ArticleJMIR mHealth and uHealth2022
Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework.
Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Chatbots That Deliver Contraceptive Support: Systematic Review.Journal of medical Internet research · 2024Pooled it
- A Chatbot-Delivered Stress Management Coaching for Students (MISHA App): Pilot Randomized Controlled Trial.JMIR mHealth and uHealth · 2024Trial
- Systematic and Collaborative Approach to Learning and Educational Content Development (SCALED) for Health Apps: An Experience-Informed Conceptual Framework.JMIR mHealth and uHealth · 2026Article
- A Chatbot to Meet Parents' Information Needs for Sickle Cell Trait Newborn Screening Results: Multiple Methods Formative Study.Journal of medical Internet research · 2026Article
- "An App That Truly Works for Us": Co-Designing a Mobile Health Intervention to Support the Transition to Adulthood for the Latino Autism Community.Journal of technology in behavioral science · 2026Article
- Chatbots as frontline educators in sexual reproductive health rights: evidence, limitations, and ethical considerations.Frontiers in digital health · 2026Article
- Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.Frontiers in public health · 2026Article
- Article
- Assessing the practicality of using freely available AI-based GPT tools for coach learning and athlete development.Frontiers in sports and active living · 2025Article
- Persuasive chatbot-based interventions for depression: a list of recommendations for improving reporting standards.Frontiers in psychiatry · 2025Article
- Think FAST: a novel framework to evaluate fidelity, accuracy, safety, and tone in conversational AI health coach dialogues.Frontiers in digital health · 2025Article
- Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review.Journal of medical Internet research · 2024Review
- Article
- Psychosocial Functioning of Individuals at Risk of Developing Compulsive Buying Disorder.Journal of clinical medicine · 2024Article
- Person-based design and evaluation of MIA, a digital medical interview assistant for radiology.Frontiers in artificial intelligence · 2024Article
- ChatGPT, GPT-4, and Other Large Language Models: The Next Revolution for Clinical Microbiology?Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Conversational Agents in Health Care: Expert Interviews to Inform the Definition, Classification, and Conceptual Framework.Journal of medical Internet research · 2023Article
- Chatbots to Improve Sexual and Reproductive Health: Realist Synthesis.Journal of medical Internet research · 2023Review
- Framework for Guiding the Development of High-Quality Conversational Agents in Healthcare.Healthcare (Basel, Switzerland) · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundConversational agents (CAs), also known as chatbots, are computer programs that simulate human conversations by using predetermined rule-based responses or artificial intelligence algorithms. They are increasingly used in health care, particularly via smartphones. There is, at present, no conceptual framework guiding the development of smartphone-based, rule-based CAs in health care. To fill this gap, we propose structured and tailored guidance for their design, development, evaluation, and implementation.
objectiveThe aim of this study was to develop a conceptual framework for the design, evaluation, and implementation of smartphone-delivered, rule-based, goal-oriented, and text-based CAs for health care.
methodsWe followed the approach by Jabareen, which was based on the grounded theory method, to develop this conceptual framework. We performed 2 literature reviews focusing on health care CAs and conceptual frameworks for the development of mobile health interventions. We identified, named, categorized, integrated, and synthesized the information retrieved from the literature reviews to develop the conceptual framework. We then applied this framework by developing a CA and testing it in a feasibility study.
resultsThe Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER) conceptual framework includes 8 iterative steps grouped into 3 stages, as follows: design, comprising defining the goal, creating an identity, assembling the team, and selecting the delivery interface; development, including developing the content and building the conversation flow; and the evaluation and implementation of the CA. They were complemented by 2 cross-cutting considerations-user-centered design and privacy and security-that were relevant at all stages. This conceptual framework was successfully applied in the development of a CA to support lifestyle changes and prevent type 2 diabetes.
conclusionsDrawing on published evidence, the DISCOVER conceptual framework provides a step-by-step guide for developing rule-based, smartphone-delivered CAs. Further evaluation of this framework in diverse health care areas and settings and for a variety of users is needed to demonstrate its validity. Future research should aim to explore the use of CAs to deliver health care interventions, including behavior change and potential privacy and safety concerns.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.