Self-reported and self-monitored smoking patterns

Addictive> Brhoviors, Printed in the USA.

Vol. 13. pp. 201-204, All rights reserved.

1988 Copyright

0306-4603188 $3.00 + .OO D 1988 Pergamon Press plc

BRIEF REPORT SELF-REPORTED

AND SELF-MONITORED

SMOKING

PATTERNS

SAUL SHIFFMAN University

of Pittsburgh

MARK PRANGE University

of South

Florida

- Individual differences in smoking patterns are usually assessed with self-report measures such as Horn’s Reasons for Smoking Test, which have not been systematically validated. This paper compares results from several self-report scales with self-monitoring data obtained from 164 smoking clinic subjects who monitored their smoking for at least two days. Self-monitoring data were factor-analyzed and correlated with self-report measures. Most of the hypothesized relationships failed to appear. The Sedative Smoking (tensionreduction) factor of the Reasons for Smoking Test received the strongest support. In general, however, the results did not support the validity of Commonly-used self-report scales of smoking motives and situations. Abstract

Differences among smokers in when and why they smoke are thought to be theoretically and clinically important. Theoretically, these differences are critical to models which consider emoking to be stimulus-bound. Clinically, they may allow treatment to be tailored to different kinds of smokers. Several self-report instruments designed to measure these differences in smoking motives or situational determinants are widely used. Probably the most widely used is Horn’s Reasons for Smoking (RFS) Test (Ikard, Green, & Horn, 1969), which has been restructured by Russell using factor-analytic techniques (Russell, Peto, & Patel, 1974). Russell et al. (1974) deleted the Horn Tension Reduction factor, which they felt resulted from artifacts. McKennel(l970) and others (e.g., Mausner & Platt, 1971) have developed similar instruments focusing less on motives for smoking and more on situations in which subjects smoke. McKennel’s scales were validated on large samples of adolescent and adult smokers. Despite their widespread use, evidence for the validity of these instruments is meager. Leventhal and Avis (1976) found support for the Habit factor of the RFS test, but not for the Addiction factor, and only mixed support of the Pleasure factor. Adesso and Glad (1978) found little relation between smoking in an analogue setting and scores on Mausner’s (Mausner 8z Platt, 1971) smoking patterns test. Ikard and Tomkins (1973) report mixed support of the Horn typology. The RFS has also proved disappointingly inert in predicting smoking cessation outcome (e.g., Joffe, Lowe, & Fisher, 1981). Clinically, smoking is often assessed through self-monitoring, which relies on subjects’ real-time observations without need for recall and summary, and is demonstrably accurate (McFall, 1977). Although self-monitoring is reactive in clinical An earlier version of this report was presented at the annual meeting of the American Psychological Association, August, 1984, Toronto, Canada. Requests for reprints should be addressed to Saul Shiffman, Department of Psychology, 706 Old Engineering Hall, University df Pittsburgh, Pittsburgh, PA 15260. 201

202

SAUL

SHlFFMAN

and MARK

PRANGE

populations, self-monitoring of reasons for smoking under proper instructions minimizes reactivity (Epstein & Collins, 1977; Leventhal & Avis, 1976: Joffe et al., 1981). Thus, self-monitoring appears a better choice for characterizing smoking behavior, but it has seldom been used to examine individual differences in smoking patterns. Only Joffe et al. (1981) have examined the RFS scale in relation to natural smoking patterns. They found only weak support for the scale’s validity, with only two of six factors (Negative Affect and Handling) correlating with self-monitoring data. Their study was limited by a small sample and low statistical power, thus perhaps underestimating the scale’s validity. The study also examined only a measure of moti\ves for smoking; scales measuring situational antecedents of smoking have more observable referents and may therefore be more valid. This paper examines the validity of self-report measures of smoking motives and patterns by comparing them to data obtained through self-monitoring of smoking patterns. METHOD

Subjects were 164 smokers attending paid to participate. The average subject smoked 28.0 cigarettes per day (SI) = Sixty-four percent of the subjects were cessation attempt. Subjects were drawn demographic or substantive differences

smoking cessation clinics. Subjects were was 39.4 years of age (SD = 12.3) and had 12.78) for 22.9 years (M = 19; SD = 12.9). women; most (84.4%) had made a previous from two different clinics, but there were no between the two samples.

