Data handling practices and commercial features of apps related to children: a scoping review of content analyses

Abstract

Background

Child interaction (including via parent proxy) with mobile apps is common, generating concern about children’s privacy and vulnerability to advertising and other commercial interests. Researchers have conducted numerous app content evaluations, but there is less attention to data sharing or commercial practices.

Objective

This scoping review of commercial app evaluation studies describes the nature of such evaluations, including assessments of data privacy, data security and app-based advertising.

Methods

We searched Scopus, PubMed, Embase and ACM Digital Library (2005–2020). We included studies that evaluated the properties of apps available through commercial app stores and targeted children, parents of a child (0–18 years) or expectant parents. Data extracted and synthesised were study and app user characteristics, and app privacy, data sharing, security, advertisement and in-app purchase elements.

Results

We included 34 studies; less than half (n=15; 44.1%) evaluated data privacy and security elements and half (n=17; 50.0%) assessed app commercial features. Common issues included frequent data sharing or lax security measures, including permission requests and third-party data transmissions. In-app purchase options and advertisements were common and involved manipulative delivery methods and content that is potentially harmful to child health.

Conclusions

Research related to the data handling and the commercial features of apps that may transmit children’s data is preliminary and has not kept pace with the rapid expansion and evolution of mobile app development. Critical examinations of these app aspects are needed to elucidate risks and inform regulations aimed at protecting children’s privacy and well-being.

Alternate abstract:

A scoping review of apps related to children finds that data privacy and commercial features are rarely evaluated. These apps show frequent data sharing, manipulative delivery of In-app purchases and advertisements with content that is potentially harmful to child health.

Correspondence to Dr Lindsay Jibb, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Canada; [email protected]

What is already known on this topic?

• Mobile app developers encourage users to enter personal information and routinely share collected data with third parties to enhance the user experience or monetise the app.

• Apps focused on children may be among the worst in terms of the number of associated third-party data trackers—posing privacy and safety concerns to children.

• Child and parent app content analyses are increasingly conducted, but little is known associated data privacy, data security and app-based advertising assessments.

What this study adds?

• Comprehensive evaluations of the data privacy and security elements and commercial features of apps that may transmit children’s data are rarely conducted.

• When evaluated, child and parent apps show frequent data sharing and lax security measures, including permission requests and third-party data transmissions.

• In-app purchase options and advertisements appear common in child and parent apps and involved manipulative delivery methods and content that is potentially harmful to child’s health.

Introduction

Today’s children are growing up in an immersive digital media era where frequent interaction with mobile applications (apps) is the norm. In addition to their own use of technology, children’s data including photographs, videos and personal information are shared via their parents’ online behaviours. Engagement with technology spans childhood, with 49% of parents using parenting apps,¹ 60% of children less than 3 years having used a mobile device² and, in the UK, 53% of children aged 7 years and 90% of children aged 11 years reporting mobile phone ownership.³ Unfortunately, children and their parents are generally engaging with apps without a fulsome understanding of the privacy implications of their actions or the commercial interests in monetising their app-based activities.⁴

Mobile app developers encourage users to enter personal information and routinely share collected data with third parties to enhance the user experience or commercialise the app.⁵ Adult apps are known to share personal and health information with an array of commercial entities, which are then capable of aggregating data across apps and re-identifying users.^{6 7} Recognising children’s particular vulnerabilities, regulations designed to protect child privacy include Europe’s General Data Protection Regulation (GDPR) and the United States’ Children’s Online Privacy Protection Act (COPPA). These regulations require operators of online services such as apps to give detailed notice of privacy practices and prohibit the processing of children’s personal information without consent.^{8 9} Still, evidence suggests that apps containing children’s data are among the worst in terms of the number of associated third-party trackers¹⁰—and developers may skirt privacy regulation by claiming their app is targeted at general audiences rather than children.¹¹

This mobile ecosystem and current regulatory situation creates serious risks to children. The ubiquitous online presence and purchasing power of young parents and children mean these groups are now at the centre of the e-commerce market. This is highly problematic as serious child privacy and safety issues may arise if information shared with apps is used for data-driven advertising. Furthermore, there is a real danger that data aggregators may create digital dossiers that follow young people into adulthood and impact their future education, employment and health insurance acquisition opportunities.¹²

In parallel with these data handling issues, research attention has increasingly turned to app stores and the content and quality of commercially available apps. Given the availability of such evaluations and that these apps may transmit child data to a host of third parties, the objective of this review was to understand the scope of such evaluations, including whether and how researchers are assessing data privacy, data security and app-based advertising and what results they are finding in these areas.

Methods

Design and reporting

We conducted a scoping review according to the framework developed by Levac et al ¹³ using an internal protocol that was based on a previous, similar review by a member of our group.¹⁴ Review reporting is in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for scoping reviews (PRISMA-ScR) checklist.¹⁵

Eligibility criteria

We included studies that evaluated apps available in commercial stores which collected data directly related to children; thus users would be children, a parent of a child (0–18 years) or an expectant parent. We excluded commentaries, topical or systematic literature reviews, protocols, book chapters and conference abstracts. No language restrictions were placed. The search was limited to studies published from 2005 onward—the timeframe where mobile apps have been publicly available.¹⁶

Information sources and evidence screening

On 18 November 2020, we conducted searches in the Scopus (Elsevier), PubMed, Embase (Ovid) and ACM Digital Library databases. Our search strategy was developed in consultation with a research librarian (online supplemental appendix 1) and piloted to validate applicability. We supplemented the search with searches of our own databases of mobile app literature. Using Covidence software, duplicates were removed and three authors independently screened titles and abstracts, and then full texts, in duplicate according to the eligibility criteria. Eligibility disagreements were resolved through discussion with a third reviewer.

