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Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study
7 references·0 citing·36 second hopsampled
Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study (2023)Adoption of Wearable Insulin Biosensors f…Acceptance of Artificial Intelligence Application in the Post-Covid Era and Its Impact on Faculty Members’ Occupational Well-being and Teaching Self Efficacy: A Path Analysis Using the UTAUT 2 Model (2023)Acceptance of Artificial Inte…What factors contribute to the acceptance of artificial intelligence? A systematic review (2022)What factors contribute to th…Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants (2022)Application and extension of …Understanding Factors Influencing Elderly Diabetic Patients’ Continuance Intention to Use Digital Health Wearables: Extending the Technology Acceptance Model (TAM) (2020)Understanding Factors Influen…Exploring the Usage Intentions of Wearable Medical Devices: A Demonstration Study (2020)Exploring the Usage Intention…Behaviour change in diabetes: behavioural science advancements to support the use of theory (2019)Behaviour change in diabetes:…The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education (2017)The Use of Cronbach’s Alpha W…Coefficient Alpha and the Internal Structure of Tests (1951)What is coefficient alpha? An examination of theory and applications. 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(2008)The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions (2013)Behavior change in diabetes practitioners: An intervention using motivation, action planning and prompts (2020)Health Behavior Change (2021)How is the NHS Low-Calorie Diet Programme expected to produce behavioural change to support diabetes remission: An examination of underpinning theory (2022)Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)The theory of planned behavior (1991)Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives (1999)Impact of the Moderating Effect of National Culture on Adoption Intention in Wearable Health Care Devices: Meta-analysis (2022)User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology (2022)Attention based hybrid deep learning model for wearable based stress recognition (2023)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)Alternative Ways of Assessing Model Fit (1992)User Acceptance of Information Technology: Toward A Unified View1 (2003)Assessing the factors that influence the adoption of healthcare wearables by the older population using an extended PMT model (2022)A Study on Technology Acceptance of Digital Healthcare among Older Korean Adults Using Extended Tam (Extended Technology Acceptance Model) (2023)The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology (2025)The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration (2009)Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework (2023)Generative Artificial Intelligence Acceptance Scale: A Validity and Reliability Study (2023)Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial Intelligence (2024)User Acceptance of Computer Technology: A Comparison of Two Theoretical Models (1989)Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1 (2012)Predicting Adoption Intention of Artificial Intelligence ChatGPT (2023)Acceptance of Educational Use of AI Chatbots in the Context of Self-Directed Learning with Technology and ICT Self-Efficacy of Undergraduate Students (2024)Students' behavioural intention to use content generative AI for learning and research: A UTAUT theoretical perspective (2025)Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory (2024)Economics students’ behavioural intention and usage of ChatGPT in higher education: a hybrid structural equation modelling-artificial neural network approach (2024)Evaluating privacy, security, and trust perceptions in conversational AI: A systematic review (2024)
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References

  • 2017The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education12,129 cited
  • 2022What factors contribute to the acceptance of artificial intelligence? A systematic review1,187 cited
  • 2022Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants148 cited
  • 2020Understanding Factors Influencing Elderly Diabetic Patients’ Continuance Intention to Use Digital Health Wearables: Extending the Technology Acceptance Model (TAM)120 cited
  • 2023Acceptance of Artificial Intelligence Application in the Post-Covid Era and Its Impact on Faculty Members’ Occupational Well-being and Teaching Self Efficacy: A Path Analysis Using the UTAUT 2 Model105 cited
  • 2019Behaviour change in diabetes: behavioural science advancements to support the use of theory66 cited
  • 2020Exploring the Usage Intentions of Wearable Medical Devices: A Demonstration Study36 cited

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