Table 3.

Characteristics and outcomes of studies evaluating efficacy of app-based intervention for supporting healthy food purchasing and consumption.

First Author (Year), Country	Study Name/Apps Name	Device	Study Design	Sample Characteristics, Mean Age	Female (%)	Grouping	Intervention Time Frame	Outcomes and Measures	Findings	Quality
Allen (2013), USA [24]	SLIM (Smart coach for LIfestyleManagement) study	smartphone	RCT	68 obese adults	78%	(1) intensive counseling intervention, (2) intensive counseling + smartphone intervention, (3) a less intensive counseling + smartphone intervention, and (4) smartphone intervention only	baseline and 6-month	self-reported dietary intake	Not significant.	Poor
Alnasser (2019), Saudi Arabia [60]	Twazon app.	smartphone	pre-post single-arm pilot study	40 overweight adult; engaged: n = 26, age = 31 years, Unengaged: n = 14, age = 31 years	100%	engaged users (65%) and unengaged users (35%)	baseline, 2- and 4-months	Dietary intake	The daily energy consumption was decreased by >600 calories in the engaged users group compare with the unengaged group.	Poor
Atienza (2008), USA [52]	NR	PDA	RCT	27 healthy mid-life and older adults (≥50 years); AG: n = 16, age = 63 years; CG: n = 11, age = 58 years	AG: 69% CG: 70%	PDA program vs. control	baseline and 8 weeks	vegetable and whole-grain intake	Intervention participants reported significantly greater increases in vegetable servings and dietary fibre from grains.	Poor
Banerjee (2020), India [59]	S Health®, Calorie Counter—MyFitnessPal®, and Calorie Counter	smartphone	prospective controlled trial	58 healthy young adults (18–45 years); AP: n = 30; CG: n = 28	AG: 63%; CG: 46%	apps group vs. control	baseline and 8 weeks	Food consumption	Not significant.	Poor
Brindal (2019), Australia [57]	MotiMate	smartphone	RCT	88 healthly adults; AG: n = 45, age = 45 years; CG: n = 43, age = 46 years	AG:75%; CG: 69%	intervention app (MotiMate) vs. control app	baseline, 4, 8, 12 and 24 weeks	healthy eating	Not significant.	Poor
Dodd (2017), Australia [56]	SNAPP trial	smartphone	RCT	162 healthy pregnant women; AG: n = 77, age = 31 years; CG: n = 85, age = 31 years	100%	Lifestyle Advice + Smartphone App vs. Lifestyle Advice Only	baseline, 28 and 36 weeks	healthy eating index (HEI)	Not significant.	Good
Eyles (2017), New Zealand [29]	SaltSwitch	smartphone	RCT	66 adults with diagnosed cardiovascular disease; AG: n = 33, age = 64 years; CG: n = 33, age = 65 years	AG:9%; CG: 24%	SaltSwitch app vs. control group (usual care).	baseline and 4 weeks	(1) salt content of household packaged food purchases (2) saturated fat content (g/MJ), energy content (kJ/kg) and expenditure (NZ$) of household food purchases	A significant reduction in mean household purchases of salt was observed. Not significant for the second outcome.	Good
Gill (2019), Canada [58]	HealtheSteps™	smartphone	RCT	118 adults at risk or diagnosed with a chronic disease; AG: n= 59, age = 57 years; CG: n = 59, age = 59 years	AG:76%; CG: 81%	HealtheSteps™ smartphone app and Healthe-Steps™ website vs. wait-list control	baseline and 18 months.	self-reported eating habits	Improved their overall healthful eating	Good
Glanz (2006), USA [25]	NR	PDA	Intervention pilot test	33 healthy women, 64 years	100%	PDA diet-monitoring system	baseline and 1 month	food choice and dietary intakes	Reported total fat intake and percent energy from fat decreased significantly.	Poor
Huberty (2019). USA [55]	Calm	smartphone	RCT	88 healthy adult; AG: n = 41, age = 20 years; CG: n = 47, age = 22 years	AG:41%; CG: 49%	Calm app vs. wait-list control	baseline, 8 and 12 weeks	alcohol consumption and healthy eating (fruit and vegetable consumption)	Not significant.	Poor
Inauen (2017), USA [30]	NR	smartphone	RCT	140 healthy adult; AG: n = 70, age 27.5 years; CG: n = 70. Age = 27.5 years	75.5%	Whatsapp support group (1. eating more fruit and vegetables 2. eating fewer unhealthy snacks) vs. control	baseline, 1- and 2-months	Self-reported healthy eating (fruits, vegetables and unhealthy snacks)	Intervention group showed a gradual increase in healthy eating over time, ate more fruits and vegetables, and less unhealthy snacks compare to the control group on Day 10. However, it is not significant at the follow ups.	Poor
