Improving the Reliability of LLMs as Medical Assistants for the General Public (LAMP-1)
tiistai 1. syyskuuta 2026 päivittänyt: Ji Xunming,MD,PhD, Capital Medical University
Improving the Reliability of LLMs as Medical Assistants for the General Public: a Proof of Concept Simulation Trial
This study will evaluate whether three-minute six-dimensions education(3M-6D education) can improve the reliability of large language models as medical assistants for the general public.
Participants will be randomly assigned to receive or not receive 3M-6D education and then use ChatGPT, Gemini, or non-AI information resources.
The study will assess relevant condition identification, disposition concordance, red-flag identification, and NASA-TLX score.
Tutkimuksen yleiskatsaus
Tila
Valmis
Interventio / Hoito
Yksityiskohtainen kuvaus
This randomized, controlled, proof-of-concept simulation trial will evaluate whether three-minute six-dimensions education (3M-6D education) can improve the reliability of large language models as medical assistants for the general public.
Eligible participants will be randomly assigned in a 1:1:1:1:1 ratio to one of five study groups: the 3M-6D education GPT group, the GPT group, the 3M-6D education Gemini group, the Gemini group, or the control group. Participants in the 3M-6D education GPT and 3M-6D education Gemini groups will receive approximately three minutes of education before using ChatGPT or Gemini.Each participant will be randomly assigned one of 10 standardized clinical scenarios and complete a simulated counseling task in unrestricted natural language within approximately 10 minutes. The study will assess relevant condition identification, disposition concordance, red-flag identification, and NASA-TLX score.
Opintotyyppi
Interventio
Ilmoittautuminen (Todellinen)
527
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Tässä osiossa on tutkimuksen suorittajien yhteystiedot ja tiedot siitä, missä tämä tutkimus suoritetaan.
Opiskelupaikat
-
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Beijing Municipality
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Beijing, Beijing Municipality, Kiina
- Beijing Ctiy
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-
Osallistumiskriteerit
Tutkijat etsivät ihmisiä, jotka sopivat tiettyyn kuvaukseen, jota kutsutaan kelpoisuuskriteereiksi. Joitakin esimerkkejä näistä kriteereistä ovat henkilön yleinen terveydentila tai aiemmat hoidot.
Kelpoisuusvaatimukset
Opintokelpoiset iät
- Aikuinen
- Vanhempi Aikuinen
Hyväksyy terveitä vapaaehtoisia
Joo
Kuvaus
Inclusion Criteria:
- Age 18 years or greater, male or female;
- Completed primary school or higher education;
- Able to use a smartphone or computer to complete online interaction;
- No history of acute ischemic stroke, systemic lupus erythematosus, gastric ulcer, pneumonia, acute cardiac infarction, urinary tract infection, uterine fibroids, diabetes, osteoarthritis, or migraine.
- Able to understand and comply with study procedures and to provide written informed consent.
Exclusion Criteria:
- Currently or previously employed as a healthcare worker;
- Previously received systematic medical training;
- Currently involved in concurrent research that may interfere with the results of the present trial;
- The investigator considered that the participant had other conditions that might affect compliance or preclude participation.
Opintosuunnitelma
Tässä osiossa on tietoja tutkimussuunnitelmasta, mukaan lukien kuinka tutkimus on suunniteltu ja mitä tutkimuksella mitataan.
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Terveyspalvelututkimus
- Jako: Satunnaistettu
- Inventiomalli: Rinnakkaistehtävä
- Naamiointi: Yksittäinen
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
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Kokeellinen: 3M-6D education GPT Group
Participants will first be trained in 3M-6D education, then use ChatGPT to complete a consultation task in unrestricted natural language in approximately 10 minutes.
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Participants use ChatGPT to complete a standardized simulated clinical scenarios in unrestricted natural language.
3M-6D education is designed based on Cognitive Load Theory to reduce the cognitive burden on patients during medical interactions with AI and to improve the clarity and completeness of symptom reporting. Guided by cognitive load theory and the natural process physicians use to take medical histories, the investigators identified candidate information dimensions and developed a structured expression framework with six dimensions for public health queries through a Delphi expert consensus process. Participants were instructed to use the framework to describe their symptoms across these six dimensions; this process can typically be completed within three minutes, so the investigators call this approach three minutes six dimensions education (3M-6D education). |
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Kokeellinen: 3M-6D education Gemini Group
Participants will first be trained in 3M-6D education, then use Gemini to complete a consultation task in unrestricted natural language in approximately 10 minutes.
|
Participants use Gemini to complete a standardized simulated clinical scenarios in unrestricted natural language.
