Adaptive and Maladaptive Coping with an It Threat

References

• Abraham, C. S., Sheeran, P., Abrams, D., & Spears, R. (1994). Exploring teenagers’ adaptive and maladaptive thinking in relation to the threat of HIV infection. Psychology & Health, 9(4), 253–272. doi:10.1080/08870449408407485
   PubMed Web of Science ®Google Scholar
• Anderson, C. L., & Agarwal, R. (2010). Practicing safe computing: A multimethod empirical examination of home computer user security behavioral intentions. MIS Quarterly, 34(3), 613–643. doi:10.2307/25750694
   Web of Science ®Google Scholar
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. doi:10.1037/0033-2909.103.3.411
   Web of Science ®Google Scholar
• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. doi:10.1007/BF02723327
   Google Scholar
• Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.
   Google Scholar
• Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of marketing scales: Multi-Item measures for marketing and consumer behavior research. Newbury Park, CA: SAGE Publications.
   Google Scholar
• Boer, H., & Seydel, E. (1996). Protection motivation theory. In: Conner, M. and Norman, P. (Eds.), Predicting health behavior: Research and practice with social cognition models (pp. 95–120). Buckingham, UK: Open University Press.
   Google Scholar
• Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods & Research, 21(2), 205–229. doi:10.1177/0049124192021002004
   Web of Science ®Google Scholar
• Boss, S. R., Galletta, D. F., Lowry, P. B., Moody, G. D., & Polak, P. (2015). What do users have to fear? Using fear appeals to engender threats and fear that motivate protective security behaviors. MIS Quarterly, 39(4), 837–864. doi:10.25300/MISQ/2015/39.4.5
   Web of Science ®Google Scholar
• Carver, C., Scheier, M., & Weintraub, J. (1989). Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56(2), 267–283.
   PubMed Web of Science ®Google Scholar
• Chen, X., Lunn, S., Deveaux, L., Li, X., Brathwaite, N., Cottrell, L., & Stanton, B. (2009). A cluster randomized controlled trial of an adolescent HIV prevention program among Bahamian youth: Effect at 12 months post-intervention. AIDS and Behavior, 13(3), 499–508. doi:10.1007/s10461-008-9511-0
   PubMed Web of Science ®Google Scholar
• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Chin, W. W., Gopal, A., & Salisbury, W. D. (1997). Advancing the theory of adaptive structuration: The development of a scale to measure faithfulness of appropriation. Information Systems Research, 8(4), 342–367. doi:10.1287/isre.8.4.342
   Web of Science ®Google Scholar
• Collett, S. (2013, March 25). Straight talk on security gets employees to listen – And comply. (Retrieved September 9, 2016, from) http://www.computerworld.com/s/article/9237798/Straight_talk_on_security_gets_employees_to_listen_and_comply?pageNumber=1
   Google Scholar
• Crossler, R. E., Johnston, A. C., Lowry, P. B., Hud, Q., Warkentin, M., & Baskerville, R. (2013). Future directions for behavioral information security research. Computers & Security, 32, 90–101. doi:10.1016/j.cose.2012.09.010
   Web of Science ®Google Scholar
• D’Arcy, J., Herath, T., & Shoss, M. K. (2014). Understanding employee responses to stressful information security requirements: A coping perspective. Journal of Management Information Systems, 31(2), 285–318. doi:10.2753/MIS0742-1222310210
   Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008
   Web of Science ®Google Scholar
• Delacre, M., Lakens, D., & Leys, C. (2017). Why psychologists should by default use Welch’s t-test instead of Student’s t-test. International Review of Social Psychology, 30(1), 92–101.
   Google Scholar
• Dinev, T., & Hu, Q. (2007). The centrality of awareness in the formation of user behavioral intention toward protective information technologies. Journal of the Association for Information Systems, 8(7), 386–408. doi:10.17705/1jais
   Web of Science ®Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. doi:10.2307/3151312
   Web of Science ®Google Scholar
• Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1–77. doi:10.17705/1CAIS.00407
   Google Scholar
• Good, A., & Abraham, C. (2011). Can the effectiveness of health promotion campaigns be improved using self-efficacy and self-affirmation interventions? An analysis of sun protection messages. Psychology & Health, 26(7), 799–818. doi:10.1080/08870446.2010.495157
   PubMed Web of Science ®Google Scholar
• Hanus, B., & Wu, Y. A. (2016). Impact of users’ security awareness on desktop security behavior: A protection motivation theory perspective. Information Systems Management, 33(1), 2–16. doi:10.1080/10580530.2015.1117842
   Web of Science ®Google Scholar
• Hardin, E. E., & Longhurst, M. O. (2016). Understanding the gender gap: Social cognitive changes during an introductory stem course. Journal of Counseling Psychology, 63(2), 233–239. doi:10.1037/cou0000119
   PubMed Web of Science ®Google Scholar
• He, J., & Freeman, L. A. (2010). Are men more technology-oriented than women? The role of gender on the development of general computer self-efficacy of college students. Journal of Information Systems Education, 21(2), 203–212.
