotion and disease prevention. This example clearly demonstrates that apps developed by scientific bodies can be of a very high standard and have significant potential to influence young children for disease prevention. The reality is that people’s adoption of guidelines for disease prevention into everyday life remains low due multiple factors including lack of health promotion and infrastructure deficits [5]. The prevalence of the internet and e-technology could be used as a significant mode of promoting the cardiovascular prevention guidelines for adults and children [38].
The accelerometer is the only validated monitoring tool for physical activity and as such is held as the appropriate standard for the presence of monitoring capability [7]. Although this feature is preferable, app content design does not always lend itself to this form of monitoring and during the course of this research, it became apparent that the accelerometer is not commonly used to measure children’s physical activity in these apps. It was therefore decided that all monitoring tool should be included for the purpose of the analysis as they are useful as motivational tools [6]. We found that only 9 (19%) of the apps monitored activity of children through various methods such as recording times, scores, app usage and play levels. Only 4 apps (9%) used accelerometry. The use of objective motion sensors such as accelerometers, which provide more precise estimates of activity, would hypothetically increase the level of physical exercise through direct feedback to the users. This feature would motivate both parents and children to achieve target exercise goals. We believe that incorporation of acclerometer and/or pedometer in children apps through a fun- based means can improve outcomes and help achieve the desired results of physical fitness.
Only half of children in the United States meet the guidelines for physical activity [39]. In a study of data collected from 105 countries, including Ireland, only 20% of 13–15-year olds reached the target [4]. There are still many gaps in data collection and monitoring of youth physical activity which makes it more difficult to implement appropriate measures and policy to counteract this problem [5]. This is particularly true in the categories of home and family settings, variable school settings, active play, and quality of recreational facilities, sport settings and transport surveillance.
These gaps are present for two main reasons. Physical activity monitoring has been difficult historically. Self-reporting has been shown to be unreliable as a monitoring tool for children [6] although it is useful as a motivational tool. It is difficult to capture all of the different types of activities in which the child might be involved. The use of objective motion sensors such as accelerometers—which provide more precise estimates of activity— has now been shown to be valid and reliable [7, 8]. Also, a lack of government funding for basic infrastructure for National Physical Activity programmes which would enable coordinated data collection and sharing [5]. This whole area of development appears to be in its infancy. The Canadian model of a National Report Card on Physical Activity in Children and Youth [40] has been expanded to other countries in an effort to achieve a standardised worldwide approach [4]. As a result, a global matrix of grades was published in 2014 [4], however it is telling that only fifteen countries participated. The European network for the promotion of health-enhancing physical activity (HEPA Europe) aims to develop standardised measurement methods and systematic research in partnership with other agencies and work is ongoing in this area [41].
Our search criteria gave a high percentage of yoga apps (38%) that fulfilled the inclusion criteria. However, our data analysis showed that all these apps fell into the low intensity category of physical activity. The American College of Sports Medicine guidelines also state that Yoga does not meet the current standard for aerobic and cardiovascular exercise. Studies have shown that Yoga can reduce heart disease through the reduction of blood pressure, atherosclerosis and better glucose control but this not achieved through aerobic exercise [42]. Another recommendation of this study therefore is that future research of cardiovascular physical activity apps should exclude ‘yoga’ apps.
In this study we found that in general, quality of the apps was satisfactory. Advertising was allowed in only 6% of the apps (data not shown). The quality of the sound (89%), audio presence to support written text (96%), user-friendliness (83%), and good picture quality (78%) was present in majority of the apps. Age-appropriate text was seen in 65% of the apps, 91% of them were visually stimulating, and contained motivational content (56.5%) and also promoted creativity (91%). These results highlight that the currently available apps are of reasonably adequate quality. Most apps promoted creativity and contained motivational content.
