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In recent years, the use of mobile phone weight-management apps has increased significantly. Weight-management apps have been found effective in promoting health and managing weight. However, data on user perception and on barriers to app usage are scarce.
This study aimed to investigate the use of weight-management apps and barriers to use as well as reasons for discontinuing use in a sample of mobile phone users in Saudi Arabia.
Mobile phone users aged 18 years and above from the general public in Saudi Arabia completed a Web-based survey. The survey included questions on weight-management app usage patterns, user perceptions concerning weight management, efficacy of weight-management apps, and reasons for discontinuing use. Participants were classified into normal weight (body mass index [BMI]: 18.5 to 24.9 kg/m2) and overweight or obese (BMI: ≥25.0 kg/m2).
The survey included 1191 participants; 513 of them used weight-management apps. More overweight or obese respondents used these apps compared with normal weight respondents (319/513, 62.2% vs 194/513, 37.8%, respectively). App features that overweight or obese users were most interested in were mainly the possibility to be monitored by a specialist and barcode identification of calorie content, whereas normal weight users mostly preferred availability of nutrition information of food items. Reasons for discontinuing use among overweight or obese respondents were mainly that monitoring by a specialist was not offered (80/236, 33.9%) and the app was not in the local language (48/236, 20.3%). Among normal weight users, the main reason for noncontinuance was the app language (45/144, 31.3%) and difficulty of use (30/144, 20.8%).
To better address the needs of both normal weight and overweight or obese adults, improved app designs that offer monitoring by a specialist are needed. Developers may consider ways of overcoming barriers to use, such as language, by developing local language apps, which can improve the efficacy of such apps and help spread their use.
Long-term analyses of trends in body mass index (BMI) levels show that obesity increased globally between 1980 and 2008 [
A recent, encouraging development is the marked increase in the number of mobile phone apps for weight loss or weight management [
With the projected epidemic in increasing obesity, frequent recording of both food intake and physical activity with weight-management apps may be a useful, potentially cost-effective and conveniently available method for modifying health-related behaviors [
Development and use of weight-management apps is still in an early phase, and sample populations in various countries have reported barriers such as limited functionality, lack of input options for tracking data, no evidence-based guidelines, and improper app classification (ie, only one-fifth of the apps classified as
Despite growing research on weight-management apps, evidence on user perspective—especially among users in Saudi Arabia, whose perspective varies vastly from that of the West—has been little explored. To the author’s knowledge, this is the first survey aimed to identify the sociodemographic characteristics of weight-management app users, app usage patterns, user perceptions, efficacy, and reasons for continuing or discontinuing use of a weight-management phone app in Saudi Arabia.
From May to July 2018, mobile phone users aged 18 years and older from the general public in the city of Riyadh filled out an open Web-based survey. The survey was designed using
The survey comprised 28 items in the following domains: (1) sociodemographic characteristics (gender, age, employment, education, and income), (2) general health questions (weight, height, physical activity, smoking habits, and medical history), (3) usage patterns (number of apps used, frequency of use, reasons for use, and desired features), (4) user conceptions and efficacy of weight-management apps (effectiveness of weight-reduction apps, effectiveness of fitness apps, and effectiveness of long-term use), and (5) reasons for discontinuing use (number of apps that the respondent no longer uses and reasons for discontinuing use).
Krebs et al previously used the survey questions in their national survey throughout the United States [
The items were presented in a logical order, and consideration was taken to reduce response set bias. Each question required a response before the respondent was allowed to advance to the next screen. The Web-based survey displayed 1 item per screen, with the first screen asking respondents for their informed consent to participate in the study. Following consent, participants were allowed to begin the survey. Participation was completely voluntary. A
Statistical analyses were conducted using JMP (version 12; SAS Institute). No statistical correction procedures or weightings were applied. Categorical variables are presented as percentages, whereas continuous variables are presented as means and SDs. Participants were stratified by gender and by BMI, where participants were considered of normal weight if their BMI was 18.5 to 24.9 kg/m2 and overweight or obese if their BMI was ≥25 kg/m2.
