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Health App Use Among US Mobile Phone Owners: A National Survey

DOI:10.2196/mhealth.4924
Authors:
Paul Krebs
Paul Krebs
Dustin T Duncan
Dustin T Duncan
Dustin T Duncan
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Abstract

Background Mobile phone health apps may now seem to be ubiquitous, yet much remains unknown with regard to their usage. Information is limited with regard to important metrics, including the percentage of the population that uses health apps, reasons for adoption/nonadoption, and reasons for noncontinuance of use. Objective The purpose of this study was to examine health app use among mobile phone owners in the United States. Methods We conducted a cross-sectional survey of 1604 mobile phone users throughout the United States. The 36-item survey assessed sociodemographic characteristics, history of and reasons for health app use/nonuse, perceived effectiveness of health apps, reasons for stopping use, and general health status. ResultsA little over half (934/1604, 58.23%) of mobile phone users had downloaded a health-related mobile app. Fitness and nutrition were the most common categories of health apps used, with most respondents using them at least daily. Common reasons for not having downloaded apps were lack of interest, cost, and concern about apps collecting their data. Individuals more likely to use health apps tended to be younger, have higher incomes, be more educated, be Latino/Hispanic, and have a body mass index (BMI) in the obese range (all P
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Table 2. Characteristics of health app use
Item
Response Category
N
%
1.What brand of phone
do you have? (n=1604)
iPhone
565
35.22
Samsung
567
35.35
HTC
96
5.99
Nokia
63
3.93
Blackberry
29
1.81
Other
284
17.71
2. What company provides you cell
phone service? (n=1604)
AT&T
420
26.18
Verizon
342
21.32
T-Mobile
311
19.39
Sprint
177
11.03
Boost
73
4.55
Metro PCS
89
5.55
Other:
192
11.97
3. Have you ever downloaded an
“app” to track anything related to
your health? (n=1604)
No
670
41.77
Yes
934
58.23
4. How many health-related
smartphone apps have you used?
(n=934)
1-5 apps
545
58.4
6-10 apps
104
11.1
11-15 apps
67
7.2
16- 20 apps
93
9.9
21-25 apps
85
9.1
26-30 apps
22
2.4
30+ apps
18
1.9
5. Please check off all the reasons
you have used health apps. (n=934)
Track how much activity/exercise I get
493
52.8
Help me watch what I eat/improve what I eat
445
47.6
Weight loss
437
46.8
Show/teach me exercises
318
34.1
Track a health measure (such as blood
pressure, blood sugar)
266
28.5
Track how much sleep I get
263
28.2
Check my medical records/labs
216
23.1
Help me relax (like a meditation or Yoga
app)
210
22.5
Keep a diary or log of my symptoms
189
20.2
Help me stop a habit (such as smoking)
177
18.9
Chat with my doctor/s or another health
173
18.5
Remind me to take my medication (such
blood pressure, HIV/AIDS)
168
18.0
Access health information on symptoms,
treatments, diagnoses, etc.
165
17.7
I want to kill time when bored
66
7.1
Other Reason
28
3.0
6. Rank the most important reasons
you have not downloaded a health
app (for those who answered No to
Question 3). (n=670)
I’m just not interested in health apps
181
27.0
They cost too much to buy
156
23.3
I don’t trust letting apps collect my data
103
15.4
They would use too much of my data plan
85
10.9
My health is fine and I don’t need one
73
12.7
They are too complicated/too much of a
hassle to use
72
10.7
7. What would be the maximum
amount you would pay for a health-
related app? (n=1604)
I wouldn't pay anything
662
41.27
Less than $1
108
6.73
$1- $1.99
217
13.53
$2-$3.99
183
11.41
$4-$5.99
182
11.35
$6-$9.99
139
8.67
$10-$19.99
58
3.62
$20+
55
3.43
8. On average, how often do you
open or log on to use the health app
you use most often? (n=934)
Less than once a month
59
6.3
A few times a month
68
7.3
A few times each week
195
20.9
About 1 time each day
299
32.0
2 or more times a day
313
33.5
9. On average, how many minutes do
you spend using health-related
smartphone apps on days that you
use them? (n=934)
1-10 minutes
415
44.43
11-30 minutes
415
44.43
more than 30 minutes
104
11.13
10. How much do you trust that your
health apps automatically record
your data accurately? (n=934)
I don't use a health app that records my
health data
23
2.5
Don't trust them at all
11
1.2
Somewhat distrust
52
5.6
Neither trust nor distrust
88
9.4
Moderately trust
416
44.5
Very much trust
344
36.8
11. How much do you trust your
health apps to keep your data safe
and secure? (n=934)
Don't trust them at all
14
1.5
Somewhat distrust
42
4.5
Neither trust nor distrust
148
15.8
Moderately trust
411
44
Very much trust
319
34.2
12. How did you typically learn
about the health apps you use?
