Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Modeling in Therapy

Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...

Decision Making: Traditional Method

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...

Patient-centered Care

Patient-centered Care

Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...

Persuasion Strategies

Persuasion Strategies

Researchers have tested many persuasion strategies, including the foot-in-the door and the door-in-the-face techniques, in a variety of contexts. Ultimately, the principles are effective in selling products and changing people’s attitude, ideas, and behaviors (Cialdini & Goldstein, 2004).

Routes of Persuasion

Routes of Persuasion

Persuasion is the process of changing our attitude toward something based on some kind of communication. Much of the persuasion we experience comes from outside forces. How do people convince others to change their attitudes, beliefs, and behaviors? What communications do you receive that attempt to persuade you to change your attitudes, beliefs, and behaviors?

The Anchoring-and-Adjustment Heuristic

The Anchoring-and-Adjustment Heuristic

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Evaluating the accuracy of ChatGPT model versions for giving care-seeking advice.

Communications medicine·2026

Same author

How to Evaluate the Accuracy of Symptom Checkers and Diagnostic Decision Support Systems: Symptom Checker Accuracy Reporting Framework (SCARF).

JMIR human factors·2026

Same author

Privacy Fact Sheets for Mitigating Disease-Related Privacy Concerns and Facilitating Equal Access to the Electronic Health Record: Randomized Controlled Trial.

JMIR human factors·2026

Same author

Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial.

Journal of medical Internet research·2025

Same author

Generalizability in real-world trials.

Clinical and translational science·2024

Same author

Alarm Management in Intensive Care: Qualitative Triangulation Study.

JMIR human factors·2024

Same journal

Effect of a Spinal Orthosis With Leaf Spring and Programmable Local Vibration on Kyphosis Angle and Trunk Muscle Strength in Hyperkyphosis: Development and Feasibility Study.

JMIR biomedical engineering·2026

Same journal

Psychosocial Stress in the Chinese Community: Speech Analytics Through Linguistic and Acoustic Fusion Using Machine Learning.

JMIR biomedical engineering·2026

Same journal

Remote Monitoring of Bioelectrical Impedance in Patients With Breast Cancer-Related Lymphedema: 1-Year Pilot Longitudinal Study.

JMIR biomedical engineering·2026

Same journal

Age-Related Differences in Joint Kinematics and Spatiotemporal Parameters During Ramp Walking and Level Walking: Cross-Sectional Study.

JMIR biomedical engineering·2026

Same journal

Assessing the Safety and Efficacy of a Noninvasive Device in the Management of Musculoskeletal Pain Using Low-Level Light Therapy: Double-Blinded, Randomized, Placebo-Controlled, Multicentric Study.

JMIR biomedical engineering·2026

Same journal

Conceptual Model for the Integration of Marketing Strategies and Biomedical Innovation in Patient-Centered Care: Mixed Methods Study.

JMIR biomedical engineering·2026

See all related articles

Search research articles

Home
Increasing Large Language Model Accuracy For Care-seeking Advice Using Prompts Reflecting Human Reasoning Strategies In The Real World: Validation Study.

Home
Increasing Large Language Model Accuracy For Care-seeking Advice Using Prompts Reflecting Human Reasoning Strategies In The Real World: Validation Study.

Related Experiment Video

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Increasing Large Language Model Accuracy for Care-Seeking Advice Using Prompts Reflecting Human Reasoning Strategies

Marvin Kopka¹, Markus A Feufel¹

¹Division of Ergonomics, Department of Psychology & Ergonomics (IPA), Technische Universität Berlin, Straße des 17. Juni 135, Berlin, State of Berlin, 10623, Germany, 49 31470806.

JMIR Biomedical Engineering

|April 8, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

Keywords:

artificial intelligence bounded rationality care-seeking cognitive science decision-making human factors human-technology interaction naturalistic decision support naturalistic decision-making prompting self-triage

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Naturalistic decision-making (NDM) inspired prompts enhance large language model (LLM) accuracy for uncertain care-seeking decisions, especially for self-care advice. This approach improves LLM performance in real-world scenarios without compromising emergency or non-emergency case recommendations.

Area of Science:

Artificial Intelligence
Cognitive Science
Human-Computer Interaction

Background:

Current large language model (LLM) prompting focuses on structured problems, neglecting high-uncertainty real-world tasks like care-seeking decisions.
Naturalistic decision-making (NDM) studies human reasoning in uncertain environments but hasn't been applied to LLM prompt engineering.

Purpose of the Study:

To investigate if NDM-inspired prompting strategies can enhance LLM performance on ambiguous care-seeking decisions.
To evaluate the effectiveness of recognition-primed decision-making and data-frame theory in LLM prompt design.

Main Methods:

Ten ChatGPT models were tested using default, recognition-primed, and data-frame prompts on 45 patient case vignettes across three urgency levels.
Each model-prompt combination was tested 10 times to assess accuracy and output variability.

Accuracy was analyzed using mixed-effects logistic regression.

Main Results:

NDM-inspired prompts improved overall LLM accuracy (recognition-primed: 67.6%; data-frame: 66.7%) compared to the default prompt (63.3%).
Significant accuracy gains were observed for self-care recommendations (default: 13.4% to NDM-inspired: 24.6%-29.8%).
NDM prompts enabled non-reasoning models to provide self-care advice, previously rare.

Conclusions:

NDM-inspired prompts improve LLM accuracy in high-uncertainty care-seeking tasks, particularly for self-care advice.
These prompts enhance LLM utility for real-world decisions involving ambiguity without negatively impacting performance on emergency or non-emergency cases.
Future research should explore the impact of NDM-inspired LLM outputs on user decision-making.