Sample size was calculated based on the current population of Riyadh—the capital of Saudi Arabia has 5.5 million adults aged above 18 years [
Of the respondents, 43.07% (513/1191) reported that they had previously used an app to manage their weight; only analyses for weight-management app users are presented (
Most weight-management app users used 1 to 5 apps (476/513, 92.8%;
The app features that overweight or obese users were most interested in were (1) the possibility to be monitored by a specialist (126/319, 39.5%), (2) barcode identification of calorie content (77/319, 24.1%), (3) availability of nutrition information on numerous food items (56/319, 17.6%), (4) a weekly or monthly progress report (44/319, 13.8%), and (5) constant reminders to follow a chosen diet or exercise (16/319, 5.0%). For normal-weight users, the desired features were (1) availability of nutrition information on numerous food items (67/194, 34.5%), (2) barcode identification of calorie content (54/194, 27.8%), (3) the possibility to be monitored by a specialist (31/194, 16.0%), (4) a weekly or monthly progress report (26/194, 13.4%), and (5) constant reminders to follow a chosen diet or exercise (16/194, 8.3%;
Most weight-management app users agreed or strongly agreed that apps were helpful in losing weight (
Concerning efficacy, overweight or obese users were unsure whether weight-management apps would be effective in the long term (170/319, 53.3%), whereas normal-weight users agreed or strongly agreed that they were effective (102/194, 52.6%;
Most users (380/513, 74.1%) reported that they have downloaded weight-management apps they no longer use, and the majority of these were overweight or obese (236/380, 62.1%;
Sociodemographic characteristics and health status of participants stratified by body mass index.
Characteristics | Body mass index | Total | ||
18.5 to 24.9 kg/m2 | >25 kg/m2 | |||
No | 283 (59.33) | 395 (55.32) | 678 (56.93) | |
Yes | 194 (40.67) | 319 (44.68) | 513 (43.07) | |
Female | 127 (65.46) | 178 (55.80) | 305 (59.45) | |
Male | 67 (34.54) | 141(44.20) | 208 (40.55) | |
Non-Saudi | 8 (4.12) | 18 (5.64) | 26 (5.07) | |
Saudi | 186 (95.88) | 301 (94.36) | 487 (94.93) | |
Age (years), mean (SD) | 24.4 (6.9) | 27.7 (8.3) | — | |
In school | 122 (62.89) | 161 (50.47) | 283 (55.17) | |
Not working or retired | 7 (3.61) | 20 (6.27) | 27 (5.26) | |
Working full-time | 65 (33.51) | 138 (43.26) | 203 (39.57) | |
High school degree | 42 (21.65) | 45 (14.11) | 87 (16.96) | |
Bachelor’s degree | 122 (62.89) | 189 (59.25) | 311 (60.62) | |
Graduate degree (Masters, PhD, or MD) | 30 (15.46) | 85 (26.65) | 115 (22.42) | |
Less than 5,000 SR/month | 7 (3.61) | 20 (6.27) | 27 (5.26) | |
5,100 to 10,000 SR/month | 55 (28.35) | 93 (29.15) | 148 (28.85) | |
10,100 to 20,000 SR/month | 76 (39.18) | 105 (32.92) | 181 (35.28) | |
>20,000 SR/month | 56 (28.87) | 101 (31.66) | 157 (30.60) | |
Poor | 2 (1.03) | 14 (4.39) | 16 (3.12) | |
Average | 32 (16.49) | 66 (20.69) | 98 (19.10) | |
Good | 22 (11.34) | 43 (13.48) | 65 (12.67) | |
Very good | 80 (41.24) | 112 (35.11) | 192 (37.43) | |
Excellent | 58 (29.90) | 84 (26.33) | 142 (27.68) | |
Never | 55 (28.35) | 119 (37.30) | 174 (33.92) | |
1 day | 28 (14.43) | 23 (7.21) | 51 (9.94) | |
2 days | 39 (20.10) | 49 (15.36) | 88 (17.15) | |
3-4 days | 39 (20.10) | 66 (20.69) | 105 (20.47) | |
5-7 days | 33 (17.01) | 62 (19.44) | 95 (18.52) | |
Poor | 22 (11.34) | 80 (25.08) | 102 (19.88) | |
Fair | 39 (20.10) | 77 (24.14) | 116 (22.61) | |
Good | 62 (31.96) | 111 (34.80) | 173 (33.72) | |
Very good | 59 (30.41) | 45 (14.11) | 104 (20.27) | |
Excellent | 12 (6.19) | 6 (1.88) | 18 (3.51) | |
Yes | 23 (11.86) | 53 (16.61) | 76 (14.81) | |
No | 171 (88.14) | 266 (83.39) | 437 (85.19) | |
None | 135 (69.59) | 212 (66.46) | 347 (67.64) | |
Hypercholesterolemia | 9 (4.64) | 8 (2.51) | 17 (3.31) | |
Hypertension | 9 (4.64) | 9 (2.82) | 18 (3.51) | |
Depression | 8 (4.12) | 46 (14.42) | 54 (10.53) | |
Diabetes | 21 (10.82) | 21 (6.58) | 42 (8.19) | |
Other chronic disease | 12 (6.19) | 23 (7.21) | 35 (6.82) |
Pattern of use of weight-management apps stratified by body mass index.
