AGE AND TECHNOLOGY REPORT

RUNNING HEAD: AGE AND TECHNOLOGY 1
AGE AND TECHNOLOGY
Kumiko Sasa
Colorado Mesa University
SOCO 303- May 7, 2014

Age and Technology 2
Abstract
The “digital divide” is a relevant topic to understand as technology continues to advance along
with age. In efforts to understand the patterns of technology use with various age groups this
study was designed. In total, 115 people were surveyed through random and convenience
sampling. Results demonstrated that individuals ages 18 to 30 are less likely to own a desktop
computer; whereas, those over 70 are more likely to own one. Furthermore, those in the age
range of 18 to 34 are also more likely to use social networks. Those over 34 are half as likely as
this group to use social networks. This study also found that those 18 to 64 years old are more
likely to own a smartphone than those 65 and older. In summary, age was found to be somewhat
correlated to owning a desktop computer, social network use, and owning a smartphone.

Introduction
The primary purpose for conducting this research project was to gain a better
understanding of age and its correlation on technology use. As individuals continually age,
technology also continues to advance. Today, social media, cell-phones, internet, and gadgets
have become primary ways of communication. Everyday individuals are seen with various
devices, connecting with friends, parents, and family. They are also seen using the internet for
online shopping, playing games, gathering news, and sending e-mails. However, to gain a better
understanding for the extremity of these patterns the author finds it necessary to see the effects of
age on technology use. Previous research has concluded that according to age, measures such as
time spent on technology, the number of social networks individuals have, and motives for using
the internet vary. This is another reason for conducting this research project as older individuals
are perceived as using technology less than younger individuals. This poses a central question of
understanding what patterns of technology use exist across various age groups.
Given previous research, it is expected that the survey data will exemplify individuals
around 21 to 30 will more than likely own a laptop computer than those ages 70 and over. In
2010, Jelf and Richardson (2012) conducted a survey of students at UK Open University. Of the
7,000 people surveyed, 2,000 students were randomly selected from those aged 60-69, 1,000
from 70 and over, and 1000 from 21-29, 30-39, 40-49, and 50-59. The results from the survey
questionnaire indicated that of 21-30 year olds 86% had access to a laptop computer; whereas,
only 52.3% of individuals 70 and over. Interestingly, those 70 and over were 26.8% more likely
to have access to a desktop computer than students ages 20-30. Therefore, these results signify
that those around 70 years old and older are more likely to have access a desktop computer. In
contrast, those ages 21-30 are more likely to have access to a laptop computer.

H1A) Individuals over 70 will have more access to a desktop computer than a laptop.
H1B) The age range from 20 to about 30 years of age will have more access to a laptop
than a desktop computer.
Previous research suggests that usage of social networking websites also varies by age.
Lenhart, Purcell, Smith and Zickuhr (2010) with the Pew Research Center also completed a
survey in 2009 of 800 adolescents between the ages of 12 and 17, and 2,253 adults ages 18 and
over. Results exemplified that of respondents ages 18-24, 73% indicated that they use social
networking websites. This is similar to those ages 25-29 with 71% indicating that they use social
networks. In contrast, data also suggests that only 39% of internet users 30 and older use social
networking websites.
H2: Due to the statistics above, it is hypothesized that respondents ages 18 to 24 and 25-
29 will have similar results for their use in social networks. As for those ages 30 and
older, there will be almost two times as less use in social networking websites.
In addition to these two hypothesizes, Smith (2014) in review of the Pew Research
Center’s Internet Project in 2013, found that smartphone ownership for older adults is fairly low.
. Since May of 2011, the Pew Research Center began tracking data on smartphone ownership.
Nationally, smartphone adoption “has increased by 20 percentage points—from 35% to 55% of
American adults—but adoption levels among seniors have increased by just seven percentage
points, from 11% to 18%” (Smith 2014:8). In other words, roughly 18% of seniors (65 and older)
own a smartphone.
H3: From this previous information, it is hypothesized that respondents ages 65 and
older will own a significantly less number of smartphones than younger adults.

