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Digital health resources have the potential to assist women in optimizing gestational weight gain (GWG) during pregnancy to improve maternal health outcomes.
In this study, we aimed to evaluate the quality and behavior change potential of publicly available digital tools (websites and apps) that facilitate GWG tracking.
Digital tools were identified using key search terms across website search engines and app stores and evaluated using the Mobile App Rating Scale, the App Behavior Change Scale, as well as criteria to evaluate the rigor and safety of GWG information.
Overall, 1085 tools were screened for inclusion (162 websites and 923 apps), and 19 were deemed eligible. The mean Mobile App Rating Scale quality score was 3.31 (SD 0.53) out of 5, ranging from 2.26 to 4.39, and the mean App Behavior Change Scale score was 6 (SD 3.4) out of 21, ranging from 19 to 0. Of the 19 items used to evaluate rigor of GWG advice, most tools (n=11, 57.9%) contained ≤3 items.
This review emphasizes the substantial limitations in current digital resources promoting the monitoring and optimization of GWG. Most tools were of low quality, had minimal behavior change potential, and were potentially unsafe, with minimal linkage to evidence-based information or partnership with health care.
During pregnancy, gestational weight gain (GWG) is essential to ensure the development of a healthy fetus [
Digital health, including internet-based information and mobile Health (mHealth) apps, have become popular and widely used sources of health information for pregnant women, often replacing traditional paper-based and supplementing face-to-face health professional consultations [
During pregnancy, freely accessible web-based resources, including trackers, calculators, or graphs, to record and self-monitor GWG have the potential to assist women in identifying whether weight gain is outside the recommended thresholds. In conjunction with the promotion of healthy lifestyle behaviors, these web-based resources have the potential to assist women in achieving healthy GWG [
In this study, we aimed to evaluate the quality and behavior change potential of publicly available digital tools (websites and apps) that facilitate GWG tracking. Given the benefits of self-weighing for weight management [
The methods of this study have been informed by previous reviews exploring the quality, features, functions, behavior change capacity, and quality of digital applications and resources [
Searches were conducted in an Australian web browser using website search engines (Google, BING, and Yahoo) and mobile app stores (Apple AppStore, iOS and Google Play, Android) using a combination of search terms emulating terms likely used by end users, including
Websites and apps were included according to the following criteria: publicly available or ability to download (free or paid, but with free discovery capacity); written in or available in English; title or description suggested inclusion of tools or advice or resources relating to pregnancy weight gain; and weight-tracking tool enabled multiple logs or entries of weight across pregnancy (ie, not just 1 static weight log).
Apps that met the inclusion criteria were further filtered using the following app-specific inclusion criteria: updated within 18 months from the search date, May 2021; user rating of ≥4.0 stars if ≥6 months old (apps <6 months were included irrespective of user rating) as a proxy for app popularity per previous research [
Eligible websites and apps were randomly allocated to 2 reviewers and independently reviewed on a mobile device. All reviewers (AC, BRB, MJH, QVH, RMG, and SJdJ) have expertise in public health and form a multidisciplinary team (ie, O&G, midwifery, nursing, dietetics and nutrition, and exercise physiology). Where the same app was available on both Google Play Store and Apple App Store, app details and descriptions were reviewed to ensure consistency across the 2 platforms and downloaded for review on an Apple device. The reviews were conducted from June to July 2021. Apps were user tested for evaluation using numerous validated scales and relevant questions (
Collections of user demographic and pregnancy-specific data were recorded, including username; contact details (name, email, phone, or other); date of birth or age; country of origin; gestation (due date, last menstrual cycle, or date of conception); type of pregnancy (singleton, twin, triplet, etc); parity (first, second, third, etc); and preconception weight and height.
