A DESCRIPTIVE ASSESSMENT OF SMOKING USING ECOLOGICAL MOMENTARY ASSESSMENT

Transcription

1 A DESCRIPTIVE ASSESSMENT OF SMOKING USING ECOLOGICAL MOMENTARY ASSESSMENT By ALANA M. ROJEWSKI A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA

2 2009 Alana M. Rojewski 2

3 ACKNOWLEDGMENTS I thank my mentor, Jesse Dallery, for his guidance through this stage of my academic career, the members of my supervisory committee for their helpful suggestions, and my labmates and friends for their support. I also thank my parents and sister for their constant love and encouragement. 3

4 TABLE OF CONTENTS ACKNOWLEDGMENTS...3 LIST OF TABLES...5 LIST OF FIGURES...6 ABSTRACT...7 INTRODUCTION...8 METHODS...12 page Participants...12 Data Collection...13 Assessments...14 Assessment Follow-up...15 Data Analysis...15 RESULTS...17 Environmental Events...17 Internal States...18 Assessment Follow-up...19 DISCUSSION...29 LIST OF REFERENCES...34 BIOGRAPHICAL SKETCH

5 LIST OF TABLES Table page 3-1 Participant demographics Assessment items and abbreviations Assessment follow-up Number of cigarettes or assessments

6 LIST OF FIGURES Figure page 3-1 Examples of assessment items on the PocketPC The proportions of observations for environmental events Average and individual difference scores for internal states

7 Chair: Jesse Dallery Major: Psychology Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science A DESCRIPTIVE ASSESSMENT OF SMOKING USING ECOLOGICAL MOMENTARY ASSESSMENT By Alana M. Rojewski December 2009 Descriptive assessment measures can identify antecedent and consequent events that may maintain behavior, but few such measures have been utilized to assess smoking. The purpose of the current study was to employ a real-time, computer-based method, ecological momentary assessment (EMA), to identify individual differences in the events associated with smoking (e.g., direct drug effects, social reinforcers, presence of antecedent stimuli such as coffee, alcohol, etc.). Eight participants indicated the presence of various antecedent and consequent events on a PocketPC before and after each cigarette smoked. Frequency counts of reported items were obtained to assess the number of times each item was associated with an instance of smoking. Participants also completed assessments independent of smoking occasions to determine the frequency of the events when smoking did not occur. Individual differences in the events associated with smoking were apparent. Results suggest a descriptive assessment of smoking is feasible using the proposed methods. 7

8 CHAPTER 1 INTRODUCTION Smoking poses a highly significant health threat, yet only 4 to 7 percent of the 19 million adult American smokers that attempt to quit smoking each year are successful (Fiore et al., 2008). Researchers and clinicians attempt to improve smoking cessation rates through a variety of behavioral and pharmacological methods, yet success is only moderate and long-term abstinence rates remain low (Jorenby et al., 2006; Kassel & Yates, 2002). One possible way to enhance treatment effects is to use assessment instruments to identify conditions that maintain smoking for individual smokers. Based on assessment results, these conditions could be targeted more directly in treatment (Axelrod, 1991; Fiore, et al., 2008; Kassel & Yates, 2002). The purpose of the present study is to take a preliminary step toward assessing some of the events associated with smoking. Smoking assessments are typically conducted using self-report measures in the form of questionnaires or self-monitoring procedures. Researchers or clinicians administer questionnaires prompting participants to recall variables that are associated with smoking (e.g., settings, events, activities, affect states, etc.). Unfortunately, long-term recall can be inaccurate, raising questions about the validity of the self-report (Shiffman, et al., 1997b; Stone & Shiffman, 1994). An alternative is to incorporate self-monitoring procedures (e.g., Epstein & Collins, 1977; Shiffman & Prange, 1988). For example, Epstein and Collins (1977) asked participants to complete questionnaires about instances in which they smoke prior to a period of self-monitoring. During self-monitoring, participants were instructed to record the time of day and what they were doing when they smoked a cigarette (e.g., driving a car or watching TV). Only moderate correlations were reported between the self-recorded and questionnaire data. Relationships between particular events and smoking were observed for a majority of participants, and reliability of the data was 8

