Investigating the relation between placement of Quit antismoking advertisements and number of telephone calls to Quitline: a semiparametric modelling approach. Issue 2 (13th January 2006)

• Record Type: Journal Article
• Authors: Erbas, Bircan; Bui, Quang; Huggins, Richard; Harper, Todd; White, Victoria
• Is Part Of: Journal of epidemiology and community health. Volume 60:Issue 2(2006)
• Page Start: 180
• Page End: 182
• Publication Date: 2006-01-13
• Subjects: smoking cessation -- semiparametric models -- mass media advertising -- telephone helpline; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech.2005.038109
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : Study objectives: Quitline—an antismoking advertising and a telephone helpline service—is an effective public health intervention strategy for tobacco control. The objective of this short report is to model the relation between placement of antismoking advertisements and calls to Quitline on a given day. Methods/design: Data on daily Quitline antismoking advertisements, television target audience rating points (TARPS), and calls to Quitline Victoria were studied for the period 1 August 2000 and 31 July 2001. The outcome—calls to Quitline—is a count and thus assumed to follow a Poisson distribution. Generalised partial linear models were used to model the logarithm of mean daily calls as a non-parametric function of time and a linear parametric function of the day of week, number of advertisements, and TARPS. Main results: Peak calls to Quitline Victoria occurred during Monday to Wednesday with around three times as many calls compared with Sunday. Both placement of Quitline advertisements (p<0.001) and an increase in TARPS (p<0.001) on a given day significantly increased the number of calls made to Quitline Victoria. The model adequately captured fluctuations in call volume and diagnostics showed no model inadequacy. Conclusions: In this short report the emphasis is on modelling the parametric components—day of week, placement of advertisements, and TARPS on call volume. The dynamics of the underlying time trend in call volume is captured in a non-parametric component. Future analysis of hourly data would provide additional information to assess different media buying strategies that might increase call volume.