Pattern of use | Body mass index | Total | ||
18.5-24.9 kg/m2 | ≥25 kg/m2 | |||
1-5 apps | 174 (89.6) | 302 (94.6) | 476 (92.79) | |
6-10 apps | 15 (7.73) | 12 (3.76) | 27 (5.26) | |
>11 apps | 5 (2.58) | 5 (1.57) | 10 (1.95) | |
2 or more times a day | 29 (14.95) | 40 (12.54) | 69 (13.45) | |
About 1 time each day | 17 (8.76) | 32 (10.03) | 49 (9.55) | |
A few times each week | 43 (22.16) | 70 (21.94) | 113 (22.03) | |
A few times a month | 43 (22.16) | 60 (18.81) | 103 (20.08) | |
Less than once a month | 62 (31.96) | 117 (36.6) | 179 (34.89) | |
Weight loss | 26 (13.40) | 134 (42.0) | 160 (31.19) | |
Monitor food intake | 82 (42.27) | 88 (27.59) | 170 (33.14) | |
Track how much activity or exercise I get | 52 (26.80) | 47 (14.73) | 99 (19.30) | |
Show or teach me exercises | 19 (9.79) | 24 (7.52) | 43 (8.38) | |
I want to kill time when bored | 7 (3.61) | 12 (3.76) | 19 (3.70) | |
Other reasons | 8 (4.12) | 14 (4.39) | 22 (4.29) | |
Best ranked in the app store | 53 (27.32) | 101 (31.6) | 154 (30.02) | |
Recommendations from friends or family | 66 (34.02) | 88 (27.59) | 154 (30.02) | |
Social media influencers | 32 (16.49) | 61 (19.12) | 93 (18.13) | |
Web searches (eg, Google) | 15 (7.73) | 45 (14.11) | 60 (11.70) | |
Recommended by other apps | 26 (13.40) | 18 (5.64) | 44 (8.58) | |
TV | 2 (1.03) | 6 (1.88) | 8 (1.56) | |
Monitored by a specialist | 31 (15.98) | 126 (39.5) | 157 (30.60) | |
Can identify calories using barcode | 54 (27.84) | 77 (24.14) | 131 (25.54) | |
Nutrition information of many food items | 67 (34.54) | 56 (17.55) | 123 (23.98) | |
Provides a weekly or monthly progress report | 26 (13.40) | 44 (13.79) | 70 (13.65) | |
Reminders to follow a diet or exercise | 16 (8.25) | 16 (5.02) | 32 (6.24) |
User conceptions and efficacy of weight-management apps stratified by body mass index.
User conceptions | Body mass index | Total | ||
18.5-24.9 kg/m2 | >25 kg/m2 | |||
Strongly disagree | 65 (33.51) | 74 (23.20) | 139 (27.10) | |
Disagree | 11 (5.67) | 19(5.96) | 30 (5.85) | |
Unsure | 20 (10.31) | 78 (24.45) | 98 (19.10) | |
Agree | 82 (42.27) | 125 (39.18) | 207 (40.35) | |
Strongly agree | 16 (8.25) | 23 (7.21) | 39 (7.60) | |
Strongly disagree | 51 (26.29) | 71 (22.26) | 122 (23.78) | |
Disagree | 9 (4.64) | 15 (4.70) | 24 (4.68) | |
Unsure | 18 (9.28) | 56 (17.55) | 74 (14.42) | |
Agree | 96 (49.48) | 148 (46.39) | 244 (47.56) | |
Strongly agree | 20 (10.31) | 29 (9.09) | 49 (9.55) | |
Strongly disagree | 50 (25.77) | 52 (16.30) | 102 (19.88) | |
Disagree | 0 (0.00) | 7 (2.19) | 7 (1.36) | |
Unsure | 42 (21.65) | 170 (53.29) | 212 (41.33) | |
Agree | 80 (41.24) | 60 (18.81) | 140 (27.29) | |
Strongly agree | 22 (11.34) | 30 (9.40) | 52 (10.14) |
Reasons for discontinuing use, stratified by body mass index.