9 assessed. Epstein and Collins concluded that data gathered from self-monitoring provides more reliable information on smoking events than questionnaire data. One innovative self-monitoring method in behavior assessment is Ecological Momentary Assessment (EMA; Shiffman & Stone, 1998; Stone & Shiffman, 1994). Like other selfmonitoring methods, EMA uses monitoring or sampling strategies to assess phenomena at the moment they occur in natural settings, thus maximizing ecological validity while avoiding retrospective recall (p. 199, Stone & Shiffman, 1994). The four defining characteristics of EMA are 1) assessment of phenomena at the moment they occur, 2) careful timing of assessments, 3) many repeated observations, and 4) measurement in the environments that the subjects typically inhabit (Stone & Shiffman, 1994). Participants are prompted to complete questionnaires or report on the frequency of occurrence of specific events in their natural environment using electronic diaries (EDs), such as palm-top computers, cell phones, or other hand-held devices. Shiffman (1993a) suggested that EMA, as a form of self-monitoring, allows for convenient recording of events associated with smoking. Researchers have utilized EMA to assess antecedent stimuli such as affect, situations (e.g., location, presence of friends, etc.), pharmacological stimuli (e.g., alcohol, coffee, etc.), other smoking-related stimuli (e.g., cigarettes, a lighter, etc.), and the urge to smoke (Shapiro, Jamner, Davydov, & James, 2002; Shiffman et al., 2002; Shiffman et al., 1997a). For example, Shiffman et al. (2002) assessed the association between antecedent stimuli and instances of smoking as participants engaged in normal smoking. They found that smoking was related to smoking urges, consumption of coffee and food, and the presence of other smokers. Research from applied behavior analysis highlights the importance of understanding environmental variables involved in the maintenance of behavior on an individual level (Hanley, 9

10 Iwata, & McCord, 2003; Iwata, Kahng, Wallace, & Lindberg, 2000). Descriptive assessments involve direct observation of behavior under naturalistic conditions with no variable or environment manipulation (Herzinger & Campbell, 2007; Iwata et al., 2000). Hawkins (1979) suggests that these assessments can include self-monitoring in the natural environment as a form of direct observation. Information provided by smokers about the events preceding and following smoking can be collected and used to make hypotheses about behavioral function (Iwata et al., 2000). For example, positive reinforcement could be associated with the direct pharmacological effects of nicotine, social reinforcement, or conditioned reinforcement (e.g., the cigarettes themselves; Pomerleau, 1979; Rose & Levin, 1991). Negative reinforcement could be related to escape from aversive activities (e.g., work) or escape from aversive emotional or physiological states (e.g., urge; Tiffany, 1990). Further, antecedent events such as just having eaten food or being in the car may occasion or elicit smoking (Niaura, Rohsenow, Binkoff, Monti, Pedraza, & Abrams, 1988; Tiffany, 1990). EMA sheds light on antecedents of smoking, but does not evaluate consequences. Participants are typically instructed to report on events in their environment prior to smoking cigarettes (Shiffman et al., 2002). The variables are exclusively evaluated as antecedents although they may be functioning as reinforcing consequences. For example, a participant may report that friends are present before they have a cigarette. The presence of friends could either occasion smoking, or the participant s friends may deliver socially reinforcing consequences for smoking. The assessment of consequences is a vital aspect of understanding smoking behavior. Given the advantages of using EMA to assess antecedents of smoking, an integrated assessment of antecedent and consequent events across time may provide useful information about variables associated smoking on the individual level (Iwata et al., 2000). To this end, we 10

11 developed a questionnaire encompassing both antecedents and consequences of smoking to be used in conjunction with EMA. The present study was conducted to assess the feasibility of assessing the variables associated with smoking at an individual level by incorporating EMA with descriptive assessment methodology. 11

