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. 2019 Feb 6;15(3):e12768. doi: 10.1111/mcn.12768

A review of pregnancy iPhone apps assessing their quality, inclusion of behaviour change techniques, and nutrition information

Hannah M Brown 1,2, Tamara Bucher 1,2, Clare E Collins 1,2, Megan E Rollo 1,2,✉
PMCID: PMC7650606  PMID: 30569549

Abstract

Smartphone apps for use in pregnancy are common and could influence lifestyle behaviours, but they have not been evaluated. This review aimed to assess the quality of iPhone pregnancy apps and whether they included behaviour change techniques (BCTs) and/or pregnancy‐specific nutrition information. A keyword search of the Australian iTunes app store was conducted. For inclusion, apps had to be available at no cost, in English, intended for use by pregnant women, and contain nutrition information. App quality was assessed using the Mobile Application Rating Scale (MARS). Absence or presence of BCTs was assessed using the CALO‐RE taxonomy, with type of nutrition information included also reported. The initial key word search identified 607 apps, with 51 iPhone apps included in final evaluation. Mean overall MARS quality rating score was 3.05 out of 5 (1 = inadequate; 5 = excellent). The functionality subscale scored highest (mean = 3.32), and aesthetics scored lowest (mean = 2.87). Out of a possible 40 BCTs, 11 were present across the apps with a median of three BCTs (range: 0–6) identified per app. The median number of pregnancy‐specific nutrition topics per app was three (range 0 to 7). Despite the availability of a large number of iPhone pregnancy apps, few are of high quality, with only a small number of BCTs used and limited inclusion of pregnancy‐specific nutrition information. It is important to be aware of limitations within current pregnancy apps before recommending usage during this key life stage.

Keywords: app quality, apps, behaviour change techniques, iPhone, maternal nutrition, pregnancy and nutrition

Key messages.

  • This app review identified 51 pregnancy iPhone apps that were assessed on the basis of their quality, inclusion of behaviour change techniques, and nutrition information.

  • Few of the apps were found to be high quality, and most contained only a small number of behaviour change techniques and limited nutrition information.

  • Current apps on the market cannot be recommended exclusively as an appropriate nutrition resource for pregnant women.

  • Health professionals and researchers need to work in collaboration with app developers to develop high‐quality apps that incorporate evidence‐based nutrition information as well as positive behaviour change techniques.

1. INTRODUCTION

Dietary intake prior to and during pregnancy can impact on both short‐ and long‐term health outcomes of a mother and the infant (Gluckman & Hanson, 2006; Kind, Moore, & Davies, 2006; Scholl, 2008). Foods and drinks consumed during pregnancy can induce permanent alterations in offspring phenotype, therefore influencing the infant's future risk of non‐communicable diseases, such as type 2 diabetes (Fall, 2011; McMillen & Robinson, 2005). The nutritional status of pregnant women therefore makes an important contribution to the future health trajectory of their offspring (Gluckman & Hanson, 2006).

Smartphone apps have emerged as a mode to provide information to women during pregnancy, with more apps available for this condition than for any other medical topic (Tripp et al., 2014). The use of pregnancy and parenting apps is common among Australian women (Lupton & Pedersen, 2016). An online survey of 410 Australian women who were pregnant or had given birth in the past 3 years found that almost three quarters had used at least one pregnancy app and half reported using at least one parenting app (Lupton & Pedersen, 2016).

A systematic review by Overdijkink et al. (2018) examined the usability and effectiveness of mobile health (mHealth) lifestyle and medical apps to support health care during pregnancy. The results indicated that the apps tested in most of the studies were found to be acceptable and effective in increasing fruit and vegetable intakes and reducing gestational weight gain (Overdijkink et al., 2018). However, these findings, which focused on apps developed specifically for and evaluated as part of research interventions studies, differ from research that has looked at popular and freely available apps for use during pregnancy. Scott et al. examined the trustworthiness of 10 popular maternal and child health apps that were freely available in the Google and Apple app stores (Scott, Gome, Richards, & Caldwell, 2015). Only four of the apps were fully functional, two were fully usable, and three adequately implemented security mechanisms to guarantee privacy of user data (Scott et al., 2015).

Given the rapid propagation of smartphone apps, it is increasingly difficult for users, health professionals, and researchers to readily identify and assess the quality of apps (Cummings, Borycki, & Roehrer, 2013). The Mobile Application Rating Scale (MARS) is a reliable tool that provides a multidimensional measure of various indicators of app quality and has been found to have a high level of interrater reliability (Stoyanov et al., 2015). The MARS tool has been used to assess the quality of apps for various health topics including weight management (Bardus, van Beurden, Smith, & Abraham, 2016), mindfulness (Mani, Kavanagh, Hides, & Stoyanov, 2015), medication adherence (Santo et al., 2016), heart failure symptom monitoring (Masterson Creber et al., 2016), rheumatoid arthritis (Grainger, Townsley, White, Langlotz, & Taylor, 2017), self‐care (Anderson, Burford, & Emmerton, 2016), diabetes management (Chavez et al., 2017), and back pain (Machado et al., 2016) as well as for improving the diet and physical activity of children and adolescents (Schoeppe et al., 2017). However, it has not yet been used to assess the quality of pregnancy apps. Similarly, the inclusion of behaviour change techniques (BCTs) has been assessed in apps for medication adherence (Morrissey, Corbett, Walsh, & Molloy, 2016) and physical activity (Conroy, Yang, & Maher, 2014) as well as weight management (Bardus et al., 2016) but not in pregnancy apps. This is important because inclusion of BCTs, which are observable and replicable components designed to change behaviour (Michie et al., 2015), is associated with effectiveness of internet‐based interventions (Webb, Joseph, Yardley, & Michie, 2010).