   Google Scholar
• Herath, T., Chen, R., Wang, J., Banjara, K., Wilbur, J., & Rao, H. R. (2014). Security services as coping mechanisms: An investigation into user intention to adopt an email authentication service. Information Systems Journal, 24(1), 61–84. doi:10.1111/j.1365-2575.2012.00420.x
   Web of Science ®Google Scholar
• Herath, T., & Rao, H. R. (2009). Protection motivation and deterrence: A framework for security policy compliance in organisations. European Journal of Information Systems, 18(2), 106–125. doi:10.1057/ejis.2009.6
   Web of Science ®Google Scholar
• Ho, R. (2000). Predicting intention for protective health behavior: A test of the protection versus the ordered protection motivation model. Australian Journal of Psychology, 52(2), 110–118. doi:10.1080/00049530008255376
   Web of Science ®Google Scholar
• Hodgkins, S., & Orbell, S. (1998). Can protection motivation theory predict behaviour? A longitudinal test exploring the role of previous behavior. Psychology and Health, 13(2), 237–250. doi:10.1080/08870449808406749
   Web of Science ®Google Scholar
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi:10.1080/10705519909540118
   Web of Science ®Google Scholar
• Hu, Q., & Dinev, T. (2005). Is spyware an internet nuisance or public menace? Communications of the ACM, 48(8), 61–66. doi:10.1145/1076211
   Web of Science ®Google Scholar
• Ifinedo, P. (2012). Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory. Computers & Security, 31(1), 83–95. doi:10.1016/j.cose.2011.10.007
   Web of Science ®Google Scholar
• Jatana, N., & Roebuck, M. J. (2014). The impact of employees left to their own devices: Top ten BYOD considerations. Association of Corporate Counsel Legal Resources Retrieved from http://www.acc.com/legalresources/publications/topten/tioelttod.cfm
   Google Scholar
• Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: An empirical study. MIS Quarterly, 34(3), 549–566. doi:10.2307/25750691
   Web of Science ®Google Scholar
• Kindsight Security Labs. (2012). Kindsight Security Labs Malware report – Q4 2012 (Kindsight_Security_Labs-Q412_Malware_Report-final.pdf) Kindsight, Inc. Retrieved September 7, 2016, from http://www.kindsight.net/sites/default/files/Kindsight_Security_Labs-Q412_Malware_Report-final.pdf.
   Google Scholar
• Kleinot, M. C., & Rogers, R. W. (1982). Identifying effective components of alcohol misuse prevention programs. Journal of Studies on Alcohol, 43(7), 802–811.
   PubMed Web of Science ®Google Scholar
• Kok, G., Jonkers, R., Gelissen, R., Meertens, R., Schaalma, H., & de Zwart, O. (2010). Behavioral intentions in response to an influenza pandemic. BMC Public Health, 10, 174–192. doi:10.1186/1471-2458-10-174
   PubMed Web of Science ®Google Scholar
• Lai, F., Li, D., & Hsieh, C. T. (2012). Fighting identity theft: The coping perspective. Decision Support Systems, 52(2), 353–363. doi:10.1016/j.dss.2011.09.002
   Web of Science ®Google Scholar
• Lee, C. L., & Huang, M. K. (2014). The influence of computer literacy and computer anxiety on computer self-efficacy: The moderating effect of gender. Cyberpsychology, Behavior, and Social Networking, 17(3), 172–180. doi:10.1089/cyber.2012.0029
   PubMed Web of Science ®Google Scholar
• Lee, D., Larose, R., & Rifon, N. (2008). Keeping our network safe: A model of online protection behaviour. Behaviour & Information Technology, 27(5), 445–454. doi:10.1080/01449290600879344
   Web of Science ®Google Scholar
• Lee, Y., & Kozar, K. A. (2008). An empirical investigation of anti-spyware software adoption: A multitheoretical perspective. Information & Management, 45(2), 109–119. doi:10.1016/j.im.2008.01.002
   Web of Science ®Google Scholar
• Lee, Y., & Larsen, K. R. (2009). Threat or coping appraisal: Determinants of SMB executives’ decision to adopt anti-malware software. European Journal of Information Systems, 18(2), 177–187. doi:10.1057/ejis.2009.11
   Web of Science ®Google Scholar
• Leventhal, H. (1970). Findings and theory in the study of fear communications. Advances in Experimental Social Psychology, 5, 119–186.