12 CHAPTER 2 METHODS Participants Participants were eight self-reported smokers recruited via advertisement from the local community and paid $50 on completion of the study. Participants qualified for participation if they were between the ages of 18 and 60, smoked 5 or more cigarettes per day, had an exhaled carbon monoxide (CO) reading greater than or equal to 7 ppm (if reported having smoked within the last 3 hours), and smoked for at least one year. Participant demographics and exhaled CO readings at intake are presented in Table 3-1. Screening. Applicants were screened over the phone for age, years smoking, cigarettes smoked per day, and student or employment status. If they qualified, they were invited to the laboratory for a 30-minute screening which included the informed consent process, a psychosocial history questionnaire, an exhaled CO reading, a drug test, a pregnancy test (if necessary), and the Fagerström test for nicotine dependence (FTND; Fagerstrom & Schneider, 1989; Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991). The psychosocial history contained questions related to demographics, smoking history, and alcohol and marijuana use. The FTND is a six-item questionnaire assessing nicotine dependence. Scores can range from zero to ten with a score of zero representing very low dependence and a score of ten representing very high dependence. To prevent the possibility of theft of any loaned equipment, they also provided a valid driver s license and proof of employment or student status. Exclusion criteria were a positive result on the drug (methamphetamine, cocaine, morphine, benzodiazepines) and pregnancy tests, self-reported medical conditions that would interfere with study procedures, and self-reported clinically diagnosed mental illness (e.g., schizophrenia). 12

13 If they qualified for the study, participants were contacted to return to the University of Florida Smoking Lab and Clinic (UF-SLC) and were issued a PocketPC (Dell Axim X51v or Pharos GPS 525). They were also asked to sign a property contract stating that they would return the PocketPC when asked. The participants were asked to use the Pockect PC to record each cigarette they smoked and answer brief questionnaires about the events preceding and following the cigarette for four days. Data Collection The researcher initiated the data collection program at the lab prior to loaning the device out. The program only allowed participants access to a main-menu of options for their data collection. Access to all other features of the device was blocked. Participants were instructed to begin the 4-day data collection period the day after they picked up the PocketPC. Two days consisted of self-reporting each cigarette smoked and completing the corresponding questionnaires (Pre-Post Cigarette Assessments). The other two days consisted of quasi-random prompts throughout the day to report on events not associated with smoking (No Cigarette Assessments). The Pre-Post Cigarette (smoking) and No Cigarette Assessment (non-smoking) days were alternated for each participant and the order was counterbalanced. On smoking days, the participants were asked to complete the Pre-Cigarette Assessment immediately before smoking. After finishing the cigarette, they were asked to complete the Post Cigarette Assessment. Initiating the assessments required only the selection of the corresponding button on the main menu. On non-smoking days, participants were instructed to select a button on the main menu labeled No Cigarette Assessment upon waking, which initiated a 14-hour locked data collection period of quasi-random prompts to complete the corresponding questionnaires. The program was set such that a maximum of 30 quasi-random prompts were issued during the data collection period. The time between prompts was drawn from a 13

14 distribution of 9 values derived from Fleschler and Hoffman (1962). The minimum and maximum inter-assessment intervals were and minutes (M = 34.81). A prompt began when the PocketPC beeped and asked the participant if they had smoked in the last 15 minutes. If they confirmed, a 15-minute time out was initiated and the participant was asked not to smoke. The participant was prompted on their smoking status until they reported not smoking in the last 15 minutes and the No Cigarette Assessment began. Completion of the first portion of the assessment initiated a five-minute countdown, mimicking the time elapsed during cigarette consumption. Participants were instructed not to smoke during this break. At the end of the break, participants were then prompted again to complete the second portion of the No Cigarette Assessment. If a prompt was not immediately attended to, the device beeped once a minute until the participant initiated the assessment. Assessments The assessment items were developed by Dallery, Karlson, and Ivie (2007). Some of the items were derived from Axelrod (1991), and they were originally published in The Wellness Encyclopedia (Health Letter Associates, 1991). Additionally, experts in the field of smoking cessation and applied behavioral analysis and long-term smokers were consulted during the construction of this questionnaire. The assessment items included in the present study are presented in Table 3-2. The smoking and non-smoking questionnaires were identical except for the exclusion of cigarette-related items on the non-smoking questionnaire (i.e., the last 8 items in Table 3-2). Two example items as they would appear on the PocketPC are presented in Figure 3-1. Each item was presented one at a time and participants could not return to previous answers. For the environmental events, participants recorded whether or not specific stimuli were present in their environment of if they were engaged in specific activities. They were able to 14

