e.g. mhealth
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Skip search results from other journals and go to results- 5 Journal of Medical Internet Research
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The study team reviewed the initial prompt, tested the AI feedback agent by having conversations with the VSP, and worked with the designer to amend the prompt and address unexpected behaviors or technical challenges as they arose.
To provide context to the AI debriefing agent, the designer prompted the agent to play the role of an experienced clinician and educator:
You are an expert physician with years of experience and a clinical educator at the hospital simulation center.
JMIR Form Res 2025;9:e65670
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“Agenti() ⇒ Agentj()” or “Agenti() ⇐ Agentj()”: Indicates that the message is being passed to another agent. A message declaration needs to be specified on the sender side and a rule declaration on the receiver side.
“then”: Indicates that the clause before it must continue the clause after it.
J Med Internet Res 2025;27:e55341
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This may be particularly advantageous in adolescent MH interventions, as this group is well-versed in conversational agent and texting interactions [19]. Such interactions may improve users’ treatment responsiveness to interventions [20,21].
Woebot for Adolescents (W-Gen ZD) is an investigational mobile app with a relational agent, “Woebot,” that offers a CBT-guided self-help program designed to reduce symptoms of depression and/or anxiety.
JMIR Res Protoc 2023;12:e44940
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Therefore, we further developed our agent-based simulation model of Washington, DC to test the impact of such a place-tailored digital health app.
All authors’ institutions were included in the institutional review board approval (IRB #00004203) at Johns Hopkins as the study began while certain members of the research team (MCF, KJO, YA, MM, SMB, PTW, SS, SR, MSG, MD, KR, DH, RS, and BYL) were based at Johns Hopkins.
J Med Internet Res 2022;24(8):e30581
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Interactive Versus Static Decision Support Tools for COVID-19: Randomized Controlled Trial
The other tool was implemented as a simple, interactive conversational agent, where participants clicked buttons to respond to questions, guiding them through the nodes of the decision tree step-by-step (Multimedia Appendix 2). The individual screens of the interactive DST were also designed using Microsoft Power Point and then linked together using In Vision [30], enabling dynamic interaction.
JMIR Public Health Surveill 2022;8(4):e33733
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Intervention delivery characteristics of the companies’ digital behavior change interventions.
a DBCI: digital behavior change intervention.
b HHP: human health professional.
c CA: conversational agent.
d—app not accessible.
e Hb A1c: glycated hemoglobin A1c.
f GPS: Global Positioning System.
g INR: Indian Rupee.
h CHF: Swiss Franc.
The findings regarding the usage of self-reports as well as sensor and device analytics are summarized in Figure 2.
J Med Internet Res 2022;24(1):e33348
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An Agent-Based Model of the Local Spread of SARS-CoV-2: Modeling Study
Agent-based models (ABMs) are a class of computational models based on computer simulations of actions and interactions of autonomous agents, aimed at evaluating how these actions affect the system as a whole. The agent-based approach emphasizes the importance of learning through the agent-environment interaction. This approach is part of a recent trend in the computational models of learning toward developing new ways of studying autonomous organisms in virtual or real environments.
JMIR Med Inform 2021;9(4):e24192
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We hypothesized that a virtual agent made available via a smartphone app would be efficient and acceptable not only in providing autonomous screening for insomnia complaints but also in establishing digital behavioral interventions to help the population during the COVID-19 crisis. Therefore, to test our hypothesis, we launched a proof-of-concept study during the COVID-19 confinement.
J Med Internet Res 2020;22(12):e24268
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