To date, limited research has been conducted on the quality of freely available pregnancy apps. This review therefore aimed to assess the quality of pregnancy apps freely available within the Australian iTunes app store using the MARS tool. Secondary aims of the review included the assessment of BCTs and pregnancy‐specific nutrition information of included apps.

2. METHODS

In October 2017, a keyword search for iPhone apps was conducted of the Australian iTunes Apple store using the keywords Pregnancy, Pregnant, Pregnancy Diet, Pregnant Diet, Pregnancy Nutrition, Pregnant Nutrition, Pregnancy Food, and Pregnant Food. As the Australian iTunes store limits keyword searches to 100 apps, an identical keyword search was performed on the website https://fnd.io/.

Data related to each app identified in the initial search was extracted, including the name and category of the app, whether the app was free or cost money to download, presence of in‐app purchases, and the version number of each app. App store descriptions, which included screen shots of app content were saved as PDF files and then screened for eligibility. Apps were considered eligible if they were free to download (with or without containing in‐app purchases), in English, aimed at pregnant women, and contained nutrition or dietary information. If, from the app store description, it was uncertain whether an app met the inclusion criteria, it was included for further screening. Included apps were downloaded onto an iPhone 6s for evaluation and data extraction.

The quality of apps was assessed by one reviewer using the MARS tool. Briefly, the MARS tool assesses four subcategories that assess the app's qualities: (a) engagement (entertainment, interest, customisation, interactivity, and target group), (b) functionality (performance, ease of use, navigation, and gestural design), (c) aesthetics (layout, graphics, and visual appeal), and (d) information quality (accuracy of app description, goals, quality and quantity of information, visual information, credibility, and evidence base). Each item is marked on a 5‐point Likert scale (1 = inadequate, 2 = poor, 3 = acceptable, 4 = good, 5 = excellent). For example, the question that assesses entertainment, which is part of the engagement section asks “Is the app fun/entertaining to use? Does it use any strategies to increase engagement through entertainment (e.g., through gamification)?” The response options include (a) dull, not fun or entertaining at all; (b) mostly boring; (c) OK, fun enough to entertain user for a brief time (<5 min); (d) moderately fun and entertaining, would entertain user for some time (5–10 min); and (e) highly entertaining and fun, would stimulate repeat use. The quality score is derived from the mean of the scores for the engagement, functionality, aesthetics, and information quality subscales. More detail on the tool can be found elsewhere (Stoyanov et al., 2015).

Presence or absence of BCTs in relation to healthy and safe eating during pregnancy was assessed using the Coventry, Aberdeen & London‐Refined (CALO‐RE) taxonomy. The CALO‐RE taxonomy is a theoretical framework commonly used to evaluate app content in detail. It consists of definitions for 40 BCTs that could be employed to facilitate change in dietary and physical activity behaviours, such as goal setting and self‐monitoring. One reviewer used the CALO‐RE taxonomy to code the BCTs in the apps as either present or absent using the BCT definitions provided in the taxonomy (Michie et al., 2011).

Finally, the presence of pregnancy‐specific nutrition information relevant to pregnant women in Australia was evaluated through expert review by a dietitian. A list of specified nutrition topics was classified by the expert opinion of the authors of this review. The topics included guidance to reduce or abstain from alcohol, guidance to reduce caffeine consumption, fish consumption guidelines for pregnancy (i.e., reducing exposure to mercury or other potential contaminants from fish consumption), food safety guidelines for pregnancy (i.e., to reduce the risk of foodborne illness such as exposure to Listeria monocytogenes) and Institute of Medicine (IOM) weight gain guidelines for pregnancy. The presence of recommendations from the Australian Dietary Guidelines and Australian Guide to Healthy Eating for pregnancy was also evaluated (National Health and Medical Research Council, 2015a).

3. RESULTS

The search strategy identified 607 unique apps, for which the app title, cost, and language were screened, generating 142 app store descriptions that were further screened for inclusion (see Figure 1). This resulted in 91 apps being downloaded onto an iPhone 6s and 51 apps being included in the final analysis. The main reasons for exclusion following the download step were that the app version was not compatible with the current operating system (n = 13, 32.50%), the app was no longer available to download (n = 7, 17.50%), and the app did not contain nutrition information (n = 5, 12.5%).

Figure 1.

Figure 1

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Flow diagram of app inclusion process

Only four of the 51 (7.84%) included apps specified their country of origin; three of these apps were from Australia/the Australian version of an app, and one was from the United States. Most of the included apps were from the “health and fitness” category (n = 29, 56.86%), followed by “medical” (n = 17, 33.33%), “food and drink” (n = 4, 7.84%), and “productivity” (n = 1, 1.96%). Only 15 apps (29.41%) had more than 10 ratings/reviews in the app store, and 22 apps (43.14%) contained in‐app purchases. Many of the apps (n = 22, 43.14%) required an internet connection to function.

Only three apps declared their affiliations and sources of funding. These included the app Safe Pregnancy and Birth, which was a collaboration between Hesperian (non‐profit publisher of resources [e.g., books] for community‐based health care) and UnaMesa (public charity). The app My South West Sydney Baby Pregnancy Journey declared that the app was developed by South Western Sydney Local Health District (SWSLHD; government department) and was financially supported by SWSLHD Innovation Fund, South Western Sydney Primary Health Care Network, Liverpool, Bankstown, and Fairfield hospitals (New South Wales, Australia). Finally, the app Pregnant with Diabetes declared that the Australian version of the app was sponsored by the Australasian Diabetes in Pregnancy Society (professional organisation).