15 select Yes or No in response to the item. For internal states, participants rated affect adjectives and urge to smoke on a 10-point scale (1 = Not at All, 10 = Very Much ). Assessment Follow-up Upon completion of the study, participants returned the device to the UF-SLC and were compensated for their participation. They also completed a questionnaire on their experience during the data collection period. Items included: 1. Please estimate the amount of the time the pre- and post-cigarette assessment items accounted for the instances in which you smoke. For example, you could give a percentage. 2. Are there any important instances in which you smoked that the assessments did not cover? 3. Do you think the assessment helped you understand some of the reasons you smoke? Please provide a rating as to how helpful the assessment was in helping you understand the reasons you smoke on a scale of 0-100, where 0 is not helpful at all and 100 is extremely helpful. 4. Is there anything else we should know about your experience completing the assessments? For example, instances in which you did not or could not complete the assessments. A research assistant provided the results of the assessment and resources and referrals for smoking cessation upon request. Data Analysis Frequency counts were obtained for the environmental variables to assess the number of times each item was associated with an instance of smoking. Because each participant smoked a different number of cigarettes each day, proportions were calculated based on the frequency counts and the total number of cigarettes smoked. Difference scores were calculated for affect and urge items on the Pre- and Post-Cigarette Assessments to assess any effect smoking a cigarette had on these items. These analyses were also conducted for the No Cigarette Assessments. Assessments in which the participant completed both the Pre- and Post-Cigarette 15

16 Assessment were considered acceptable assessments. Assessments that did not include a Post- Cigarette Assessment following initiation of the Pre-Cigarette Assessment were considered unacceptable and dropped from the analysis. Similarly, assessments that did not include a Pre- Cigarette Assessment prior to a Post-Cigarette Assessment were dropped from the analysis. 16

17 CHAPTER 3 RESULTS All participants completed the four days of data for analysis. CD19 and KT07 completed one additional day because they accidentally initiated a locked No Cigarette Assessment during a smoking day which they had to complete in order to return to the main menu. SS01 took two days off in the middle of data collection due to scheduling conflicts, but asked to keep the device and completed all four days. The mean number of smoking occasions per participant over the two days was 15.9 (SD = 9.3). Of these, 12.5 (SD = 7.8) were acceptable smoking assessments. The mean number of non-smoking prompts completed per participant over the two days was 27.6 (SD = 6.8). The estimated number of cigarettes smoked daily from the intake screening, the total number of cigarettes reported on smoking days, and the total number of assessments completed on non-smoking days are presented for each participant in Table 3-3. Environmental Events Proportions of observations for each item on the cigarette assessments were calculated for each of the conditions (smoking and non-smoking days). The number of instances in which the participant reported the item were totaled for both data collection days and divided by the total number of cigarettes smoked. Item abbreviations are presented in Table 3-2. The proportions of observations for each item on the cigarette assessments are shown in the left column of Figure 3-2. Individual differences in the events associated with instances of smoking are apparent. Some participants reported a high frequency of the consequent events. For example, CL08 reported liking handling the cigarettes for all of the cigarettes she reported smoking. Others reported a high frequency of the antecedent events. For example, all of the cigarettes AS05 reported smoking were in the presence of non-smokers and 0.80 occurred when he had nothing to do. For other participants, both antecedent and consequent events were 17