Jarvela (2018), Finland [31]	NR	smartphone	RCT	219 healthy adult; face to face group: n = 70, age = 50 years; AG: n = 78, age = 49; CG: n = 71, age = 49 years	(1) Face-to-face: 87% (2) AG: 85% 3) CG: 82%	(1) Face-to-face (2) mobile app (3) control	baseline, 10 and 36 weeks	eating behaviour	App group showed beneficial effects on reported eating behaviour.	Poor
Lee (2019), Korea [33]	NR	smartphone	RCT pilot test	65 adult who diagnosis of colorectal polyps; AG: n = 32, age = 49 years; CG: n = 33, age 21 years	AG:34%; CG: 46%	intervention app vs. control (traditional mail)	baseline and 3 month	changes in dietary intake, such as that of vegetables, fruits, and fatty food.	Not significant.	Poor
McCarroll (2015), USA [53]	LoseIt!	smartphone	Prospective intervention	50 adult women cancer survivors, age = 58 years	100%	web- or mobile-based apps	baseline and 4 weeks	macronutrient (carbohydrate, fat and protein) and fibre consumption	Not significant.	Poor
Palacios (2018), USA [54]	MyNutriCart	smartphone	pilot randomised trial	51 overweight and obese adult; AG: n = 24, age = 34 years; TG: n = 27, age = 37 years	AG:92%; TG: 89%	intervention app vs. face-to-face counseling session	baseline and 8 weeks.	healthy food choice and dietary behaviour	“MyNutriCart” app use led to significant improvements in food-related behaviours compared to baseline, with no significant differences when compared to the traditional group.	Poor
Park (2016), Korea [28]	Strong bone, Fit body (SbFb)	smartphone	RCT	82 young adult women with low bone mass; AG: n = 28, age = 24 years; Group education: n = 32, age = 25 years; CG: n = 22, age = 23 years	100%	(1) apps (2) group education (3) control	baseline and 20 weeks	nutrient intake	calcium intake is higher in app and group education than control group.	Poor
Recio-Rodriguez (2018), Spain [19]	EVIDENT II study	smartphone	RCT	833 healthy adult; AG: n = 415, age = 51 years; CG: n = 418, age = 52 years	AG:60%; CG: 64%	intervention: counseling + application group; control: counseling group	baseline and 12-month	Macro and Micronutrients intake	The app group reported a higher percentage intake of carbohydrates, and lower percentage intakes of fats and saturated fats	Good
Rodgers (2015), France [27]	NR	smartphone	Intervention only	40 healthy female adults, age = 19 years	100%	intervention: app (food journal + messages)	baseline and 3 weeks	fruit, vegetable, and sugar-sweetened beverage consumption.	Among participants with body mass index (BMI) ≥25, fruit and vegetable consumption increased with time. Among participants with BMI <21, consumption of fruit decreased, whereas the consumption of vegetables remained stable. No effects were found for sugar-sweetened beverage consumption.	Poor
Sarcona (2017), USA [32]	NR	smartphone	cross-sectional study	401 university students	73%	Users and Nonusers of Mobile Health Apps	NA	healthy eating behaviour	App users were found to have more positive eating behaviours than nonusers, and the impact of using more than one type of mobile-based health app significantly improved eating behaviour.	Poor
Turner (2013), USA [26]	Fat Secret’s Calorie Counter, My Fitness Pal, and Lose it	smartphone	RCT	78 overweight and obese adult; AG: n = 37, age = 41 years; website: n = 24, age = 45 years; paper journal: n = 17, age = 47 years;	AG: 70%; website: 87%; paper journal: 76%;	(1) mobile app, (2) website, and (3) paper journal	baseline and 6 months	dietary intake (energy intake, fat, added sugar, fruit, vegetables) and eating behaviour	App users consumed less energy than paper journal users. No significant difference on the dietary intake and eating behaviour.	Poor

PDA: Hand-Held Computer (personal digital assistant); RCT: randomised controlled trial; AG: App group; CG: control group; TG: traditional group.