The mean overall MARS quality score (mean score of the four subscales) across all apps was 3.05 (SD: 0.66) out of 5 (1 = inadequate and 5 = excellent). The apps that had the highest quality scores were Pregnancy+ (4.60), Ovia Pregnancy Tracker App (4.20), and My South West Sydney Baby Pregnancy Journey (4.16). The apps that had the lowest quality scores were Pregnant Eating: A Guide to Safe Dietary Choice for Expectant Mothers (1.65), Food Guide for Pregnant Women (2.05), and Pregnancy & Baby Development Handbook (2.08).

Overall, the MARS subscale Functionality was rated the highest (mean = 3.32), followed by Engagement (mean = 3.07), then Information (mean = 2.93). Aesthetics was the lowest scoring subscale (mean = 2.87). The app Pregnancy+ scored the highest for three out of the four MARS subscales (Engagement: 4.8; Functionality: 5; and Aesthetics: 5), whereas the app WebMD Pregnancy scored the highest for the MARS subscale Information (4.6).

Eleven BCTs out of a possible 40 were present across the included apps, with frequency details summarised in Table 1, along with the number of apps that included each technique.

Table 1.

Frequency of behaviour change technique inclusion across the apps (n = 51)

Behaviour change technique (BCT)[Link] Number of apps that included the BCT (%)
21: Provide instruction on how to perform the behaviour 46 (90.20)
2: Provide information on consequences of behaviour to the individual 46 (90.20)
17: Prompt self‐monitoring of behavioural outcome 17 (33.33)
1: Provide information on consequences of behaviour in general 13 (25.50)
24: Environmental restructuring 8 (15.69)
16: Prompt self‐monitoring of behaviour 4 (7.84)
4: Provide normative information about others' behaviour 3 (5.88)
32: Fear arousal 3 (5.88)
20: Provide information on where and when to perform the behaviour 2 (3.92)
22: Model/demonstrate the behaviour 2 (3.92)
40: Stimulate anticipation of future rewards 1 (1.96)
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Corresponding number of the BCT, as defined by Michie's CALO‐RE taxonomy (24).

Table A1.

