Mobile Health 2010
By Susannah Fox, Associate Director
October 19, 2010
Pew Research Center’s Internet & American Life Project
1615 L St., NW - Suite 700
Washington, D.C. 20036
202-419-4500 | pewinternet.org
1
Overview
The online health-information environment is going mobile, particularly among younger adults. The Pew
Internet Project’s latest survey of American adults, conducted in association with the California
HealthCare Foundation, finds that 85% use a cell phone. Of those:
17% of cell owners have used their phone to look up health or medical information and 29% of
cell owners ages 18-29 have done such searches.
9% of cell owners have software applications or “apps” on their phones that help them track or
manage their health. Some 15% of those ages 18-29 have such apps.
This means that health-information searches and communications have joined the growing array of non-
voice data applications that are being bundled into cell phones.1 Fully 76% of cell phone owners (age
18+) use their phones to take pictures, for example, up from 66% in April 2009. Seven in ten cell phone
owners send or receive text messages; four in ten access the internet on their phones. In addition, 35%
of U.S. adults have software applications or “apps” on their phones (but only one in four adults actually
use them).2
Even with the proliferation of mobile and online opportunities, however, most adults’ search for health
information remains anchored in the offline world. Most people turn to a health professional, friend, or
family member when they have a health question; the internet plays a growing but still supplemental
role - and mobile connectivity has not changed that.3
Mobile health apps
There are now more than 250,000 apps available for the iPhone4, more than 30,0005 such apps for
smartphones running Android, and several thousand for those who have Blackberry devices.
There are apps for counting calories and nutrition information; apps for logging fitness workouts; apps
to monitor vital signs; apps providing health tips; apps to calculate disease risks; apps to calculate body
mass index; apps for keeping personal health records and for providing users’ health information to
physicians and emergency workers; apps to learn about medicines; apps for smoking cessation; and
apps for yoga stretching exercises people can perform at their desks at work.
Cell phone users between 18-29 years old are more likely than older cell owners to use mobile health
apps: 15% do so, compared with 8% of cell users ages 30-49, for example. African American cell phone
owners are more likely than other groups to use such apps: 15% do so, compared with 7% of white and
11% of Latino cell phone users. Urban cell phone owners are more likely than those who live in
suburban or rural areas to have a mobile health app on their phone. There are no significant differences
between men and women, nor among income groups.
2
Mobile health apps
Percentage of cell phone users in each group who have a software application or "app" on their
phone to help them track or manage their health
Total cell phone users
9%
Gender
Male
10
Female
8
Race
White
7
Black
15*
Hispanic
11
Age (at time of survey)
18-29
15*
30-49
8
50-64
6
65+
5
Education
Some high school
9
High school graduate
6
Some college
13*
College graduate or more
9
Household Income
< $30,000
7
$30,000 - $49,999
8
$50,000 - $74,999
12
$75,000+
11
Language
English
9*
Spanish
1
Community Type
Rural
4
Suburban
9
Urban
12*
* indicates a significant difference
Source: Pew Research Center's Internet & American Life Project, August 9-September 13, 2010
Tracking Survey. N=3,001 adults and N for cell phone users=2,485. The margin of error is +/- 2.5
percentage points for all adults and 3 points for cell phone users.
3
Mobile health information
The demographic mix shifts a bit when it comes to looking for health information on the go.
Younger cell phone users are certainly the most likely group to do this activity, but the drop-off point is
closer to age 50, rather than age 30. Latino cell phone users are significantly more likely than other
groups to use their cell phone to look for health information: 25% do so, compared with 15% of non-
Hispanic whites, for example. Cell phone owners living in urban areas are more likely than their
suburban and rural counterparts to use their phones to gather health information.
4
Used cell phone to look up health information
Percentage of cell phone users in each group who have used their phone to look up health or
medical information
Total cell phone users
17%
Gender
Male
17
Female
16
Race
White
15
Black
19
Hispanic
25*
Age (at time of survey)
18-29
29*
30-49
18*
50-64
7
65+
8
Education
Some high school
16
High school graduate
12
Some college
21*
College graduate or more
20*
Household Income
< $30,000
15
$30,000 - $49,999
17
$50,000 - $74,999
17
$75,000+
22*
Language
English
17
Spanish
14
Community Type
Rural
11
Suburban
16
Urban
21*
* indicates a significant difference
Source: Pew Research Center's Internet & American Life Project, August 9-September 13, 2010
Tracking Survey. N=3,001 adults and N for cell phone users=2,485. The margin of error is +/- 2.5
percentage points for all adults and 3 points for cell phone users.