On enrollment in the clinics and the study, all subjects completed the Horn RFS Test. Most of the sample (N = 114) also completed the expanded RFS form developed by Russell et al. (1974), and McKennel’s (1970) Smoking Motivation questionnaire. The Horn RFS scale yields subscores for Sedative Smoking (tension reduction), Stimulation Smoking, Relaxation Smoking, Addictive Smoking, Habitual Smoking, and Sensorimotor Manipulation. The overlapping Russell typology yields scores for Stimulation Smoking, Indulgent Smoking, Psychosocial Smoking, Sensorimotor Smoking, Addictive Smoking, and Automatic Smoking. The McKennel scale subscores are: Nervous Irritation (negative affect) Smoking, Relaxation Smoking, Solitary Smoking, Activity Accompaniment Smoking, Food Substitution Smoking, Social Smoking, and Social Confidence Smoking. Subjects monitored their smoking patterns for a minimum of two days under instructions not to change their smoking habits, but only to record them. Subjects used a checklist to indicate their emotional state and activity using one or more checklist categories. The categories for emotional state were: Angry, Anxious, Bored, Depressed, Frustrated, Happy, Relaxed, or Tired. For activity, they were: Eating or drinking, Relaxation, Work, Socializing, or Other.

The self-monitoring data were summarized across days by taking the proportion of cigarettes smoked under each affect and activity. We then factor-analyzed these data, favoring factor solutions which corresponded to the structures reported for the self-report instruments. A six-factor oblique solution accounted for 67.4% of the variance; the resulting factors were only slightly correlated. The factors and their component items and loadings were (slashes indicate the poles of bipolar factors):

Assessment

of smoking

patterns

203

Negative

.4ffct (Depressed, .76, Frustrated, ._59, Angry, .57); Anxious/Happy (Anx- .91, Happy, .70); Re/axed/Bowd (Relaxed, - .94; Relaxing, - .69; Bored, .57; Tired (Other activity, .83, Tired, .59); WorkinRISocializing (Socializing, -.87, Working, .62); and Eating (Eating, .95). The tendency towards bipolar factors is due to the checklist method, which results in many negative correlations. Subjects who check one activity, for example, are then less likely to also check another activity, even though the coding system allows it.

ious,

RESULTS

We examined the correlations of scores on self-monitoring factors with scores on hypothetically-related scales of the smoking typology measures. The results showed surprisingly little correspondence between self-reported and self-monitored smoking patterns. The mean of all 17 hypothesized correlations was .18. For the McKennel scales, only two of the hypothesized relationships between self-monitoring factors and typology scores were significant. Smoking when Anxious (vs. Happy) correlated with Social Confidence Smoking, r = .28, p < .OOl; smoking when Working vs. Socializing correlated with Solitary Smoking, r = .20, p < .02. Several hypothesized correlations were negative. The other observed correlations were (the smoking typology factor is always listed first): Relaxation with Negative Affect, .Ol ; Relaxation with Bored/Relaxed, .06; Activity Accompaniment with Bored/Relaxed, -.03. The mean correlation was .05. The Horn RFS Test fared better. Of five hypothesized relationships, three, all involving the Sedative Smoking factor, were significant. Sedative smoking was related to Smoking when Anxious (vs. Happy), when Bored (vs. Relaxed), and under Negative Affect (r = .19, .26, and .30, all p < .Ol). The other correlations were: Relaxation with Bored/Relaxed, - .07; Stimulation with Tired, -.09. The mean correlation was .16. Russell’s version of this test performed less well. Only one hypothesized relationship with self-monitoring data was confirmed: smoking when Eating correlated with Sensorimotor Smoking, r = .16, p < .05. The other correlations were: Stimulation with Tired, -.Ol; Psychosocial with Work/Socializing, .07. The mean correlation was .03. (Several unhypothesized correlations turned up in this analysis. Although all the correlations are significant (p < .05), they should be interpreted with caution, as they are post hoc findings from a large correlation matrix and are therefore prone to random error. The Bored/Relaxed factor correlated with the Russell Addictive score, r = .28, and with the Horn Craving score, r = .13. The Eating factor correlated with the Russell Sensorimotor score, r = .16, the Horn Handling score, r = .14, and the McKennel Solitary Smoking score, r = .20. The McKennel Food Substitution score correlated with the Tired/Other Activity factor, r = .16, and with the Negative Affect factor, r = -.17. Both the reliability and the meaningfulness of these post hoc correlations is weak. These unhypothesized correlations in no way support the validity of the self-report scales.) DISCUSSION