Data charting

We developed, piloted and refined a data charting table with reference to those used in our previous research in this topic area^{14 17} and we charted data into this table. The data items charted are shown in online supplemental appendix 2.

Synthesis of results

Data abstraction fields were grouped according to key data features to enable synthesis. Quantitative data were summarised using descriptive statistics. Where appropriate, qualitative data items were categorised descriptively, and frequencies calculated. Charting and categorisation were conducted by one author and checked by a second author.

Results

Study selection

We identified 15 762 records across all databases (figure 1). After the removal of duplicate and screening of titles and abstracts, we assessed 140 full-text articles for inclusion. Following full-text screening, 34 articles were included in this review.

Figure 1. Study selection process.

Study and general app characteristics

The number of published studies meeting our inclusion criteria has increased over time (figure 2). Study details are shown in table 1. Studies were conducted in the USA (n=18; 52.9%), Australia (n=9; 26.5%), Canada (n=2; 5.9%), Iran (n=1; 2.9%), India (n=1; 2.9%) and the UK (n=1; 2.9%). Two studies (5.9%) were conducted across multiple countries. Most commonly, study designs were reported as systematic reviews or evaluations (n=13; 38.2%), descriptive or content analyses (n=10; 9.4%), or reviews (n=5; 14.7%). Stated designs represented the authors’ own labelling, and we did not find meaningful correspondences between reported study designs and the methods used. Study funding was from government agencies (n=10; 29.4%), universities (n=3; 8.8%), non-for-profit organisations (n=1; 2.9%), for-profit organisations (n=1; 2.9%) or a combination of these sources (n=5; 14.7%). Nine studies (26.5%) did not identify the funding source and 5 (14.7%) received no funding.

Figure 2. Study publication number over time.

Table 1

Study and associated app sample characteristics

First author and year	Country of origin	Reported design	Funding source(s)	Target user	Targeted user characteristics	App stores searched	App store search date(s)	Method for app sampling	App sample number	App sample language restriction	Children’s app content
Biviji et al 39	USA	Review and content analysis	None	Parents	Pregnant people, future parents, other caregivers of infants	Apple App and Google Play	Not reported	Scraping software	29	English	Pregnancy or early childhood health education or user decision-making support functions
Biviji et al 40	USA	Cross-sectional report	Combination	Parents	Parents-to-be, other caregivers of infants	Apple App and Google Play	March 2017	Scraping software	421	English	Pregnancy or early childhood health education or user decision-making support function
Bland et al 41	UK	Content analysis	Combination	Parents	Pregnant people	Apple App and Google Play	November 2018	Keyword	29	English	Pregnancy-specific nutritional support functions
Brown et al 42	Australia	Review	None	Parents	Pregnant people	Apple App	October 2017	Keyword	51	English	Nutrition or dietary information
Bry et al 43	USA	Systematic evaluation	Not reported	Parents or children	Children with anxiety, parents of a children with anxiety	Apple App and Google Play	February 2016	Keyword	121	English	Anxiety-related symptom treatment or management
Chen et al 44	USA	Systematic review	For-profit	Children	Adolescents and young adults who are sexually active	Apple App and Google Play	July 2015	Keyword	22	English	Pregnancy prevention information
Cheng et al 24	Australia	Systematic evaluation	Not reported	Parents	Parents of infants up to 1 year	Apple App and Google Play	September 2018 to January 2019	Keyword	47	English	Milk feeding behaviours, solid food feeding behaviours or infant activity information
Das et al 20	USA	Content analysis	Government	Children	Children or adolescents under the age of 18	Apple App and Google Play	March 2016	Store-reported highly ranked apps	64	Not reported	All app content types included
Davis et al 45	USA	Content analysis	Not reported	Parents	New parents	Apple App	2016	Keyword	46	English	Parenting, infant health or child health information
Furlong et al 46	Australia	Systematic review	Government	Children	Children up to 12 years old with a speech disorder	Apple App and Google Play	November 2016 to May 2017	Keyword	132	English	Includes tasks that require production of speech by user
Hotwani et al 47	India	Content analysis	Not reported	Parents or children	All children	Apple App	Not reported	Keyword	6	English	Tooth brushing promoting functions
Hswen et al 48	USA	Content analysis	Not reported	Children	Children aged 4 and older	Apple App	March 2012	Store-reported highly ranked apps	20	Not reported	All app content types included
Liu et al 22	USA	Not reported	Government	Children	All children	Google Play	April 2015	Classifier software	67 778	Not reported	All app content types included
Meyer et al 23	USA	Content analysis	University	Children	Children less than 5 years old	Google Play	December 2017 to March 2017	Store-reported highly ranked apps	135	Not reported	All app content types included
Mousavi et al 49	Iran	Systematic review	None	Parents or children	All parents or children	Apple App and Google Play	December 2017	Keyword	4	English	Health monitoring, health decision support and diagnosis support functions
Musgrave et al 50	Australia	Systematic review	University	Parents	Pregnant people	Apple App and Google Play	November 2017 to October 2019	Store-reported highly ranked apps	10	English	General pregnancy information
Quinn et al 51	USA	Not reported	None	Children	Children preschool and/or kindergarten age	Apple App and Google Play	Not reported	Keyword	472	English	Handwriting, spelling and/or composing training
Reyes et al 18	Multiple	Content analysis	Combination	Children	Children less than 13 years old	Google Play	November 2016 to March 2018	Scraping software	5855	English	All app content types included
Richardson et al 52	Canada	Systematic review	Government	Parents	Parents of children in the NICU (inclusive of guardians, additional family or individuals that provide care to infants in the NICU)	Apple App and Google Play	2017	Keyword	18	English	Information or support functions for parents of infants in NICUs
Robinson et al 53	USA	Content analysis	Government	Children	Smoking adolescents attempting to quit	Apple App and Google Play	November 2016	Keyword	46	Not reported	Smoking cessation education
Sardi et al 21	Multiple	Systematic review	Government	Parents	Postpartum women	Apple App and Google Play	January 2019	Keyword	48	English	Postnatal care support functions for the mother and/or newborn
Schoeppe et al 54	Australia	Systematic review	Combination	Children	All children and adolescents	Apple App and Google Play	May 2016 to November 2016	Keyword	25	English	Diet, physical activity and sedentary behaviour improvement functions
Schoffman et al 55	USA	Systematic evaluation	None	Children	Children and adolescents with obesity	Apple App and web search	June 2012	Keyword	57	English	Weight loss/healthy eating/physical activity support functions
Sidhu et al 56	USA	Content analysis	Government	Parents	Breastfeeding mothers of infants 0–6 months	Apple App and Google Play	August 2017 and October 2017	Keyword	41	English	Breastfeeding education or breastfeeding experience tracking
Taki et al 57	Australia	Systematic evaluation	Government	Parents	Parents of infants up to 1 year	Apple App and Google Play	December 2013, March 2014, and December 2014	Keyword	46	English	Healthy milk or solid food feeding behaviour information
Virani et al 58	Canada	Review	Not reported	Parents	All parents	Google Play	June 1 2018	Keyword	16	English	Parenting information and support functions
Weber et al 59	USA	Review	Government	Parents	Participants in a special supplemental nutrition programme for women, infants, and children	Apple App and Google Play	December 2017 to June 2018	Keyword	17	Not reported	Relating to the supplemental nutrition programme from women, infants and children
Weekly et al 60	USA	Review	Not reported	Parents or children	Palliative paediatric patients, caregivers of palliative paediatric patients	Apple App, Google Play and Blackberry World App	May 2017 to July 2017	Keyword and expert referral	16	English and Spanish	Mindfulness, relaxation or distraction education or training
Wisniewski et al 61	USA	Systematic evaluation	Government	Parents or children	All parents or children	Google Play	April 2016 to May 2016	Keyword	75	Not reported	Adolescent online safety functions
Womack et al 62	USA	Content analysis	Not reported	Parents	Pregnant people	Apple App and Google Play	November 2015	Keyword	48	English	Pregnancy information
Zarnowiecki et al 63	Australia	Systematic review	Not-for-profit	Parents or children	Parents of children under 15, children under 15	Apple App and web search	October 2018 to November 2018	Keyword	4	Not reported	Meal planners, shopping list or lunchbox functions
Zhao et al 25	Australia	Comprehensive assessment and exploratory qualitative research	University	Parents	Parents of infants and young children	Apple App and 360 Android Mobile Assistant	April 2016	Keyword	26	Accessible in simplified Chinese characters	Healthy infant feeding provision functions
Zhao et al 26	Australia	Not reported	Not reported	Parents	Mothers of children 3 years of age and less or mothers-to-be	360 Android Mobile Assistant	February 2018	Store-reported highly ranked apps	79	Accessible in simplified Chinese characters	Pregnancy and early parenting information or support functions
Zhao et al 19	USA	Prospective cohort study	Combination	Children	Children aged 3–5 years	Google Play	August 1 2019 to November 1 2019	Parent list of used apps	451	Not reported	All app content types included