Overall, given previous research these three hypothesizes were developed and will be
used to analyze the patterns of age and technology use. The first hypothesis will give an
understanding of age and its corollary pattern in laptop or desktop ownership. The second
hypothesis will examine age and its correlation to social network use. Then the final hypothesis
will give information regarding age and ownership of smartphones.
METHOD
Population
The primary population was to gain an understanding of technology use across the age
range of 18 to 75 and over. Of this population, the study involved a total sample of 115
individuals. Within this sample, as seen in Table 1, 20 individuals were selected from the 18-24
age range, 13 individuals from 25-34, 14 from 35-44, 21 from 45-54, 18 from 55-64, 13 from 65-
74, and 16 individuals from the 75 and over age range. Each individual was randomly and
conveniently selected from various contexts such as nursing facilities, family, friends, and ski
lodges.
Research Design
After gathering into a group with four other individuals, previous literature, as well as
other surveys regarding this topic of age and technology, were analyzed. Using the information
found within the literature, questions were developed for a survey questionnaire. Each member
was then responsible for gathering a minimum of 15 surveys. Given the wide age range, each
member then selected a target population for respondents to the survey. This would allow each
age range to have some representation within the sample. Based on each group member’s age

range, respondents would be found within their families, friends, or other contexts such as work
related areas or communities.
Measurement Instruments
Furthermore, the survey questionnaire was compiled from various articles and other
surveys on age and technology use. A twelve question survey was created, with the last four
questions indicating the respondent’s demographics. These questions were placed at the end of
the survey to eliminate the possibilities of priming age with technology use.
RESULTS
Data Collecting Methods and Response Rate
Data was collected using the convenience of respondents, in relation to the surveyor’s
location and age range. Surveys were then handed out and returned to the surveyor for analysis.
Each respondent was initially responsible for 15 surveys each, giving this study a sample of 75;
however, more surveys were given out resulting in a total sample size of 115. This allowed for a
better understanding of each age’s thoughts and uses of technology in comparison to the actual
population.
Data Analysis and Statistical Testing
In analysis of the hypothesized related variables, Chi-Square tests were used to measure
statistical significance and Lambda was used to measure the strength of the association.
Given the first hypothesis, the variables analyzed were age and respondents indication of
ownership for laptop and desktop. Age is considered to be the independent variable that has an
effect on the dependent variable of owning a laptop and desktop computer. The level of
measurement for age is ordinal, given the age categories are different and ranked. Then the level

of measurement for ownership of laptop and desktops is nominal, considering the answers were
either “0=no” or “1=yes,” which are simply different answers without a rank. With the lowest
level of measurement being nominal, Lambda was used for the Measure of Association. Then
given the level of measurement for the independent variable as ordinal, and the dependent
variable as nominal, the appropriate test of significance is a Chi-Square test. Along with this test,
the correct measures of central tendency are median and mode.
Given the second hypothesis, the variables analyzed were age and respondents indication
of social network use. Age is considered to be the independent variable that has an effect on the
dependent variable of using social networks. The level of measurement for age is ordinal, given
the age categories are different and ranked. Then the level of measurement for social network use
is nominal, considering the answers were either “0=no” or “1=yes,” which are simply different
answers without a rank. Again, with the lowest level of measurement being nominal, Lambda
was used for the Measure of Association. A Chi-Square test was also used to measure the
significance of this relationship, as the independent variable is ordinal and the dependent variable
is nominal.
Then for the third hypothesis, the variables analyzed were age and respondents indication
of smartphone ownership. Age is considered to be the independent variable that has an effect on
the dependent variable of owning a smart phone. The level of measurement for age is ordinal,
given the age categories are different and ranked. Then the level of measurement for smartphone
ownership is nominal, considering the answers were either “0=no” or “1=yes,” which are simply
different answers without a rank. Once more, with the lowest level of measurement being
nominal, Lambda was used for the Measure of Association. Then for the test of statistical