18 reported frequently. For example, EK10 reported the presence of non-smokers and smokers and eating a meal for 0.67, 0.75, and 0.84 of the cigarettes reported (respectively). He also reported socializing with others for 0.75 of the cigarettes reported and liked handling the cigarettes, handling the lighter, watching the smoke on exhalation, and feeling the smoke in their mouth for all cigarettes reported. While some differentiation in responses is apparent for most participants, AT02 s responses appear undifferentiated. AT02 never reported any event occurring for more than half of the cigarettes reported. Proportions of observations for each item on the non-smoking assessments are shown in the right column of Figure 3-2. Few differences between smoking and non-smoking days are apparent. In some instances, participants reported a greater frequency of one or two items. For example, BH09 reported being with smokers more often when smoking than when not. Overall, smoking days appear to be similar to non-smoking days. This may be due to the fewer number of observations on smoking days than non-smoking days for most participants. Internal States Average and individual difference scores for the affect items and urge on the Pre- and Post-Cigarette Assessments are shown in the left column of Figure 3-3. Item abbreviations are presented in Table 3-2 and the scale ranges from -10 to 10. Different patterns emerged in the average differences from before to after cigarette smoking. Three participants reported average changes near zero for most of the items. Slight increases in feelings of relaxation, satisfaction, contentedness, and happiness and slight decreases in need for a lift were reported by some participants. For BH09, these changes were generally near ±2. For CL08, EK10, KT07, SS01, these changes range from 0 to ±2. One notable deviation from these general patterns is the item assessing urge. Seven of the eight participants, regardless of the pattern of affect items, 18

19 reported an average decrease greater than 2 for urge to smoke a cigarette. The eighth participant reported an average decrease of 1.4. Average and individual difference scores for the affect items and urge on the No Cigarette Assessments are shown in the right column of Figure 3-3. A malfunction in the program resulted in the item lift not being recorded on No Cigarette Assessment days. The results are presented without this item. Different patterns from the ones observed on smoking days emerged in the average differences from before to after the five-minute break. Only one participant, KT07, reported a decrease in urge for a cigarette after the break. This participant and SS01 were the only ones to show a similar pattern on smoking and non-smoking days for changes in affect items. AT02 showed slight average increases and decreases in affect items between smoking and non-smoking days. The remainder of participants showed no average changes in affect from just experiencing the passage of time. Assessment Follow-up Information gathered from the assessment follow-up is presented in Table 3-4. Participants estimated that the assessments accounted for an average of 66% of the instances in which they smoked. None of the participants felt the assessments accounted for all of their smoking situations, yet only two participants provided additional information. EK10 suggested that he often smoked when bored and none of the items covered these instances. BH09 said that the items did not cover his habitual smoking or smoking as food replacement between meals. Participants reported an average helpfulness rating of 56 out of 100 in understanding their smoking patterns. KT07, who gave a low rating for helpfulness, reported doing so because she already knew why she smoked. When asked if we should know anything else about their experience with the device or data collection, about half of the participants provided additional information. KT07 reported 19

20 that some of the Post-Cigarette Assessment items reflected something that happened while she was smoking and not the cigarette itself. No examples were provided, but a plausible situation would be having an argument while smoking and reporting feeling angrier on the Post-Cigarette Assessment. AT02, BH09, CL08, and KT07 reported being in situations in which they could not attend to the No Cigarette prompts or could not hear them. AS05 reported forgetting to fill out Post-Cigarette Assessments because he was not prompted to do so, like with the No Cigarette Assessments. KT07 also admitted not accurately reporting the number of cigarettes she smoked; she had smoked many cigarettes one evening but only accounted for one because she was afraid of losing the device while drinking. EK10 claimed that his smoking increased from 0 to 5 cigarettes to 2 to 8 cigarettes a day from having to fill out the assessments. This participant, however, never reported more than four cigarettes on either of the cigarette assessment days, raising questions about the validity of this statement. 20

