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Medications are typically administered to achieve therapeutic effects. Some drugs can modify an individual's mood and perception, frequently resulting in various enjoyable experiences. However, this can result in drug dependency, a condition marked by continuous drug use despite potential negative consequences. Drug dependency primarily falls into two categories: psychological and physical dependence. Psychological dependence occurs when the pleasurable feelings induced by the drug...
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Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements
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Share2Quit: Web-Based Peer-Driven Referrals for Smoking Cessation.

Rajani S Sadasivam1, Erik M Volz, Rebecca L Kinney

  • 1Division of Health Informatics & Implementation Science, Quantitative Health Sciences, The University of Massachusetts Medical School, Worcester, MA, United States. rajani.sadasivam@umassmed.edu.

JMIR Research Protocols
|September 27, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces proactive Web-based chain-referral tools to improve access to smoking cessation programs. These innovative methods leverage social networks to reach more smokers effectively.

Keywords:
Web-assisted tobacco interventionspeer-driven chain referralsrecruitmentrespondent-driven sampling

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06:39

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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

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Published on: May 31, 2019

Area of Science:

  • Public Health
  • Digital Health Interventions
  • Behavioral Science

Background:

  • Smoking remains a leading preventable cause of death in the U.S.
  • Web-assisted tobacco interventions (WAT-I) are underutilized.
  • Innovative engagement strategies are needed to increase WAT-I reach.

Purpose of the Study:

  • To develop and test proactive Web-based chain-referral tools.
  • To enhance access to the Decide2Quit.org Web-assisted tobacco intervention system.
  • To explore peer-driven recruitment for smoking cessation.

Main Methods:

  • Development and refinement of email and Facebook referral tools.
  • Implementation of respondent-driven sampling (RDS) to mitigate bias and ensure representativeness.
  • Recruitment of initial 'seed' participants (smokers) to initiate chain referrals within their social networks.

Main Results:

  • Protocol for evaluating proactive Web-based chain-referral tools.
  • Potential for increased access to smoking cessation interventions for hard-to-reach populations.
  • Modeling of referral success predictors using RDS sample weights.

Conclusions:

  • Share2Quit utilizes technology trends for innovative smoker recruitment.
  • Capitalizes on social networks for Web-assisted tobacco interventions.
  • Represents an advancement in engaging smokers in cessation programs.