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Mobile health services are thriving in the field of maternal and child health in China due to expansions in the field of electronic health and the introduction of the two-child policy. There are numerous maternal and child health apps in computer stores, but the exact number of apps, number of downloads, and features of these apps is not known.
This study aimed to explore the use of maternal and child health apps in Android and iOS app stores and to describe the key functional features of the most popular apps, with the purpose of providing insight into further research and development of maternal and child health mobile health products.
The researchers conducted a search in the 3 most popular Android app stores (Tencent MyApp, Baidu Mobile Assistant, and 360 Mobile Assistant) and the iTunes App Store in China. All apps regarding family planning (contraception and preparing for pregnancy), pregnancy and perinatal care, neonatal care and health, and development for children under 6 years were included in the initial analysis. Maternal and child health mobile apps with predominant features of product marketing, children’s songs, animation, or games were excluded from the study. The 50 most frequently used apps in each of the Android stores as well as the iTunes store (a total of 78 deduplicated apps) were selected and downloaded for an in-depth analysis.
A total of 5276 Android apps and 877 iOS apps developed for maternal and child health care were identified. Of the 78 most frequently used apps, 43 (55%) apps focused on one stage of MCH care, mainly targeting child care (25 apps) and before pregnancy care (11 apps), whereas 35 (45%) of the apps covered 2 or more stages, most of which (32 apps) included both pregnancy and child care services. The app features that were commonly adopted by the popular apps were health education, communication, health status self-monitoring, a diary, reminders, and counseling. Within the app feature of “health status self-monitoring,” the researchers found 47 specific tools supporting activities such as pregnancy preparation, fetal heart monitoring, blood glucose and blood pressure monitoring, and doctor visits. A few apps were equipped with external devices (n=3) or sensors. No app with intelligent decision-support features to support disease management for conditions such as gestational diabetes and pregnancy-induced hypertension was found. A small number of apps (n=5) had a Web connection with hospital information systems to support appointment making, payments, hospital service guidance, or checking of laboratory results.
There are thousands of maternal and child health apps in the Chinese market. Child care, pregnancy, and before pregnancy were the mostly covered maternal and child health stages, in that order. Various app features and tools were adopted by maternal and child health apps, but the use of internal or external sensors, intelligent decision support, and tethering with existing hospital information systems was rare and these features need more research and development.
In the 21st century, mobile health (mHealth), defined as the use of mobile phones and other wireless technology in health care, is a burgeoning field within public health [
With the rapid development of mHealth, thousands of maternal and child health (MCH) apps have appeared in China in Android app markets and Apple’s app market. The popularity of mobile internet use (through devices such as mobile phones) and the universal two-child policy [
According to “The most popular apps for Androids” released by the
We selected the apps developed for family planning (contraception and preparation for pregnancy), pregnancy and perinatal care, neonatal care and health, and development of children under 6 years. We did a preliminary search in the 4 app markets using the following keywords in the Chinese language:
For each of the 4 app markets, the official website or App store was visited, and we searched for the MCH apps using the identified keywords. For each search, we logged in as a guest so that the search results could not be tailored to an existing account [
All found apps were ordered by number of downloads (Android) or reviews (iOS). The top 50 apps from Android and iOS markets respectively were deemed as the most frequently used apps and were selected for in-depth analysis in this study. A large number of apps were found which focused on early child education by predominantly using children’s songs, animation, and intelligence games. These apps had limited features or research significance, but the rankings were comparatively high. For our research purposes, we excluded these apps when identifying the top 50 apps in both markets.
For the apps that employed both Android and iOS systems, only the iOS system was used for in-depth analysis, as small differences could be identified between the different versions. Finally, the lists of the top 50 searches for Android and iOS were integrated into a combined list, which contained 78 unique apps.
Additionally, apps developed by, or mainly used by MCH institutions, were ordered by number of downloads (Android) and reviews (iOS), and the 10 most frequently used “top 10 institution apps” were selected for further analysis.
The 78 frequently used apps and the top 10 institution apps were all downloaded and installed on an iPhone 6s (iOS 10.3.1) or a Huawei MATE8 (NXT-AL10 Android 6.0) for in-depth analysis. For each app, 2 independent investigators registered and logged in to check all app modules and information. For the app or interventions that could only be activated at specific situations or stages, we activated them by simulating the required situations such as setting the expected date of confinement or fetal birth, registering multiple accounts, and adjusting the system time of the mobile phone.
