The Impact of Subjective Technology Adaptivity on the Willingness of Persons with Disabilities to Use Emerging Assistive Technologies: A European Perspective
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Alexandra König, Laura Alčiauskaitė, Tally Hatzakis
Emerging digital technologies like augmented reality (AR) hold promising prospects for people with disabilities. It remains, however, an open question how persons with disabilities respond to technological demands. The paper examines the potential impact of users’ self-assessment of their own competence in using these technologies on users’ responses by examining their Subjective Technology Adaptivity (STA) [1] and use intention to study the relationship between their self-assessed adaptivity and volitional technology use. To this end, data from 545 Europeans with different types of disabilities were collected based on an online survey. The research focused on six emerging assistive technologies related to mobility: accessible navigation systems, artificial intelligence alerts, wearables, robots, augmented reality and location-based alerts. The results show that the adaptivity to technology of people with disabilities predicts the use intention for emerging assistive technologies. There was, however, great variability depending on the type of disability. For example, a high STA of people with physical, visual, hearing or intellectual impairments predicted their willingness to use intention of AI-based alters but not for people with mental health issues or multiple impairments. Our findings shed new light on the role of perceived technology adaptivity of persons with disabilities for future technology use intention.
1 Introduction
The emergence of new digital technologies is accompanied by a significant growth in the diversity and availability of assistive technologies. Advances in artificial intelligence, Big Data analytics for robotics or augmented reality offer promising perspectives for persons with disabilities in the next years [2‐4]. However, we need to know more about the willingness of persons with disabilities to use emerging technologies and the determinants of their use intention. One approach to studying the determinants of technology use of persons with disabilities is the concept of digital capital [5], that is inspired by Bourdieu’s (1997) notions of social and cultural capital [6] It can be described as a person’s technological competencies and knowledge that enable her or him to use technology [7]. A related concept, that focusses on the individual’s perception of its own abilities to deal with technologies, is the concept of Subjective Technology Adaptivity (STA), defined as “an individual’s response to technological demands that are associated with improved competence, and with more frequent use of technology” [1, p. 16]. It was shown that the higher the score of the STA, the more interest in technological innovations and the more confidence while dealing with technology people exhibit [8]. It was shown that subjective technology adaptivity predicts technology use in higher age [1], but the concept has not been applied to the group of people with disabilities before. The paper aims to answer to the research question: Does adaptivity to technology predict the willingness of persons with disabilities to use emerging assistive technologies?
2 Methodology
2.1 Online Survey
To answer the research question, a survey study was conducted. The survey was conducted under the auspices of the European research project TRIPS (Transport Innovation for disabled People needs Satisfaction, https://trips-project.eu/). The survey focused on 13 future assistive technologies that were identified and reviewed within the TRIPS project [9]. For this paper, we report on six emerging technologies of wider appeal: accessible navigation systems, artificial intelligence (AI) alerts, wearables, robots, augmented reality (AR) and location-based alerts [10]. These technologies could potentially assist persons with various types of disabilities, as well as non-disabled users.
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The survey items were based on preceding qualitative research that was conducted to identify barriers of current transport use for persons with disabilities [11]. Besides an English version, the questionnaire was translated into 14 languages (Bulgarian, Croatian, Dutch, French, German, Greek, Italian, Lithuanian, Polish, Portuguese, Romanian, Russian, Spanish and Swedish).
Use intention for the assistive technologies was measured using one single question (Would you use this system?) in a 5-point Likert scale with 1 = never, 2 = rarely, 3 = sometimes, 4 = frequently and 5 = always. Subjective technology adaptivity (STA) was measured using the Subjective Technology Adaptivity Inventory (STAI) [1]. STAI consists of 15 items regarding three dimensions: Technology-related Goal-Engagement (TGE), e.g., “I invest as much effort as I can until a device works as intended”, Perceived Adaptive Utility (PAU), e.g., “Using modern technology helps me to master everyday life”, Perceived Safety of Technology (PST), e.g., “I trust modern technology”. Responses are given using a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) (Fig. 1).
The survey was conducted online via the project website, using the software SoSciSurvey. The survey was disseminated by TRIPS project partners and local disability user groups in seven EU cities and in European-wide NGOs working in the field of disability. More than 100 organizations had been contacted to disseminate the invitation to the survey via newsletter or social media. Data was collected from November 2020 until February 2021.
