Search Articles

View query in Help articles search

Search Results (1 to 10 of 168 Results)

Download search results: CSV END BibTex RIS

CSV download: Download all 168 search results (up to 5,000 articles maximum)

Understanding Adherence to Digital Health Technologies: Systematic Review of Predictive Factors

Understanding Adherence to Digital Health Technologies: Systematic Review of Predictive Factors

These domains are initial adoption (starting use), consistency and duration (sustained engagement aligned with intended use), dropout (premature discontinuation), and intensity (depth or frequency of use) [13,16,17]. Accordingly, this conceptualization will guide how adherence is defined, analyzed, and interpreted in this review. Two related but distinct concepts are engagement and acceptance. Engagement refers to how individuals use and interact with the DHT, irrespective of the intended use.

Teodora Figueiredo, Leovaldo Alcântara, Joana Carrilho, Constança Paúl, Elísio Costa

J Med Internet Res 2025;27:e77362


Evaluation of Cancer Survivors’ Experience of Using AI-Based Conversational Tools: Qualitative Study

Evaluation of Cancer Survivors’ Experience of Using AI-Based Conversational Tools: Qualitative Study

However, there is a knowledge gap regarding the barriers and facilitators that influence the adoption and use of AI chatbots among cancer survivors [20]. Examining the user acceptance of chatbots in cancer care is essential for determining how patients, caregivers, and HCPs incorporate these tools into their decision-making and support systems [21]. Patients with cancer require highly personalized and trustworthy information.

Saif Khairat, Hanna Mehraby, Safoora Masoumi, Melissa Coffel, Callie Rockey-Bartlett, Andrea Huang, William Wood, Ethan Basch

JMIR Cancer 2025;11:e77390


Exploring Attitudes and Obstacles Around Digital Public Health Tools: Insights From a Statewide Cross-Sectional Survey on Washington’s Vaccine Verification System

Exploring Attitudes and Obstacles Around Digital Public Health Tools: Insights From a Statewide Cross-Sectional Survey on Washington’s Vaccine Verification System

The Technology Acceptance Model (TAM) provides such a framework for understanding the adoption of emerging health-focused technologies. TAM proposes that perceived usefulness (the belief that using a given technology can improve the ability to perform a task) and perceived ease of use (the belief that the technology is easy to use) determine attitudes toward technology adoption [15]. While these 2 beliefs can be measured independently, TAM posits that perceived ease of use influences perceived usefulness.

Andrea R Molino, Debra Revere, Rebecca A Hills, Adam S Elder, Laura M West, Bryant T Karras, Chris Baumgartner, Janet G Baseman

J Med Internet Res 2025;27:e66550


Health Care Professionals’ Experiences Regarding Facilitators of and Barriers to Sustained Use of Social Robot Ivy for People With Intellectual Disabilities: Qualitative Interview Study

Health Care Professionals’ Experiences Regarding Facilitators of and Barriers to Sustained Use of Social Robot Ivy for People With Intellectual Disabilities: Qualitative Interview Study

We investigated the staff perspective as their perceptions play a key role in the adoption of social robots [16,17]. Our research questions were as follows: What value does sustained use of social robot Ivy create for people with intellectual disabilities and health care professionals? What facilitators and barriers influence the continuation versus abandonment of use of social robot Ivy during the execution and continuation phases of implementation?

Mark Steins, Claire Huijnen, Gaby Odekerken-Schröder, Dominik Mahr, Kars Mennens, Ramon Daniels, Frank Mathmann

J Med Internet Res 2025;27:e74168


Using Theory-Based Frameworks to Identify Barriers and Enablers of Physicians’ Telemedicine Adoption and Develop Intervention Strategies in China: Multicenter Qualitative Study

Using Theory-Based Frameworks to Identify Barriers and Enablers of Physicians’ Telemedicine Adoption and Develop Intervention Strategies in China: Multicenter Qualitative Study

Barrier-related themes to physicians’ (n=36) adoption of telemedicine. Enabler-related themes for physicians’ (n=36) adoption of telemedicine. Available resources and the environment influence a physician’s inclination to perform [46]. Environmental context and resources have emerged as key barriers to using telemedicine.

Xinxia Wu, Yuting Yang, Yuchan Li, Yuhan Li, Huixian Li, Yanli Lyu, Ke Liu, Tracy Liu, Zheng Hou, Ke Zhang, Xuedong Xu, Changxiao Jin, Yipei Wang

J Med Internet Res 2025;27:e73412


Enabling Physicians to Make an Informed Adoption Decision on Artificial Intelligence Applications in Medical Imaging Diagnostics: Qualitative Study

Enabling Physicians to Make an Informed Adoption Decision on Artificial Intelligence Applications in Medical Imaging Diagnostics: Qualitative Study

Researching technology adoption on an individual level is a core focus of IS research [14,15]. Adoption primarily concerns the individual user’s acceptance of technology as well as the adoption decision [15,16]. To explain technology adoption, the most well-known IS theories from an individual perspective are the Technology Adoption Model (TAM) [21] and the Unified Theory of Acceptance and Use of Technology (UTAUT) [14].

Jasmin Hennrich, Eileen Doctor, Marc-Fabian Körner, Reeva Lederman, Torsten Eymann

J Med Internet Res 2025;27:e63668


Adoption of Personal Health Records in Dutch Hospitals and Private Medical Clinics: Longitudinal Study

Adoption of Personal Health Records in Dutch Hospitals and Private Medical Clinics: Longitudinal Study

Although many studies examine the functionality, accessibility, and usability of PHRs, as well as their barriers and benefits [5,9,10,12], fewer studies focus on PHR adoption by patients and health care professionals [14], which is essential to ensure PHR usage. Rouleau et al [15] mapped the theories, models, and frameworks in a scoping review that addressed the adoption, implementation, and embedment of e Health.

Doris van der Smissen, Christine Leenen-Brinkhuis, Kim M E Janssens, Petra J Porte, Marcel A L M van Assen, Anne Marie Weggelaar-Jansen

J Med Internet Res 2025;27:e71915


Attitudes, Perceptions, and Factors Influencing the Adoption of AI in Health Care Among Medical Staff: Nationwide Cross-Sectional Survey Study

Attitudes, Perceptions, and Factors Influencing the Adoption of AI in Health Care Among Medical Staff: Nationwide Cross-Sectional Survey Study

It is equally crucial to explore the factors associated with the attitudes and perceptions of medical staff toward the adoption of AI in health care. Previous studies have demonstrated that variations in views on AI can be ascribed to a range of factors, including age, sex, educational level, and experience related to AI [15].

Qianqian Dai, Ming Li, Maoshu Yang, Shiwu Shi, Zhaoyu Wang, Jiaojiao Liao, Zhaoji Li, Weinan E, Liyuan Tao, Yi-Da Tang

J Med Internet Res 2025;27:e75343


Factors Influencing the Implementation and Adoption of Digital Nursing Technologies: Systematic Umbrella Review

Factors Influencing the Implementation and Adoption of Digital Nursing Technologies: Systematic Umbrella Review

Given their central role in patient care, nurses are key users of digital nursing technologies (DNTs) and play a crucial role in their adoption and effective implementation in nursing care settings [6].

Stefan Walzer, Christoph Armbruster, Sonja Mahler, Erik Farin-Glattacker, Christophe Kunze

J Med Internet Res 2025;27:e64616