21 Table 3-1. Participant demographics ID Sex Race Education Age Years smoking CO (ppm) FTND AS05 AT02 BH09 CD19 CL08 EK10 KT07 SS01 Male Female Male Male Female Male Female Male Latino Caucasian Caucasian Native American Caucasian Caucasian Caucasian Caucasian Some college Some college Some college GED Some college Some college Some college Some college Note. CO (carbon monoxide) refers to a measure of exhaled carbon monoxide in parts per million (ppm). FTND refers to the Fagerstrom Test for Nicotine Dependence. Table 3-2. Assessment items and abbreviations Items I feel like I need a lift. I feel relaxed. I feel satisfied. I feel content. I feel happy. I feel angry. I feel frustrated. I feel sad or depressed. I feel anxious. I have an urge to smoke. I am with other people who are smoking. I am with other people who are NOT smoking. I just ate a meal or a snack. I am in my car. I am talking on the phone. I am waiting for someone or something. I have nothing to do. I am drinking a beer or other alcoholic beverage. I am drinking coffee. I am taking a break from work. I liked handling the cigarettes and cigarette container. I liked watching the smoke as I exhaled it. I liked handling the lighter or matches. I liked the feel of the smoke in my mouth and throat. I liked the way smoking made me feel around other people. I liked the way people looked at me when I smoked. I liked the way people interacted with me with I smoked. I socialized with other when I smoked. Abbreviation Lift Relaxed Satisfied Content Happy Angry Frustrated Depressed Anxious Urge With smokers With non-smokers Meal Car Phone Waiting Nothing to do Alcohol Coffee Break Handling Cigarettes Watching smoke Handling lighter Feel of smoke Feel around others Looked at me Interacted with me Socialized with others 21

22 Table 3-3. Number of cigarettes or assessments ID Intake Smoking Non-smoking AS AT BH CD CL EK KT SS Table 3-4. Assessment follow-up ID % Accounted For Additional Items Helpfulness AS05 AT02 BH09 CD19 CL08 EK10 KT07 SS No No Habit/Food replacement No No Boredom No No

23 I am with other people who are smoking. Yes Next No I feel like I need a lift Not at all Very much Next Figure 3-1. Examples of assessment items on the PocketPC. 23

24 With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke A AS05 - Pre-Post B AS05 - No Cig With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke AT02 - Pre-Post AT02 - No Cig With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke BH09 - Pre-Post BH09 - No Cig With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke CD19 - Pre-Post CD19 - No Cig Figure 3-2. The proportions of observations for environmental events. A) Smoking assessments. B) Non-smoking assessments. 24

25 With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke A CL08 - Pre-Post EK10 - Pre-Post B CL08 - No Cig EK10 - No Cig With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke KT07 - Pre-Post KT07 - No Cig With non-smokers With smokers Coffee Meal Alcohol Phone Car Break from work Waiting Nothing to do Socialized with others Interacted with me Feel around others Looked at me Handling cigarettes Handling lighter Watching smoke Feel of smoke Figure 3-2. Continued SS01 - Pre-Post SS01 - No Cig

26 A B 10 AS05 - Pre-Post AS05 - No Cig Difference Score AT02 - Pre-Post 10 AT02 - No Cig Difference Score BH09 - Pre-Post BH09 - No Cig Difference Score Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Question Question Figure 3-3. Average and individual difference scores for internal states. A) Smoking assessments. B) Non-smoking assessments. Filled data points represent the first day of the assessment. Unfilled data points represent the second day of the assessment. Bars represent the two-day average for the item. 26

27 10 8 A CD19 - Pre-Post B CD19 - No Cig 6 4 Difference Score CL08 - Pre-Post CL08 - No Cig Difference Score EK10 - Pre-Post EK10 - No Cig 6 4 Difference Score Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Question Question Figure 3-3. Continued 27

