Applying the technology acceptance model to digital mental health interventions: a qualitative exploration with adults with intellectual disabilities

Vereenooghe, Leen; Trussat, Felix; Klose, Katja

doi:10.31234/osf.io/vtbr7

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…On the other hand, self-efficacy was found to be a strong factor in the adoption of technology by individuals with orthopedic disabilities (Cho & Lee, 2020). It has been stated that the usefulness of the relevant technology, ease of use, in other words, accessibility for the sense of hearing and vision are the most important factors in the use of technology and feeling self-sufficient in individuals with hearing and vision impairments (Vereenooghe et al, 2020).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

University Students with Special Needs in the E-Learning System: Characteristics, Experiences and Competencies

Yıldız

Şahin

Doğan

2022

Anadolu Journal of Educational Sciences International

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Individuals with special needs consist of different groups with individual differences such as hearing impairment, visual impairment, orthopedic and developmental disability, and health-related deficiencies. Main purpose of special education is to create flexible learning environments adapted to the individual differences of these individuals. It is possible to see that e-learning systems used in online learning environments have become an indispensable element of education these days when we transition to digital age. For these individuals to use e-learning systems effectively, it must first be determined how they use e-learning systems, what level of competence they have in using these systems, and what kind of support they need. The aim of the research is to determine demographic characteristics of individuals with special needs, their experiences in distance education and e-learning process, their proficiency levels, and assistive technologies they use. In this study, case study design was used. 590 university students with special needs participated in study. Data were collected through a questionnaire consisting of open and closed-ended questions. Quantitative data were analyzed descriptively using SPSS 21. Answers obtained from the open-ended questions were analyzed qualitative descriptive analysis. According to study, individuals continue open and distance education actively. It was observed that male students participating in the study were more numerous than female students, and students with visual impairment were more numerous than other disability groups. It has been concluded that most of the participants have very low experience in e-learning systems and they see themselves having very low competence levels. Also, the results showed that the participants use various assistive technologies that support hearing and vision in e-learning systems. According to the findings, it can be stated that there is a need to consider individual differences in design process of e-learning systems, to include user-oriented designs, and to provide individual assistive technologies.

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Section: Conclusion and Discussionmentioning

confidence: 99%

University Students with Special Needs in the E-Learning System: Characteristics, Experiences and Competencies

Yıldız

Şahin

Doğan

2022

Anadolu Journal of Educational Sciences International

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“…These findings indicate that the beliefs of students with disability in their own knowledge and skills in the context of performing a task using technology influence their perceptions of the performance increase they will achieve by using technology and their intention to continue using information technologies. It has been stated that the perceived usefulness and ease of use affect adopting digital mental health applications for intellectual disability (Vereenooghe et al, 2020). It was concluded that hearing loss alone does not have an effect on academic achievement in hearing impaired students who continue distance education, but additional disabilities and severe hearing impairment have a negative effect on the academic performance of students (Richardson, 2015).…”

Section: Introductionmentioning

confidence: 99%

Influential factors on e‐learning adoption of university students with disability: Effects of type of disability

Yıldız

Şahin

Doğan

et al. 2022

Brit J Educational Tech

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The number of studies providing empirical evidence on e‐learning in the field of special education is limited. From this point of view, the aim of this study is to examine whether the factors influencing the e‐learning adoption of university students with disability differ according to the type of disability and gender. The participants of the study consist of 809 university students with a single disability (orthopaedic, visual or hearing). Confirmatory factor analysis and two‐way ANOVA were used in the analysis of the study. The factor analysis showed that validity and reliability of the measurement tool was established and the model fit was good. The results revealed that for all dependent variables (social influence, self‐efficacy, compatibility and facilitating conditions), students with orthopaedic disability and visual impairment had higher scores than students with hearing impairment. On the other hand, contrary to expectations, there was no difference between students with orthopaedic disability and students with visual impairment in any of the factors according to the type of disability. In addition, none of the factors differed by gender. The findings provide empirical evidence that can contribute to the planning of online education processes of students with disability by revealing the similarities and differences in the use of e‐learning systems according to the type of disability. What is already known about this topic The field of special education deals with the special needs of individuals and frequently uses technology to provide the support they need. It is observed that educational processes have been moved to online environments due to the COVID‐19 pandemic, which has affected the field of education nowadays and e‐learning systems in online environments have become indispensable for students with special needs. With their flexible structure, e‐learning systems create universal and inclusive learning environments for all students. Accessibility and special education adaptations are needed for individuals with special needs to use e‐learning systems effectively. For this, first of all, the effects of the disabilities of these individuals in using e‐learning systems should be determined. What this paper adds The results showed that social influence, self‐efficacy, compatibility, and facilitating conditions all differed significantly by type of disability. The research findings revealed that all factors differed significantly in terms of orthopaedic and visual impairment versus hearing impairment. The main contribution of the study can be summarized as investigating the relationships between technology adoption and types of disability with empirical evidence and the fact that the implications and inferences made for theory and practice have the potential to make critical contributions to technology acceptance and use of individuals with special needs. It can be stated that the tool adapted in this study offers a valid and reliable tool for future studies with university students with special n...

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An Approach to Potentially Increasing Adoption of an Artificial Intelligence–Enabled Electronic Medical Record Encounter in Canadian Primary Care: Protocol for a User-Centered Design

Francisco,

Burns

2024

JMIR Res Protoc

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Background Primary care physicians are at the forefront of the clinical process that can lead to diagnosis, referral, and treatment. With electronic medical records (EMRs) being introduced and, over time, gaining acceptance by primary care users, they have now become a standard part of care. EMRs have the potential to be further optimized with the introduction of artificial intelligence (AI). There has yet to be a widespread exploration of the use of AI in primary health care and how clinicians envision AI use to encourage further uptake. Objective The primary objective of this research is to understand if the user-centered design approach, rooted in contextual design, can lead to an increased likelihood of adoption of an AI-enabled encounter module embedded in a primary care EMR. In this study, we use human factor models and the technology acceptance model to understand the results. Methods To accomplish this, a partnership has been established with an industry partner, TELUS Health, to use their EMR, the collaborative health record. The overall intention is to understand how to improve the user experience by using user-centered design to inform how AI should be embedded in an EMR encounter. Given this intention, a user-centered approach will be used to accomplish it. The approach of user-centered design requires qualitative interviewing to gain a clear understanding of users’ approaches, intentions, and other key insights to inform the design process. A total of 5 phases have been designed for this study. Results As of March 2024, a total of 14 primary care clinician participants have been recruited and interviewed. First-cycle coding of all qualitative data results is being conducted to inform redesign considerations. Conclusions Some limitations need to be acknowledged related to the approach of this study. There is a lack of market maturity of AI-enabled EMR encounters in primary care, requiring research to take place through scenario-based interviews. However, this participant group will still help inform design considerations for this tool. This study is targeted for completion in the late fall of 2024. International Registered Report Identifier (IRRID) DERR1-10.2196/54365

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Applying the technology acceptance model to digital mental health interventions: a qualitative exploration with adults with intellectual disabilities

Cited by 4 publications

References 6 publications

University Students with Special Needs in the E-Learning System: Characteristics, Experiences and Competencies

University Students with Special Needs in the E-Learning System: Characteristics, Experiences and Competencies

Influential factors on e‐learning adoption of university students with disability: Effects of type of disability

An Approach to Potentially Increasing Adoption of an Artificial Intelligence–Enabled Electronic Medical Record Encounter in Canadian Primary Care: Protocol for a User-Centered Design

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