App data extraction table

App characteristics MARS scoringa BCTsb (type) Nutrition topicsc (type)
App name (version) Rating (number of ratings) Developer Last update Cost to upgrade Affiliation Tech aspects total (type) Country of origin Engagement Functionality Aesthetics Info Overall score
Pregnancy+ (4.7.1) 4.5 stars (n = 1816) Health & Parenting Ltd. 11 Jan 2018 $5.99 Unknown 5 (Sharing, password, login, reminders, web) Not stated 4.80 5.00 5.00 3.60 4.60 4 (1, 2, 17, 21) 6 (alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Ovia Pregnancy Tracker App (4.1.2) 5 stars (n = 343) Ovuline, Inc. 26 Dec 2017 NIL Unknown 3 (community, reminders, web) Not stated 4.60 4.00 4.00 4.20 4.20 4 (2, 16, 17, 21) 7 (serves, alcohol, caffeine, fish, f. safety, wt. gain, exercise)
My South West Sydney Baby Pregnancy Journey (1.6.3) Not available (n = 2) SWSLHD 15 Feb 2018 NIL Financially supported by SWSLHD Innovation Fund, South Western Sydney Primary Health Care Network 2 (login, reminders) Australia 4.20 4.25 4.00 4.20 4.16 2 (2, 21) 4 (alcohol, caffeine, f. safety, exercise)
WebMD Pregnancy (2.0.10) Not available (n = 14) WebMD Health Corporation 30 Jan 2018 NIL Unknown 6 (sharing, community, password, login, reminders, web) USA 4.60 3.75 3.66 4.60 4.15 4 (1, 2, 17, 21) 6 (alcohol, caffeine, fish, f. safety, wt. gain, exercise)
The Bump‐Pregnancy Countdown (5.1.0) 4.5 stars (n = 185) The Knot Inc. 12 Mar 2018 NIL Unknown 5 (sharing, community, login, reminders, web) Not stated 4.40 3.00 4.33 4.40 4.03 5 (1, 2, 4, 21, 24) 6 (alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Baby2Body. Pregnancy Australia (2.3.9) 4.5 stars (n = 28) Baby2Body Limited 21 Mar 2018 $9.99/month after trial Unknown 5 (sharing, community, login, reminders, web) Not stated 4.00 4.00 4.67 3.40 4.02 2 (2, 21) 5 (alcohol, caffeine, fish, f. safety, exercise)
Pregnancy Tracker! (1.0.5) 4.5 stars (n = 5) Sevenlogics, Inc. 7 Dec 2016 NIL Unknown 4 (sharing, login, reminders, web) Not stated 4.40 3.50 4.00 4.00 3.98 5 (2, 17, 21, 24, 32) 7 (serves, alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Glow Nurture‐Pregnancy App (4.2.1) 5 stars (n = 74) Glow, Inc. 12 Mar 2018 $12.99/month or $71.99/year or $89.99/lifetime Unknown 5 (sharing, community, login, reminders, web) Not stated 4.60 3.75 3.33 4.20 3.97 4 (2, 16, 17, 21) 7 (serves, alcohol, caffeine, fish, f. safety, wt. gain, exercise)
I'm Expecting Pregnancy App (2.8.2) 4.5 stars (n = 33) MedHelp 20 Mar 2018 NIL Unknown 2 (login, web) Not stated 3.80 3.75 4.00 4.00 3.89 4 (2, 16, 17, 21) 6 (alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Pregnancy Food Guide! (1.1.2) Not available (n = not available) Kigorosa UG (haftungsbeschränkt) 24 Mar 2018 Pro version is a separate app and costs $1.99 Unknown NIL Not stated 3.80 4.25 3.33 3.60 3.75 3 (1, 2, 21) 4 (alcohol, caffeine, fish, f. safety)
Pregnancy Tracker & Baby App (3.14.1) 5 stars (n = 744) Babyleft 31 Jan 2018 NIL Unknown 5 (sharing, community, login, reminders, web) Not stated 4.20 3.00 3.33 4.20 3.68 3 (2, 20, 21) 6 (alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Sprout Pregnancy (8.6) 4.5 stars (n = 150) Med ART Studios 20 Dec 2017 $7.99 Unknown 3 (sharing, login, reminders) Australia/New Zealand edition 4.20 3.75 3.33 3.40 3.67 6 (1, 2, 4, 17, 21, 24) 4 (alcohol, caffeine, f. safety, exercise)
Pregnancy & Baby Tracker (9.16) 4.5 stars (n = 981) Everyday Health, Inc. 29 Jan 2018 NIL Unknown 6 (sharing, community, password, login, reminders, web) Not stated 4.00 3.00 3.00 3.80 3.45 3 (1, 2, 21) 7 (serves, alcohol, caffeine, fish, f. safety, wt. gain, exercise)
Pregnancy Health & Fitness Week by Week (1.0.9) Not available (n = not available) SparkPeople, Inc. 8 Mar 2016 NIL Unknown 1 (login) Not stated 3.60 3.50 3.00 3.60 3.43 4 (1, 2, 21, 22) 4 (fish, f. safety, wt. gain, exercise)
Pregnant‐Day by Day (2.2.0) 4.5 stars (n = 7) Interaktion.Co ApS 19 Jan 2018 $9.99 Unknown 2 (sharing, reminders) Not stated 3.20 3.75 3.00 3.20 3.29 2 (2, 21) 2 (fish, exercise)
9Months Guide (1.1) Not available (n = not available) Seller is Bhushan Waghode 22 Nov 2016 $1.00 Unknown 1 (sharing) Not stated 3.40 4.00 3.33 2.40 3.28 3 (2, 17, 21) 1 (wt. gain)
Pregnancy App & Chat Mom.Life (4.21.1) Not available (n = 1) Wunderkind Media & Technology Corporation 29 Apr 2018 NIL Unknown 6 (sharing, community, password, login, reminders, web) Not stated 4.00 3.00 3.00 3.00 3.25 4 (2, 17, 21, 24) 2 (alcohol, exercise)
SmartMomma Food Guide (2.1) Not available (n = not available) Maria Maisuradze 15 May 2017 NIL Unknown NIL Not stated 2.80 3.50 3.00 3.60 3.23 2 (2, 21) 4 (alcohol, caffeine, fish, f. safety)
Pregnant with Diabetes (1.4.1) Not available (n = not available) Soren Rasmussen 20 Oct 2016 NIL Sponsored by the Australasian Diabetes in Pregnancy Society NIL Australian version and has been modified 2.60 4.00 3.00 3.25 3.21 2 (2, 21) 2 (wt. gain, exercise)
Pregnancy Today‐Baby Tracker (1.5) 4.5 stars (n = 43) Mushroom Apps and says the Seller is John Benson 22 Dec 2017 Kind tip: $2.99, generous tip: $7.99, amazing tip $14.99. Unknown 2 (login, reminders) Not stated 2.80 4.00 3.33 2.50 3.16 1 (2) 0.00
Full Term‐Contraction Timer & Pregnancy Toolkit (3.5.0) Not available (n = 19) Mustansir Golowala 18 Aug 2017 $1.49 Unknown 2 (sharing, reminders) Not stated 3.20 3.50 3.00 2.75 3.11 4 (1, 2, 17, 21) 3 (fish, wt. gain, exercise)
Free Pregnancy App | Baby Chronicles (1.1) Not available (n = not available) Dania Lebovics 21 Jun 2016 NIL Unknown 3 (login, reminders, web) Not stated 3.20 3.25 3.33 2.50 3.07 2 (17, 21) 2 (alcohol, exercise)
BabyCheck‐Todos and Task (1.5) Not available (n = not available) Stefan Eipeltauer 23 Dec 2017 NIL Unknown 1 (sharing) Not stated 2.60 3.75 3.00 2.75 3.03 1 (21) 2 (alcohol, f. safety)
Pregnancy Due Date Guide (1.3) Not available (n = not available) Rahi Patel 25 Nov 2014 NIL Unknown 1 (sharing) Not stated 2.80 4.00 2.67 2.60 3.02 3 (2, 21, 22) 3 (caffeine, fish, f. safety)
