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

StatisticsWhat is your age?

NValid 115Missing 1

Median 4.0000Mode 4.00Std. Deviation 2.00754Variance 4.030Range 6.00

What is your age?Frequency Percent Valid

PercentCumulative

Percent

Valid

18-24 20 17.2 17.4 17.425-34 13 11.2 11.3 28.735-44 14 12.1 12.2 40.945-54 21 18.1 18.3 59.155-64 18 15.5 15.7 74.865-74 13 11.2 11.3 86.175 + 16 13.8 13.9 100.0Total 115 99.1 100.0

Missing 99.00 1 .9Total 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? CrosstabulationCount

What is your age? Total18-24 25-34 35-44 45-54 55-64 65-74 75 +

laptop computer

no 3 3 5 8 7 7 7 40yes 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 TestsValue df Asymp. Sig.

(2-sided)Pearson Chi-Square 7.231a 6 .300Likelihood Ratio 7.686 6 .262Linear-by-Linear Association

5.829 1 .016

N of Valid Cases 114a. 3 cells (21.4%) have expected count less than 5. The

minimum expected count is 4.56.

Table 7: Lambda test for association between age and ownership of laptop computersDirectional Measures

Value Asymp. Std. Errora

Approx. Tb

Approx. Sig.

Nominal by Nominal

Lambda

Symmetric .045 .035 1.233 .218laptop 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


.011 .007 .278c

a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.


Table 8: Frequency of age and response to use of social networks

Social networking (Facebook, Myspace, etc.) * What is your age? CrosstabulationCount

What is your age? Total18-24 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 networksChi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 26.219a 6 .000Likelihood Ratio 33.203 6 .000Linear-by-Linear Association

23.891 1 .000

N of Valid Cases 114a. 3 cells (21.4%) have expected count less than 5. The minimum expected count is 4.56.

Table 10: Lambda Test for association between age and use of social networksDirectional Measures


Approx. Tb

Approx. Sig.

Nominal by Nominal

Lambda

Symmetric .128 .073 1.663 .096social networking (Facebook, MySpace, etc.) Dependent

.175 .130 1.227 .220


.108 .073 1.399 .162


Social networking (Facebook, Myspace, etc.) Dependent

.230 .055 .000c


.041 .012 .000c

a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.c. Based on chi-square approximation


Table 11: Frequency of age and response to ownership of smartphonessmart phone * What is your age? Crosstabulation

Count What is your age? Total

18-24 25-34 35-44 45-54 55-64 65-74 75 +

smart phoneno 1 1 2 5 10 8 12 39yes 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 TestsValue df Asymp. Sig.

(2-sided)Pearson Chi-Square 34.652a 6 .000Likelihood Ratio 37.455 6 .000Linear-by-Linear Association

31.955 1 .000

N of Valid Cases 114a. 3 cells (21.4%) have expected count less than 5. The minimum expected count is 4.45.

Table 13: Lambda Test for association between age and ownership of a smart phoneDirectional Measures


Approx. Tb

Approx. Sig.

Nominal by Nominal

Lambda

Symmetric .180 .062 2.701 .007smart phone Dependent

.333 .144 1.927 .054


.117 .036 3.184 .001


smart phone Dependent

.304 .080 .000c


.051 .014 .000c

a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.c. Based on chi-square approximation


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-mailI 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!

AGE AND TECHNOLOGY REPORT

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