NICU, neonatal intensive care unit.

The median app sample size across studies was 46 (range 4–67 778). Parents were the intended app users in 16 studies (47.1%), children in 12 studies (35.3%), and parents or children in 6 studies (17.6%). Apps were most commonly available through both iTunes (Apple) and Google Play stores (n=19; 55.9%)—followed by Google Play (n=6; 17.6%) or iTunes alone (n=4; 11.8%). To sample apps, authors most commonly used keyword searches in app stores (n=23; 67.6%), store-reported ranking lists (n=5; 14.7%) or software to support searching of app store contents (n=4; 11.8%).

App data privacy and security-related findings

Less than half (n=15; 44.1%) of the studies evaluated any data privacy or security features. A total of two studies (5.9%) evaluated apps’ third-party data sharing practices.^{18 19} In both cases, studies automated the process of app execution using simulated data inputs and determined the number and domain destination of data transmissions. Results showed that 67%¹⁹ and 73%¹⁸ of apps transmitted children’s personal data to third parties including those providing advertising-related services. Transmitted data included email addresses, information enabling user geolocation and advertising IDs that can be used to create behaviour profiles for advertising. Third-party transmission counts were not associated with child sex, parent age or marital status, or family income-to-needs ratio. However, transmissions were twofold to threefold higher in the case of children whose parents did not have advanced degrees.¹⁹

Table 2 shows other app privacy-related and security-related evaluation data from studies. Eight studies (23.5%) reported on apps’ capacity to share information via social media. These studies did not explicitly evaluate whether the nature of such sharing was active (ie, user-initiated data sharing for purposes including seeking peer support) or passive (ie, data transmission to social media networks unbeknownst to the app user). The potential to share data to social media platforms occurred in 14%–63% of apps (median 28%).

