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A Joint Real-World Study of Digital Smoking Cessation Interventions

NCT05996029 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2214

Last updated 2023-08-16

No results posted yet for this study

Summary

According to the "China Smoking Health Hazard Report 2020", the total number of smokers in China is estimated to be 350 million, of which 180 million are already addicted. In addition, more than 700 million nonsmokers are exposed to secondhand smoke and become passive smoking victims, among which the family is one of the main places of secondhand smoke exposure, and mothers and children are the most affected group.

Passive smoking is a risk factor for spontaneous abortion in pregnant women and an important risk factor for the occurrence of gestational hypertension syndrome and pregnancy complications, and it also affects embryonic development with adverse pregnancy outcomes such as miscarriage, stillbirth, intrauterine growth retardation, preterm birth, immune deficiency, birth defects, and mental retardation.

Helping smokers quit is the fundamental solution to reducing secondhand smoke exposure. The accessibility and effectiveness of traditional offline smoking cessation intervention services do not meet the needs of society. With the development of mobile communication technology, digital cessation such as SMS cessation, WeChat cessation, and APP cessation have emerged, which combine clinical cessation guidelines with software technology and present rich product features and interactive design, providing a new solution to expand the accessibility of clinical cessation interventions and address the problem of secondhand smoke exposure.We hope to explore the impact of different digital cessation tools and their combinations on reducing smoking prevalence and maternal tobacco exposure.

Conditions

  • Tobacco Smoke Pollution
  • Passive Smoking
  • Secondhand Smoking

Interventions

COMBINATION_PRODUCT

Digital Smoking Cessation

The core technology of the study is a smoking cessation assistance practice service driven by a machine learning algorithm. The small programs used by the intervention group in this study included smoking cessation service packages based on cognitive behavioral therapy and online guidance from medical staff on staff, and more digital smoking cessation tools.

Sponsors & Collaborators

  • Sir Run Run Shaw Hospital

    collaborator OTHER

  • Hangzhou Medisol Technology Co.

    collaborator UNKNOWN

  • Peking Union Medical College Hospital

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-31
Primary Completion
2024-06-30
Completion
2024-06-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05996029 on ClinicalTrials.gov