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Exploring the association of number of cigarettes smoked and confidence to quit smoking in Korean American emerging adults: a multilevel modeling approach
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Content
1
Exploring the association of number of cigarettes smoked and
confidence to quit smoking in Korean American emerging adults: A
multilevel modeling approach
by
Katherine Yang
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER IN SCIENCE
APPLIED BIOSTATISTICS AND EPIDEMIOLOGY
August 2015
2
Table of Contents
Header Page number
Title page 1
Acknowledgements 3
Abstract 4
Background 5
Methods 7
Results 13
Discussion 14
References 17
Figures and Tables 19
3
Acknowledgements
I would like to sincerely thank Dr. Jimi Huh, Dr. Chih Ping Chou, and Dr. Stanley Azen for their
amazing support and feedback during this process.
4
Abstract
Social cognitive theory and the behavioral theory have been used to explain the relationship
between self-efficacy for abstaining from smoking and smoking behavior change. Social
cognitive theory suggests increased perceived self-efficacy for abstaining from smoking leads to
smoking reduction; in contrast, the behavioral theory suggests it is the decrease in smoking
behavior that leads to an increase in perceived self-efficacy. The purpose of this study was to test
these two competing theories in Korean American emerging adults (KAEA) (18 through 25
years of age) smokers. Data were obtained from a 7 day mobile Ecological Momentary
Assessment (EMA) of situational and social contexts associated with smoking behaviors of
KAEA smokers through electronic surveys on their own smartphones. Daily measures were
collected for 7 days from 78 participants for a total of 546 observations. Two multilevel models
were conducted to assess the bidirectional association between self-confidence to quit and
number of cigarettes smoked per day. The first model was used to evaluate whether daily number
of cigarettes was a predictor of the level of confidence to quit smoking the next day. The second
model was used to evaluate whether daily confidence to quit was a predictor of next day’s
number of cigarettes smoked. The main predictors, self-confidence to quit and number of
cigarettes smoked, were disaggregated into within person effects and between person effects.
Results from the first model demonstrated that smoking more than one’s usual self that day
(within-person) was associated with lower levels of confidence to quit cigarettes, but this
relationship was not statistically significant (est=-0.04, p=0.18). However, being a heavier
smoker than average (between-person) was significantly associated with lower levels of
confidence to quit smoking (est = -.03, p=0.02). Results from the second model showed having
higher confidence to quit smoking than one’s usual confidence level (within-person) was not
5
significantly associated with next day’s number of cigarettes smoked (p=0.95), but being a
smoker with higher confidence to quit than the average (between-person) was significantly
related to lower numbers of number of cigarettes smoked the next day (est=-0.19, p=0.04). These
findings are helpful in understanding the KAEA smoking behavior, but more work needs to be
done to understand how one’s self confidence to quit smoking and smoking frequency affect the
behavior of KAEA smokers.
Background
The social cognitive theory and the behavioral theory present two different explanations
to the relationship between self-efficacy and behavior change. The social cognitive theory states
that it is the change in self-efficacy that lead to change in behavior (Bandura, 1994, 1977), while
the behavioral theory states that it is the change in behavior that leads to change in self-efficacy
(Skinner, 1974). These two theories have been used to explain the relationship between smoking
and behavior and one’s self efficacy to quit smoking. Some believe that it is the change in one’s
self efficacy to quit smoking that leads to a change in the smoking behavior (Gwaltney,
Schiffman, Balabanis, & Paty, 2005; Manfredi, Cho, Crittenden, & Dolecek, 2007). For
example, if a person wanted to decrease the level of cigarette use or quit using cigarettes
altogether, they would first have to increase their confidence in their ability to quit smoking. In
contrast, others have claimed it is actually the change in behavior that predicts change in one’s
self efficacy to quit smoking (Romanowich, Mints, & Lamb, 2009; Van Zundert, Engles,
Ferguson, & Schiffman, 2010). Simply put, it is the act of smoking fewer number of cigarettes
used that results in someone having higher confidence in their ability to quit smoking.
