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A Personal Resource for Technology Interaction: Development and Validation of the Affinity for Technology Interaction (ATI) Scale
Abstract
Successful coping with technology is relevant for mastering daily life. Based on related conceptions, we propose affinity for technology interaction (ATI), defined as the tendency to actively engage in intensive technology interaction, as a key personal resource for coping with technology. We present the 9-item ATI scale, an economical unidimensional scale that assesses ATI as an interaction style rooted in the construct need for cognition (NFC). Results of multiple studies (n > 1500) showed that the scale achieves good to excellent reliability, exhibits expected moderate to high correlations with geekism, technology enthusiasm, NFC, self-reported success in technical problem-solving and technical system learning success, and also with usage of technical systems. Further, correlations of ATI with the Big Five personality dimensions were weak at most. Based on the results, the ATI scale appears to be a promising tool for research applications such as the characterization of user diversity in system usability tests and the construction of general models of user-technology interaction.
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“Additionally, we administered the Afnity for Technology Interaction Scale (ATI) [41] to determine participants' level of comfort and familiarity with technology [120].”
From Dealing with Uncertainty: Understanding the Impact of Prognostic Versus Diagnostic Tasks on Trust and Reliance in Human-AI Decision Making (2024) · cites this paper as [41]
In the citing paper
“We measured Affinity for Technology Interaction ( α = .92) using the scale from Franke et al. [50], which measures the construct on a 9-item scale.”
From Is FIDO2 the Kingslayer of User Authentication? A Comparative Usability Study of FIDO2 Passwordless Authentication (2020) · cites this paper as Franke et al. [50]
In the citing paper
“On the other hand, the ATI scores, which usually correlate negatively with the age variable, are in our sample comparable to other studies that had a much more diverse age distribution among their participants (e.g., [50]).”
From Is FIDO2 the Kingslayer of User Authentication? A Comparative Usability Study of FIDO2 Passwordless Authentication (2020) · cites this paper as [50]
In the citing paper
“Technical affinity was measured with the Affinity for Technology Interaction Scale (Franke et al., 2019). The questionnaire was answered on a 6-point scale ranging from (1) strongly disagree to (6) strongly agree (Cronbach α = 0.93).”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Franke et al., 2019
In the citing paper
“We used the Affinity for Technology Interaction scale by Franke et al [ 61 ], which consists of 9 items.”
From Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists (2025) · cites this paper as [61]
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Metadata
- Authors
- Franke, T., Attig, C., & Wessel, D.
- Affiliations
- University of Lübeck (DE)
- Chemnitz University of Technology (DE)
- Corresponding author
- Franke, Thomas
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2018-03-30
- Volume
- 35
- Issue
- 6
- Pages
- 456-467
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W2794740256
- Cited by
- 828
- References
- 63
- Citations by year
- 2026: 140 · 2025: 172 · 2024: 150 · 2023: 128 · 2022: 101 · 2021: 73 · 2020: 43 · 2019: 15 · 2018: 6
- FWCI
- 63.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Funders
- European Social Fund and the Free State of Saxony (100269974)
- Topics
- Social Sciences › Gender Studies › Gender and Technology in Education
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- technology interaction, need for cognition, scale development, technical problem solving, user heterogeneity, Big Five personality traits
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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