To conduct the in-depth analysis, a semistructured database to collect and record the app characteristics was used. This database included the app’s name, the number of downloads or reviews, MCH stages, mHealth app features, specific interventions or services, and the mobile phone functions. Specifically, the MCH stages were classified as before pregnancy, pregnancy, birth, postpartum (mother), and child care (covering postnatal newborn, infancy, and childhood). The mHealth app features we intend to analyze comprise of 3 key components, namely (1) a list of 12 common app features mainly targeting health care providers, (2) a list of 5 app features serving client users, and (3) a list of 4 app features observed in the identified apps during the in-depth analysis. The first list of app features was based on a 12-category framework evaluating health systems performance for mHealth innovations in MCH field [
A total of 5276 Android system MCH apps and 877 iOS system MCH apps were identified. The flowchart of MCH app selection is shown in
After excluding apps whose predominant feature was early child education through songs, animation, and games (n=2774), the top 50 apps from Android and iOS app markets separately were selected, and 78 deduplicated apps were regarded as the most frequently used ones and downloaded for analysis.
All of the 78 frequently used apps used in this study were developed by private companies and were available for free download and use. Each app had over 2,570,000 downloads or more than 1235 reviews. For
The app features adopted by the 78 frequently used apps are illustrated in
The top 10 MCH institute apps developed for maternal and child health organizations were also screened for and analyzed. They had, at most, 18,000 downloads and no more than 39 reviews. The main app features were hospital service promotion, appointment making, health education, financial transaction and incentive (only payment for service), checking laboratory results, and counseling.
Within the “health status self-monitoring” app feature, 47 specific tools were found to provide users with individualized feedback as a response to regular or occasional health data collection (
Flowchart of app selection for maternal and child health. MCH: maternal and child health.
Distribution of maternal and child health care apps with different number of downloads or reviews.
Frequently used apps | n (%) | |
≥50,000,000 | 8 (0.15) | |
≥10,000,000 | 40 (0.76) | |
≥5,000,000 | 40 (0.76) | |
≥1,000,000 | 219 (4.15) | |
≥500,000 | 148 (2.81) | |
≥100,000 | 488 (9.25) | |
≥50,000 | 303 (5.74) | |
≥10,000 | 781 (14.80) | |
≥5000 | 411 (7.79) | |
≥1000 | 1074 (20.36) | |
<1000 | 1764 (33.43) | |
≥100,000 | 3 (0.3) | |
≥50,000 | 3 (0.3) | |
≥10,000 | 24 (2.7) | |
≥5000 | 25 (2.9) | |
≥1000 | 96 (10.9) | |
≥500 | 64 (7.3) | |
≥100 | 197 (22.5) | |
≥100 | 465 (53.0) |
Stages of maternal and child health care covered by the 78 most popular apps.
App features adopted in the 78 most popular apps on maternal and child health care.
App features covered in apps developed by maternal and child health institutions.
Specific tools within the “health status self-monitoring” feature found in the 78 popular apps on maternal and child health.
Tools | Apps, n (%) | |
Menstruation | 21 (27) | |
Sex life | 16 (21) | |
Ovulation | 13 (17) | |
Body symptoms | 13 (17) | |
Basic body temperature | 13 (17) | |
Leucorrhea | 7 (9) | |
Defecation | 4 (5) | |
Folic acid | 3 (4) | |
Type-B ultrasonic to test ovulation | 2 (3) | |
Sleep | 2 (3) | |
Medication | 2 (3) | |
Fetal movement | 13 (17) | |
Antenatal examination | 10 (13) | |
Expected date of confinement | 10 (13) | |
Abdominal girth perimeter | 10 (13) | |
Biparietal diameter | 9 (12) | |
Femur length | 9 (12) | |
Uterine contraction | 8 (10) | |
Antenatal examination report | 2 (3) | |
Blood pressure | 2 (3) | |
Fetal heart | 2 (3) | |
Parents blood type | 2 (3) | |
Progesterone value | 1 (1) | |
Human chorionic gonadotropin value | 1 (1) | |
Blood glucose | 1 (1) | |
Fundal height | 1 (1) | |
Postpartum depression | 1 (1) | |
Children’s height | 18 (23) | |
Children’s weight | 18 (23) | |
Vaccination | 11 (14) | |
Children’s head circumference | 9 (12) | |
Nurse | 5 (6) | |
Children’s sleep | 5 (6) | |
Children’s defecation | 4 (5) | |
Supplementary food | 3 (4) | |
Children taking drugs | 2 (3) | |
Children’s body temperature | 1 (1) | |
Exercise | 9 (12) | |
Diet | 7 (9) | |
Body weight | 23 (29) | |
Body height | 11 (14) | |
Body mass index | 3 (4) | |
Medical advice | 2 (3) | |
Medical records | 2 (3) | |
Heart rate | 1 (1) | |
Users’ blood type | 1 (1) | |
Laboratory test report result | 1 (1) |
This study revealed that there is a large demand for MCH mobile apps in the Chinese market. The cumulative downloads for all MCH apps amounted to hundreds of millions. When considering the stage of MCH which the developed apps targeted, child care was the most covered stage if the app was developed to target only 1 stage or the whole stage from (before) pregnancy to child care were the most covered stages when the apps were developed. Health education, communication, health status self-monitoring, shopping, diary, reminders, and counseling were the most developed app features. With respect to the specific app feature, “health status self-monitoring,” there were 47 tools helping women through family planning to child care. However, very few apps had effective communication between market MCH apps and existing hospital information systems, and very few apps were equipped with external or internal sensors or devices to support prompt data collection and point-of-care diagnostics.