Table 2

App privacy-related and security-related evaluation methods and results

	Privacy policy		Social media		Permissions requested		Data security
	Methods	Results	Methods	Results	Methods	Results	Methods	Results
Bry et al 43	Evaluated app store page and/or downloaded app manually	Privacy policy presence: Less than 5% of apps					Evaluated app store page and/or downloaded app manually	Login and/or password presence: Less than 5% of apps
Cheng et al 24							Evaluated app store page and/or downloaded app manually	Investigator-developed security assessment scale: 6% of apps rated as excellent; 10% of apps rated as good
Das et al 20	Statistics calculated with web-based readability calculator	Privacy policy readability: average reading grade level (12.8) higher than average US adult level (8.0)
Liu et al 22			Comparison of app library package names with libraries relevant to social networks	Potential for social medial sharing: 20% of apps	Examination of privacy grade as listed in online crowdsourced dataset	Potential for permission requests: 82% of apps use few permissions for unusual purposes; 10% may use permissions in this way
Meyer et al 23			Evaluated app store page and/or downloaded app manually	Social media links: 14% of apps	Evaluated app store page and/or downloaded app manually	Permission requests: 100% of apps Requests for notifications (100%), files/photo storage (53%), phone (13%), microphone (8%), camera (7%); and location (4%).
Musgrave et al 50							Evaluated app store page and/or downloaded app manually	Login and/or password presence: 90% of apps required logins; 70% required passwords
Reyes et al 18							Automated analysis of whether data transmissions are protected	Data encryption: 40% of apps do not use TLS*
Robinson et al 53			Evaluated app store page and/or downloaded app manually	Social media links: 63% of apps			Evaluated app store page and/or downloaded app manually	Login and/or password presence: 0% of apps
Sardi et al 21	Evaluated app store page and/or downloaded app manually	Privacy policy presence: 63% of apps Privacy policy content: 27% of privacy policies complied with international and federal laws including COPPA†, GDPR‡ and HIPAA§.	Evaluated app store page and/or downloaded app manually	Social media links: 31% of apps			Evaluated app store page and/or downloaded app manually	Login and/or password presence: 29% of apps Cloud storage backup option: 8% of apps
Schoeppe et al 54			Evaluated app store page and/or downloaded app manually	Social media links: 60% of apps			Evaluated app store page and/or downloaded app manually	Login and/or password presence: 20% of apps
Schoffman et al 55			Evaluated app store page and/or downloaded app manually	Social media links: 16% of apps
Virani et al 58	Evaluated app store page and/or downloaded app manually	Privacy policy presence: 100% of apps					Evaluated app store page and/or downloaded app manually	Login and/or password presence: 33%–100% of apps
Weber et al 59			Evaluated app store page and/or downloaded app manually	Social media links: Less than or equal to 35% of apps			Evaluated app store page and/or downloaded app manually	Login and/or password presence: 70% of apps
Zarnowiecki et al 63			Evaluated app store page and/or downloaded app manually	Social media links: 25% of apps			Evaluated app store page and/or downloaded app manually	Login and/or password presence: 0% of apps

*Transport Layer Security.

†Children’s Online Privacy Protection Act.

‡General Data Protection Regulation.

§Health Insurance Portability and Accountability Act.

Additionally, three studies (8.8%) documented the presence of privacy policies and single studies (2.9%) evaluated each of privacy policy content and readability. These studies showed 5%–100% of apps (median 63%) had an associated privacy policy. Policy readability was poor²⁰ and often failed to comply with international or federal regulations.²¹ Two studies (5.9%) documented actual or potential permission requests,^{22 23} showing that permission requests occurred in up to 100% of apps and may violate jurisdictional privacy regulations such as location data tracking.

App data security features were evaluated in 29.4% (n=10) of studies and included presence of login or password protection element (n=7; 20.6%), login/password and cloud storage option (n=1; 2.9%), or data encryption (n=1; 2.9%), and the application of an investigator-developed security assessment scale (n=1; 2.9%). Security-related results showed: login or password protection presence in 0%–100% of apps (median: 31%), high proportions of apps not protecting data transmissions using standard methods,¹⁸ and few apps with high security assessment scale ratings.²⁴

App commercial feature-related findings

Commercial features were assessed in 17 studies (50.0%) (table 3) and included the proportion of apps with in-app purchase options (n=15; 44.1%), the proportion of apps with in-app advertisements (n=10; 29.4%) and the type of advertisements (n=3; 8.8%). In-app purchases and advertisements were present in 0%–46% (median 25%) and 9%–95% (median 51%) of apps, respectively. To evaluate advertisement content, all studies used manual content analysis using a predefined and investigator-developed advertising coding scheme.^{23 25 26} Content analysis conducted by Meyer et al ²³ showed advertisements were presented using traditional methods (eg, product videos as shown on television) but also in insidious ways that might prompt further advertising consumption (eg, embedding advertising videos within gamified app features). In the two studies that assessed the relationships of advertisements to health outcomes, advertisements promoted formula-feeding for premature babies, toddlers or older children,^{25 26} which may be in contravention of the WHO Code on the Marketing of Breast Milk Substitutes²⁷ due to potentially harmful impacts on health.