5
Wireless access
In addition to the findings related to cell phones, the September 2010 survey finds that 57% of American
adults have a wireless connection and use a laptop or a cell phone to access the internet.
The “mobile difference,” which Pew Internet first identified in 2009,6 is the observation that once
someone has a wireless device, that person is more likely to use the internet to gather information,
share information and create new content. These patterns are beginning to emerge in mericans’
pursuit of health information on mobile devices as well as traditional wired computers.
This survey finds that 78% of wireless internet users have looked online for health information,
compared with 70% of internet users with desktop access and 59% of all American adults.
Previous research by the Pew Internet Project has shown that wireless connections are associated with
deeper engagement in health-related social media. Mobile internet users are more likely than those
with tethered access to post comments and reviews online about health and health care, for example.7
Information is now portable, personalized, and participatory, thanks in part to the growing number of
American adults who are leading the wireless pack.
7 The Social Life of Health Information, 2009.
6
Methodology
This report is based on the findings of a daily tracking survey on Americans' use of the Internet. The
results in this report are based on data from telephone interviews conducted by Princeton Survey
Research Associates International between August 9 and September 13, 2010, among a sample of 3,001
adults, age 18 and older. Interviews were conducted in English and Spanish. For results based on the
total sample, one can say with 95% confidence that the error attributable to sampling is plus or minus
2.5 percentage points. For results based Internet users (n=2,065), the margin of sampling error is plus or
minus 2.9 percentage points. In addition to sampling error, question wording and practical difficulties in
conducting telephone surveys may introduce some error or bias into the findings of opinion polls.
A combination of landline and cellular random digit dial (RDD) samples was used to represent all adults
in the continental United States who have access to either a landline or cellular telephone. Both samples
were provided by Survey Sampling International, LLC (SSI) according to PSRAI specifications. The
landline sample for this survey was designed to generalize to the U.S. adult population and to
oversample African-Americans and Hispanics. To achieve these objectives in a cost effective manner, the
design uses standard list-assisted random digit dialing (RDD) methodology, but telephone numbers are
drawn disproportionately from telephone exchanges with higher than average density of African-
American and/or Hispanic households. The cellular sample was not list-assisted, but was drawn through
a systematic sampling from dedicated wireless 100-blocks and shared service 100-blocks with no
directory-listed landline numbers.
New sample was released daily and was kept in the field for at least five days. The sample was released
in replicates, which are representative subsamples of the larger population. This ensures that complete
call procedures were followed for the entire sample. At least 7 attempts were made to complete an
interview at a sampled telephone number. The calls were staggered over times of day and days of the
week to maximize the chances of making contact with a potential respondent. Each number received at
least one daytime call in an attempt to find someone available. For the landline sample, half of the time
interviewers first asked to speak with the youngest adult male currently at home. If no male was at
home at the time of the call, interviewers asked to speak with the youngest adult female. For the other
half of the contacts interviewers first asked to speak with the youngest adult female currently at home.
If no female was available, interviewers asked to speak with the youngest adult male at home. For the
cellular sample, interviews were conducted with the person who answered the phone. Interviewers
verified that the person was an adult and in a safe place before administering the survey. Cellular
sample respondents were offered a post-paid cash incentive for their participation. All interviews
completed on any given day were considered to be the final sample for that day.
Disproportionate sampling and non-response in telephone interviews can produce biases in survey-
derived estimates. The dataset was weighted in two stages. The first stage of weighting corrected for
the disproportionate landline sample design and also accounted for the overlapping landline and cellular
sample frames as well as different probabilities of selection associated with the number of adults in the
household. The second stage of weighting matched overall sample demographics to population
parameters. The demographic weighting parameters are derived from a special analysis of the most
recently available Census Bureau’s March 2009 nnual Social and Economic Supplement. This analysis
produces population parameters for the demographic characteristics of adults age 18 or older. These
parameters are then compared with the sample characteristics to construct sample weights. The
weights are derived using an iterative technique that simultaneously balances the distribution of all
weighting parameters.