Fig. 1.
Exemplary questions from the survey
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2.2 Study Participants
Overall, 872 completed responses were submitted. After the exclusion of people from non-European countries and persons who do not identify themselves as having a disability, the final sample consisted of 545 participants from 21 European countries. The sample comprised 253 women (45.8%) and 284 men (51.4%, rest missing). While a large proportion of participants (87.7%) answered the survey themselves, 68 surveys (12.3%) were answered by another person on behalf of a disabled person. The average age of the sample was 46.4 years (SD = 15.7). Persons with physical impairments were by far the largest group of respondents regarding the type of disability (n = 297, 53.7%), followed by visual impairments (n = 85, 15.4%), multiple impairments (n = 85, 15.4%), hearing impairments (n = 45, 8.1%), intellectual disabilities (n = 17, 3.1%), mental health issues (n = 16, 2.9%) and others (n = 6, 1.1%). It should be noted that a person with multiple impairments was assigned once and not multiple times according to his or her various impairments. Most people did not specify their kind of physical impairment using the free text field, which results in a big and heterogeneous group of people with disabilities.
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3 Results
3.1 Subjective Technology Adaptivity
According to Kamin & Lang (2013), the subjective technology adaptivity (STA) was calculated based on its components PAU, PST and TGE. Principal components analysis confirmed the three factors. The resulting STA was rather high with M = 3.81 (SD = 0.72). No significant differences in STA were identified between men (M = 3.83, SD = 0.72) and women (M = 3.81, SD = 0.73, (t(535) = 0.26, p = .793). Furthermore, no significant age effect was shown (r < .01, p = .920). However, the type of disability had an important effect on the STA (F(5,539) = 3.648, p = .003, ηp2 = .033). In detail, persons with visual impairments reported a significant higher STA (M = 3.99, SD = 0.64) than respondents with multiple impairments (M = 3.61, SD = 0.81, p = .003) (Fig. 2).
Fig. 2.
Mean STA according to kind of disability. Significant differences are indicated by an asterisk (p < .05).
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3.2 Use Intention for Emerging Technologies
Wearables, robots and location-based alerts were favored by the majority of respondents. A high use intention as stated by the selection of the option “frequently” or “always” was shown by 57.7% (n = 310) for wearables, 54% (n = 290) for robots, 47.1% (n = 253) for location-based alerts and 43,3% (n = 254) for augmented reality.
A descriptive analysis (Fig. 3) showed, that persons with multiple impairments showed a high use intention for all presented technologies, except accessible navigation systems that were deemed not applicable or unwilling to use them by 31.7% (n = 27). Persons with intellectual disabilities exhibited a high willingness to use to robots and a somewhat lower use intention to wearables and accessible navigation systems. Persons with mental health issues showed a similar high willingness to use for robots. Hearing-impaired individuals were particularly interested in artificial intelligence alerts and location-based alerts. Visually-impaired persons shared their high interest for artificial intelligence alerts and a furthermore showed a high willingness for accessible navigation systems and augmented reality. Persons with a physical impairment showed a high use intention for robots and wearables.
Fig. 3.
Use intention for future assistive technologies by type of disability in percent
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With regard to the relationship between the subjective technology adaptivity and the use intention for future assistive technologies, it was shown, that the correlation between the STA and the use intention was positive and significant for every assistive technology (Table 1). This implies that respondents who reported a higher subjective technology adaptivity are more willing to use the presented technologies in the future. A more detailed analysis regarding the effect disability on the relationship between STA and use intention based on linear regression showed, that the for physical impairments, the significant effect of STA on use intention remained appeared for all of the emerging mobility systems, but not for persons with mental health issues. As shown in Table 1, STA predicted the use intention for augmented reality for persons with physical (r = .18, p = .001, f = .18), visual (r = .26, p = .015, f = .27), and intellectual disabilities (r = .48, p = .049, f = .55), but not for the other groups. For respondents with multiple impairments, the significant relationship between STA and use intention was only shown for wearables (r = .29, p = .007, f = .30), and robots (r = .22, p = .049, f = .23). It should be emphasized, that the effect sizes of the relationship between the STA of persons with intellectual impairments and the use intention for AI-based alerts (r = .55, p = .021, f = .66), augmented reality (r = .48, p = .049, f = .55) and location-based alerts (r = .61, p = .009, f = .77) were large.
