Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23) |
| Number of pages | 15 |
| ISBN (electronic) | 9781450394215 |
| Publication status | Published - 19 Apr 2023 |
Publication series
| Name | Conference on Human Factors in Computing Systems - Proceedings |
|---|
Abstract
The ubiquity of devices connected to the internet raises concerns about the security and privacy of smart homes. The effectiveness of interventions to support secure user behaviors is limited by a lack of validated instruments to measure relevant psychological constructs, such as self-efficacy - the belief that one is able to perform certain behaviors. We developed and validated the Cybersecurity Self-Efficacy in Smart Homes (CySESH) scale, a 12-item unidimensional measure of domain-specific self-efficacy beliefs, across five studies (N = 1247). Three pilot studies generated and refined an item pool. We report evidence from one initial and one major, preregistered validation study for (1) excellent reliability (α = 0.90), (2) convergent validity with self-efficacy in information security (rSEIS = 0.64, p < .001), and (3) discriminant validity with outcome expectations (rOE = 0.26, p < .001), self-esteem (rRSE = 0.17, p < .001), and optimism (rLOT-R = 0.18, p < .001). We discuss CySESH's potential to advance future HCI research on cybersecurity, practitioner user assessments, and implications for consumer protection policy.
Keywords
- cybersecurity, scale development, self-efficacy, smart homes, validation
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
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Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23). 2023. 507 (Conference on Human Factors in Computing Systems - Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Home Is Where the Smart Is
T2 - Development and Validation of the Cybersecurity Self-Efficacy in Smart Homes (CySESH) Scale
AU - Borgert, Nele
AU - Reithmaier, Oliver D.
AU - Jansen, Luisa
AU - Hillemann, Larina
AU - Hussey, Ian
AU - Elson, Malte
N1 - Publisher Copyright: © 2023 Owner/Author.
PY - 2023/4/19
Y1 - 2023/4/19
N2 - The ubiquity of devices connected to the internet raises concerns about the security and privacy of smart homes. The effectiveness of interventions to support secure user behaviors is limited by a lack of validated instruments to measure relevant psychological constructs, such as self-efficacy - the belief that one is able to perform certain behaviors. We developed and validated the Cybersecurity Self-Efficacy in Smart Homes (CySESH) scale, a 12-item unidimensional measure of domain-specific self-efficacy beliefs, across five studies (N = 1247). Three pilot studies generated and refined an item pool. We report evidence from one initial and one major, preregistered validation study for (1) excellent reliability (α = 0.90), (2) convergent validity with self-efficacy in information security (rSEIS = 0.64, p < .001), and (3) discriminant validity with outcome expectations (rOE = 0.26, p < .001), self-esteem (rRSE = 0.17, p < .001), and optimism (rLOT-R = 0.18, p < .001). We discuss CySESH's potential to advance future HCI research on cybersecurity, practitioner user assessments, and implications for consumer protection policy.
AB - The ubiquity of devices connected to the internet raises concerns about the security and privacy of smart homes. The effectiveness of interventions to support secure user behaviors is limited by a lack of validated instruments to measure relevant psychological constructs, such as self-efficacy - the belief that one is able to perform certain behaviors. We developed and validated the Cybersecurity Self-Efficacy in Smart Homes (CySESH) scale, a 12-item unidimensional measure of domain-specific self-efficacy beliefs, across five studies (N = 1247). Three pilot studies generated and refined an item pool. We report evidence from one initial and one major, preregistered validation study for (1) excellent reliability (α = 0.90), (2) convergent validity with self-efficacy in information security (rSEIS = 0.64, p < .001), and (3) discriminant validity with outcome expectations (rOE = 0.26, p < .001), self-esteem (rRSE = 0.17, p < .001), and optimism (rLOT-R = 0.18, p < .001). We discuss CySESH's potential to advance future HCI research on cybersecurity, practitioner user assessments, and implications for consumer protection policy.
KW - cybersecurity
KW - scale development
KW - self-efficacy
KW - smart homes
KW - validation
UR - http://www.scopus.com/inward/record.url?scp=85160013782&partnerID=8YFLogxK
U2 - 10.1145/3544548.3580860
DO - 10.1145/3544548.3580860
M3 - Conference contribution
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23)
ER -