28 A B KT07 - Pre-Post KT07 - No Cig Difference Score SS01 - Pre-Post SS01 - No Cig Difference Score Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Lift Relax Satisfied Content Happy Angry Frustrated Sad/Depressed Anxious Urge Question Question Figure 3-3. Continued 28

29 CHAPTER 4 DISCUSSION The results of this study suggest a descriptive assessment of smoking is feasible using the proposed methods. Individual differences in the events associated with smoking were observed, suggesting that our methods can effectively assess smoking behavior at an individual level. The results also suggest that the inclusion of consequences may be useful in this assessment, as some participants reported these events as frequently occurring. Hypotheses about reinforcement contingencies and specific maintaining variables can be derived from the data gathered by these assessments. For example, a hypothesis of CL08 s smoking would be that the reinforcing consequence of stimulation from handling the cigarettes maintains her smoking given that report of this item occurs frequently with smoking. In general, this study is consistent with results from prior studies suggesting that assessment of situations associated with smoking is possible using this monitoring strategy in the natural environment (Shapiro, et al., 2002; Shiffman et al., 2002). For example, Shapiro et al. (2002) reported that smoking occasions were positively associated with being in a car, outdoors, or on a work break; while waiting, being with friends, or being with others who are smoking; or after consumption of alcohol or food. Additionally, compared with control occasions, smoking was associated with an increased urge to smoke, feeling happy, and feeling stressed. The results of the present study also suggest smoking was associated with these items; however, the frequency of the events varied markedly across participants. Assessing smoking at the individual level is possible and provides a more clear account of smoking events. Furthermore, previous research exclusively evaluated smoking-related events as antecedents (Shapiro, et al., 2002; Shiffman et al., 2002; Shiffman, et al., 2007). The present study assessed antecedents prior to and consequences following cigarette consumption. Consequences were frequently reported, 29

30 suggesting that they were relevant to smoking for some participants and provide more information on smoking-related events. The data gathered from non-smoking days suggest few differences in the events reported when compared to smoking days. In other words, many of the antecedent events reported seem to occur frequently regardless of whether or not the participant is smoking. Unfortunately, the degree to which each item is associated with smoking cannot be determined (Epstein & Collins, 1977; Schwartz & Stone, 1998). The data from smoking days do not tell us how many times the stimulus was present in the environment and smoking did not take place. Further, large discrepancies were observed in the number of cigarettes reported on smoking days versus randomly prompted assessments on non-smoking days (Table 3-3). Comparisons between smoking and non-smoking assessments may be misleading. For example, a report of being in the car for 2 of 6 assessments on smoking days versus 2 of 20 assessments on non-smoking days may suggest that the car is more often associated with smoking (proportions of 0.33 and 0.10, respectively). The comparisons between the two types of assessments should be interpreted with caution; however, the information gained from the smoking assessment independently may still be useful in that we have a depiction of smoking-related events. Although descriptive assessment is feasible, interpretation may prove to be more difficult. Events reported less frequently than others does not preclude any of those events from playing a role in smoking. Even an item reported only twice out of 20 cigarettes may be functioning to maintain smoking for that individual. This may be the case for AT02, whose results seem to be undifferentiated. Additionally, these items could be functioning as complex stimuli, with two or more items occurring simultaneously. For example, social reinforcement from friends combined with tactile stimulation from inhaling could occur simultaneously for each cigarette. Or perhaps a 30