Tracker App for Pregnant Mom (2.5.2) Not available (n = 1) Mobile Dimension LLC 2 Mar 2018 $3.99 Unknown 1 (sharing) Not stated 3.00 3.50 3.00 2.50 3.00 4 (1, 2, 17, 21) 3 (alcohol, caffeine, f. safety)
iBirth Daily Pregnancy, Postpartum & Baby Tracker (4.0.1) Not available (n = not available) Lula B. 10 May 2017 NIL Unknown 3 (sharing, login, web) Not stated 3.00 2.75 3.00 3.20 2.99 4 (1, 2, 17, 21) 2 (fish, exercise)
Pregnancy‐Week by Week Pregnancy (1.0) Not available (n = not available) Mahyra Indietech 7 Feb 2017 NIL Unknown 1 (reminders) Not stated 2.20 3.75 3.33 2.50 2.95 2 (2, 21) 1 (alcohol)
Totally Pregnant (2.8) Not available (n = 1) 40 weeks 12 Apr 2018 $7.99 Unknown 4 (sharing, login, reminders, web) Not stated 3.80 2.25 2.67 3.00 2.93 3 (2, 21, 24) 5 (alcohol, caffeine, fish, f. safety, exercise)
iPregnant Pregnancy Tracker Free (iPeriod's Pregnancy Companion) (2.1) 3 stars (n = 10) Winkpass Creations, Inc. 5 Feb 2015 NIL Unknown 4 (sharing, community, reminders, web) Not stated 3.00 3.25 2.67 2.75 2.92 3 (2, 17, 21) 1 (alcohol)
280 days: Pregnancy Diary App (1.6.7) 5 stars (n = 24) Amane Factory Inc. 24 Feb 2018 $2.99 Unknown 4 (sharing, login, reminders, web) Not stated 3.40 2.50 2.67 3.00 2.89 3 (2, 17, 21) 3 (alcohol, wt. gain, exercise)
Pregnancy Recipes‐Healthy Cooking Tips, Ideas (2.6) Not available (n = not available) Huyen Trang Nguyen 7 Oct 2016 NIL Unknown 2 (sharing, web) Not stated 3.20 3.25 2.33 2.75 2.88 3 (2, 20, 21) 4 (alcohol, caffeine, fish, f. safety)
Tips for Pregnant: Hello Belly (1.3.11) Not available (n = 4) HelloBaby, Inc 29 Mar 2018 “Buy forever” is $30.99 onetime payment or $6.99/month Unknown 2 (sharing, reminders) Not stated 3.20 3.00 3.00 2.25 2.86 6 (2, 4, 16, 21, 24, 40) 5 (alcohol, caffeine, fish, f. safety, exercise)
Pregnancy Recipes‐Dessert & Snacks Recipes (1.0) Not available (n = not available) Hicham Achbab 19 May 2016 NIL Unknown 1 (sharing) Not stated 3.00 3.50 2.30 2.25 2.76 1 (21) 0.00
Healthy Nutrition Pregnancy (1.0.1) Not available (n = not available) Cristina Gheorghisan 23 April 2016 $1.49 Unknown NIL Not stated 2.40 3.00 2.33 3.25 2.75 3 (1, 2, 21) 5 (serves, alcohol, fish, f. safety, exercise)
Fertility and Pregnancy Magazine‐How to Get Pregnant and Have a Healthy Baby (7.6.1) Not available (n = not available) Sequoia Peak LLC 31 Dec 2014 NIL Unknown 5 (sharing, community, password, login, reminders) Not stated 3.60 2.50 2.67 2.00 2.69 2 (2, 21) 2 (caffeine, exercise)
Pregnancy Tracker: Week by Week (2.0) Not available (n = not available) Hitbytes Technologies 24 Apr 2017 NIL Unknown 1 (login) Not stated 3.00 2.50 2.30 2.60 2.60 2 (2, 21) 5 (alcohol, caffeine, f. safety, wt. gain, exercise)
iPregnancy and Baby Guide Free App (1.0) Not available (n = not available) Tashlik 17 Sep 2015 NIL Unknown 1 (web) Not stated 2.80 3.00 2.30 2.20 2.58 2 (2, 21) 3 (caffeine, fish, f. safety)
Foods to Avoid During Pregnancy‐Pregnancy Diet Tips & Recipes (1.2) Not available (n = not available) Pregniful Solutions LTD 1 May 2015 NIL Unknown NIL Not stated 2.00 2.50 2.33 3.25 2.52 4 (1, 2, 21, 24) 5 (alcohol, caffeine, fish, f. safety, exercise)
Safe Pregnancy and Birth (2.0.2) Not available (n = 3) Hesperian Health Guides 18 Mar 2017 NIL Hesperian (non‐profit publisher) and UnaMesa (public charity). NIL Not stated 1.80 3.50 2.33 2.20 2.46 3 (2, 21, 32) 1 (alcohol)
Pregnancy Workout Advisor (2.1) Not available (n = not available) ORGware Technologies Pvt. Ltd 11 Jan 2017 $1.49 Unknown 1 (login) Not stated 2.40 2.50 2.33 2.50 2.43 3 (2, 17, 21) 1 (exercise)
iPregnancy and Baby Guide App‐Great App for Pregnancy Diet (1.2) Not available (n = not available) Gyan Sahoo 13 May 2015 NIL Unknown 1 (web) Not stated 1.80 4.00 2.30 1.50 2.40 2 (2, 21) 3 (caffeine, fish, f. safety)
Pregnancy Diet (No Internet Needed) (3) Not available (n = not available) Ouamassi Brahim 21 Jun 2016 $4.49 Unknown NIL Not stated 1.40 4.00 1.67 2.50 2.39 2 (2, 21) 4 (alcohol, caffeine, fish, f. safety)
Pregnancy‐Tracker & Calendar (2.4.1) 5 stars (n = 25) Aliaksei Khanenia 27 Apr 2018 $2.99 Unknown 2 (login, web) Not stated 2.40 2.50 2.67 2.00 2.39 2 (2, 17) 0.00
Pregnancy Checklists (2.2.0) Not available (n = not available) Kigorosa UG 20 Dec 2017 $0.99 Unknown NIL Not stated 2.20 2.50 2.30 2.50 2.38 2 (2, 21) 3 (caffeine, fish, f. safety)
Pregnancy Trivia (3.1.19) Not available (n = not available) Shawn Tan 25 Aug 2015 NIL Unknown 1 (sharing) Not stated 1.40 4.00 2.00 2.00 2.35 0.00 0.00
Pregnancy Food Checker (1.0) Not available (n = not available) Sylvia Gaudin 10 Sep 2016 $2.99 Unknown NIL Not stated 1.80 4.00 2.00 1.50 2.33 0.00 0.00
Pregnancy Countdown‐Weekly Fetus & Mother Development Plus Tips, Information and Checklists (4.5.2) 3 stars (n = 29) Pregniful Solutions LTD 28 Jul 2016 $3.99 Unknown 1 (web) Not stated 2.20 2.75 1.67 2.60 2.31 2 (2, 21) 2 (fish, f. safety)
Virtuous Child‐Pregnancy Health Fitness Trainer (1.8) Not available (n = not available) DawnSun Technologies, LLC 14 Jul 2017 1 month = $4.49, 3 months = $7.99, lifetime = $9.99 Unknown 2 (login, reminders) Not stated 2.60 2.25 1.33 2.75 2.23 3 (2, 21, 32) 4 (alcohol, caffeine, fish, f. safety)
Pregnancy & Baby Development Handbook (4.5.1) Not available (n = not available) Pregniful Solutions LTD 15 July 2016 NIL Unknown 1 (web) Not stated 2.80 2.25 1.67 1.60 2.08 1 (2) 2 (fish, f. safety)
Food Guide for Pregnant Women (1.1) Not available (n = not available) Rahul Baweja 31 Aug 2016 NIL Unknown NIL Not stated 1.20 2.50 2.00 2.50 2.05 4 (1, 2, 21, 24) 6 (serves, alcohol, caffeine, fish, f. safety, wt. gain)
Pregnant Eating: A Guide to Safe Dietary Choice for Expectant Mothers (1.3) Not available (n = not available) Ryan Peters 18 Apr 2015 $1.49 Unknown NIL Not stated 1.20 2.25 1.33 1.80 1.65 2 (2, 21) 4 (alcohol, caffeine, fish, f. safety)
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Note. BCT: behaviour change technique; MARS: Mobile Application Rating Scale; SWSLHD: South Western Sydney Local Health District.