Given that the target population of the most frequently used apps was the general public , the application features facilitating professional staff providing health service management and reporting were rarely adopted. These features included registries and vital events tracking, data collection and reporting, electronic health records, electronic decision support, provider-to-provider communication, provider work planning and scheduling, provider training and education, human resource management, supply chain management, and financial transaction and incentive. Instead, health education, personalized reminders, health status self-monitoring, counseling and client-to-client communication were the most adopted app features.
mHealth has large potential in health education activities due to its effectiveness in delivering verbal and visual messages [
Personalized reminders can reinforce behavioral changes in app users [
Health status self-monitoring tools are often a means to track changes in physical, biological, social, and psychological indicators, which in turn can guide corresponding behavior change [
Counseling is also a widely adopted app feature among the studied MCH apps. It can be a convenient way to connect users and experts, including either real-time consultations or nonreal-time queries through text, voice, and picture messages. This feature could facilitate, if adopted properly, education, medication instruction, and appointment scheduling. However, it must be noted that all the counseling behaviors should comply with the local regulations and laws.
Client-to-client communication could meet the desire of users to seek peer support by communicating with people who had similar health issues. Many apps would assign some pregnant women who are experienced in receiving health service with the support of app to answer questions in order to enhance the interaction. In fact, communication has been determined as an important measure to ensure the success of an app [
Other supportive features such as diaries, shopping, and games, which were not key components of MCH care but were highly welcomed by users, had a large impact on users’ adherence to apps. A diary can help people to record their mood and psychological status and experience being a new mother; shopping features can help people finding food, clothes, and other daily necessities good for health; and games might attract continuing use of an app. More and more apps now have features that promote what to eat and where to shop; however, this would have a negative impact if the app gives improper advice regarding food, nutritional products, and other daily necessities. The shopping app feature is the main profit model of current MCH apps in the Chinese app markets and needs further improvement.
Some apps were trying to connect with the MCH units in hospitals through features on clinical support services, namely appointments, payments, test results, etc; however, the relative downloads of apps with these features were much lower. Currently, most hospital information systems are closed networks. It is challenging to achieve free data transmission between apps and existing hospital electronic systems, given the concern over safety issues. Another attempt to connect with medical system was to develop MCH hospitals’ own apps. Such apps focused on hospital service promotion, appointment making, and checking of laboratory results. Due to the lack of commercial running, most of the apps were not well developed or maintained.
The study retrieved 5276 and 877 MCH apps, respectively, in the Android market and iTunes App store by using the most comprehensive keywords. However, not all apps were recruited, given that an increasing number of apps were developed on WeChat (a communication app of Tencent), and we did not include them in the study due to its unique interface and app structure. In addition, we are not able to backtrack the dates of release for all the studied apps. The difference on survival time will have an influence on the number of downloads and reviews. As a result, this may cause bias when identifying the most frequently used apps based on the number of downloads or reviews of the apps.
MCH apps have been rising in China’s market. Most of the apps were equipped with various features and tools. This study may provide an insight on the selection of appropriate features, functions, and tools and may facilitate a better understanding for mobile app developers of the gaps existing in mHealth products.
maternal and child health
mobile health
This study was funded by Qualcomm Wireless Reach and China Children and Teenagers’ Fund. The sponsors had no role in the study design, data analysis, result interpretation, or writing. The corresponding author (Puhong Zhang) had the final decision for the publication.
PZ and JL designed the study. LD and YC were responsible for app search, analysis, and data collection. LD, PZ, and HC drafted the manuscript. All authors contributed to the review and editing of the manuscript.
None declared.