Table 1.
Linear regression of subjective technology adaptivity (STA) and intention to use emerging assistive technologies by type of disabilities. Regression coefficient (r), effect size (f) and p-value in brackets. Significant regressions are indicated in bold.
Physical
(n = 297)
Visual
(n = 85)
Hearing
(n = 45)
Ment. Health issues
(n = 16)
Intellectual
(n = 17)
Multiple
(n = 85)
Navigation systems
r = .15
f = .15
(.009)
r = .32
f = .34
(.003)
r = .29
f = .30
(.058)
r = .28
f = .29
(.300)
r = .31
f = .33
(.222)
r = .16
f = .16
(.141)
AI-based alerts
r = .14
f = .14
(.019)
r = .34
f = .36
(.002)
r = .34
f = .36
(.023)
r = .38
f = .41
(.143)
r = .55
f = .66
(.021)
r = .14
f = .14
(.192)
Wearables
r = .14
f = .14
(.013)
r = .25
f = .26
(.021)
r = .17
f = .17
(.254)
r = .13
f = .13
(.624)
r = .36
f = .39
(.155)
r = .29
f = .30
(.007)
Robots
r = .25
f = .26
(.001)
r = .20
f = .20
(.065)
r = .32
f = .34
(.032)
r = .16
f = .16
(.561)
r = .27
f = .28
(.032)
r = .22
f = .23
(.049)
Augmented reality
r = .17
f = .17
(.003)
r = .26
f = .27
(.015)
r = .13
f = .13
(.393)
r = .01
f = .01
(.998)
r = .48
f = .55
(.049)
r = .19
f = .19
(.078)
Location-based alerts
r = .21
f = .21
(.001)
r = .14
f = .14
(.193)
r = .30
f = .31
(.043)
r = .12
f = .12
(.667)
r = .61
f = .77
(.009)
r = .09
f = .09
(.405)
4 Discussion
This pan-European study showed that out of the six options the most preferred emerging technologies were wearables, robots, augmented reality and location-based alerts. Some variations on the degree of use intention were observed depending on the type of disability. Some unexpected findings require further research to explain; for example, (a) the preference of visually impaired individuals for augmented reality; (b) variations in intention to use of wearables and location-based alerts, yet not for other technologies depending on age; (c) the slightly higher preference for robots by women as opposed to men. Furthermore, some assistive technologies experienced a lower or higher use intention depending on the type of disability. For example, wearables were attributed a high use intention by persons having physical or multiple impairments, but a rather low intention for persons with hearing impairments. Such findings suggest that certain disability or impairment is not necessarily a key limitation for persons in using an assistive technology and perhaps other factors play an important role when it comes to use intention or alternative uses of such technologies are envisioned by users.
It was shown that the resulting STA was comparable to the mean STA of elderly in the study by [1]. However, the construct PAU showed a higher mean in this sample than in the group of elderly, indicating that persons with disabilities assess the perceived adaptive utility of technologies higher than elderly. However, comparable data of STA from a group of users who have no disability is still lacking.
With regard to the research question, it was shown that a disabled person’s adaptivity to technology predicts the willingness to use emerging assistive technologies. However, the analyses indicate that the relationship depends on the type of disability and the kind of technology. Whereas STA was a significant predictor for the use intention of AI-based alters for people with physical, visual, hearing or intellectual impairments, it was not for people with mental health issues or multiple impairments. Interestingly, the effect sizes of the relationship between STA of people with intellectual impairments and the use intention for AI-based alerts, augmented reality and location-based alerts were high. It can be further concluded that the effect of subjective technology adaptivity on use intention for emerging mobility systems is not based on gender or age effects but more depending on the type of disability.
To conclude, our findings shed new light on the role of perceived technology adaptivity of persons with disability for future technology use intention. This may contribute to an improved understanding of psychological mechanisms of using technology and subsequently may result in a new view on the widespread deficit model of disability [12] and the rippled effects of the digital divide [13]. The results underline the importance of education for improving person’s adaptivity to technology though equiping them with technological knowledge and improving their digital competences might help them to become more technical savvy and therefore, to be more open to new technology systems, which might help them to become more independent and overcome disability-related issues.
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The Impact of Subjective Technology Adaptivity on the Willingness of Persons with Disabilities to Use Emerging Assistive Technologies: A European Perspective
