AI-assisted Quality Control Study of Multimodal Data in the Epidemiological Survey of Shanghai Nicheng Cohort Study

NCT06961461 | Not Yet Recruiting DMC

• 1 other identifier: 2025-04
• Study Type: observational
• Target: 900
• Locations: 0 countries
• Sites: N/A

Brief 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.

Conditions

Quality Control; Cohort Studies

Outcome Measures

Primary Outcomes (1)

• Accuracy

  changes in the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys with AI-assisted tool

  From enrollment to the end of questionnaire quality control at 8 weeks

Secondary Outcomes (1)

• Completeness and consistency

  From enrollment to the end of questionnaire quality control at 8 weeks

Study Arms (2)

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.

Other: AI-assisted quality control tool

Interventions

AI-assisted quality control tool OTHER

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.

Use AI tools to conduct quality control

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Questionnaires in the Nicheng cohort

You may qualify if:

• 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.

You may not qualify if:

• 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;

Sponsors & Collaborators

• Shanghai 6th People's Hospital: lead

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: April 29, 2025
• First Posted: May 8, 2025
• Study Start: May 1, 2025
• Primary Completion: June 15, 2025
• Study Completion: August 15, 2025
• Last Updated: May 8, 2025

Record last verified: 2025-04