Table 3

App commercial feature evaluation results

Study		Results of commercial feature assessment
	Total number of apps sampled	% of sampled apps with in-app purchases	% of sample apps with advertisements	Advertisement-related analyses
Biviji et al 40	29	18%	51%
Brown et al 42	51	43%
Chen et al 44	22	0%	9%
Cheng et al 24	47	26%
Davis et al 45	46		13%
Furlong et al 46	132	33%
Liu et al 22	67 778	22%	Potential for advertisements in 53%
Meyer et al 23	135	46%	95%	Apps included commercial characters (42%), full-app teasers (46%), advertisements that interrupted gameplay (35%), distracting banners (17%) or camouflaged advertisements (7%). Advertisements more prevalent in free apps.
Richardson et al 52	18	6%	17%
Sardi et al 21	48	32%
Schoeppe et al 54	25	24%
Virani et al 58	16	19%	50%
Wisniewski et al 61	75	24%
Womack et al 62	48		63%
Zarnowiecki et al 63	4	50%	25%
Zhao et al 25	26	46%	85%	Most apps (77%) promoted infant formula
Zhao et al 26	451	95%		Advertisements coded as being related to formula for premature infants, term infants, toddlers and older children including in circumstances where potentially harmful or unnecessary to health

Discussion

Evaluations of the content and quality of commercially available apps that may transmit child data have proliferated steadily over time. Rigorous, independent evaluations of the data sharing practices and commercial features of these apps remain rare. However, there is rapid methodological development in the field and strategies to evaluate these practices are being increasingly developed and used by interdisciplinary research groups.^{10 18 19}

Study and app characteristics

Reviews of apps that collect, and potentially share, children’s data are conducted most often by investigators in high-income, predominantly English-speaking countries, and commonly include only apps available in English. Most studies focused on understanding the content of apps designed for specific health or education purposes and few examined game-based and other types of apps children commonly engage with. Surrogate measures are largely used to evaluate the privacy and security features of apps as only a handful of studies have examined app data sharing and security practices directly. Still, our data show that, when data privacy and security evaluations are conducted, issues with frequent data sharing or lax security measures are uncovered.

Data sharing practices

Most researchers included only proxy measures for actual data sharing practices, such as permission requests or the presence of a privacy policy. In the few studies that measured actual data sharing, identifying children’s data were provided to third parties.¹⁹ This is problematic as aggregation of these data can support the characterisation of parent and child users according to their app interaction patterns or demographics, and these characterisations may be commercially exploited to encourage impulse purchasing or suggest unhealthy products in ways that exacerbate health inequities.^{19 28}

Data sharing policies

Privacy policies in child and parenting apps are variable in terms of both presence and readability. Thus, the data tracking and commercialisation practices of apps, and their associated risks, are generally unknown to children and adults alike^29–31—challenging the value of the dominant ‘notice and consent’ privacy framework of the information age. Digital literacy skills-building may mitigate some risks to users and, in the case of children, such programmes have been developed.²⁹ However, lower socioeconomic status, as well as age and gender, may be associated with lower digital literacy,³¹ suggesting that equitable access to literacy training remains elusive. In addition, even when privacy policies are present, they oftentimes do not reflect actual app data sharing behaviours.^{32 33}

In-app purchasing and advertisements

Half of our included studies evaluated apps’ commercial features with results showing several areas of potential concern. In-app purchase options and advertisements are common, manipulative methods are used to deliver advertisements, and advertising information is potentially harmful to health.^{26 34} These issues pose a problem as research shows both parents and children may not always be able to distinguish app content from advertising.^{23 35} The content of advertisements within children’s apps is also often not age-appropriate with advertisement content often exceeding developer-stated app maturity levels.³⁶ Finally, furthering digital disparities, free apps—which parents and children of lower socioeconomic status may more frequently engage with—more frequently contain these in-app purchase options and advertisements.²³

Implications

Our results have important implications for regulatory bodies, app developers and parents. Although regulations such as the GDPR and COPPA have been enacted to protect children’s online privacy, our results point to the limits of these efforts. For instance, COPPA is reported as underenforced in the USA¹¹ and, as such, non-compliance with the regulation appears widespread.^{18 19} These privacy regulations also rely on the idea that an informed consumer can select apps with adequate privacy protections in place.³⁷ However, we show that privacy policies are not always present in children’s apps and, when present, vary greatly in terms of readability. As such, the onus of responsibility for personal data protection is placed on those who may not be adequately equipped for privacy decision making by default (ie, the child or parent). Combined with more stringent regulatory enforcement—app developers, who may not be consistently aware of the destinations of data transmitted from their apps,¹⁸ can reduce personal identifier collection in the spirit of data minimisation¹⁹ and systematically evaluate app privacy behaviours before release.¹⁸ Ahead of these needed regulatory and industry shifts, parents and older children may install apps from trusted developers,¹⁹ disable advertisement identifiers, adjust app permissions and use advertisement blockers to reduce the likelihood of privacy breaches.³⁸

Limitations

First, although sensitive, the nature of our research question resulted in a search strategy that was imprecise and identified many irrelevant studies. We used duplicate screening and team discussions to resolve discrepancies and systematically exclude such studies. Second, even though we developed a broad search strategy, the cross-disciplinary nature of our research question may mean that we may not have located all studies accessible in disparate, discipline-focused databases. Third, although not the goal of a scoping review, we did not conduct a methodological quality assessment and instead included all identified studies.

Conclusion

Research related to the data handling behaviours and commercial aspects of apps that may transmit children’s data is emerging but has not kept pace with the rapid expansion and evolution of the mobile ecosystem. The lack of evaluations may be related to the technical difficulty in doing so—an issue that may be solved by collaborative research efforts spanning the disciples of computer science, child health and commercial regulatory policy. These collaborations may be fruitful in rooting out and acting on risks to children’s privacy and well-being within mobile ecosystems.¹⁹ Studies are needed to understand the intersection between transmitted data and advertisements within apps and how this commercial exposure effects children’s health and well-being. Ultimately, enforced and stricter regulation may be key to protecting children’s online privacy and dampening any impacts of data sharing.

We acknowledge the support of the Government of Canada’s New Frontiers in Research Fund (NFRF) (NFRFE-2019-00806).

