Efficacy Regarding Social Media and Its Implications for NonProfit Agencies Targeting Older Adults
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The document explores technological anxiety and self-efficacy among older adults (57 and over) regarding social media, highlighting that 97% of nonprofits use social media yet face challenges in engaging this demographic. Research indicates a significant relationship between technological anxiety and technological efficacy, with age, ethnicity, and income influencing the latter. The document concludes with recommendations for nonprofits to effectively support older adults in navigating social media.
Efficacy Regarding Social Media and Its Implications for NonProfit Agencies Targeting Older Adults
- 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 2 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 3 Campus Technology Forum 2014
- 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. Campus Technology Forum 2014
- 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? Campus Technology Forum 2014
- 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 Campus Technology Forum 2014
- 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 Campus Technology Forum 2014
- 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. Campus Technology Forum 2014
- 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. Campus Technology Forum 2014
- 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. Campus Technology Forum 2014
- 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 Campus Technology Forum 2014
- 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. Campus Technology Forum 2014
- 13. 13 #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. Campus Technology Forum 2014
- 14. 14 #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 Campus Technology Forum 2014
- 15. 15 #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” Campus Technology Forum 2014
- 16. #1 Have Patience • Use creativity to grab their attention • Use patience when exploring how to provide products and services through social media channels 16 Campus Technology Forum 2014
- 17. 17 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. Campus Technology Forum 2014