significance the Chi-Square test was used since the independent variable is ordinal and the
dependent variable is nominal.
Outcomes
Hypothesis #1: A & B
For the first hypothesis, Table 2 illustrates that of the 20 respondents ages 18 to 24, 18
indicated they don’t have a desktop computer. Then of the 13 respondents ages 25 to 34, 9 had
indicated “no” to owning a desktop computer. For older respondents, out of the 13 respondents
ages 65-74, 4 indicated “no”, and out of 16 respondents ages 75 and over, 10 indicated that they
don’t own a desktop computer. According to Table 3, the Chi-Square test indicates that the
relationship between age and ownership of a desktop computer is significant at the .020 level. As
for the measure of association, Table 4 demonstrates that the association between age and
ownership of a desktop computer is .149.
As for laptop ownership, Table 5 illustrates that of the 20 respondents ages 18 to 24, 17
indicated they have a laptop computer. Then of the 13 respondents ages 25 to 34, 10 had
indicated “yes” to owning a desktop computer. For older respondents, out of the 13 respondents
ages 65-74, 6 indicated “yes”, and out of 16 respondents ages 75 and over, 9 indicated that they
own a laptop computer. According to Table 6, the Chi-Square test indicates that the relationship
between age and ownership of a desktop computer is significant at the .300 level. As for the
measure of association, Table 7 demonstrates that the association between age and ownership of
a desktop computer is .025.

Hypothesis #2
For the second hypothesis, Table 8 shows that of the 20 respondents ages 18 to 24, 20
indicated they use social networks such as Facebook and Myspace. Then of the 13 respondents
ages 25 to 34, 12 had indicated “yes” to using social networks. Out of 14 respondents ages 35-
44, nine said yes; out of 21 respondents ages 45-54, 13 said yes; out of 17 respondents ages 55-
64, eight said yes; out of 13 respondents ages 65-74, seven said yes; and out of respondents ages
75 and over, five said yes. Then according to Table 9, the Chi-Square test indicates that the
relationship between age and use of social networks is significant at the .000 level. As for the
measure of association, Table 10 demonstrates that the association between age and social
network use is .175.
Hypothesis #3
For the third hypothesis, Table 11 shows that of the 85 respondents ages 18 to 64, 66
indicated they have a smartphone. Then of the 29 respondents ages 65 to 75 and over, 9
identified that they were owners of smartphones. The Chi-Square test in Table 12 illustrates that
the relationship between age and ownership of a smartphone is significant at the .000 level. As
for the measure of association, Table 13 demonstrates that the association between age and
owners of smartphones is .333.
DISCUSSION
Hypothesis 1: A
Based off the information provided by Table 2, of individuals ages 18-24, 90% of
respondents don’t own a desktop computer. In comparison, of those ages 25-34, almost 70% of

respondents also don’t own a desktop computer. Whereas, out of the 29 respondents ages 70 and
over (including the frequency responses of 65-74 group and 75 plus), only 48% don’t own a
desktop computer. This indicates support for Jelf’s and Richardson’s (2012) study that signified
those ages 70 and over are more likely to have access to a desktop computer. Furthermore,
Tables 3 and 4 suggest that this correlation is highly significant and a somewhat strong
relationship. The Pearson’s chi-square statistic in Table 3 is lower than .05 indicating this
significance. Then the Lambda test in Table 4 exemplifies a relatively weak relationship as the
value is .149 which is closer to one than zero, but not a perfect statistical association value of
one. Therefore, age is somewhat correlated to the ownership of a desktop computer.
Hypothesis 1: B
In relation to the second part of hypothesis one, Table 5 illustrates that of the individuals’
ages 18-24, 85% of respondents have a laptop computer. In comparison, of those ages 25-34,
almost 77% of respondents also own one. Whereas, out of the 29 respondents ages 70 and over
(including the frequency responses of 65-74 group and 75 plus), only 52% own a laptop. This
also gives support for Jelf’s and Richardson’s (2012) study that signified those ages 20 to 30
years of age are more likely to have access to a laptop computer than those over 70. However,
given the information from Tables 6 and 7, there is no significant correlation and a weak
relationship. The Pearson’s chi-square statistic in Table 6 is higher than .05 with a .300
indicating this isn’t significant. Then the Lambda test in Table 7 exemplifies a weak relationship
as the value is .025 which is closer to zero than one as the perfect statistical association value.
In other words, age isn’t necessarily correlated to ownership of a laptop computer.