Reasons for discontinuing use | Body mass index | Total | |||
18.5-24.9 kg/m2 | >25 kg/m2 | ||||
No | 50 (25.77) | 83 (26.02) | 133 (25.93) | ||
Yes | 144 (74.23) | 236 (73.98) | 380 (74.07) | ||
Monitoring by a specialist was not offered | 21 (14.58) | 80 (33.90) | 101 (26.58) | ||
The app language was not in the local language | 45 (31.25) | 48 (20.34) | 93 (24.47) | ||
There were hidden costs | 21 (14.58) | 37 (15.68) | 58 (15.26) | ||
Loss of interest | 17 (11.81) | 30 (12.71) | 47 (12.37) | ||
The app was confusing to use | 30 (20.83) | 34 (14.41) | 64 (16.84) | ||
I no longer need it, or I met my goals | 10 (6.94) | 7 (2.97) | 17 (4.47) |
The survey found that only 43% of respondents used weight-management apps. Most users were young, educated women with a high income, and were overweight or obese. Overweight or obese users download a weight-management app mostly to lose weight, whereas normal-weight participants, on the contrary, download a weight-management app mainly to monitor food intake and track physical activity. The feature of the weight-management app that overweight or obese users desired most was the possibility to be monitored by a specialist, whereas the least desired feature was the constant reminders to follow a diet or exercise. On the contrary, normal-weight participants mainly desired apps that could provide nutrition information and calorie content of food items through barcode identification.
Among all users of a weight-management app, this study found that one of the main reasons for discontinuing use was that the language of the app was not the local language of the user. Among overweight or obese users, another main reason was lack of monitoring by a specialist, and among normal-weight users, difficulty of use.
In this study, 43% of the study sample currently used weight-management apps. A similar survey by Krebs and Duncan showed health app use among US adults to be about 60% [
Findings regarding the characteristics of weight-management app users in our survey are consistent with the results of a previous large-scale study in the United States [
We found that overweight or obese participants mostly preferred to be monitored by a specialist compared with other features of the app such as constant reminders to follow a diet or exercise. A previous intervention found that, for encouraging healthy behavior, individually tailored feedback and action plans were preferable to general health instructions [
As for efficacy of use, more normal-weight users found that weight-management apps helped them lose weight compared with overweight or obese users. A randomized controlled trial, however, found that apps for weight loss did not affect the weight of overweight primary care patients and were only useful for individuals who were willing to self-monitor their calories [
Participants in our survey also tended to discontinue use of the app for various reasons such as monitoring by a specialist was not offered and app was not in the local language. Similar barriers were reported in a previous qualitative study on the challenges of app use in supporting health behavior changes, showing that users generally found health apps to be time consuming, have unexpected costs, and lack the possibility of consulting an expert [
The strength of this study is that it is the first of its kind to target app users in Saudi Arabia. Additionally, it provides information on the demographics of this particular region along with insight into the extent of weight-management app use and barriers of use, which varies from barriers in other regions. This study also highlighted that weight-management apps are not only used by overweight or obese adults but also by normal-weight adults who wish to maintain their weight. Data on the differences in perception of use between overweight and normal-weight adults are also provided.
Although this is the first study to characterize user perspective on weight-management apps in Riyadh, Saudi Arabia, there were a few limitations. The main limitation was study design; a causal relationship cannot be inferred, and usage patterns may change over time. Second, the study sample included the city of Riyadh only and was not representative of the general population. A third limitation was the self-recorded weight and height of participants, which is a possible source of error. Finally, as this was a convenience sample, it did not include individuals who are overweight or obese but do not own mobile phones, although a large percentage of the population use mobile phones.
Although the majority of users believe that weight-management apps are efficacious, considerable challenges remain. Given the increasing prevalence of overweight and obesity in Saudi Arabia and the high accessibility to mobile phones among adults, app developers should address findings of this study, especially regarding reasons for use and discontinuance. More specifically, app developers should consider the aforementioned barriers by developing apps in local languages and by developing apps which are linked to health professionals to provide individualized plans to manage the weight of both normal and overweight adults.
Sociodemographic characteristics and health status of participants stratified by gender.
Pattern of use of weight-management apps stratified by gender.
User conceptions and efficacy of weight-management apps stratified by gender.
Reasons for discontinuing use stratified by gender.
body mass index
This research project was supported by a grant from the Research Center of the Female Scientific and Medical Colleges, Deanship of Scientific Research, King Saud University.
None declared.