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

Not applicable.

Footnote

Twitter @lindsayjibb

Contributors QG conceptualised and designed the study, designed the data collection instruments, and reviewed and revised the manuscript. LJ designed the study, designed the data collection instruments, collected and synthesised the data, drafted the initial manuscript, and revised the manuscript. LR designed the search strategy, conducted the search, and reviewed and revised the manuscript. EA and MH designed the data collection instruments and collected and synthesised the data, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. LJ acts as guarantor and accepts full responsibility for the finished work and the conduct of the study, had access to the data, and controlled the decision to publish.

Funding This study was funded by the Natural Sciences and Engineering Research Council of Canada, New Frontiers in Research Fund (NREF-2019-00806), Canadian Institutes of Health Research and Social Sciences and Humanities Research Council of Canada.

Disclaimer The Government of Canada had no role in the design or conduct of this study or decision to publish.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

References

¹ Kinsner K, Parlakian R, Sanchez GR, et al. Millennial Connections: Findings from ZERO TO THREE’s 2018 Parent Survey, 2018. Available: https://www.zerotothree.org/resources/2475-millennial-connections-executive-summary#downloads

² Levine LE, Waite BM, Bowman LL, et al. Mobile media use by infants and toddlers. Comput Human Behav 2019; 94: 92–9. doi:10.1016/j.chb.2018.12.045

³ The Guardian. Most children own mobile phone by age of seven, study finds, 2020. Available: https://www.theguardian.com/society/2020/jan/30/most-children-own-mobile-phone-by-age-of-seven-study-finds [Accessed 23 Sep 2021 ].

⁴ Pangrazio L, Selwyn N. “It’s Not Like It’s Life or Death or Whatever”: Young People’s Understandings of Social Media Data. Soc Media Soc 2018; 4: 2056305118787808.

⁵ Vallina-Rodriguez N, Sundaresan S, Razaghpanah A. Tracking the trackers: towards understanding the mobile advertising and tracking ecosystem. In: 1st data and algorithm transparency workshop, 2016: 1–6.

⁶ Grundy Q, Chiu K, Held F, et al. Data sharing practices of medicines related apps and the mobile ecosystem: traffic, content, and network analysis. BMJ 2019; 364: l920. doi:10.1136/bmj.l920 http://www.ncbi.nlm.nih.gov/pubmed/30894349

⁷ Huckvale K, Torous J, Larsen ME. Assessment of the data sharing and privacy practices of smartphone apps for depression and smoking cessation. JAMA Netw Open 2019; 2: e192542. doi:10.1001/jamanetworkopen.2019.2542 http://www.ncbi.nlm.nih.gov/pubmed/31002321

⁸ Information Commissioner’s Office. Children and the UK GDPR. Available: https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/children-and-the-uk-gdpr/ [Accessed 29 Jul 2021 ].

⁹ Federal Trade Commission. Children’s Online Privacy Protection Rule (“COPPA”). Available: https://www.ftc.gov/enforcement/rules/rulemaking-regulatory-reform-proceedings/childrens-online-privacy-protection-rule [Accessed 29 Jul 2021 ].

¹⁰ Binns R, Lyngs U, Kleek MV. Third party tracking in the mobile ecosystem. 10th ACM Conference, 2018: 23–31.

¹¹ Campbell AJ. Children's privacy laws must be strengthened and enforced. JAMA Pediatr 2020; 174: e203393. doi:10.1001/jamapediatrics.2020.3393 http://www.ncbi.nlm.nih.gov/pubmed/32897300

¹² Montgomery KC, Chester J, Milosevic T. Children's privacy in the big data era: research opportunities. Pediatrics 2017; 140: S117–21. doi:10.1542/peds.2016-1758O http://www.ncbi.nlm.nih.gov/pubmed/29093045

¹³ Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci 2010; 5: 69. doi:10.1186/1748-5908-5-69 http://www.ncbi.nlm.nih.gov/pubmed/20854677

¹⁴ Grundy QH, Wang Z, Bero LA. Challenges in assessing mobile health app quality. Am J Prev Med 2016; 51: 1051–9. doi:10.1016/j.amepre.2016.07.009

¹⁵ Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med 2018; 169: 467–73. doi:10.7326/M18-0850 http://www.ncbi.nlm.nih.gov/pubmed/30178033

¹⁶ Mobile app, 2021. Available: https://en.wikipedia.org/wiki/Mobile_app#cite_note-19 [Accessed 2 Jan 2022 ].

¹⁷ Lalloo C, Jibb LA, Rivera J, et al. “There’s a pain app for that”: review of patient-targeted smartphone applications for pain management. 2015; 31: 557–63.

¹⁸ Reyes I, Wijesekera P, Reardon J, et al. “Won’t Somebody Think of the Children?” Examining COPPA Compliance at Scale. Proc Priv Enhancing Technologies 2018; 2018: 63–83. doi:10.1515/popets-2018-0021

¹⁹ Zhao F, Egelman S, Weeks HM, et al. Data collection practices of mobile applications played by preschool-aged children. JAMA Pediatr 2020; 174: e203345. doi:10.1001/jamapediatrics.2020.3345 http://www.ncbi.nlm.nih.gov/pubmed/32897299

²⁰ Das G, Cheung C, Nebeker C, et al. Privacy policies for Apps targeted toward youth: descriptive analysis of readability. JMIR Mhealth Uhealth 2018; 6: e3. doi:10.2196/mhealth.7626 http://www.ncbi.nlm.nih.gov/pubmed/29301737

²¹ Sardi L, Idri A, Redman LM, et al. Mobile health applications for postnatal care: review and analysis of functionalities and technical features. Comput Meth Prog Bio 2020; 184: 105114. doi:10.1016/j.cmpb.2019.105114 http://www.ncbi.nlm.nih.gov/pubmed/31655305

²² Liu M, Wang H, Guo Y, et al. Identifying and analyzing the privacy of Apps for kids. 2016: 105–10.