   Google Scholar
• Liang, H., & Xue, Y. (2009). Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 33(1), 71–90. doi:10.2307/20650279
   Web of Science ®Google Scholar
• Liang, H., & Xue, Y. (2010). Understanding security behaviors in personal computer usage: A threat avoidance perspective. Journal of the Association for Information Systems, 11(7), 394–413. doi:10.17705/1jais
   Web of Science ®Google Scholar
• Lippke, S., & Plotnikoff, R. C. (2009). The protection motivation theory within the stages of the transtheoretical model–Stage specific interplay of variables and prediction of exercise stage transitions. British Journal of Health Psychology, 14(2), 211–229. doi:10.1348/135910708X399906
   PubMedGoogle Scholar
• Markoff, J. (2004, October 25). Home web security falls short, survey shows. New York Times, C4. (1923-Current File) Retrieved September 7, 2016, from http://libproxy.boisestate.edu/login?url=http://search.proquest.com/docview/92760680?accountid=9649
   Google Scholar
• McCrae, R. R. (1984). Situational determinants of coping responses: Loss, threat, and challenge. Journal of Personality and Social Psychology, 46(4), 919–928.
   PubMed Web of Science ®Google Scholar
• McMath, B. F., & Prentice-Dunn, S. (2005). Protection motivation theory and skin cancer risk: The role of individual differences in responses to persuasive appeals. Journal of Applied Social Psychology, 35(3), 621–643. doi:10.1111/jasp.2005.35.issue-3
   Web of Science ®Google Scholar
• Menard, P., Gatlin, R., & Warkentin, M. (2014). Threat protection and convenience: Antecedents of cloud-based data backup. The Journal of Computer Information Systems, 55(1), 83–91. doi:10.1080/08874417.2014.11645743
   Web of Science ®Google Scholar
• Milne, S., Orbell, S., & Sheeran, P. (2002). Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions. British Journal of Health Psychology, 7(2), 163–184. doi:10.1348/135910702169420
   PubMed Web of Science ®Google Scholar
• Milne, S., Sheeran, P., & Orbell, S. (2000). Prediction and intervention in health related behavior: A meta analytic review of protection motivation theory. Journal of Applied Social Psychology, 30(1), 106–143. doi:10.1111/jasp.2000.30.issue-1
   Web of Science ®Google Scholar
• Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. doi:10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Ng, B. Y., Kankanhalli, A., & Xu, Y. C. (2009). Studying users’ computer security behavior: A health belief perspective. Decision Support Systems, 46(4), 815–825. doi:10.1016/j.dss.2008.11.010
   Web of Science ®Google Scholar
• Orr, J. (2004). To be effective, anti-drug ads for should focus on thrill-seeking teens. Office of Research, University of Florida. Gainesville Florida. Retrieved September 7, 2016, from, http://news.ufl.edu/archive/2004/05/to-be-effective-anti-drug-adsshould-focus-on-thrill-seeking-teens.html
   Google Scholar
• Ouimet, M. C., Morton, B. G. S., Noelcke, E. A., Williams, A. F., Leaf, W. A., Preusser, D. F., & Hartos, J. L. (2008). Perceived risk and other predictors and correlates of teenagers’ safety belt use during the first year of licensure. Traffic Injury Prevention, 9(1), 1–10. doi:10.1080/15389580701638793
   PubMed Web of Science ®Google Scholar
• Prentice-Dunn, S., McMath, B. F., & Cramer, R. J. (2009). Protection motivation theory and stages of change in sun protective behavior. Journal of Health Psychology, 14(2), 297–305. doi:10.1177/1359105308100214
   PubMed Web of Science ®Google Scholar
• Prentice-Dunn, S., & Rogers, R. W. (1986). Protection motivation theory and preventive health: Beyond the health belief model. Health Education Research, 1(3), 153–161. doi:10.1093/her/1.3.153
   Google Scholar
• Rimal, R. N. (2001). Perceived risk and self‐efficacy as motivators: Understanding individuals’ long term use of health information. Journal of Communication, 51(4), 633–654. doi:10.1111/j.1460-2466.2001.tb02900.x
   Web of Science ®Google Scholar
• Rimal, R. N., & Real, K. (2003). Perceived risk and efficacy beliefs as motivators of change. Human Communication Research, 29(3), 370–399.