Hypothesis 2
Based off the information provided in Table 8, of respondents ages 18 to 24, 100%
indicated they use social networks. This is similar to those ages 25 to 34 as 92% indicates they
also use social networks. As for those ages 30 and older, (including the age range of 35-44, 45-
54, 55-64, 65-74), only 52% of respondents indicated the use of social networks. In other words,
the data suggests that respondents ages 18 to 24 and 25-34 use social networks approximately
just as much. But, data also demonstrates that those ages 34 and older tend to social networks
almost half as much as those ages 18 to 30. This is in support of Lenhart, Purcell, Smith, and
Zickuhr’s (2010) survey data. Furthermore, Table 9 and 10 indicates that the relationship
between age and use of social networks is highly significant, and has a weak association. The
Pearson’s chi-square statistic in Table 9 is way smaller than .05 with a .000 indicating this
relationship is significant. Then the Lambda test in Table 10 exemplifies a relatively weak
relationship as the value is .175 which is closer to one than zero, but not a perfect statistical
association value of one. Therefore, age is somewhat correlated to the usage of social networks.
Hypothesis 3
With regards to the information in Table 11, of respondents ages 18 to 64, 78% indicated
they own a smartphone. As for those ages 65 to 75 and over, only 31% of respondents said “yes”
to ownership of a smartphone. In short, older respondents own a little under half the amount of
smartphones that those ages 18-64 own. This information demonstrates a somewhat increase in
ownership of smartphones for older generations in comparison to Smith’s (2014) reflection of
Pew Institute’s research. However, those 65 and over still don’t own smartphones as much as
younger adults. In addition to this data, the Pearson’s chi-square statistic in Table 12 is way

smaller than .05 with a .000 indicating this relationship is significant. Also the Lambda test in
Table 13 demonstrates a somewhat strong relationship as the value is .333 which is closer to one
than zero, but not a perfect statistical association value of one. Therefore, age is somewhat
correlated to the ownership of smartphones.
CONCLUSION
In summary, this survey data suggests four things about age and technology use. First,
that age has some correlation to ownership of desktop computers. Younger adults, primarily
those ages 18-34, are less likely to own a desktop computer. Whereas, those over 70 are more
likely to own a desktop computer. Secondly and surprisingly, age isn’t necessarily correlated
with ownership of laptop computers. The data indicates that younger adults, ages 18-30 are more
likely to own a laptop computer than those over 70. Yet is also suggests that this relationship
isn’t significant, and that owning a laptop isn’t solely explained by age. Third, age is somewhat
correlated to the usage of social networks. 18-34 year olds use social networks similarly. In
contrast, those over 34 tend to use social networks half as much as 18 to 34 year olds. Fourth,
age is also somewhat correlated to the ownership of smartphones. Older adults (65-75+) are less
likely to own a smartphone than those ages 18-64.
These four implications mostly meet the conclusions of previous research provided by
Jelf and Richardson (2012), Lenhart, Purcell, Smith, and Zickuhr’s (2010), and Smith (2014).
Overall, this data implies that age to some extent influences the ownership of various devices
such as desktop computers and smartphones. It also suggests that age correlates to the usage of
social networks. In particular, this data demonstrates that older adults (65+) are more likely to
own a desktop computer, less likely to use social networks, and less likely to own a smartphone.

In addition, it also illustrates that younger adults (18 to 64) are less likely to own a desktop
computer, more likely to use social networks, and more likely to own a smartphone.
Validity and Reliability
As for the validity and reliability of this study, the data resembles similar characteristics
of those represented in the articles mentioned. By the repetition of these studies the data
produced similar results for both hypothesis one A, two and three. For hypothesis one B,
however there was a lack of reliability. The article suggested that there was a correlation between
age and the ownership of a laptop. From this study, there was no significant correlation between
these two variables. In general thou, the measurement quality in this study produced the same
results and accurately reflected the concepts it was intended to measure.
Future Implications
Upon further analysis, this study should be re-examined using a larger sample with
approximately the same number of respondents for each age group. Each age range was
represented in the sample, but some age ranges had less respondents than other groups. In other
words, each age group wasn’t adequately represented. Furthermore, more in-depth questions
should be constructed from the literature itself. This study gave some great information regarding
different corollary patterns of age in relation to devices and social networking, but nothing more.
When looking at research many data sets were aimed at devices rather than age and thoughts on
technology use. Maybe next time it may be helpful to use the research to guide the questions
rather than ideas that were thought to be affected with age.

