Table 2.
Descriptions of baseline, interventions, apps, and findings of the included studies.
| First author (year) | Baseline variables | Intervention type | App description | Control group treatment | Difference of the intervention group, mean (SD) | Difference of the control group, mean (SD) | Inference | Recommendation |
| Patel (2019) | Age, gender, marital status, race/ethnicity, education, employment status, annual household income, body mass index category, self-monitoring of diet frequency, and type of smartphone | App, email, MyFitnessPal, mobile, and internet | Weight loss goal, calorie goal, self-monitoring of body weight, dietary intake, rea-time feedback, skill training, and reminder of the goal | Self-regulation, email, and action plans via weekly email | −1.8 (1.53) | −2.55 (1.11) | The mobile app is an effective intervention for clinically meaningful weight loss. | Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach. |
| Farinelli (2016) | Age, gender, weight status, BMI, WHO-5 score, SESa, ethnic background, education, fruit, vegetable, SSBb, take-out meals, and physical activity | Mobile app, email, online weight tracker, physical activity planner, a blog facility for communication, and printable eating chart | Smart mobile apps for education and self-monitoring | Four text messages, one on each key behavior, and a two-page handout based on dietary guidelines. | −3.8 (4.9) | −0.80 (3.7) | The mHealth intervention has the potential to reduce weight and improve physical activity. | Replication of trials and widespread adoption of this model are needed. |
| Partridge (2015) | Age, gender, SES, ethnicity, education level, and weekly income | App, text messages, email, internet forum, a community blog, and usual care. | Educational program and self-monitoring | Mailed two-page handout, four text messages, and access to a website | −1.9 (2.84) | 0.2 (2.99) | The app has huge potential for preventing weight gain with modest weight loss. It also helps to improve lifestyle behaviors. | Implementation of a large-scale study is needed. |
| Laing (2014) | Gender, self-reported race, education, annual income, and type of smartphone | App and usual care plan | MyFitnessPal app | Counseling and one-page educational handout for eating plan | −0.03 (4.64) | 0.27 (4.64) | The app was an effective tool for reducing weight. | NRc |
| Hebden (2014) | Age, gender, SES, education, work history, lives with parents, and English proficiency | App, text messaging, email, internet forum, and usual care | Four types of behavior plans | 10-page printed book | −1.6 (3) | −1.4 (3.18) | The app provided short-term positive changes in weight, nutrition, and physical activity. | More studies are needed to explore engagement and personalized support |
| Smith (2014) | Age, English language, cultural background, socioeconomic position, weight, height, BMI, weight status, and waist circumference | App, parent newsletters, seminars, spot sessions, lunchtime physical activity monitoring, and teaching material | Fitness challenges, activity monitoring, and motivational messages | Traditional approaches | 0.6 (1.21) | 0.61 (1.07) | The app-based intervention helped to improve fitness, movement skill, and key weight-related behavior. | More studies require to capture objective data on app usage throughout the intervention period and find out the association. It is also important to add some features like gamification. |
| Glynn (2014) | Gender, age, systolic and diastolic blood pressure, weight, BMI, HADSd, EQ-VASe, EQ-5Df, and daily step count | App and usual care plan | Accupedo-Pro Pedometer app | Education program about the benefits of physical activity and exercise | −2.2 (3.4) | −1.5 (4.3) | The mobile app–based intervention had a positive impact on weight loss | NR |
| Brindal (2013) | Weight and dietary status | App and celebrity slim program | Support apps like my meals, my weight, and my task | Only celebrity slim program | −2.9 (6.4) | −2.1 (1) | The app intervention was useful for weight loss and psychological changes. | Integrating more dynamic stage-based tailoring, as behavioral changes of individuals may further enhance similar apps in the future. |
| Carter (2013) | Age, weight, BMI, body fat, gender, race, smoking status, occupation, and education | App | Self-monitoring | Food diary and a calorie-counting book | −4.6 (5.2) | −2.9 (5.85) | The mobile app was an acceptable and feasible weight loss intervention | More studies are needed to investigate the cost of implementing a smartphone app intervention compared with other types of interventions |
| Allen (2013) | Age, weight, BMI, waist circumference, education, and marital status | App and intensive counseling | Lose it! | Comprehensive counseling | −5.4 (4) | −2.5 (4.1) | The app intervention had a positive impact on weight loss and contributed to behavioral changes. | Need to conduct a large-scale population-based study. |
| McGrievy (2011) | NR | App + podcast + twitter | Diet plan and physical activity monitoring | Podcast only | −2.57 (2.6) | −2.45 (4.39) | NR | NR |
| Li (2010) | Age, occupation, education, monthly income, smoking, drinking, and exercise history | Mobile app and usual care | Mobile apps that provided a personal diet profile based on gender and promoted knowledge about nutrition and physical activity | NR | −1.9 (2.3) | −0.9 (4.64) | Improved user satisfaction. | A more effective study to motivate participants and extend study duration is required. |
aSES: socioeconomic status.
bSSB: sugar-sweetened beverage.
cNR: not reported.
dHADS: Hospital Anxiety and Depression Scale.
eEQ-VAS: EuroQol visual analogue scale.
fEQ-5D: EuroQol five-dimension scale.