   Web of Science ®Google Scholar
• Rippetoe, P. A., & Rogers, R. W. (1987). Effects of components of protection-motivation theory on adaptive and maladaptive coping with a health threat. Journal of Personality and Social Psychology, 52(3), 596–604.
   PubMed Web of Science ®Google Scholar
• Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In J. Cacioppo & R. Petty (Eds.), Social psychophysiology: A sourcebook (pp. 153–177). New York, NY: Guilford Press.
   Google Scholar
• Rogers, R. W., & Mewborn, C. R. (1976). Fear appeals and attitude change: Effects of a threat’s noxiousness, probability of occurrence, and the efficacy of coping responses. Journal of Personality and Social Psychology, 34(1), 54–61.
   PubMed Web of Science ®Google Scholar
• Ruxton, G. D. (2006). The unequal variance t-test is an underused alternative to Student’s t-test and the Mann–Whitney U test. Behavioral Ecology, 17(4), 688–690. doi:10.1093/beheco/ark016
   Web of Science ®Google Scholar
• Siponen, M., Mahmood, M. A., & Pahnila, S. (2014). Employees’ adherence to information security policies: An exploratory field study. Information & Management, 51, 217–224. doi:10.1016/j.im.2013.08.006
   Web of Science ®Google Scholar
• Siponen, M., & Vance, A. (2010). Neutralization: New insights into the problem of employee information systems security policy violations. MIS Quarterly, 34(3), 487–502. doi:10.2307/25750688
   Web of Science ®Google Scholar
• Smith, R. A., Witte, K., & Downs, E. (2003, May). I want to be like you: Entertainment education, EPPM, and health education. In annual meeting of the International Communication Association, New Orleans, Louisiana.
   Google Scholar
• Stewart, H. (2013). New infection rate data for unprotected computers. Microsoft Malware Protection Center. Retrieved September 7, 2016, from http://blogs.technet.com/b/mmpc/archive/2013/10/29/new-infection-rate-data-for-unprotected-computers.aspx
   Google Scholar
• Sumner, M. (2009). Information security threats: A comparative analysis of impact, probability, and preparedness. Information Systems Management, 26(12), 2–12. doi:10.1080/10580530802384639
   Google Scholar
• Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. doi:10.1007/BF02291170
   Web of Science ®Google Scholar
• Vance, A., Siponen, M., & Pahnila, S. (2012). Motivating IS security compliance: Insights from habit and protection motivation theory. Information & Management, 49(3–4), 190–198. doi:10.1016/j.im.2012.04.002
   Web of Science ®Google Scholar
• Witte, K. (1992). Putting the fear back into fear appeals: The extended parallel process model. Communications Monographs, 59(4), 329–349. doi:10.1080/03637759209376276
   Web of Science ®Google Scholar
• Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior, 27(5), 591–615. doi:10.1177/109019810002700506
   PubMed Web of Science ®Google Scholar
• Witte, K., Girma, B., & Girgre, A. (2002). Addressing underlying mechanisms to HIV/AIDS preventive behaviors in Ethiopia. International Quarterly of Community Health Education, 21(2), 163–176. doi:10.2190/QLKP-PY9C-MPYV-FXTY
   Google Scholar
• Woon, I., Tan, G. W., & Low, R. (2005, December). A protection motivation theory approach to home wireless security. In Proceedings of the Twenty-Sixth Annual International Conference on Information Systems 367–380. Las Vegas: Association for Information Systems.
   Google Scholar
• Workman, M., Bommer, W. H., & Straub, D. (2008). Security lapses and the omission of information security measures: A threat control model and empirical test. Computers in Human Behavior, 24(6), 2799–2816. doi:10.1016/j.chb.2008.04.005
   Web of Science ®Google Scholar