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Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
Chronic Obstructive Pulmonary Disease III: Chronic Bronchitis Features01:24

Chronic Obstructive Pulmonary Disease III: Chronic Bronchitis Features

Chronic bronchitis is a key phenotype of chronic obstructive pulmonary disease (COPD), characterized by airway-centered inflammation and mucus overproduction. It develops from long-term exposure to harmful particles or gases, most commonly cigarette smoke, which triggers a persistent inflammatory response.Cellular and Structural ChangesInflammation initially affects the large bronchi and later the smaller airways, with infiltration by immune cells, including neutrophils, macrophages, and...
Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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Related Experiment Video

Updated: May 28, 2026

Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements
06:39

Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements

Published on: August 28, 2017

Identifying Subgroups Among Current Smokers Enrolled in the Smoking Cessation Clinic Program: A Latent Class Analysis

Mi Sook Jung1, Ah Rim Lee1, Sok Goo Lee2

  • 1College of Nursing, Chungnam National University, Daejeon 35015, Republic of Korea.

Healthcare (Basel, Switzerland)
|May 27, 2026
PubMed
Summary

Identifying distinct smoker subgroups reveals varied cessation success. Tailoring interventions to these profiles, like sedentary vs. active smokers, can improve smoking cessation outcomes in community clinics.

Keywords:
community health centershealth behaviorlatent class analysissmoking cessation

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Last Updated: May 28, 2026

Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements
06:39

Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements

Published on: August 28, 2017

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

Area of Science:

  • Public Health
  • Behavioral Science
  • Tobacco Control

Background:

  • Smoking cessation outcomes vary significantly among individuals.
  • Current clinic-based services often use uniform intervention strategies, potentially limiting effectiveness.
  • Understanding diverse smoking behaviors and psychological profiles is crucial for refining community-based cessation programs.

Purpose of the Study:

  • To identify distinct subgroups of smokers in public health center-based cessation clinics.
  • To examine differences in cessation outcomes and related characteristics across these subgroups.

Main Methods:

  • Latent class analysis was performed on data from 21,105 adult smokers across 16 clinics.
  • Analysis used indicators: time to first cigarette, cigarettes per day, prior quit attempts, alcohol use, and physical activity.
  • A three-step approach examined associations between latent class membership, covariates, and outcomes.

Main Results:

  • Four distinct smoker subgroups were identified: Sedentary Heavy Smokers (46.8%), Active Social Heavy Smokers (34.6%), Inactive Nicotine Addictive Light Smokers (13.6%), and Active Lifestyle Light Smokers (5.0%).
  • Classes differed in socioeconomic status, smoking patterns, and confidence in quitting.
  • Six-month cessation success rates varied, with higher abstinence in light-smoking classes and among Sedentary Heavy Smokers compared to Active Social Heavy Smokers.

Conclusions:

  • Person-centered profiling is valuable for developing precise, context-sensitive smoking cessation strategies.
  • Integrating behavioral and environmental factors is supported for community-based tobacco control.
  • Tailored approaches can enhance the effectiveness of smoking cessation interventions.