(n=934)
Searching the app store
327
35.0
Friends or family
287
30.7
Web searches (e.g. Google)
170
18.2
TV
48
5.1
Doctor, nurse or another health professional
38
4.2
Newspaper/magazine
16
1.7
From other apps
48
5.1
13. To what extent do you think
health apps have improved your
health? (n=934)
Made my health worse
25
2.7
Didn't help at all
73
7.8
Just a little bit improved
224
24.0
Somewhat improved
339
36.3
Very much improved
273
29.2
14. Which health apps do you
currently have on your phone?
(n=934)
Walgreens
123
13.2
Fitbit
107
11.5
Weight Watchers
59
6.3
Web MD
36
3.9
Nike+
34
3.6
MyFitnessPal
33
3.5
CVS
32
3.4
MapMyFitnesss
31
3.3
Loseit
25
2.7
Noom
24
2.6
Rite Aid
20
2.1
Calorie Counter
20
2.1
Pedometer/Steps
16
1.7
Fooducate
15
1.6
Runtastic
14
1.5
Moves
14
1.5
Blood Pressure
11
1.2
MotionX247
7
0.7
MapMyWalk
7
0.7
Period Tracker
6
0.6
15. Are there any health apps you
downloaded and no longer use?
(n=427)
No
507
54.3
Yes
427
45.7
16. What reasons do you no longer
use them? (check all that apply)
(n=427)
Takes too much time to enter data
190
44.5
Lost interest
173
40.5
There were hidden costs
154
36.1
Too confusing to use
140
32.8
I felt too connected to my
friends/family/colleagues who used it too
124
29.0
Didn’t help me as I wanted
81
19.0
Found better apps
66
15.5
I no longer need it/ I met my goals
44
10.3
No longer works on my phone
44
10.3
Other
11
2.6
17. How interested would you be in
using an app to make appointments
with your doctors? (n=1604)
I already use this
123
7.67
Not very interested at all
350
21.82
Just a little interested
211
13.15
Somewhat interested
363
22.63
Very interested
557
34.73
18. How interested would you be in
using an app to look at your medical
records? (n=1604)
I already use this
148
9.23
Not very interested at all
290
18.08
Just a little interested
169
10.54
Somewhat interested
354
22.07
Very interested
643
40.09
19. How interested would you be in
using an app to write to your
doctors? (n=1604)
I already use this
124
7.73
Not very interested at all
353
22.01
Just a little interested
196
12.22
Somewhat interested
354
22.07
Very interested
577
35.97
20. Has a doctor ever recommended
you use a health app? (n=1031)
No
821
79.63
Yes
210
20.37
... Regarding cost, participants in the current study showed a strong preference for free apps, re ecting previous work demonstrating that paywalls are a barrier to uptake (31,32). Interestingly, as the majority of the current sample had a higher annual household income than the median household income of the UK of £32,300 as of 2022 (33) a paywall may be a barrier to uptake for reasons other than affordability. ...
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... Így például kiemelték a hozzáférhetőséggel (Attig és Franke, 2020), kényelemmel (Canhoto és Arp, 2017), (de)motivációval (Choi, Keil és Baird, 2022), egészségi állapottal (Keeling, de Ruyter, Mousavi, & Laing, 2019), célokkal (Lee & Lee, 2020), észlelt hasznossággal (Santos-Vijande, Gómez-Rico, Molina-Collado, & Davison, 2022), magánélettel és használhatósággal (Simblett, és mtsai., 2018) kapcsolatos problémákat. Krebs és Duncan úgy találták, hogy a nagy adatbeviteli teher, illetve az érdeklődés elvesztése akadályozzák a használhatóságot (Krebs & Duncan, 2015). Kwon és munkatársai olyan gátló tényezőket azonosítottak, mint az attitűd, a hasznosság megítélése, az életkor, valamint az egészséggel kapcsolatos információk gyűjtése (Kwon, Mun, Lee, McLeod, & D'Angelo, 2017). ...