²³ Meyer M, Adkins V, Yuan N, et al. Advertising in Young Children’s Apps. J Dev Behav Pediatrics 2019; 40: 32–9.

²⁴ Cheng H, Tutt A, Llewellyn C, et al. Content and quality of infant feeding smartphone Apps: five-year update on a systematic search and evaluation. JMIR Mhealth Uhealth 2020; 8: e17300. doi:10.2196/17300 http://www.ncbi.nlm.nih.gov/pubmed/32459187

²⁵ Zhao J, Freeman B, Li M. How do infant feeding Apps in China measure up? A content quality assessment. JMIR Mhealth Uhealth 2017; 5: e186. doi:10.2196/mhealth.8764 http://www.ncbi.nlm.nih.gov/pubmed/29212627

²⁶ Zhao J, Li M, Freeman B. A baby formula designed for Chinese babies: content analysis of milk formula advertisements on Chinese parenting apps. JMIR Mhealth Uhealth 2019; 7: e14219–12. doi:10.2196/14219 http://www.ncbi.nlm.nih.gov/pubmed/31782743

²⁷ World Health Organization. International Code of marketing of breast-milk substitutes. Available: https://www.who.int/nutrition/publications/code_english.pdf [Accessed 30 Jul 2021 ].

²⁸ Pechmann C, Levine L, Loughlin S, et al. Impulsive and Self-Conscious: Adolescents’ Vulnerability to Advertising and Promotion. J Public Policy Amp Mark 2005; 24: 202–21. doi:10.1509/jppm.2005.24.2.202

²⁹ In:;. Zhao J, Wang G, Dally C. ‘I make up a silly name’: Understanding Children’sPerception of Privacy Risks Online, 2019.

³⁰ Desimpelaere L, Hudders L, Van de Sompel D. Children’s perceptions of fairness in a data disclosure context: The effect of a reward on the relationship between privacy literacy and disclosure behavior. Telemat Inform 2021; 61: 101602. doi:10.1016/j.tele.2021.101602

³¹ Livingstone S, Stoilova M, Nandagiri R. Children’s Data and Privacy Online: Growing up in a Digitial Age. LSE Media and Communications, 2018.

³² Tangari G, Ikram M, Ijaz K, et al. Mobile health and privacy: cross sectional study. BMJ 2021; 373: n1248. doi:10.1136/bmj.n1248 http://www.ncbi.nlm.nih.gov/pubmed/34135009

³³ Okoyomon E, Samarin N, Wijesekera P. On the Ridiculousness of notice and consent: contradictions in app privacy policies 2019.

³⁴ Freeman B, Kelly B, Baur L, et al. Digital junk: food and beverage marketing on Facebook. Am J Public Health 2014; 104: e56–64. doi:10.2105/AJPH.2014.302167 http://www.ncbi.nlm.nih.gov/pubmed/25322294

³⁵ Wojdynski BW. The Deceptiveness of sponsored news articles. Am Behav Sci 2016; 60: 1475–91. doi:10.1177/0002764216660140

³⁶ Chen Y, Zhu S, Xu H. Children’s Exposure to Mobile In-App Advertising: An Analysis of Content Appropriateness. Int Conf Soc Comput 2013: 196–203.

³⁷ Marelli L, Lievevrouw E, Van Hoyweghen I. Fit for purpose? The GDPR and the governance of European digital health. Policy Stud 2020; 41: 447–67. doi:10.1080/01442872.2020.1724929

³⁸ Thompson S, Warzel C. The privacy project: twelve million phones, one dataset, zero privacy. The New York Times, 2019.

³⁹ Biviji R, Vest JR, Dixon BE. Content analysis of behavior change techniques in maternal and infant health apps. Transl Behav Med 2020.

⁴⁰ Biviji R, Vest JR, Dixon BE, et al. Factors related to user ratings and user Downloads of mobile Apps for maternal and infant health: cross-sectional study. JMIR Mhealth Uhealth 2020; 8: e15663. doi:10.2196/15663 http://www.ncbi.nlm.nih.gov/pubmed/32012107

⁴¹ Bland C, Dalrymple KV, White SL, et al. Smartphone applications available to pregnant women in the United Kingdom: an assessment of nutritional information. Matern Child Nutr 2020; 16: e12918. doi:10.1111/mcn.12918 http://www.ncbi.nlm.nih.gov/pubmed/31833237

⁴² Brown HM, Bucher T, Collins CE, et al. A review of pregnancy iPhone apps assessing their quality, inclusion of behaviour change techniques, and nutrition information. Matern Child Nutr 2019; 15: e12768. doi:10.1111/mcn.12768 http://www.ncbi.nlm.nih.gov/pubmed/30569549

⁴³ Bry LJ, Chou T, Miguel E, et al. Consumer smartphone Apps marketed for child and adolescent anxiety: a systematic review and content analysis. Behav Ther 2018; 49: 249–61. doi:10.1016/j.beth.2017.07.008 http://www.ncbi.nlm.nih.gov/pubmed/29530263

⁴⁴ Chen E, Mangone ER. A systematic review of Apps using mobile criteria for adolescent pregnancy prevention (mCAPP). JMIR Mhealth Uhealth 2016; 4: e122. doi:10.2196/mhealth.6611 http://www.ncbi.nlm.nih.gov/pubmed/27833070

⁴⁵ Davis DW, Logsdon MC, Vogt K. Parent education is changing: a review of smartphone Apps. Mcn Am J Maternal Sol Child Nurs 2017; 42: 248–56.