Following is the full disposition of all sampled telephone numbers:
7
Table 1:Sample Disposition
Landline
Cell
53,160
17,075
Total Numbers Dialed
2,613
441
Non-residential
2,430
32
Computer/Fax
21
---
Cell phone
27,936
6,428
Other not working
4,308
311
Additional projected not working
15,852
9,863
Working numbers
29.8%
57.8%
Working Rate
1,436
104
No Answer / Busy
2,734
2,370
Voice Mail
84
17
Other Non-Contact
11,598
7,372
Contacted numbers
73.2%
74.7%
Contact Rate
1,020
1,027
Callback
8,303
4,597
Refusal
2,275
1,748
Cooperating numbers
19.6%
23.7%
Cooperation Rate
158
60
Language Barrier
---
646
Child's cell phone
2,117
1,042
Eligible numbers
93.1%
59.6%
Eligibility Rate
116
42
Break-off
2,001
1,000
Completes
94.5%
96.0%
Completion Rate
13.6%
17.0%
Response Rate
The disposition reports all of the sampled telephone numbers ever dialed from the original telephone
number samples. The response rate estimates the fraction of all eligible respondents in the sample that
were ultimately interviewed. At PSRAI it is calculated by taking the product of three component rates:
Contact rate - the proportion of working numbers where a request for interview was made
Cooperation rate - the proportion of contacted numbers where a consent for interview was at
least initially obtained, versus those refused
Completion rate - the proportion of initially cooperating and eligible interviews that were
completed
Thus the response rate for the landline sample was 13.6 percent. The response rate for the cellular
sample was 17.0 percent.
8
Final Topline
9/17/10
September Health Tracking Survey 2010
Data for August 9 - September 13, 2010
Princeton Survey Research Associates International
for the Pew Research Center‟s Internet & American Life Project
Sample: n= 3,001 national adults, age 18 and older, including 1,000 cell phone interviews
Interviewing dates: 08.09.10 - 09.13.10
Margin of error is plus or minus 3 percentage points for results based on Total [n=3,001]
Margin of error is plus or minus 3 percentage points for results based on internet users [n=2,065]
Margin of error is plus or minus 3 percentage points for results based on cell phone users [n=2,485]
Q1
Overall, how would you rate the quality of life for you and your family today? Would
you say it is… excellent, very good, good, fair or poor?
CURRENT
MAY 2010i
SEPT 2009ii
APRIL 2009iii
DEC 2008iv
%
17
Excellent
18
16
17
15
26
Very good
27
26
26
26
34
Good
34
35
34
34
16
Fair
16
17
16
19
6
Poor
5
5
5
5
Don‟t know
*
Refused
*
*
1
1
There are no Questions Q2 thru Q5.
Princeton Survey Research Associates International
Q6a Do you use the internet, at least occasionally?
Q6b Do you send or receive email, at least occasionally?1
DOES NOT USE
USES INTERNET
INTERNET
Current
74
26
May 2010
79
21
January 2010v
75
25
December 2009vi
74
26
September 2009
77
23
April 2009
79
21
December 2008
74
26
November 2008vii
74
26
August 2008viii
75
25
July 2008ix
77
23
May 2008x
73
27
April 2008xi
73
27
January 2008xii
70
30
December 2007xiii
75
25
September 2007xiv
73
27
February 2007xv
71
29
December 2006xvi
70
30
November 2006xvii
68
32
August 2006xviii
70
30
April 2006xix
73
27
February 2006xx
73
27
December 2005xxi
66
34
September 2005xxii
72
28
June 2005xxiii
68
32
February 2005xxiv
67
33
January 2005xxv
66
34
Nov 23-30, 2004xxvi
59
41
November 2004xxvii
61
39
June 2004xxviii
63
37
February 2004xxix
63
37
November 2003xxx
64
36
August 2003xxxi
63
37
June 2003xxxii
62
38
May 2003xxxiii
63
37
March 3-11, 2003xxxiv
62
38
February 2003xxxv
64
36
Q6a/b continued…
1 Prior to January 2005, question wording was “Do you ever go online to access the Internet or World Wide Web or to send
and receive email?”
Princeton Survey Research Associates International
Q6a/b continued…
DOES NOT USE
USES INTERNET
INTERNET
December 2002xxxvi
57
43
November 2002xxxvii
61
39
October 2002xxxviii
59
41
September 2002xxxix
61
39
July 2002xl
59
41
March/May 2002xli
58
42
January 2002xlii
61
39
December 2001xliii
58
42
November 2001xliv
58
42
October 2001xlv
56
44
September 2001xlvi
55
45
August 2001xlvii
59
41
February 2001xlviii
53
47
December 2000xlix
59
41
November 2000l
53
47
October 2000li
52
48
September 2000lii
50
50
August 2000liii
49
51
June 2000liv
47
53
May 2000lv
48
52
Princeton Survey Research Associates International
Q10 As I read the following list of items, please tell me if you happen to have each one, or
not. Do you have… [INSERT ITEMS IN ORDER]?