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... For instance, although the current sample was relatively diverse, no analyses were conducted regarding VHB in certain subpopulations (e.g., White versus person of color, straight versus lesbian/gay or bisexual, cisgender versus transgender, or gender diverse). This nuanced work is warranted in light of research that indicates that suicidal thoughts and behaviors (Stephenson et al., 2006) as well as mobile app utilization (Krebs & Duncan, 2015) differ across demographic groups. ...
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A multitude of mhealth (mobile health) apps have been developed in recent years to support effective self-management of patients with diabetes mellitus type 1 or 2. We carried out a systematic review of all currently available diabetes apps for the operating systems iOS and Android. We considered the number of newly released diabetes apps, range of functions, target user groups, languages, acquisition costs, user ratings, available interfaces, and the connection between acquisition costs and user ratings. Additionally, we examined whether the available applications serve the special needs of diabetes patients aged 50 or older by performing an expert-based usability evaluation. We identified relevant keywords, comparative categories, and their specifications. Subsequently, we performed the app review based on the information given in the Google Play Store, the Apple App Store, and the apps themselves. In addition, we carried out an expert-based usability evaluation based on a representative 10% sample of diabetes apps. In total, we analyzed 656 apps finding that 355 (54.1%) offered just one function and 348 (53.0%) provided a documentation function. The dominating app language was English (85.4%, 560/656), patients represented the main user group (96.0%, 630/656), and the analysis of the costs revealed a trend toward free apps (53.7%, 352/656). The median price of paid apps was €1.90. The average user rating was 3.6 stars (maximum 5). Our analyses indicated no clear differences in the user rating between free and paid apps. Only 30 (4.6%) of the 656 available diabetes apps offered an interface to a measurement device. We evaluated 66 apps within the usability evaluation. On average, apps were rated best regarding the criterion "comprehensibility" (4.0 out of 5.0), while showing a lack of "fault tolerance" (2.8 out of 5.0). Of the 66 apps, 48 (72.7%) offered the ability to read the screen content aloud. The number of functions was significantly negative correlated with usability. The presence of documentation and analysis functions reduced the usability score significantly by 0.36 and 0.21 points. A vast number of diabetes apps already exist, but the majority offer similar functionalities and combine only one to two functions in one app. Patients and physicians alike should be involved in the app development process to a greater extent. We expect that the data transmission of health parameters to physicians will gain more importance in future applications. The usability of diabetes apps for patients aged 50 or older was moderate to good. But this result applied mainly to apps offering a small range of functions. Multifunctional apps performed considerably worse in terms of usability. Moreover, the presence of a documentation or analysis function resulted in significantly lower usability scores. The operability of accessibility features for diabetes apps was quite limited, except for the feature "screen reader".
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Mobile medical and health apps: State of the art, concerns, regulatory control and certification
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  • Feb 2014
This paper examines the state of the art in mobile clinical and health-related apps. A 2012 estimate puts the number of health-related apps at no fewer than 40,000, as healthcare professionals and consumers continue to express concerns about the quality of many apps, calling for some form of app regulatory control or certification to be put in place. We describe the range of apps on offer as of 2013, and then present a brief survey of evaluation studies of medical and health-related apps that have been conducted to date, covering a range of clinical disciplines and topics. Our survey includes studies that highlighted risks, negative issues and worrying deficiencies in existing apps. We discuss the concept of 'apps as a medical device' and the relevant regulatory controls that apply in USA and Europe, offering examples of apps that have been formally approved using these mechanisms. We describe the online Health Apps Library run by the National Health Service in England and the calls for a vetted medical and health app store. We discuss the ingredients for successful apps beyond the rather narrow definition of 'apps as a medical device'. These ingredients cover app content quality, usability, the need to match apps to consumers' general and health literacy levels, device connectivity standards (for apps that connect to glucometers, blood pressure monitors, etc.), as well as app security and user privacy. 'Happtique Health App Certification Program' (HACP), a voluntary app certification scheme, successfully captures most of these desiderata, but is solely focused on apps targeting the US market. HACP, while very welcome, is in ways reminiscent of the early days of the Web, when many "similar" quality benchmarking tools and codes of conduct for information publishers were proposed to appraise and rate online medical and health information. It is probably impossible to rate and police every app on offer today, much like in those early days of the Web, when people quickly realised the same regarding informational Web pages. The best first line of defence was, is, and will always be to educate consumers regarding the potentially harmful content of (some) apps.