⁴⁶ Furlong L, Morris M, Serry T, et al. Mobile apps for treatment of speech disorders in children: an evidence-based analysis of quality and efficacy. PLoS One 2018; 13: e0201513. doi:10.1371/journal.pone.0201513 http://www.ncbi.nlm.nih.gov/pubmed/30092095

⁴⁷ Hotwani K, Sharma K, Nagpal D, et al. Smartphones and tooth brushing: content analysis of the current available mobile health apps for motivation and training. Eur Arch Paediatr Dent 2020; 21: 103–8. doi:10.1007/s40368-019-00457-1 http://www.ncbi.nlm.nih.gov/pubmed/31154620

⁴⁸ Hswen Y, Murti V, Vormawor AA, et al. Virtual avatars, gaming, and social media: designing a mobile health app to help children choose healthier food options. J Mob Technol Med 2013; 2: 8–14. doi:10.7309/jmtm.2.2.3 http://www.ncbi.nlm.nih.gov/pubmed/25419244

⁴⁹ Mousavi Jazayeri SM, Jamshidnezhad A. Top Mobile Applications in Pediatrics and Children’s Health: Assessment and Intelligent Analysis Tools for a Systematic Investigation. Malays J Med Sci 2019; 26: 5–14.

⁵⁰ Musgrave LM, Kizirian NV, Homer CSE, et al. Mobile phone Apps in Australia for improving pregnancy outcomes: systematic search on app stores. JMIR Mhealth Uhealth 2020; 8: e22340. doi:10.2196/22340 http://www.ncbi.nlm.nih.gov/pubmed/33196454

⁵¹ Quinn M, Bliss M. Moving beyond tracing: The nature, availability and quality of digital apps to support children’s writing. J Early Child Lit 2021; 21: 230–58. doi:10.1177/1468798419838598

⁵² Richardson B, Dol J, Rutledge K, et al. Evaluation of mobile Apps targeted to parents of infants in the neonatal intensive care unit: systematic APP review. JMIR Mhealth Uhealth 2019; 7: e11620. doi:10.2196/11620 http://www.ncbi.nlm.nih.gov/pubmed/30985282

⁵³ Robinson CD, Seaman EL, Grenen E, et al. A content analysis of smartphone apps for adolescent smoking cessation. Transl Behav Med 2020; 10: 302–9. doi:10.1093/tbm/iby113

⁵⁴ Schoeppe S, Alley S, Rebar AL, et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act 2017; 14: 83. doi:10.1186/s12966-017-0538-3 http://www.ncbi.nlm.nih.gov/pubmed/28646889

⁵⁵ Schoffman DE, Turner-McGrievy G, Jones SJ, et al. Mobile apps for pediatric obesity prevention and treatment, healthy eating, and physical activity promotion: just fun and games? Transl Behav Med 2013; 3: 320–5. doi:10.1007/s13142-013-0206-3 http://www.ncbi.nlm.nih.gov/pubmed/24073184

⁵⁶ Sidhu S, Ma K, Sadovnikova A. Features and educational content related to milk production in breastfeeding Apps: content analysis informed by social cognitive theory. JMIR Pediatr Parent 2019; 2: e12364. doi:10.2196/12364 http://www.ncbi.nlm.nih.gov/pubmed/31518317

⁵⁷ Taki S, Campbell KJ, Russell CG, et al. Infant feeding websites and Apps: a systematic assessment of quality and content. Interact J Med Res 2015; 4: e18. doi:10.2196/ijmr.4323 http://www.ncbi.nlm.nih.gov/pubmed/26420339

⁵⁸ Virani A, Duffett-Leger L, Letourneau N. Parenting apps review: in search of good quality apps. Mhealth 2019; 5: 44. doi:10.21037/mhealth.2019.08.10 http://www.ncbi.nlm.nih.gov/pubmed/31620471

⁵⁹ Weber SJ, Dawson D, Greene H, et al. Mobile phone Apps for low-income participants in a public health nutrition program for women, infants, and children (WIC): review and analysis of features. JMIR Mhealth Uhealth 2018; 6: e12261. doi:10.2196/12261 http://www.ncbi.nlm.nih.gov/pubmed/30455172

⁶⁰ Weekly T, Walker N, Beck J, et al. A review of Apps for Calming, relaxation, and mindfulness interventions for pediatric palliative care patients. Children 2018; 5: 16. doi:10.3390/children5020016 http://www.ncbi.nlm.nih.gov/pubmed/29373515

⁶¹ Wisniewski P, Ghosh AK, Xu H. Parental control vs. teen self-regulation: is there a middle ground for mobile online safety? Proc 2017 Acm Conf Comput Supported Cooperative Work Soc Comput, 2017: 51–69.

⁶² Womack JJ, Anderson LN, Ledford CJW. Presence of complex and potentially conflicting information in prenatal mobile Apps. Health Promot Pract 2020; 21: 238–45. doi:10.1177/1524839918796216 http://www.ncbi.nlm.nih.gov/pubmed/30146903

⁶³ Zarnowiecki D, Mauch CE, Middleton G, et al. A systematic evaluation of digital nutrition promotion websites and apps for supporting parents to influence children’s nutrition. Int J Behav Nutr Phys Act 2020; 17: 17. doi:10.1186/s12966-020-0915-1