In this study, we developed a scoring system to assess the quality of web-based apps for cardiovascular disease prevention for children. This was achieved through use of a score. Each variable was assigned a number and the total sum was calculated based on the presence or absence of the desired feature. The result showed a score of mean 12, median 12, and standard deviation of 3.4. In order to reduce bias in the study, consumer ratings from the app stores and from Common Sense Media (CSM) a not-for-profit organisation which reviews media for children were also collected. However, it became apparent during data collection that many apps were not yet rated and that some of the ratings appeared to be excessively negatively biased due to personal expectations. It was therefore deemed appropriate not to include these in the score results. This scoring system has the potential to be used a future tool for other researchers to evaluate the quality of web-based health applications for children. Further validation is required for this scoring system and if validated this may prove to be a very useful tool to provide badly needed quality standard for children’s cardiovascular apps.
Technology has often been cited as one of the main reasons for sedentary behaviour however there are other factors which also influence a child’s activity levels such as parental behaviour, peers, urban/rural setting, proximity of services and amenities, infrastructure for safe physical commuting, education and sports policies [11]. To assume that technology is the sole reason for poor performance in this area would be short sighted and would conveniently ignore the great benefits which it can bestow upon our youth [43, 44]. For example, apps have become increasingly significant as education tools. Over 80% of the top selling paid apps in the Education category of the iTunes Store target children and that number is growing. A report published for The Joan Ganz Centre at Sesame Workshop, New York in 2012 states that ‘the percentage of apps for children has risen in every age category, accompanied by a decrease in apps for adults. Media convergence has great potential for the delivery of educational content, allowing for multi-platform educational initiatives that were never before possible and enabling a 360-degree approach toward educating and reaching children’.39 Studies have shown that internet-based education can make children more confident, results in faster learning, and enables earlier reading compared to traditional methods.
The ideal scenario is one where if outdoor play is not feasible under certain circumstances, the apps accessible to children are of high quality as educational/motivational tools. This implies that the app content should be of a standard set by appropriate professional bodies and that the apps are engaging and motivating to the child as set out by appropriate education standards.
Based on our results, our recommendations are that a policy of structured data collection and focused research groups should be implemented so that health professionals have an opportunity to influence future input into the content and development of apps relating to children’s health. Few of the apps analysed used the breadth of tools available through the technology to impart the content in a more meaningful way. Today, technology can provide tools such as accelerometer monitoring, feedback, assessment of performance, motivational tools, and communication capability all of which can be used to support a healthier lifestyle and it is recommended that each of these be included in order to fully engage the child and parents in the app content and to ensure accurate feedback and goal achievements. We further recommend that a system of quality control should be put in place involving review by appropriate professional bodies before health apps are published for general use and that lifestyle advice for prevention of cardiovascular modifiable risk factors should be included in physical activity apps in an age appropriate and engaging way.
We advocate the age categorisation of physical play activity apps and the development of a comprehensive library of such apps for all age groups. Appropriate text and language features should be developed to support these. Furthermore, we propose that apps be categorised by commonly known medical health search terms so that searching for a health app for a specific complaint will generate appropriate and concise results. Finally, we recommend that commercial organisations developing apps for children should collaborate with appropriate academic institutions in order to ensure high quality and targeted content for optimal health benefit to the user.
Despite the novel nature of this study, several limitations must be noted. First, the tools developed for data collection and analysis are not validated. Second, the apps were analysed by one researcher.
Third, since new apps are being developed rapidly, the results presented in this study can only be seen as a snapshot of the current state of the offered apps for future research.
This study concludes that gaps exist in the availability of specific, guideline-based cardiovascular disease prevention apps for children. The study highlights the lack of data regarding children’s physical activity levels and in the regulation of standards for children’s mobile applications for health. It is also clear that there is little in the way of a recognised professional health organisation specifically devoted to the analysis of mobile applications for children’s preventative health and wellbeing. However, the quality of available apps was adequate and had the definite potential to be used as a tool for educating and motivating children for physical fitness and disease prevention. Scores such as the one developed here, if validated, can help grade apps for quality standardisation.
The additional file for this article can be found as follows:
AppendicesAppendices 1 to 4. DOI: https://doi.org/10.29337/ijdh.42.s1
Prof. Faisal Sharif is supported by the Science Foundation Ireland Research Infrastructure Award (17/RI/5353). Dr. Haroon Zafar is supported by an Irish Research Council New Foundations Grant.
The authors have no competing interests to declare.
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