a

MARS scores in the table represent the mean scores for each of the four objective sub‐scales.

b

BCTs are coded in the table. The corresponding BCTs to the numbers presented in the table are as follows: 1: provide information on consequences of behaviour in general, 2: provide information on consequences of behaviour to the individual, 4: provide normative information about others' behaviour, 16: prompt self‐monitoring of behaviour, 17: prompt self‐monitoring of behavioural outcome, 20: provide information on where and when to perform the behaviour, 21: provide instruction on how to perform the behaviour, 22: model/demonstrate the behaviour, 24: environmental restructuring, 32: fear arousal, 40: stimulate anticipation of future rewards.

c

Nutrition topics are coded in the table. The corresponding nutrition topic to the acronym presented in the table are as follows: f. safety: food safety, alcohol: alcohol consumption, fish: fish and mercury consumption, caffeine: caffeine consumption, exercise: exercise for pregnancy, wt. gain: recommended pregnancy weight gain, serves: recommended number of daily serves from key food groups for pregnant women.

Median number of BCTs per app was 3 and ranged from 0 to 6 per app (6 BCTs: n = 2 apps, 0 BCTs: n = 2 apps). The two apps containing six BCTs each were Sprout Pregnancy and Tips for Pregnant: Hello Belly, whereas the two apps that contained no BCTs were Pregnancy Food Checker and Pregnancy Trivia.

The most common BCTs were providing information on consequences of behaviour to the individual (n = 46, 90% of apps) and providing instruction on how to perform the behaviour (n = 46, 90%).

The median number of predetermined nutrition information topics per app was three and ranged from 0 to 6 per app (six topics: n = 5 apps, zero topics: n = 5 apps). The five apps that had six topics each were Pregnancy Tracker! Ovia Pregnancy Tracker App, Glow Nurture‐Pregnancy App, Pregnancy & Baby Tracker, and Food Guide for Pregnant Women. Five apps did not contain any information related to the predetermined nutrition topics; however, they may have included more general nutrition or food facts or recipes. These apps included Pregnancy‐Tracker & Calendar, Pregnancy Recipes‐Dessert & Snacks Recipes, Pregnancy Today‐Baby Tracker, Pregnancy Food Checker, and Pregnancy Trivia.

The most common pregnancy nutrition topics are related to food safety (n = 33, 64.7% of apps), alcohol consumption (n = 32, 62.7%), and information related to fish and mercury consumption (n = 31, 60.8%). Information on caffeine consumption was present in 29 apps (56.9%), and 16 apps contained information related to recommended pregnancy weight gain (31.4%). Only six apps (11.8%) contained information related to the recommended number of daily serves from key food groups for pregnant women, and no apps contained country‐specific information related to the Australian Guide to Healthy Eating.

