1. Predictors of Technological Anxiety & Self-Efficacy
Regarding Social Media & its Implications for
Nonprofit Agencies Targeting Older Adults
Angela S. Williamson

2. Introduction
• As of 2010, 97% of nonprofit organizations are using social
media websites like Twitter and Facebook
• There could be a neglected audience during this organizational
shift
• Underrepresented audience are older adults 57 and over
• Empirical research has shown that older adults are anxious in
matters relating to technological efficacy, but there is a gap in
research
• Current research does not show how technological anxiety
influences technological self-efficacy in learning social media
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Campus Technology Forum 2014

3. Statement of the Problem
• 21% of Americans will be
over the age of 65 by 2030
• Older adults have an active
lifestyle and social media
could play a key role in an
aging society
• Technological gap may be a
major challenge for
nonprofits
• Understanding technological
anxiety may provide
guidance to nonprofit
organizations
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4. 4
Quantitative Hypotheses
• H1A: Based on a theoretical framework consisting of Bandura’s (1977) self-efficacy
theory on learning new tasks, it is hypothesized that the level of technological
anxiety influences technological efficacy in older adults learning social media.
– H10: There is no significant relation between the level of technological anxiety and
technological efficacy in older adults learning social media.
• H2A: According to current research on older adults and technology, demographic
factors like age, gender, marital status, ethnicity, income and education influence
feelings of technological anxiety in older adults learning social media.
– H20: There is no significant difference in demographic factors influencing feelings of
technological anxiety in older adults learning social media.
If a significant difference occurred then the third hypothesis was:
• H3A: If there is a significant difference in the independent and dependent variables,
then how much does technological anxiety influence feelings of technological self-
efficacy in older adults learning social media?
– H30: There is no significant difference in the demographic relations between
technology and anxiety as the independent and dependent variables respectively.
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5. 5
Quantitative Research Questions
• RQ1: Does the level of technological anxiety influence
technological efficacy in older adults learning social
media?
• RQ2: To what extent do the older adult’s demographic
factors (age, gender, marital status, ethnicity, marital
status, income, education) influence feelings of social
media anxiety?
• RQ3: To what extent do the older adult’s demographic
factors (age, gender, marital status, ethnicity, marital
status, income, education) influence feelings of
technological self-efficacy?
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6. 6
Measurement Scales
• Rosen and Weil’s (1992) Computer Anxiety Rating
Scale (CARS):
– Computer Anxiety Rating Scale (CARS) changed to
Social Media Anxiety Rating Scale
• Rosen and Weil’s (1992) Computer Thoughts Survey
(CTS):
– Computer Thoughts Survey (CTS) changed to Social
Media Thoughts Survey
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7. 7
Quantitative Methodology
• Face-to-face surveys
• Senior centers in Southern California
• Participants were 57 and older
• Survey divided into two sections:
– 40 technological anxiety and technological self-
efficacy questions
– 7 demographic questions
• Pilot study tested updated measurements
• Survey data collected & analyzed with SPSS
software
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8. 8
RQ1 Results
•A positive statistical relationship exists between
the level of technological anxiety and technological
efficacy in older adults learning social media.
•Technological anxiety predicted technological
efficacy (β = -.471, p < .000), accounting for 48% of
the variance in the level of technological anxiety
predicting technological efficacy in older adults
learning social media, R = .480, F (1, 100) = 29.88, p
< .000.
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9. 9
RQ2 Results
•Only age predicted feelings of social media
anxiety in older adults learning social media and
suggests that as older people age, their anxiety
about social media will be higher.
•Age predicted the level of social media anxiety,
accounting for 13% of the variance in predicting
social media anxiety for older adults learning
social media, R = .429, F (6, 95) = 3.58, p < .003.
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10. 10
RQ3 Results
•Ethnicity and income influenced feelings of
technological self-efficacy for older adults learning
social media.
•Ethnicity (β = -9.030, p < .008) and income (β = 7.356,
p < .019) influenced feelings of technological self-
efficacy, accounting for 20% of the variance in how
technological anxiety predicted feelings of
technological self-efficacy in older adults learning
social media, R = .480, F (6, 95) = 5.301, p < .000.
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11. 11
Conclusions
•Research concluded there is a correlation
between technological anxiety and
technological self-efficacy
•Age, income and ethnicity should be explored
further to test technological anxiety and
technological self-efficacy in older adults
learning social media
•Five key recommendations on the following
slides
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12. 12
#5 Know Your Audience
Four levels of older adults:
1.Younger boomers are born
between 1955-1964.
2.Older boomers are born
between 1946-1954.
3.The silent generation was
born between 1937-1945.
4.The GI generation was born
before 1936.
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#4 Hire the Right Talent
•Social media
community
managers should
build relationships
with older adults
•Building these
relationships may
strengthen
“stickiness” with
this particular
group.
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#3 Simplicity & Social Media Training
•More older adults are using
social media, but still have
challenges learning social
media
•Social media efforts should
include simple content and
easy navigation
•Provide a social media
handbook & on-site training
to address challenges
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#2 Focus on Active Users
• Active users are
important for social
media success
• All social media
content should address
“senior” issues or older
adults will not
participate
• Age group perfect for
“Virtual Volunteering”
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16. #1 Have Patience
• Use creativity to
grab their attention
• Use patience when
exploring how to
provide products
and services
through social
media channels
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References & Acknowledgements
• Bandura, A. (1977). Social learning theory.
Englewood Cliffs, NJ: Prentice-Hall.
• Bandura, A. (1986). Social foundations of thought
and action: A social cognitive theory. Englewood
Cliffs, NJ: Prentice-Hall.
• Berkshire, J. C. (2011). Tips for squeezing just a
little more from a tight budget. Chronicle of
Philanthropy, 23(7), 10. Retrieved from EBSCOhost
database.
• Comber, C., Colley, A., Hargreaves, D. J., & Dorn, L.
(1997). The effects of age, gender and computer
experience upon computer attitudes. Educational
Research, 39(2), 123-133.
doi:10.1080/0013188970390201
• Ellis, R. D., & Allaire, J. C. (1999). Modeling
computer interest in older adults: The role of age,
education, computer knowledge, and computer
anxiety. Human Factors, 41(3), 345-355.
• Gordon, M., Killey, M., Shevlin, M., McIlroy, D., &
Tierney, K. (2003). The factor structure of the
Computer Anxiety Rating Scale and the Computer
Thoughts Survey. Computers in Human Behavior,
19(3), 291-298.
• Lagana, L. (2008). Enhancing the attitudes and self-
efficacy of older adults toward computers and the
internet: Results of a pilot study. Educational
Gerontology, 34(9), 831-843.
doi:10.1080/03601270802243713
• Madden, M. (2010, August 27). Older adults and social
Media: Social networking use among those ages 50 and
older nearly doubled over the past year. Available At Pew
Internet & American Life Project website:
http://pewinternet.org/Reports/2010/Older-Adults-and-
Social-Media.aspx
• Mansfield, H. (2012). Social media for social good: A
how-to guide for nonprofits. New York, NY: McGraw Hill.
• Rosen, L. D., & Weil, M. M. (1992). Measuring
technophobia. A manual for the administration and
scoring of three instruments: Computer Anxiety Rating
Scale (Form C), General Attitudes toward Computers
Scale (Form C), and Computer Thoughts Survey (Form
C). Carson, CA: California State University Dominguez
Hills, Computerphobia Reduction Program.
• West, M. (2011). How nonprofits can use social media to
spark change. Chronicle of Philanthropy, 23(7), 4.
Retrieved from EBSCOhost database.
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