The data revealed little correspondence between self-reports of smoking patterns and self-monitoring of actual smoking. Few hypothesized relationships materialized; some correlations were actually negative. Among the scales examined, the RFS Sedative Smoking factor performed best; even so, only half its validity coefficients

204

SAUL

SHIFFMAN

and MARK

PRANCE

were significant. This suggests that the validity of self-reports of smoking motives and patterns is quite limited. Our findings are congruent with those of Joffe et al. (1981), who also found the RFS Sedative Smoking scale to be among the most valid. They are also consistent with Adesso and Glad’s (1978) conclusions about the scale’s validity, but at odds with the results of other analogue studies (Ikard & Tomkins, 1973; Leventhal & Avis, 1976). As Joffe et al. (1981) suggest, analogue studies may enhance apparent validity by creating a set which encourages subjects to make their behavior consistent with their self-reports. The limitations of the present study should be acknowledged. The self-monitoring factors were not perfect equivalents to the self-report scales, although the correspondence was usually self-evident. Also, although reactivity was minimized, some reactivity is to be expected among subjects quitting smoking. A study with smokers who don’t wish to change their behavior might be more credible. The lack of an observed relationship cannot be attributed to lack of statistical power, however. The study had at least a 95% probability of detecting correlations as low as .30 (Cohen, 1977). That such relationships were not observed suggests that the correspondence of smoking typology measures to smoking behavior patterns is at best weak. The lack of relationship between self-monitored and self-reported smoking patterns raises serious questions about the validity of self-report measures of smoking patterns. The self-monitoring data are more credible because subjects reported their affect and activity at the time they smoked, rather than recalling and summarizing their behavior over long intervals, and because self-monitoring of smoking has proven accurate in other contexts (McFall, 1977). The poor validity of smoking typology measures may help explain their failure to predict either process (Flaxman, 1979) or outcome (e.g., Joffe et al., 1981) in smoking cessation. Research which correlates several varieties of subject reports against objective observations and outcomes is needed. In the interim, these data suggest that investigators must use caution when using self-report measures to characterize smokers. REFERENCES Adesso. V.J.. & Glad. W.R. (197X). A behavioral test of a smoking typology. rldt/rc,ri),c, Helrc)),ic)r.\. 3, 35-38. Cohen. J. (1977). .Srclti.\ric~ct/ pon‘cr tr)rtr/~.ri.s /i,r rhc ,soc.itrl .~c~i~~~m~,s. New Yor-k: Academic Press. Epstein. L.H.. & Collins, F.L. (1977). The measurement of situational influences of smoking. AJa’ic,ri) e Bc/rtrr.ior,s. 2, 47-53. Flaxman, J. (1979). Affect management and habit mechamsms in the modification of smoking behavior. Adtlkri~~c’ B~~hcr~iors, 4, 39-46. Ikard, F.F.. & Tomkins, S. (1973). The experience of affect as a determinant of smoking behavior: A series of validity studies. Jountrrl of AhrzorrmrlP.syc~ho/ogy, 8.5, 478-488. Ikard, F., Green, D., & Horn, D. (1969). A scale to differentiate between types of smoking as related to the management of affect. f~~r~rncrriod Joumtrl ofthc Addictiorxs, 4, 645-659. Joffe, R., Lowe, M. R., & Fisher, E.B. (1981). A validjty test of the Reasons for Smoking test. Adtlicrir,c Bel7n~~ior.s. 6, 41-45. Leventhal, H.. & Avis, N. (1976). Pleasure, addiction. and habit: Factors in verbal report or factors in smoking behavior. .loumtrl c~,“Ahuormtr/ P.syc~ho/o,~~, 85, 478-488. Mausner, B., & Platt. E.S. ( 1971). SmoXirr~: A hc~lrc~~~iortrl c~ntr/~.si,s. New York: Pergamon Press. McKennel, A.C. (1970). Smoking motivation factors. HI-iris/~ .Icmrntrl cfScx?cl/ trncl C/iuic.tr/ I’.cyc~lrcdc~~~y,9, 8-23. Russell, M.A.H.. Peto. J.. & Patel. U.A. (1974). The classification of smoking by factorial structure of motives. Jourmrl