YES
NO
DON‟T KNOW
REFUSED
a. A cell phone or a Blackberry
or iPhone or other device that
is also a cell phone2
Current
85
15
May 2010
82
18
0
January 20103
80
20
0
December 2009
83
17
0
September 2009
84
15
April 2009
85
15
April 2008
78
22
--
Dec 2007
75
25
--
Sept 2007
78
22
--
April 2006
73
27
--
January 20054
66
34
--
November 23-30, 2004
65
35
--
2 Prior to April 2009, item wording was “A cell phone.” From April 2009 thru December 2009, item wording was “A cell
phone or a Blackberry or iPhone or other device that is also a cell phone.” Beginning December 2007, this item was not
asked of the cell phone sample, but results shown here reflect Total combined Landline and cell phone sample.
3 In January 2010, item wording was “A cell phone or a Blackberry or iPhone or other handheld device that is also a cell
phone.”
4 Through January 2005, question was not asked as part of a series. Question wording as follows: “Do you happen to have
a cell phone, or not?”
Princeton Survey Research Associates International
Q14 On your cell phone, do you happen to have any software applications or “apps” that
help you track or manage your health, or not?
Based on cell phone users [N=2,485]
CURRENT
%
9
Yes
90
No
1
Don‟t know
Refused
Q15 Do you ever use your cell phone to look up health or medical information?
Based on cell phone users [N=2,485]
CURRENT
%
17
Yes, do this
83
No, do not do this
Don‟t know
0
Refused
Princeton Survey Research Associates International
Endnotes
i May 2010 trends based on the Spring Change Assessment 2010 survey, conducted April 29 - May 30, 2010
[N=2,252, including 744 cell phone interviews].
ii September 2009 trends based on the September Tracking 2009 survey, conducted August 18 - September 14, 2009
[N=2,253, including 560 cell phone interviews].
iii April 2009 trends based on the Spring 2009 Tracking survey, conducted March 26-April 19, 2009 [N=2,253,
including 561 cell phone interviews].
iv December 2008 trends based on the Fall Tracking survey, conducted November 19-December 20, 2008 [N=2,253,
including 502 cell phone interviews]. Trends do not include California oversample.
v January 2010 trends based on the Online News survey, conducted December 28, 2009 - January 19, 2010
[N=2,259, including 562 cell phone interviews].
vi December 2009 trends based on the Fall Tracking “E-Government” survey, conducted November 30 - December
27, 2009 [N=2,258, including 565 cell phone interviews].
vii November 2008 trends based on the Post-Election 2008 Tracking survey, conducted November 20-December 4,
2008 [N=2,254].
viii August 2008 trends based on the August Tracking 2008 survey, conducted August 12-31, 2008 [N=2,251].
ix July 2008 trends based on the Personal Networks and Community survey, conducted July 9-August 10, 2008
[N=2,512, including 505 cell phone interviews]
x May 2008 trends based on the Spring Tracking 2008 survey, conducted April 8-May 11, 2008 [N=2,251].
xi April 2008 trends based on the Networked Workers survey, conducted March 27-April 14, 2008. Most questions
were asked only of full- or part-time workers [N=1,000], but trend results shown here reflect the total sample
[N=2,134].
xii January 2008 trends based on the Networked Families survey, conducted December 13, 2007-January 13, 2008
[N=2,252].
xiii December 2007 trends based on the Annual Gadgets survey, conducted October 24-December 2, 2007 [N=2,054,
including 500 cell phone interviews].
xiv September 2007 trends based on the Consumer Choice survey, conducted August 3-September 5, 2007 [N=2,400,
oversample of 129 cell phone interviews].
xv February 2007 trends based on daily tracking survey conducted February 15-March 7, 2007 [N=2,200].
xvi December 2006 trends based on daily tracking survey, conducted November 30 - December 30, 2006 [N=2,373].
xvii November 2006 trends based on Post-Election tracking survey, conducted Nov. 8-Dec. 4, 2006 [N=2,562]. This
includes an RDD sample [N=2,362] and a cell phone only sample [N=200]. Results reflect combined samples, where
applicable.
xviii
August 2006 trends based on daily tracking survey, conducted August 1-31, 2006 [N=2,928].
xix April 2006 trends based on the Annual Gadgets survey, conducted Feb. 15-Apr. 6, 2006 [N=4,001].
xx February 2006 trends based on the Exploratorium Survey, conducted Jan. 9-Feb. 6, 2006 [N=2,000].
xxi December 2005 trends based on daily tracking survey conducted Nov. 29-Dec. 31, 2005 [N=3,011].
xxii September 2005 trends based on daily tracking survey conducted Sept. 14-Oct.13, 2005 [N=2,251].
xxiii
June 2005 trends based on the Spyware Survey, conducted May 4-June 7, 2005 [N=2,001].
xxiv February 2005 trends based on daily tracking survey conducted Feb. 21-March 21, 2005 [N=2,201].