To evaluate the rigor and safety aspects of GWG management information, GWG-specific criteria were developed by a multidisciplinary team (
The Mobile App Rating Scale (MARS) is a 23-item evaluation tool comprising 6 domains (
The MARS also includes an App Classification section to obtain information about technical features (
The App Behavior Change Scale (ABACUS) is designed to evaluate the behavior change potential of smartphone apps and websites across 4 domains (
Criteria to evaluate the quality of the health-related digital tools were developed (
Descriptive statistics (mean and SD) and frequencies (numbers and percentages) were calculated for all scales applied. The reported percentages were rounded to the nearest whole number. Intraclass correlation (ICC) scores were calculated to determine the agreement between the MARS rating using SPSS statistical software (version 25; IBM Corp). All analyses were conducted using SPSS for Windows, with a significance level set at
This study does not meet the criteria for human research and thus did not require oversight from the authors’ institutions.
A total of 1085 digital tools were screened for inclusion across 162 websites and 923 apps. After excluding duplicates, 89 digital tools were retained for potential inclusion with 19 digital tools eligible for analysis (
Flowchart of gestational weight gain (GWG) digital tool selection.
All digital tools were based on information or education (19/19, 100%) and monitoring or tracking (19/19, 100%), and the majority included advice, tips, and strategies (15/19, 79%). A small number of tools used assessment (3/19, 16%), feedback (3/19, 15%), and goal setting (1/19, 5%). Technical aspects included reminders (11/19, 58%), log-in requirements (11/19, 58%), app communities (5/19, 26%), password protection (4/19, 21%), and sharing options (eg, social media, app to app, or email; 3/19, 16%). Only the website required web access to function, with all apps able to be used offline. All collected information about gestation (19/19, 100%) and most, but not all, collected preconception weight (16/19, 84%) and height (14/19, 74%;
Technical aspects and characteristics of digital tools for GWG management.
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Value, n (%) | Appa | Webb | |||||||||||||||||||||||||||||||||||||
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01 | 02 | 03 | 04 | 05 | 06 | 07 | 08 | 09 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 01 | |||||||||||||||||||||
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Advice or tips or strategies or skills training | 14 (74) | ✓c | ✓ |
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✓ | ✓ | ✓ | ✓ | ✓ |
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✓ | ✓ |
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✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
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Assessment | 4 (16) |
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✓ |
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✓ |
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✓ | |||||||||||||||||||
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Feedback | 4 (16) |
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✓ |
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✓ |
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✓ | |||||||||||||||||||
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Goal setting | 1 (5) |
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✓ |
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Information or education | 18 (95) | ✓ | ✓ | ✓ |
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✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
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Monitoring or tracking | 19 (100) | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
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Allows sharing (social media, app to app, or email) | 4 (21) |
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✓ |
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✓ |
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✓ |
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✓ | |||||||||||||||||||
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App community | 5 (26) |
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✓ | ✓ | ✓ |
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✓ |
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✓ |
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Needs web access to function | 1 (5) |
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✓ | |||||||||||||||||||
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Password protected | 3 (16) |
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✓ | ✓ |
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✓ |
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Requires log-in | 10 (53) |
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✓ | ✓ |
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✓ | ✓ |
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✓ | ✓ |
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✓ | ✓ | ✓ | ✓ |
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Sends reminders | 11 (58) |
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✓ | ✓ | ✓ | ✓ | ✓ |
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✓ | ✓ | ✓ |
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✓ |
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✓ |
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✓ |
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Contact details | 9 (47) |
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✓ |
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✓ | ✓ | ✓ |
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✓ |
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✓ | ✓ |
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✓ |
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✓ |
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Country or location | 4 (21) |
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✓ | ✓ |
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✓ |
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✓ |
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Date of birth or age | 6 (32) |
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✓ |
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✓ | ✓ |
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✓ |
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✓ |
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✓ |
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Name | 11 (58) | ✓ | ✓ |
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✓ | ✓ | ✓ |
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✓ |
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✓ |
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✓ | ✓ | ✓ | ✓ |
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Gestation | 19 (100) | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
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Height | 14 (74) | ✓ |
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✓ |
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✓ | ✓ |
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✓ | ✓ | ✓ | ✓ |
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✓ |
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✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
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Pregnancy number (ie, first or second etc) | 4 (21) |
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✓ |
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✓ | ✓ |
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✓ |
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Pregnancy type (single or twins etc) | 3 (16) |
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✓ | ✓ |
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✓ | |||||||||||||||||||
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Preconception weight | 15 (79) | ✓ | ✓ | ✓ |
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✓ | ✓ |
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✓ | ✓ | ✓ | ✓ |
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✓ |
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✓ | ✓ | ✓ | ✓ | ✓ |
aApp: apps included in ths study.
bWeb: website included in this study.
c✓: indicates technical aspects or characteristics present in the digital tool.
