Patterns of intermittent smoking: An analysis using Ecological Momentary Assessment

University of Pittsburgh, Pittsburgh, PA, USA.
Addictive behaviors (Impact Factor: 2.76). 02/2009; 34(6-7):514-9. DOI: 10.1016/j.addbeh.2009.01.004
Source: PubMed


Non-daily smokers comprise a substantial proportion of US smokers, but there has been little study of their patterns of smoking, which are often assumed to reflect "social smoking." We used Ecological Momentary Assessment methods to study smoking patterns in 27 non-daily smoking adults who recorded each cigarette smoked over three weeks by leaving a voice mail message indicating their circumstances at the time of smoking. All told, 689 cigarettes were recorded over 589 person-days of observation. On average, participants smoked on 67% of days, averaging 2.1 (SD=0.91) cigarettes per day on days they smoked; 22% of all cigarettes were smoked in bouts (within an hour of another cigarette). Altogether, 19% of cigarettes were smoked when drinking alcohol and 29% when participants were socializing. Smoking patterns varied widely across participants. A pair of hierarchical cluster analyses distinguished three groups: Those who smoked primarily (81% of cigarettes) in the daytime (Early smokers; n=15, 58% of total sample), those who smoked primarily (75% of cigarettes) at night (Late smokers; n=7, 27%), and a distinct, classic "Social smoking" group (n=4, 15% of total sample), who smoked mostly at night but also primarily when socializing or drinking (86% of their cigarettes), in the evening (71% of their cigarettes), on weekends (65% of their cigarettes), and in bouts (71% of their cigarettes). Overall, results suggest that non-daily smoking patterns are quite heterogeneous, and that many non-daily smokers may not be primarily social smokers.

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Available from: Deborah M Scharf, Oct 01, 2015
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    • "Based on their response to number of days smoked in past 30 days, those participants indicating smoking 28–30 days of the past 30 days were classified as daily smokers; respondents smoking less than 28 days of the past 30 days were classified as nondaily smokers. Similar grouping have been used previously (see Fish et al., 2009; Shiffman, Kirchner, Ferguson, & Scharf, 2009), although alternative definitions of smoker type are possible. Sample recruitment was targeted to reflect the demographic composition of U.S. adult smokers in terms of gender , race/ethnicity, and age. "
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    ABSTRACT: Introduction: The positive emotional and sensory expectancies of cigarette smoking include improved cognitive abilities, positive affective states, and pleasurable sensorimotor sensations. This paper describes development of Positive Emotional and Sensory Expectancies of Smoking item banks that will serve to standardize the assessment of this construct among daily and nondaily cigarette smokers. Methods: Data came from daily (N = 4,201) and nondaily (N =1,183) smokers who completed an online survey. To identify a unidimensional set of items, we conducted item factor analyses, item response theory analyses, and differential item functioning analyses. Additionally, we evaluated the performance of fixed-item short forms (SFs) and computer adaptive tests (CATs) to efficiently assess the construct. Results: Eighteen items were included in the item banks (15 common across daily and nondaily smokers, 1 unique to daily, 2 unique to nondaily). The item banks are strongly unidimensional, highly reliable (reliability = 0.95 for both), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.86). Results from simulated CATs indicated that, on average, less than 8 items are needed to assess the construct with adequate precision using the item banks. Conclusions: These analyses identified a new set of items that can assess the positive emotional and sensory expectancies of smoking in a reliable and standardized manner. Considerable efficiency in assessing this construct can be achieved by using the item bank SF, employing computer adaptive tests, or selecting subsets of items tailored to specific research or clinical purposes.
    Nicotine & Tobacco Research 09/2014; 16 Suppl 3(Suppl 3):S212-22. DOI:10.1093/ntr/ntt281 · 3.30 Impact Factor
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    • "On the basis of the reported number of days smoked in the past 30 days (which smokers seem to report with reasonable accuracy ; see, e.g., Harris et al., 2009), participants were classified as either daily (28–30 days) or nondaily (<28 days) smokers . Similar grouping have been used previously (see Fish et al., 2009; Shiffman, Kirchner, Ferguson, & Scharf, 2009), although of course alternative definitions of smoker type are possible. Of the 5,384 total participants, 4,201 were designated as daily cigarette smokers, and 1,183 were nondaily smokers. "
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    ABSTRACT: This article describes the procedures used in the PROMIS(®) Smoking Initiative for the development and evaluation of item banks, short forms, and computerized adaptive tests (CAT) for the assessment of six constructs related to cigarette smoking: nicotine dependence, affective/hedonic benefits, coping benefits, social benefits, psychosocial risks, and health risks. Analyses were conducted using response data from a large national sample of smokers. Items related to each construct were subjected to extensive item factor analyses and evaluation of differential item functioning (DIF). Final item banks were calibrated, and short form assessments were developed for each construct. The performance of the short forms and the potential use of the item banks for computerized adaptive test (CAT) administration were examined through simulation study. Item selection based on dimensionality assessment and DIF analyses produced item banks that were essentially unidimensional in structure and free of bias. Simulation studies demonstrated that the constructs could be accurately measured with a relatively small number of carefully selected items, either through fixed short forms or CAT-based assessment. Illustrative results are presented, and subsequent articles provide detailed discussion of each item bank in turn. The development of the PROMIS(®) smoking item banks provides researchers with new tools for measuring smoking-related constructs. The use of the calibrated item banks and suggested short form assessments will enhance the quality of score estimates, thus advancing smoking research. Moreover, the methods used in the current study, including innovative approaches to item selection and short form construction, may have general relevance to item bank development and evaluation.
    Nicotine & Tobacco Research 08/2013; 16(Suppl 3). DOI:10.1093/ntr/ntt123 · 3.30 Impact Factor
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    • "The so-called social smokers who smoke primarily in social situations have been the subject of exploratory research that has identified associations between smoking and binge drinking, especially among college students [11] [22] [23]. By contrast, former daily smokers who have reduced their smoking in response to tax increases or smoke-free air laws represent a different subgroup of the Nondaily smoking population that may be older and more sensitive to tobacco control policies than social smokers [24] [25] [26]. NYC provides an ideal environment in which to examine a diverse population of smokers to both assess Nondaily smoking over time and more closely examine the demographic and smoking characteristics of Nondaily smokers. "
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    ABSTRACT: Among current smokers, the proportion of Nondaily smokers is increasing. A better understanding of the characteristics and smoking behaviors of Nondaily smokers is needed. We analyzed data from the New York City (NYC) Community Health Survey to explore Nondaily smoking among NYC adults. Univariate analyses assessed changes in Nondaily smoking over time (2002-2010) and identified unique characteristics of Nondaily smokers; multivariable logistic regression analysis identified correlates of Nondaily smoking in 2010. The proportion of smokers who engage in Nondaily smoking significantly increased between 2002 and 2010, from 31% to 36% (P = 0.05). A larger proportion of Nondaily smokers in 2010 were low income and made tax-avoidant cigarette purchases compared to 2002. Smoking behaviors significantly associated with Nondaily smoking in 2010 included smoking more than one hour after waking (AOR = 8.8, 95% CI (5.38-14.27)); buying "loosies" (AOR = 3.5, 95% CI (1.72-7.08)); attempting to quit (AOR = 2.3, 95% CI (1.36-3.96)). Nondaily smokers have changed over time and have characteristics distinct from daily smokers. Tobacco control efforts should be targeted towards "ready to quit" Nondaily smokers.
    Journal of Environmental and Public Health 05/2012; 2012(2):145861. DOI:10.1155/2012/145861
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