Finally, some apps included nutrition information that could potentially be harmful to pregnant women. The app Pregnancy & Baby Development Handbook stated “beverages which contain a small percentage of alcohol, such as malt and beer, may or may not be helpful; they should be regarded as medicine, not to be taken without consulting a physician.” The app Tracker app for Pregnant Mom advised pregnant women to arrange fasting days once a week and provided information on how to fast. Finally, the app Hello Belly Pregnancy warned pregnant women to be careful with dairy products, stating “dairy products can only not add calcium to the body, but also wash away the natural mommy's calcium, and this can also damage the baby. To saturate with calcium, it is better not to rely on dairy products, but to lean on green foods. It is digested much better than ‘milk’ calcium.”

4. DISCUSSION

This study is the first to comprehensively review commercially available nutrition and pregnancy mobile apps and to independently evaluate their quality using validated instruments, including the MARS tool and CALO‐RE taxonomy, as well as expert review of pregnancy‐specific nutrition information included in the apps.

Of concern was the hidden costs contained in 43% of the apps, including in‐app purchases and the requirement of some to have internet access to function that could attract associated data costs. These hidden expenses have the potential to mislead consumers. Out of the three apps scoring highest for quality, only one, My South West Sydney Baby Pregnancy Journey, did not contain in‐app purchases or require internet access to function. Ovia Pregnancy Tracker App did not contain in‐app purchases but did require internet access to function, and the highest scoring app, Pregnancy+, contained in‐app purchases and required internet access.

The included apps were overall of moderate quality and scored higher in terms of functionality and engagement using the MARS tool. This is in line with findings in reviews by Bardus et al. (2016) and Schoeppe et al. (2017) which found functionality to be the highest scoring subcategory in health apps. This may be a result of app developers taking research findings into consideration, such as a systematic review by Payne, Lister, West, and Bernhardt (2015) who found that users want apps that are fast and easy to use. Information was the second lowest scoring subcategory in this review, and this low score is in line with other reviews on app quality as Bardus et al. (2016), and Schoeppe et al. (2017) also found information to score poorly. A number of reviews have found health apps to lack evidence‐based content (Azar et al., 2013; Breton, Fuemmeler, & Abroms, 2011; Cowan et al., 2013; Pagoto, Schneider, Jojic, DeBiasse, & Mann, 2013; Schoffman, Turner‐McGrievy, Jones, & Wilcox, 2013; Wearing, Nollen, Befort, Davis, & Agemy, 2014). Pregnancy apps and the information they contain could therefore increase rather than decrease a woman's potential stress and anxiety related to nutrition during pregnancy, which has been identified in previous research on the use of apps in pregnancy (Tripp et al., 2014). The authors of the current review therefore support the suggestion from Bardus et al. (2016) for app developers to invest more effort into developing evidence‐based content, which will subsequently improve the quality of health apps. Engaging and collaborating with clinicians and relevant pregnancy and maternal health organisations would be an effective way for app developers to achieve this recommendation.

On average, the 51 apps included in this review predominantly used three different BCTs developed by Michie et al. (2011), with a range of 0–6 BCTs per app. This is below the average number identified in previous app reviews, where the mean number of BCTs incorporated into apps that aimed to modify physical activity and dietary behaviours in adults ranged between four and eight BCTs (Conroy et al., 2014; Direito et al., 2014; Middelweerd, Mollee, van der Wal, Brug, & Te Velde, 2014). In the current review, the two most frequently used BCTs were information on consequences of behaviour to the individual and provide instruction on how to perform the behaviour. A review by Schoeppe et al. (2017) also found provide instruction on how to perform the behaviour to be the most frequently used BCT. However, other reviews of apps targeting dietary, physical activity, and sedentary behaviour in adults found goal setting, self‐monitoring, and performance feedback to be the most frequently used BCTs (Bardus et al., 2016; Lyons, Lewis, Mayrsohn, & Rowland, 2014; Middelweerd et al., 2014). These findings are in line with previous reviews that found most direct‐to‐consumer apps do not draw on BCTs (Abroms, Padmanabhan, Thaweethai, & Phillips, 2011; Breton et al., 2011; Chomutare, Fernandez‐Luque, Arsand, & Hartvigsen, 2011; Cowan et al., 2013; West et al., 2012). Further, despite evidence that pregnant women find using mHealth for receiving feedback on their nutrition behaviour acceptable (Ashman, Collins, Brown, Rae, & Rollo, 2016), no apps in this review incorporated this BCT.

In the current review, apps included a median number of three predetermined pregnancy‐specific nutrition information topics. The range of topics across the apps was 0–6, with five apps containing no pregnancy nutrition information. This is in line with a review by Abroms et al. (2011), who found that iPhone apps for smoking cessation rarely adhere to established guidelines for smoking cessation. Further, a review by Breton et al. found that many of the apps they included had insufficient evidence‐informed content related to weight control (Breton et al., 2011). This was also the case in the current review, as only 16 apps (31.4%) contained information on appropriate pregnancy weight gain, as defined by the IOM guidelines. There is a need for more rigour in ensuring these guidelines are contained in pregnancy apps, as an international nulliparous sample of 1,950 participants from Ireland, New Zealand, and Australia found that 74.3% exceeded the IOM guidelines for gestational weight gain (Chung et al., 2013). The most common nutrition information topics in this app review were related to pregnancy food safety guidelines, alcohol consumption during pregnancy, and fish consumption. It therefore seems that nutrition content in the majority of pregnancy apps are safety‐focused and aim to decrease risk through food avoidance advice in pregnant women. Although this is an important aspect of nutrition education for pregnant women, it is also imperative that such apps prioritise optimising food and nutrient intakes in pregnant women by providing information on amounts and types of food to eat.