Gestational weight tracking was a major feature of most digital tools, displayed prominently to users (15/19, 79%), in line with our inclusion criteria (
The specific MARS scores for each digital tool are presented in
Mobile App Rating Scale (MARS) scoring.
App or website name | Overall MARS quality score (A-D), mean (SD) | A (engagement), mean (SD) | B (functionality), mean (SD) | C (aesthetics), mean (SD) | D (information), mean (SD) | E (subjective), mean (SD) | F (app specific), mean (SD) | ICCa (95% CI) |
App06 | 4.39 (0.54) | 4.50 (0.71) | 4.50 (0.71) | 4.50 (0.24) | 4.07 (0.51) | 15.50 (0.71) | 2.70 (2.40) | 0.935 (0.615 to 0.991) |
App12 | 4.07 (0.15) | 3.80 (0.57) | 4.75 (0.35) | 5.00 (0.00) | 2.72 (0.40) | 13.00 (0.00) | 2.30 (0.42) | 0.973 (0.824 to 0.996) |
Web01 | 4.00 (0.18) | 3.20 (0.28) | 5.00 (0.00) | 4.00 (0.47) | 3.79 (0.91) | 12.50 (3.54) | 4.50 (0.14) | 0.836 (0.222 to 0.975) |
App08 | 3.60 (0.04) | 4.10 (0.14) | 4.00 (0.00) | 4.00 (0.00) | 2.29 (0.00) | 3.25 (0.00) | 2.60 (0.57) | 0.996 (0.976 to 0.999) |
App02 | 3.56 (0.11) | 3.30 (0.42) | 4.13 (0.88) | 4.34 (0.47) | 2.50 (0.51) | 8.00 (1.41) | 2.00 (0.57) | 0.858 (0.349 to 0.981) |
App01 | 3.54 (0.01) | 3.10 (0.14) | 4.25 (0.00) | 4.00 (0.00) | 2.79 (0.10) | 8.50 (0.71) | 2.50 (0.42) | 0.972 (0.817 to 0.996) |
App14 | 3.51 (0.24) | 3.50 (0.14) | 3.50 (0.35) | 4.34 (0.94) | 2.72 (0.21) | 10.00 (2.83) | 2.30 (0.99) | 0.856 (0.285 to 0.978) |
App05 | 3.41 (0.06) | 3.70 (0.14) | 3.88 (0.18) | 3.33 (0.00) | 2.72 (0.21) | 11.50 (0.71) | 3.20 (0.28) | 0.972 (0.999 to 0.817) |
App03 | 3.39 (0.27) | 3.10 (0.42) | 4.25 (0.35) | 4.00 (0.00) | 2.22 (0.30) | 7.50 (2.12) | 1.70 (0.42) | 0.873 (0.349 to 0.981) |
App17 | 3.38 (0.06) | 3.60 (0.00) | 4.00 (0.00) | 3.50 (0.24) | 2.43 (0.00) | 12.50 (0.71) | 3.50 (0.14) | 0.995 (0.962 to 0.999) |
App09 | 3.34 (0.08) | 3.20 (0.57) | 3.63 (0.53) | 3.33 (0.00) | 3.22 (0.30) | 9.50 (0.71) | 2.60 (0.57) | 0.957 (0.729 to 0.994) |
App15 | 3.25 (0.10) | 3.50 (0.71) | 3.50 (0.00) | 3.50 (0.24) | 2.50 (0.10) | 10.00 (1.41) | 1.60 (0.28) | 0.950 (0.693 to 0.993) |
App07 | 3.14 (0.41) | 3.20 (0.28) | 3.88 (0.18) | 3.50 (1.17) | 2.00 (0.00) | 7.00 (1.41) | 1.60 (0.57) | 0.859 (0.296 to 0.979) |
App11 | 2.96 (0.69) | 2.90 (0.71) | 3.50 (0.71) | 3.00 (0.95) | 2.43 (0.40) | 5.50 (2.12) | 1.70 (0.14) | 0.711 (−0.095 to 0.954) |
App10 | 2.85 (0.62) | 2.10 (0.14) | 4.38 (0.88) | 3.33 91.41) | 1.57 (0.00) | 6.00 (2.83) | 1.30 (0.42) | 0.713 (−0.090 to 0.954) |
App13 | 2.84 (0.01) | 2.60 (0.57) | 3.88 (0.18) | 3.00 (0.00) | 1.86 (0.40) | 7.00 (0.00) | 1.90 (0.14) | 0.972 (0.815 to 0.996) |
App16 | 2.75 (0.02) | 2.80 (0.00) | 3.13 (0.18) | 2.84 (0.23) | 2.22 (0.50) | 5.50 (0.71) | 1.50 (0.71) | 0.864 (0.315 to 0.980) |
App18 | 2.60 (0.83) | 2.50 (0.99) | 3.63 (0.53) | 2.50 (0.71) | 1.79 (1.11) | 6.50 (3.54) | 2.00 (1.13) | 0.671 (−0.169 to 0.946) |
App04 | 2.26 (0.26) | 2.00 (0.57) | 3.13 (0.18) | 2.50 (0.24) | 1.43 (0.40) | 4.00 (0.00) | 1.00 (0.00) | 0.938 (0.627 to 0.991) |
aICC: intraclass correlation; agreement between reviewers (A-F).
The overall ABACUS score was 6 (SD 3.6) of 21 (
Performance on App Behavior Change Scale (ABACUS) criteria (most to least frequently used).
Behavior change techniquea | Value, n (%) |
Customize and personalize some features | 19 (100) |