REFERENCES
Jelfs, Anne, and John T.E. Richardson. 2013. “The Use of Digital Technologies across the Adult
Life Span in Distance Education.” British Journal of Educational Technology 44(2):338
351.
Lenhard, Amanda, Kristen Purcell, Aaron Smith, and Kathryn Zickuhr. 2010. “Social Media and
Mobile Internet Use among Teens and Young Adults.” Pew Research Center 1(1):1-51.
Smith, Aaron. 2014. “Older Adults and Technology Use: Adoption Is Increasing, but Many
Seniors Remain Isolated From Digital Life.” Pew Research Center 1(1):1-26.

APPENDICES
Table 1: Frequency Distribution for each age group
Statistics
What is your age?
N
Valid 115
Missing 1
Median 4.0000
Mode 4.00
Std. Deviation 2.00754
Variance 4.030
Range 6.00
What is your age?
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
18-24 20 17.2 17.4 17.4
25-34 13 11.2 11.3 28.7
35-44 14 12.1 12.2 40.9
45-54 21 18.1 18.3 59.1
55-64 18 15.5 15.7 74.8
65-74 13 11.2 11.3 86.1
75 + 16 13.8 13.9 100.0
Total 115 99.1 100.0
Missing 99.00 1 .9
Total 116 100.0
Table 2: Frequency of age and response to ownership of desktop computer
Desktop computer * What is your age? Crosstabulation
Count
What is your age? Total
18-24 25-34 35-44 45-54 55-64 65-74 75 +
desktop
computer
no 18 9 8 9 9 4 10 67
yes 2 4 6 11 9 9 6 47
Total 20 13 14 20 18 13 16 114

Table 3: Chi-Square Test for age in relation to ownership of Desktop Computer
Chi-Square Tests
Value df Asymp. Sig.
(2-sided)
Pearson Chi-Square 15.087a 6 .020
Likelihood Ratio 16.640 6 .011
Linear-by-Linear
Association
7.130 1 .008
N of Valid Cases 114
a. 0 cells (0.0%) have expected count less than 5. The
minimum expected count is 5.36.
Table 4: Lambda test for association between age and ownership of desktop computers
Directional Measures
Value Asymp.
Std. Errora
Approx.
Tb
Approx.
Sig.
Nominal by
Nominal
Lambda
Symmetric .113 .055 1.973 .048
desktop computer
Dependent
.149 .113 1.227 .220
What is your age?
Dependent
.096 .036 2.567 .010
Goodman and
Kruskal tau
desktop computer
Dependent
.132 .053 .021c
What is your age?
Dependent
.024 .011 .012c
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on chi-square approximation

Table 5: Frequency of age and response to ownership of laptop computer
Laptop computer * What is your age? Crosstabulation
Count
18-24 25-34 35-44 45-54 55-64 65-74 75 +
laptop
computer
no 3 3 5 8 7 7 7 40
yes 17 10 9 12 11 6 9 74
Total 20 13 14 20 18 13 16 114
Table 6: Chi-Square Test for age in relation to ownership of Laptop Computer
Chi-Square Tests
(2-sided)
Linear-by-Linear
Association
5.829 1 .016
Table 7: Lambda test for association between age and ownership of laptop computers
Value Asymp.
Std. Errora
Approx.
Tb
Approx.
Sig.
Nominal by
Nominal
Lambda
Symmetric .045 .035 1.233 .218
laptop computer
Dependent
.025 .089 .277 .781
What is your age?
Dependent
.053 .034 1.523 .128
Goodman and
Kruskal tau
laptop computer
Dependent
.063 .041 .306c
What is your age?
Dependent
.011 .007 .278c

