Quality ControlNCT06961461
AI-assisted Quality Control Study of Multimodal Data in the Epidemiological Survey of Shanghai Nicheng Cohort Study
An observational study of Quality Control and Cohort Studies, run by Shanghai 6th People's Hospital.
Trial summary
This study is based on the Nicheng Cohort study. This study intends to analyze whether AI assistance can effectively improve the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys based on traditional quality control processes. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Quality Control, Cohort Studies
- How many people
- 900 participants
- Where
- No sites listed yet
- Study dates
- 1 May 2025to 15 Aug 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Questionnaires in the Nicheng cohort
Who may be able to join
- Be proficient in using computers;
- The person responsible for questionnaire quality control needs to have good dialect recognition ability;
- Have a basic understanding or high acceptance of AI-assisted tools, and be able to adapt to the learning and application of new technologies
- Be able to participate in the research throughout the process, abide by the research process, receive training, and be willing to complete quality control tasks as required.
Who cannot join
- The person responsible for questionnaire quality control cannot understand or recognize Shanghai Nanhui dialect proficiently;
- Unfamiliar with AI-assisted tools and difficult to accept technical operations;
- Unable to participate in the research, receive training or complete the specified tasks due to other work or academic reasons;
About this study
This study is based on the Nicheng Cohort study. This study intends to analyze whether AI assistance can effectively improve the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys based on traditional quality control processes.
Read the detailed description
This study randomly divided quality control personnel into an experimental group and a control group. The experimental group adopts AI assisted quality control: the AI system automatically transcribes the recorded text of the questionnaire, extracts keywords, analyzes the consistency of the Q\&A logic, and generates quality control prompts. The quality control personnel will verify the question fragments according to the prompts and determine the qualification of the questionnaire; The control group relies entirely on manual quality control: the quality control personnel listen to the recording word by word, manually record the content, independently identify keyword omissions, logical contradictions, or terminology deviations, and ultimately determine whether the questionnaire is qualified. The core difference lies in the fact that the experimental group uses AI technology to accurately locate risk issues, reducing the burden of manual comprehensive screening, while the control group requires full manual review without targeted support.
- Conditions
- Quality Control, Cohort Studies
- Being tested
- AI-assisted quality control tool
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-assisted quality control toolOther
In this study, quality control personnel will be randomly divided into an experimental group and a control group, and will use artificial intelligence-assisted quality control and manual quality control to conduct quality control on the data collected from the epidemiological survey.
Experimental group: Quality control personnel will use the AI system to perform quality control on the questionnaire recordings.
Control group: The questionnaire content was checked by manually listening back to the recordings and errors were recorded manually.
| Study group | Role | What they receive |
|---|---|---|
| Manual quality control | The questionnaire content was checked by manually listening back to the recordings and errors were recorded manually | |
| Use AI tools to conduct quality control | Quality control personnel use an integrated AI-assisted system to perform quality control on epidemiological survey data. The AI system automatically transcribes audio and analyzes data quality,. Quality control personnel conduct reviews based on AI prompts. Receives: Other: AI-assisted quality control tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy
changes in the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys with AI-assisted tool
Measured: From enrollment to the end of questionnaire quality control at 8 weeks
Secondary outcomes (1)
Completeness and consistency
AI-assisted quality control in questionnaire quality control improves the integrity and consistency of questionnaire data through automated keyword extraction and logical consistency checking.
Measured: From enrollment to the end of questionnaire quality control at 8 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 May 2025
- Study start1 May 2025 (estimated)
- Primary completion15 Jun 2025 (estimated)
- Study completion15 Aug 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Quality ControlStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 900 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai 6th People's Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Li Huating, Shanghai 6th People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06961461
- Sponsor's protocol ID
- 2025-04
- Status last verified
- Apr 2025
- First submitted
- 29 Apr 2025
- Last updated
- 8 May 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-assisted Quality Control Study of Multimodal Data in the Epidemiological Survey of Shanghai Nicheng Cohort Study
- ClinicalTrials.gov ID
- NCT06961461
- Acronym / sponsor ID
- 2025-04
- Conditions
- Quality Control, Cohort Studies
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 900 participants (estimated)
- Lead sponsor
- Shanghai 6th People's HospitalUniversity, hospital or other
- Study start
- 1 May 2025 (estimated)
- Primary completion
- 15 Jun 2025 (estimated)
- Study completion
- 15 Aug 2025 (estimated)
- First posted
- 8 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study is based on the Nicheng Cohort study. This study intends to analyze whether AI assistance can effectively improve the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys based on traditional quality control processes.
Detailed description
This study randomly divided quality control personnel into an experimental group and a control group. The experimental group adopts AI assisted quality control: the AI system automatically transcribes the recorded text of the questionnaire, extracts keywords, analyzes the consistency of the Q\&A logic, and generates quality control prompts. The quality control personnel will verify the question fragments according to the prompts and determine the qualification of the questionnaire; The control group relies entirely on manual quality control: the quality control personnel listen to the recording word by word, manually record the content, independently identify keyword omissions, logical contradictions, or terminology deviations, and ultimately determine whether the questionnaire is qualified. The core difference lies in the fact that the experimental group uses AI technology to accurately locate risk issues, reducing the burden of manual comprehensive screening, while the control group requires full manual review without targeted support.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Manual quality control | – | –The questionnaire content was checked by manually listening back to the recordings and errors were recorded manually |
| Use AI tools to conduct quality control | – | Other: AI-assisted quality control toolQuality control personnel use an integrated AI-assisted system to perform quality control on epidemiological survey data. The AI system automatically transcribes audio and analyzes data quality,. Quality control personnel conduct reviews based on AI prompts. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Questionnaires in the Nicheng cohort
Key inclusion criteria (4 listed)
- Be proficient in using computers;
- The person responsible for questionnaire quality control needs to have good dialect recognition ability;
- Have a basic understanding or high acceptance of AI-assisted tools, and be able to adapt to the learning and application of new technologies
- Be able to participate in the research throughout the process, abide by the research process, receive training, and be willing to complete quality control tasks as required.
Key exclusion criteria (3 listed)
- The person responsible for questionnaire quality control cannot understand or recognize Shanghai Nanhui dialect proficiently;
- Unfamiliar with AI-assisted tools and difficult to accept technical operations;
- Unable to participate in the research, receive training or complete the specified tasks due to other work or academic reasons;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-assisted quality control toolIn this study, quality control personnel will be randomly divided into an experimental group and a control group, and will use artificial intelligence-assisted quality control and manual quality control to conduct quality control on the data collected from the epidemiological survey. Experimental group: Quality control personnel will use the AI system to perform quality control on the questionnaire recordings. Control group: The questionnaire content was checked by manually listening back to the recordings and errors were recorded manually. | Other | Use AI tools to conduct quality control |
Primary outcome
Accuracy
Time frame: From enrollment to the end of questionnaire quality control at 8 weeks
changes in the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys with AI-assisted tool
1 secondary outcome
Completeness and consistency
Time frame: From enrollment to the end of questionnaire quality control at 8 weeks
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 May 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Quality Control and Cohort Studies, run by Shanghai 6th People's Hospital.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 8 May 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy (time frame: From enrollment to the end of questionnaire quality control at 8 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 May 2025.