3M-6D education is designed based on Cognitive Load Theory to reduce the cognitive burden on patients during medical interactions with AI and to improve the clarity and completeness of symptom reporting. Guided by cognitive load theory and the natural process physicians use to take medical histories, the investigators identified candidate information dimensions and developed a structured expression framework with six dimensions for public health queries through a Delphi expert consensus process. Participants were instructed to use the framework to describe their symptoms across these six dimensions; this process can typically be completed within three minutes, so the investigators call this approach three minutes six dimensions education (3M-6D education). |
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Active Comparator: GPT Group
Participants will use ChatGPT to complete a consultation task in unrestricted natural language in approximately 10 minutes.
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Participants use ChatGPT to complete a standardized simulated clinical scenarios in unrestricted natural language.
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Active Comparator: Gemini Group
Participants will use Gemini to complete a consultation task in unrestricted natural language in approximately 10 minutes.
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Participants use Gemini to complete a standardized simulated clinical scenarios in unrestricted natural language.
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Ei väliintuloa: Control group
Participants will use non-AI tools such as internet searches and medical websites to complete a consultation task in unrestricted natural language in approximately 10 minutes.
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Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Relevant conditions identification of the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
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Relevant conditions identification is defined as the proportion of participants whose final response includes the expert-defined final diagnosis or a relevant differential diagnosis.
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1 hour.
|
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Disposition concordance of the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
|
Disposition concordance is defined as the proportion of participants whose final care recommendation matches the expert-defined level.
The five levels are self-care, routine outpatient care, urgent outpatient care, emergency department visit, and emergency medical services.
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1 hour.
|
|
Relevant conditions identification of the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Disposition concordance of the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
Toissijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Relevant conditions identification of the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Relevant conditions identification of the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Disposition concordance of the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Disposition concordance of the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Red-flag identification in the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
|
Red-flag identification is defined as the proportion of participants whose final response includes the key warning signs that experts defined for the assigned scenario.
|
1 hour.
|
|
Red-flag identification in the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Red-flag identification in the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Red-flag identification in the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
NASA Task Load Index score of the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
|
NASA-TLX score is a self-reported task-load score measured after the simulated consultation with a physician.
It includes six domains: mental demand, physical demand, temporal demand, effort, frustration, and performance.
Each domain is scored from 0 to 100.
The total score is the mean of the six domains.
Higher scores indicate greater perceived task load.
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1 hour.
|
|
NASA Task Load Index score of the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
NASA-TLX score is a self-reported task-load score measured after the simulated consultation with a physician.
It includes six domains: mental demand, physical demand, temporal demand, effort, frustration, and performance.
Each domain is scored from 0 to 100.
The total score is the mean of the six domains.
Higher scores indicate greater perceived task load.
|
1 hour.
|
|
NASA Task Load Index score of the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
NASA-TLX score is a self-reported task-load score measured after the simulated consultation with a physician.
It includes six domains: mental demand, physical demand, temporal demand, effort, frustration, and performance.
Each domain is scored from 0 to 100.
The total score is the mean of the six domains.
Higher scores indicate greater perceived task load.
|
1 hour.
|
|
NASA Task Load Index score of the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
NASA-TLX score is a self-reported task-load score measured after the simulated consultation with a physician.
It includes six domains: mental demand, physical demand, temporal demand, effort, frustration, and performance.
Each domain is scored from 0 to 100.
The total score is the mean of the six domains.
Higher scores indicate greater perceived task load.
|
1 hour.
|
|
Relevant conditions identification of the 3M-6D education GPT group compared with the 3M-6D education Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Disposition concordance of the 3M-6D education GPT group compared with the 3M-6D education Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Red-flag identification in the 3M-6D education GPT group compared with the 3M-6D education Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
NASA Task Load Index score of the 3M-6D education GPT group compared with the 3M-6D education Gemini group
Aikaikkuna: 1 hour.
|
NASA-TLX score is a self-reported task-load score measured after the simulated consultation with a physician.
It includes six domains: mental demand, physical demand, temporal demand, effort, frustration, and performance.
Each domain is scored from 0 to 100.
The total score is the mean of the six domains.
Higher scores indicate greater perceived task load.
|
1 hour.
|
Muut tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Failure to identify red flags in the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
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Failure to identify red flags is defined as the proportion of participants whose final response does not include the expert-defined red-flag symptoms or warning signs for the assigned standardized simulated clinical scenario.
|
1 hour.
|
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Failure to identify red flags in the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Failure to identify red flags in the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
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Failure to identify red flags in the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
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Underestimation of disposition in the 3M-6D education GPT group compared with the GPT group
Aikaikkuna: 1 hour.
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Underestimation of disposition is defined as the proportion of participants whose final care recommendation is lower than the expert-defined disposition level for the assigned standardized simulated clinical scenario.
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1 hour.
|
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Underestimation of disposition in the 3M-6D education GPT group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
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Underestimation of disposition in the 3M-6D education Gemini group compared with the Gemini group
Aikaikkuna: 1 hour.
|
1 hour.
|
|
|
Underestimation of disposition in the 3M-6D education Gemini group compared with the control group
Aikaikkuna: 1 hour.
|
1 hour.
|
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