Baseline information | 16 (84) |
Allow the user to easily self-monitor behavior | 13 (68) |
Provide instruction on how to perform the behavior | 10 (53) |
Reminders or prompts or cues for activity (on app) | 8 (42) |
Data export | 7 (37) |
Information provided about the consequences of continuing or discontinuing behavior | 7 (37) |
Give user feedback (person or automatic) | 5 (26) |
Allow or encourage practice or rehearsal in addition to daily activities | 4 (21) |
Created with expertise or information consistent with national guidelines | 4 (21) |
Restructure the physical or social environment | 4 (21) |
Encourage positive habit formation | 3 (16) |
Provide the opportunity to plan for barriers | 3 (16) |
Share behaviors with others or allow for social comparison | 3 (16) |
Understand the difference between current action and future goals | 3 (16) |
Distraction or avoidance | 2 (11) |
Review goals, update, and change | 2 (11) |
Goal setting | 1 (5) |
Provide general encouragement | 0 (0) |
Material or social reward or incentive | 0 (0) |
Willingness for behavior change | 0 (0) |
aApp Behavior Change Scale average score: mean 6 (SD 4) out of 21.
Most (16/19, 84%) digital tools had a statement of purpose and all, with the exception of one (18/19, 95%), provided developer or author contact details. Ownership disclosure and copyright statements (14/19, 78%), advertisement disclosure (13/19, 68%), and author or developer disclosure (12/19, 63%) were present in most of the digital tools. No tool provided information to ascertain the independence of sponsors or funders (0/19, 0%); 5% (1/19) provided a sponsorship disclosure and 11% (2/19) outlined author or developer credentials, which included academics and O&G. Overall, 21% (4/19) of digital tools contained references (
Women are increasingly engaging with digital resources for health guidance, including healthy lifestyles and weight gain during pregnancy. A systematic search approach identified current and publicly available websites and mobile apps that contain tools and resources to monitor GWG. Those included were reviewed based on their quality, features and functions; behavior change potential; the credibility, quality, and safety of the health-related information provided; and their ability to highlight the importance of optimizing GWG. Across 19 eligible digital tools, we found that the majority reported features including pregnancy-related education, advice, monitoring, and tracking of GWG. Despite this, the quality of information related to GWG was poor, and limited ability to guide behavior change for optimized GWG was found. Advice related to achieving healthy GWG was present in ≤50% of the apps. Overall, this advice was nonspecific in nature and unlikely to be associated with evidence-based information. We found minimal likelihood of resources to alert, provide support, or direct women into partnerships with their health care provider if GWG was outside the recommended thresholds. These results emphasize a missed opportunity in information provision and support to safely optimize health behaviors and GWG for women. There is a critical need to improve the quality and regulation of publicly accessible web-based resources informed by health care, policy, and consumer needs during pregnancy.