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Using MapMyFitness to Place Physical Activity into Neighborhood Context
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  • Mar 2014
It is difficult to obtain detailed information on the context of physical activity at large geographic scales, such as the entire United States, as well as over long periods of time, such as over years. MapMyFitness is a suite of interactive tools for individuals to track their workouts online or using global positioning system in their phones or other wireless trackers. This method article discusses the use of physical activity data tracked using MapMyFitness to examine patterns over space and time. An overview of MapMyFitness, including data tracked, user information, and geographic scope, is explored. We illustrate the utility of MapMyFitness data using tracked physical activity by users in Winston-Salem, NC, USA between 2006 and 2013. Types of physical activities tracked are described, as well as the percent of activities occurring in parks. Strengths of MapMyFitness data include objective data collection, low participant burden, extensive geographic scale, and longitudinal series. Limitations include generalizability, behavioral change as the result of technology use, and potential ethical considerations. MapMyFitness is a powerful tool to investigate patterns of physical activity across large geographic and temporal scales.
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Smartphone Medical Applications for Women's Health: What Is the Evidence-Base and Feedback?
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  • Jan 2013
Background. Smartphone medical applications have a major role to play in women's health with their roles being very broad, ranging from improving health behaviours to undertaking personalised tests. Objective(s). Using Medline, Web of Knowledge, and the PRISMA guidelines 15 randomized controlled trials (RCTs) were identified, with mobile interventions being tested on 1603 females, in relation to key aspects of health. Using a similar systematic approach an iPhone database search identified 47 applications (apps) developed to improve women's health. Findings. Ten RCTs used text messaging or app interventions to support weight loss, with significant improvements being observed in eight studies. For other aspects of women's health RCTs are needed to determine possible health benefits. iPhone store data analysis identified that a substantial number of women's health apps did not have star ratings or feedback comments (68 and 49 per cent, resp.), raising concerns about their validity. Conclusion. Peer-review systems, supporting statements of evidence, or certification standards would be beneficial in maintaining the quality and credibility of future health-focused apps. Patient groups should also ideally be involved in the development and testing of mobile medical apps.
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A Lot of Action, But Not in the Right Direction: Systematic Review and Content Analysis of Smartphone Applications for the Prevention, Detection, and Management of Cancer
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Background Mobile phones have become nearly ubiquitous, offering a promising means to deliver health interventions. However, little is known about smartphone applications (apps) for cancer. Objective The purpose of this study was to characterize the purpose and content of cancer-focused smartphone apps available for use by the general public and the evidence on their utility or effectiveness. Methods We conducted a systematic review of the official application stores for the four major smartphone platforms: iPhone, Android, Nokia, and BlackBerry. Apps were included in the review if they were focused on cancer and available for use by the general public. This was complemented by a systematic review of literature from MEDLINE, Embase, and the Cochrane Library to identify evaluations of cancer-related smartphone apps. ResultsA total of 295 apps from the smartphone app stores met the inclusion criteria. The majority of apps targeted breast cancer (46.8%, 138/295) or cancer in general (28.5%, 84/295). The reported app purpose was predominantly to raise awareness about cancer (32.2%, 95/295) or to provide educational information about cancer (26.4%, 78/295), followed by apps to support fundraising efforts (12.9%, 38/295), assist in early detection (11.5%, 34/295), promote a charitable organization (10.2%, 30/295), support disease management (3.7%, 11/295), cancer prevention (2.0%, 6/295), or social support (1.0%, 3/295). The majority of the apps did not describe their organizational affiliation (64.1%, 189/295). Apps affiliated with non-profit organizations were more likely to be free of cost (χ21=16.3, P
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A General Inductive Approach for Analyzing Qualitative Evaluation Data
Article
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  • Jun 2006
A general inductive approach for analysis of qualitative evaluation data is described. The purposes for using an inductive approach are to (a) condense raw textual data into a brief, summary format; (b) establish clear links between the evaluation or research objectives and the summary findings derived from the raw data; and (c) develop a framework of the underlying structure of experiences or processes that are evident in the raw data. The general inductive approach provides an easily used and systematic set of procedures for analyzing qualitative data that can produce reliable and valid findings. Although the general inductive approach is not as strong as some other analytic strategies for theory or model development, it does provide a simple, straightforward approach for deriving findings in the context of focused evaluation questions. Many evaluators are likely to find using a general inductive approach less complicated than using other approaches to qualitative data analysis.