31 participant frequently reports drinking coffee before smoking, as well as liking the feeling of the smoke in their mouth. Does smoking make the effects of coffee more enjoyable, or is the coffee incidental to the reinforcing tactile stimulation of smoking? The results of this study were also congruent with other studies suggesting that subtle, if any, changes in affect are observed in the assessment of affect (Shiffman et al., 2002). With our data, however, interpretation of these subjective measures is difficult given how the items are scored. Difference scores from before to after cigarette consumption were calculated to assess any changes in internal states from smoking, but determining what constitutes a meaningful difference is challenging. An average increase of 2 for happy seems low, but may be a meaningful increase for maintaining smoking for one smoker but not others. The concern could be raised that our measure is not sensitive to assessing these items; however, the consistently reported average decrease in urge after smoking a cigarette is a promising indication that the assessments were measuring some aspects of the smoking situation. Some investigators may be concerned about the accuracy of self-report. There are, however, many benefits to using self-report data. Self-reports are often used in human behavioral research because they can provide information about a vast array of behavioral phenomena, many of which would be difficult to measure in other ways (Critchfield, Tucker, & Vuchinich, 1998, p. 436). As previously discussed, this is certainly the case with attempting to assess events associated with smoking. Someone reporting on their own behavior may even be at an advantage because they are subject to subtleties and special conditions affecting the behavior that any other audience would not be privy to (Johnston & Pennypacker, 1980). Future research on the proposed methodology should include an attempt at increasing the validity and accuracy of selfreports of smoking. This could be achieved by utilizing empirical validation strategies such as 31

32 comparing self-reports with different measures of the same referent behavior, seeking converging evidence from several types of self-report, and calibrating self-reports at times other than the main study (Critchfield et al., 1998). For example, calibrating self-reports may involve providing participants with operational definitions of the assessment items and training responses in the laboratory. A possible limitation of this study, closely related to self-report, is the possibility of reactivity. Reactivity refers to changes (increases or decreases) in the frequency of monitored behavior, including self-monitored behavior (Kazdin, 1979; Korotitsch & Nelson-Gray, 1999). For assessment purposes, the behavior observed would not be considered natural if it were reactive (Epstein & Collins, 1977; Kazdin, 1979). In the present study, a comparison of reported number of cigarettes smoked daily prior to and during the study reveal discrepancies (Table 3-3). In general, participants smoked less during the study than what they reported prior to data collection. One participant reported that the data-collection procedure increased the number of cigarettes smoked; however, as previously discussed, the data did not validate his statement. Two situations could explain the discrepancies in cigarettes reported by participants: 1) overestimation of the number of cigarettes they smoked and 2) reactivity to self-monitoring which resulted in a decrease in cigarettes smoked. Some participants reported not accurately reporting the cigarettes they smoked during the study because of situations in which they could not attend to the PocketPC, but none of the participants indicated deceptive reporting of cigarettes or any actual decreases in their smoking. Reactivity in the present study is a possibility, but difficulty with the data-collection device or overestimation of cigarettes smoked is a more likely explanation for any decreases in the number of cigarettes smoked during the study. 32

33 EMA and descriptive assessment provide structured methodologies for assessing smoking behavior in the natural environment. The data gathered using these methods in conjunction may allow researchers and clinicians to make hypotheses about behavioral function. Additionally, the descriptive assessment could provide a basis for a more rigorous functional assessment. As the results of this study currently stand, however, we cannot move beyond correlates of smoking and hypotheses about behavioral function. Knowledge of behavioral function may be critical in developing effective treatment strategies for smoking cessation (Axelrod, 1991; Kassel & Yates, 2002; Shiffman, 1993b). Without a delineation of causal variables, the results of the descriptive assessment may not be sufficient for making function-based treatment recommendations (Hanley et al., 2003). This is the first of many steps in an attempt to understand individual maintaining variables of smoking and how researchers can use this information to aid smokers in their search for successful treatment strategies. 33

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37 BIOGRAPHICAL SKETCH Alana M. Rojewski was born in Zanesville, Ohio. She graduated from Bishop Rosecrans High School in 2002, where she took an early interest in psychology. She was able to pursue this major at Denison University in Granville, Ohio, graduating magna cum laude with her B.A. in psychology in From her early research experiences at Denison, she also developed an interest in drug abuse research. Alana matriculated in the behavior analysis program of the Psychology Department at the University of Florida under Dr. Jesse Dallery in the fall of She received her M.S. from the University of Florida in the fall of 2009 and is currently pursuing her Ph.D. Her current research interests include smoking and cessation methods. 37