Population-based recruitment for quit-smoking programs: an analytic review of communication variables

Prev Med. 1999 Jun;28(6):545-57. doi: 10.1006/pmed.1998.0479.


Background: Attempts to reduce the prevalence of smoking through quit-smoking programs have been unsuccessful because they have not attracted large numbers of smokers to participate in them.

Method: An analytic review of the literature was conducted to identify potential communication variables that might enhance recruitment for community-based quit-smoking programs. Recruitment was defined as the number of smokers who enroll in a quit-smoking program divided by the estimated number of smokers in the target population.

Results: Thirty-three publications reporting the results of 40 recruitment campaigns were located. The median recruitment rate was 2.0%. Logistic regression was used to examine the effect of six variables on recruitment rate: the type of program sponsor, the type of program, program costs, use of participation incentives, whether messages were segmented by stage of change, and the type of channel used to send messages. The only significant predictor of recruitment rate was channel type (i.e., the method used to deliver a message). Studies that used interactive recruitment channels (telephone, interpersonal communication) were 66.5 times more effective than those using passive recruitment strategies (mass media, direct mail). Results examining the segmentation of messages by stage of change on recruitment were inconclusive.

Conclusions: Results suggest that researchers and practitioners interested in population-based smoking cessation programs should pay more attention to recruitment methods. The use of interpersonal channels has been underused and appears to be particularly promising for improving the population impact of quit-smoking programs.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Analysis of Variance
  • Community Participation
  • Female
  • Humans
  • Logistic Models
  • Male
  • Marketing of Health Services / methods*
  • Middle Aged
  • Odds Ratio
  • Smoking Cessation*