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Integrating Mobile Fitness Trackers Into the Practice of Medicine
Article
  • Apr 2015
Mobile fitness trackers are increasingly used by patients as a means to become more involved in their own self-care; however, these devices measure disparate outcomes that may have equivocal relevance to true health status. It is vital for physicians to interpret both the quality and accuracy of the information that these trackers provide, and it is important to delineate which role, if any, these devices may serve in promoting quality patient care in the future. Potential benefits of mobile fitness trackers include the ability to motivate patients toward a healthier lifestyle, to develop a community of like-minded individuals seeking to improve their health, as well as to create an environment of sustainability and accountability for long-term promotion of health maintenance. However, limitations include the fact that mobile fitness trackers are not regulated by the Food and Drug Administration, that the employed metrics are not necessarily the best surrogates for true health status, and that the accuracy of measured endpoints has not yet been proven. As mobile fitness trackers both continue to rise in popularity and become increasingly sophisticated, physicians must be equipped to interpret and use this technology to better serve patients within an ever-changing, more technology-reliant health care system.
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High Quantity But Limited Quality in Healthcare Applications Intended for HIV-Infected Patients
Article
Objective: The aim of this study was to evaluate, through the creation of a specific questionnaire, the information quality in mobile applications (apps) aimed at human immunodeficiency virus (HIV)-infected patients. We also established a quality rating and identified the main strengths and weaknesses of this kind of health app. Materials and methods: Smartphone apps specifically related to HIV/acquired immunodeficiency syndrome (AIDS) were searched. We conducted a key word search with the terms "HIV," "AIDS," and "acquired immune deficiency syndrome" in the Apple™ (Cupertino, CA) App Store and the Android™ Google™ (Mountain View, CA) Play Store. A questionnaire was developed based on the different quality recommendations for health apps up to December 2012. The recommendations consulted were as follows: the Happtique Health App Certification Program, the Food and Drug Administration (Mobile Medical Applications), and recommendations for the design, use, and evaluation of health apps of the Agency of Health Quality in Andalusia. A group of 17 experts assessed the importance of the different sections by using a Delphi method. Results: In total, 41 health apps were analyzed. Only one app (2.4%), called in Practice HIV, approached class A. The remaining were classed as follows: 2 (4.9%) class B, 1 (2.4%) class C, 5 (12.2%) class D and E, and 27 (65.9%) class F (not exceeding minimum criteria). The design and the relevance were highlighted among the strengths. The main areas for improvement are provision of services and confidentiality in addition to privacy policies. Conclusions: The quality of the revised apps is limited. Only one app complied with the excellence criteria, and over 50% of the apps did not exceed minimum quality standards. The worst rated aspects were political advertising and logical security.
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Smartphones and Pediatric Apps to Mobilize the Medical Home
Article
Objectives: To assess digital access and mobile health in urban pediatric clinics by measuring demographics of smartphone ownership, primary uses of mobile devices by teens vs parents/caregivers, and interest levels in using smartphone health apps. Study design: This cross-sectional survey studied teenagers and caregivers from 2 urban pediatric practices in Bronx, New York; 148 surveys were administered verbally in waiting rooms using a 24-item "iHealthNYC" questionnaire. A demonstration of smartphone health apps was then conducted and data analyzed using bivariate analysis and χ(2) statistics. Results: Overall, 84% of subjects were smartphone owners, with 57% using smartphones as their primary internet source. There was no statistical difference in smartphone ownership between age groups or demographics of sex, ethnicity, and socioeconomic status. Smartphone users had a mean 14.5 apps, with 70.4% accessing apps >3 times a day. The majority of participants stated interest in medical apps, although caregivers were significantly more motivated. Likewise, caregivers are more likely to search health topics via their phone (76.7% vs 47.9%, P < .01) and own medical apps vs teens (35.1% vs 16.9%, P = .02). Conclusion: The prevalence of smartphone and app use in urban pediatric populations is high. With increased interest in mobile health, smartphones are an attractive modality for patient education, disease management, and streamlining health care communication in diverse settings, thus "mobilizing" the medical home. Further research is needed so that pediatricians can promote evidence-based apps, thus enabling patients to take ownership of their health.
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