Table 8: Frequency of age and response to use of social networks
Social networking (Facebook, Myspace, etc.) * What is your age? Crosstabulation
Count
18-24 25-34 35-44 45-54 55-64 65-74 75 +
Social networking
(Facebook,
Myspace, etc.)
no 0 1 5 8 9 6 11 40
yes
20 12 9 13 8 7 5 74
Total 20 13 14 21 17 13 16 114
Table 9: Chi-Square Test for age in relation to use of social networks
Chi-Square Tests
(2-sided)
Linear-by-Linear
Association
23.891 1 .000
Table 10: Lambda Test for association between age and use of social networks
Value Asymp.
Std. Errora
Approx.
Tb
Approx.
Sig.
Nominal by
Nominal
Lambda
Symmetric .128 .073 1.663 .096
social networking
(Facebook,
MySpace, etc.)
Dependent
.175 .130 1.227 .220
What is your age?
Dependent
.108 .073 1.399 .162
Goodman and
Kruskal tau
Social networking
(Facebook,
Myspace, etc.)
Dependent
.230 .055 .000c
What is your age?
Dependent
.041 .012 .000c

Table 11: Frequency of age and response to ownership of smartphones
smart phone * What is your age? Crosstabulation
Count
18-24 25-34 35-44 45-54 55-64 65-74 75 +
smart phone
no 1 1 2 5 10 8 12 39
yes 19 12 12 15 8 5 4 75
Total 20 13 14 20 18 13 16 114
Table 12: Chi-Square Test for age in relation to ownership of a smart phone
Chi-Square Tests
(2-sided)
Linear-by-Linear
Association
31.955 1 .000
Table 13: Lambda Test for association between age and ownership of a smart phone
Value Asymp.
Std. Errora
Approx.
Tb
Approx.
Sig.
Nominal by
Nominal
Lambda
Symmetric .180 .062 2.701 .007
smart phone
Dependent
.333 .144 1.927 .054
What is your age?
Dependent
.117 .036 3.184 .001
Goodman and
Kruskal tau
smart phone
Dependent
.304 .080 .000c
What is your age?
Dependent
.051 .014 .000c

COPY OF SURVEY
Technology Use Survey
This survey is voluntary. Your name will not be used at any time, and your answers will not be
available to anyone beyond the researchers.
Directions: Please answer the following questions quickly with the answer that first comes to
your mind. Remember, it is important that you answer the questions truthfully and to the best of
your ability.
1. What types of devices do you own (check all that apply):
Smart Phone Laptop Computer Desktop Computer
Tablet (like an iPad, Kindle FIRE, Galaxy Tab, Kindle or a Nook) Other _________
2. How many hours a day do you spend on the internet?
0-1 2-3 4-5 5-6 7-8 9-10 11+
3. I use the internet for: (check all that apply)
Homework/Work Social Networking (Facebook, MySpace, etc.) Shop Online
Playing Games Watching/Sharing Information (YouTube, Videos, Etc.)
Sending Emails Instant Messaging Gathering Information (News)
Banking Other _____________ I Don’t Have internet

4. For each of the following, indicate if you: Strongly Agree, Agree, Neutral, Disagree or
Strongly Agree.
Strongly
Agree
Agree Neutral Disagree Strongly
Disagree
I feel comfortable with the
internet.
I feel comfortable sharing items
such as pictures, videos, e-mail
I think social media helps
people stay connected
Internet services make life
easier
I feel the internet leads to less
face to face interaction
5. How often do you use social network websites per week?
Never 1-2 times 3-4 times 5-6 times 7 or more times
6. Which of the following social media websites do you use or visit? (check all that apply)
Facebook Twitter Instagram Pinterest Snapchat Flickr
Tumblr Myspace Linked-In Other Do not use social media websites
7. For which of the following purposes, if any, do you use these social media websites? (check
all that apply)
School work Shopping News/Current Events Entertainment/sports/hobbies
8. Which of the following are you connected to, friends with, or follow on these sites? (check all
that apply)
Parent(s) Children Grandparent (s) Grandchild Other relatives
None No response

9. Gender:
Male Female Transgender Other: ___________
10. What is your age?
18-24 25-34 35-44 45-54 55-64 65-74 75 +
11. What is the highest degree or level of school you have completed?
Less than high school Some high school/no diploma High school diploma/GED
Some college/no degree Trade/technical/vocational training Bachelor’s Degree
Master’s Degree Professional Degree Doctorate Degree Other __________
12. What was your total household income last year?
Under $9,999 $10,000-$29,999 $30,000-$49,999 $50,000-$69,999
$70,000-$89,000 Over $90,000 Thank you for taking our survey!

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