Princeton Survey Research Associates International
xxv January 2005 trends based on daily tracking survey conducted Jan. 13-Feb.9, 2005 [N=2,201].
xxvi November 23-30, 2004 trends based on the November 2004 Activity Tracking Survey, conducted November 23-
30, 2004 [N=914].
xxvii
November 2004 trends based on the November Post-Election Tracking Survey, conducted Nov 4-Nov 22, 2004
[N=2,200].
xxviii
June 2004 trends based on daily tracking survey conducted May 14-June 17, 2004 [N=2,200].
xxix February 2004 trends based on daily tracking survey conducted February 3-March 1, 2004 [N=2,204].
xxx November 2003 trends based on daily tracking survey conducted November 18-December 14, 2003 [N=2,013].
xxxi August 2003 trends based on „E-Government‟ survey conducted June 25-August 3, 2003 [N=2,925].
xxxii
June 2003 trends based on „Internet Spam‟ survey conducted June 10-24, 2003 [N=2,200].
xxxiii
May 2003 trends based on daily tracking survey conducted April 29-May 20, 2003 [N=1,632].
xxxiv
March 3-11, 2003 trends based on daily tracking survey conducted March 3-11, 2003 [N=743].
xxxv February 2003 trends based on daily tracking survey conducted February 12-March 2, 2003 [N=1,611].
xxxvi
December 2002 trends based on daily tracking survey conducted Nov. 25-Dec. 22, 2002 [N=2,038].
xxxvii
November 2002 trends based on daily tracking survey conducted October 30-November 24, 2002 [N=2,745].
xxxviii
October 2002 trends based on daily tracking survey conducted October 7-27, 2002 [N=1,677].
xxxix
September 2002 trends based on daily tracking survey conducted September 9-October 6, 2002 [N=2,092].
xl July 2002 trends based on „Sept. 11th-The Impact Online‟ survey conducted June 26-July 26, 2002 [N=2,501].
xli March/May 2002 trends based on daily tracking surveys conducted March 1-31, 2002 and May 2-19, 2002.
xlii January 2002 trends based on a daily tracking survey conducted January 3-31, 2002 [N=2,391].
xliii
December 2001 trends represent a total tracking period of December 1-23, 2001 [N=3,214]. This tracking period
based on daily tracking surveys conducted December 17-23, 2001 and November 19-December 16, 2001.
xliv November 2001 trends represent a total tracking period of November 1-30, 2001 [N=2,119]. This tracking period
based on daily tracking surveys conducted October 19 - November 18, 2001 and November 19 - December 16,
2001.
xlv October 2001 trends represent a total tracking period of October 1-31, 2001 [N=1,924]. This tracking period
based on daily tracking surveys conducted September 20 - October 1, 2001, October 2-7, 2001, October 8-18, 2001,
and October 19 - November 18, 2001.
xlvi September 2001 trends represent a total tracking period of September 1-30, 2001 [N=742]. This tracking period
based on daily tracking surveys conducted August 13-September 10, 2001, September 12-19, 2001 and September
20 - October 1, 2001.
xlvii
August 2001 trends represent a total tracking period of August 12-31, 2001 [N=1,505]. This tracking period
based on a daily tracking survey conducted August 13-September 10, 2001.
xlviii
February 2001 trends based on a daily tracking survey conducted February 1, 2001-March 1, 2001 [N=2,096].
xlix December 2000 trends based on a daily tracking survey conducted December 2-22, 2000 [N=2,383].
l November 2000 trends based on a daily tracking survey conducted November 2, 2000 - December 1 [N=6,322].
li October 2000 trends based on a daily tracking survey conducted October 2 - November 1, 2000
[N=3,336].
lii September 2000 trends based on a daily tracking survey conducted September 15 - October 1, 2000 [N=1,302].
liii August 2000 trends based on a daily tracking survey conducted July 24 - August 20, 2000 [N=2,109].
liv June 2000 trends based on a daily tracking survey conducted May 2 - June 30, 2000 [N=4,606].
lv May 2000 trends based on a daily tracking survey conducted April 1 - May 1, 2000 [N=2,503].
Princeton Survey Research Associates International