Pregnancy presents a unique opportunity in which women are motivated to optimize lifestyle behaviors to ensure favorable health outcomes for themselves and their baby [
In the absence of availability of a framework to evaluate safety features within web-based resources, we built on our previous research [
Using the validated ABACUS framework, we evaluated the capacity of the included apps to guide and support behavior change [
Altogether, our results highlight several areas of concern, culminating in a missed opportunity to support and guide women during this formative life phase of increased health care needs. First, despite increasing awareness, there is little regulatory control currently in place for digital health resources that are publicly available, which is an area warranting improvement. A recent Australian review highlighted the complexities between developer and consumer considerations and the involvement of multiple, siloed sectors, traversing medical, privacy, advertising, finance, and digital content as barriers to improving regulations to ensure consumer safety [
This study had several strengths and limitations. To ensure that we captured the available digital health resources for GWG, we used a robust search strategy across both websites and mHealth apps with minimal exclusion criteria, reflective of our search results. By reviewing current digital tools using the validated MARS and ABACUS tools, questions specific to GWG as well as evaluation of credibility of health-related information, we were able to evaluate technical features and quality as well as the behavior change potential and health information. We applied safety criteria specific to GWG management based on our previous publications [
This review emphasizes the substantial limitations in publicly available consumer-facing digital resources for monitoring and optimizing GWG. Most tools reviewed were of low quality overall, had minimal ability to support behavior change, and were potentially unsafe, with minimal linkage to evidence-based information or partnership with health care. When women require increased support for health optimization, these results emphasize the minimal likelihood of currently available resources to positively influence GWG or, ultimately, health outcomes during this time. Owing to the extensive use of publicly available digital tools, these findings underscore the critical need for better linkage among health, research, and commercial sectors to design apps that are high quality across visual appeal, functionality, credibility, safety, and effectiveness in lifestyle modification and self-management of GWG.
Gestational weight gain criteria.
Mobile App Rating Scale.
App Behavior Change Scale.
Quality evaluation criteria.
Description of digital tools for gestational weight gain management (results table).
Performance on gestational weight gain (GWG) quality questions (inclusion of GWG-specific tools or features; results figure).
Performance on quality evaluation (results table).
App Behavior Change Scale
gestational weight gain
intraclass correlation
Mobile App Rating Scale
obstetrics and gynecology
The authors have received no specific funding for this study. Other funding support is as follows. BRB is supported by a Monash Graduate Scholarship and received funding support from Medibank. CLH is supported by a National Health and Medical Research Council Centres of Research Excellence Health in Preconception and Pregnancy Senior Postdoctoral Fellowship (APP1171142). SJdJ is supported by a Metro North Health Clinician Research Fellowship. HJT is supported by a Medical Research Future Fund and National Health and Medical Research Council Fellowship.
BRB, CLH, JAB, and RMG conceptualized and refined the research idea. CLH and HJT were responsible for funding to support the work. BRB, CLH, MJH, JAB, and RMG designed the study. BRB, CLH, and RMG conducted the literature search and screening of tools. BRB, MJH, SJdJ, AC, QVH, RMG, and CLH conducted data extraction and preparation; BRB synthesized data and conducted statistical analyses. All authors assisted in the interpretation of the analyses, had intellectual input into manuscript and reviewed and approved the manuscript. BRB prepared the manuscript. CLH and RMG supervised this work and CLH has overall responsibility for the work and is the corresponding author.
None declared.