Finally, three apps included nutrition information that could potentially be harmful to pregnant women. The app Pregnancy & Baby Development Handbook included information on alcohol consumption that contradicts with current recommendations to avoid alcohol during pregnancy (Australian Government Department of Health, 2014), whereas the app Tracker app for Pregnant Mom included information aimed to encourage pregnant women to fast. Finally, the app Hello Belly Pregnancy advised pregnant women to avoid dairy products and to instead eat “green foods” to meet their calcium requirements. This does not align with current evidence that calcium may be poorly absorbed from foods rich in oxalic acid such as spinach and beans (National Health and Medical Research Council, 2014). This information therefore has the potential to be harmful for pregnant women.

Strengths of the current review include use of a multistep methodology to evaluate pregnancy apps, including use of the MARS quality assessment tool and CALO‐RE behaviour change taxonomy. Use of the MARS tool was a strength because it is a reliable tool for classifying and assessing the quality of mHealth apps (Stoyanov et al., 2015). Using the CALO‐RE taxonomy was a further strength as it allowed for a reliable and systematic application of evidence and theory related to behaviour change (Michie et al., 2011), as was the expert review by a dietitian of the pregnancy‐specific nutrition information in the apps.

A limitation of the current review was the high percentage of apps (43%) that contained in‐app purchases. These additional features were not evaluated in this review, and so conclusions on these apps should be interpreted in this context. A further limitation relates to the fast‐moving nature of app development and required upkeep of mobile apps. Thirteen apps were excluded as the app version was not compatible with the current operating system, which was outside of the author's control. Further, it is possible that the versions of the pregnancy apps included in this review may be different from those currently available in the iTunes store, as some of the included apps are likely to have been updated. Finally, only one reviewer assessed the quality of the apps using the MARS tool and coded the inclusion of BCT's. However, any ambiguity of the assessments was clarified with a second reviewer.

On the basis of findings of the current review, it is recommended that health professionals, including dietitians, health researchers, app developers, and maternal health experts such as obstetricians, gynaecologists, and midwives work in collaboration to design high‐quality, evidence‐based pregnancy apps. Nutrition information provided within pregnancy apps should be based on up‐to‐date, evidence‐based guidelines, and the information source should be referenced. This also supports recommendations by Schoeppe et al. (2017) for apps to provide educational content informed by evidence‐based dietary guidelines. Authors of the current review support the recommendations by Dennison, Morrison, Conway, and Yardley (2013) for app developers to explore how effective BCTs can be incorporated into health apps while avoiding content that worries or distresses users. Further, a key finding of this review was the poor quality and lack of regulation of the nutrition information contained within the apps. The potential danger of pregnant women relying exclusively on apps for information about nutrition rather than seeking advice from a health professional was identified in a review by Tripp et al. (2014). Three apps in the current review were identified as containing information that could potentially be harmful to pregnant women, including encouraging the consumption of alcohol and advising regular fasting days during pregnancy. Previous reviews on apps for asthma self‐management (Huckvale, Car, Morrison, & Car, 2012), insulin dosing (Huckvale, Adomaviciute, Prieto, Leow, & Car, 2015), and suicide prevention (Larsen, Nicholas, & Christensen, 2016) have reported the inclusion of nonevidence‐based content (Huckvale et al., 2012), but some apps may also have the potential to contribute to catastrophic health outcomes (Huckvale et al., 2015; Larsen et al., 2016). The absence of regulations for app content is therefore of concern, and there is urgent need for regulation of information and health claims made in medical and health apps (Tripp et al., 2014).

Finally, based on the evaluation of quality and content, this review does not support the use of current apps on the market as an appropriate nutrition resource for pregnant women. Further, the dynamic and unpredictable nature of third party apps, in terms of release of new versions and revision of content, ensures that recommending specific apps is not possible as the evaluation of a particular app is only valid for the version of the app that was reviewed. Although this review provided an overall snapshot of the current iPhone pregnancy app landscape in Australia, more in‐depth analysis of app content is required in order to determine content quality.

5. CONCLUSION

Although there is a large number of pregnancy‐related apps available, few are of high quality. Most contain only a small number of BCTs, and the pregnancy‐specific nutrition information is limited. Given the limitations of the majority of publicly available pregnancy apps, they cannot currently be used as an appropriate tool in regard to supporting behaviour change nor provision of quality nutrition or dietary advice during this key life stage, and hence they cannot be recommended. Health professionals and researchers need to work in collaboration with app developers and pregnant women to codesign high‐quality apps that incorporate positive BCTs and evidence‐based pregnancy nutrition information derived from guidelines recommended by health professional bodies. Regulation of information contained in medical and health‐related apps, along with an increased awareness among both consumers and health professionals of the potential misinformation and harmful content contained within some current pregnancy apps is also needed.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

CONTRIBUTIONS

MER and HMB were responsible for the conception and design of the study. HMB assessed the apps, acquired the data, and completed data analysis and synthesis. HMB drafted the manuscript, which was critically reviewed by MER, TB, and CEC. All authors read and approved the final manuscript.

ACKNOWLEDGMENTS

Only the authors listed were involved in the preparation of this manuscript. No funding was received to carry out this research project. CC is supported by a NHMRC Senior Research Fellowship and Faculty of Health and Medicine Gladys M Brawn Senior Research Fellowship. HMB is supported by a Post‐Graduate Research Scholarship from the University of Newcastle and the Neville Eric Sansom Scholarship.

Brown HM, Bucher T, Collins CE, Rollo ME. A review of pregnancy iPhone apps assessing their quality, inclusion of behaviour change techniques, and nutrition information. Matern Child Nutr. 2019;15:e12768 10.1111/mcn.12768

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