A method comparison study of timeline followback and ecological momentary assessment of daily cigarette consumption.
BACKGROUND
Uncertainty exists about how best to measure daily cigarette consumption. Two common measures are timeline followback (TLFB), which involves structured, prompted recall, and ecological momentary assessment (EMA), which involves recording consumption, as it occurs, on a handheld electronic device.


METHODS
We evaluated the agreement between TLFB and EMA measures collected for 14 days prior to the target quit date from 236 smokers in a smoking cessation program. We performed a Bland-Altman analysis to assess agreement of TLFB and EMA using a regression-based model that allows for a nonuniform difference between methods and limits of agreement that can vary with the number of cigarettes smoked.


RESULTS
For pairs of measurements taken on the same smoker, TLFB counts were on average 3.2 cigarettes higher than EMA counts; this difference increased for larger numbers of cigarettes. Using a model that allows for variable limits of agreement, the width of the 95% interval ranged from 8.7 to 61.8 cigarettes, with an average of 26.4 cigarettes. Variation between the methods increased substantially for larger cigarette counts, leading to wider limits and poorer agreement for heavy smokers.


CONCLUSIONS
Throughout the measurement range, the estimated limits of agreement were far wider than the limits of clinical significance, defined a priori to be 20% of the number of cigarettes smoked. We conclude that TLFB and EMA cannot be considered equivalent for the assessment of daily cigarette consumption, especially for heavy smokers.
Griffith
Sandra D
SD
Department of Biostatistics & Epidemiology, University of Pennsylvania School of Medicine, 507 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104, USA. sgrif@upenn.edu
Shiffman
Saul
S
Heitjan
Daniel F
DF
D006801:Humans; D010043:Outcome and Process Assessment, Health Care / Q000379:methods*; D012907:Smoking; D016540:Smoking Cessation / Q000706:statistics & numerical data*