With these competing views and conclusions, it should be considered whether the
temporal order and the direction of the association would differ depending on the characteristics
of the population. Past studies have mostly focused on a broad range of age and non-specific
6
ethnic groups and evidence of change were mostly observed only relative to an individual’s own
self (Gwaltney, et al., 2005; Gwaltney, Metrik, & Kahler,2009; Perkins et al., 2012; Romanwich
et al., 2009). More data are needed on how the two theories and the association would hold when
focused on groups with characteristics associated with vulnerability for cigarette use. Korean
American 18-25 years old emerging adults (KAEA) represent a critical developmental stage
often associated with greater substance use, including tobacco (Arnett, 2000) and part of an
ethnic group where smoking is perceived as a social norm (Huh, Sami, Abramova, Spruijt-Metz,
& Pentz, 2013).
To elaborate more on the importance of studying the relationship between smoking
behavior and self-efficacy to quit smoking in the KAEA, this group is a critical group to study
because of the growing evidence supporting increasing trend in smoking initiation and high
prevalence in smoking (Lantz, 2003; Wechsler, Rigotti, Gledhill-Hoyt, & Lee, 1998).
Furthermore, it is especially important to better understand smoking behavior among KAEA due
to their greater initiation in cigarette use during this developmental period (Myers, Doran,
Trinidad, Klonoff, & Wall, 2009) and prevalence in smoking compared to other ethnic groups
(Caraballo, Yee, Gfroerer, & Mirza, 2008; Trinidad, Gilpin, Lee, & Pierce, 2004). Among Asian
Americans, which include Korean Americans, 65.4% claimed to have initiated smoking between
the ages of 18 and 25 years compared to 46.8% in Hispanic/Latino, and 46% in non-Hispanic
whites, and 52% in African Americans (Trinidad et al., 2004). To further disaggregate smoking
prevalence in Asian Americans, Koreans had the highest prevalence in smoking at 26%
compared to other Asian ethnic groups (e.g., Vietnamese-21.5%, Filipino-16.7%, and Chinese-
8.8%) (Caraballo et al., 2008). Clearly, smoking is not an uncommon health practice amongst
KAEA.
7
For this study, to test the two competing theories, the association between daily
confidence to quit cigarettes and number of cigarettes smoked per day in Korean American
emerging adults was assessed by creating 2 multilevel models (MLM) and disaggregating within
person and between person effects of the association. Within person effect is defined as effects of
covariates that take on different values for each person over time and, and between person effect
is defined as effects of covariates that only differ across persons (Curran & Bauer, 2011). It was
hypothesized that 1) the effects of within person and between person current number of
cigarettes smoked would have a negative relationship with the daily self-confidence to quit
cigarettes, and that 2) the effects of within person and between person’s daily confidence to quit
cigarettes would also have a negative relationship with the number of cigarettes smoked the
following day in Korean American emerging adults.
Methods
Study Design
This study was a 7 day mobile Ecological Momentary Assessment (EMA) longitudinal study
assessing situational and social contexts associated with smoking behaviors of KAEA smokers
through electronic surveys on their own smartphone. Each participant received their individual
surveys via a mobile app created in-house called “EMA” (ilumivu, Inc.), which participants
downloaded on to their personal mobile devices at the start of the study. Each participant
participated in baseline survey, five random surveys per day, one end of the day survey, and at
least four user-initiated (e.g., event-contingent for smoking) surveys per day.
Participants
For this study, the source population was KAEA smokers between ages of 18-25 who currently
resided in the Los Angeles or Orange County area. To participate, participants had to meet the
eligibility criteria of being Korean or Korean American, were between the ages of 18-25 years
8
old, smoked at least 4 cigarettes a day, and had constant access to a mobile device with constant
data service or internet connection. Participants who met the eligibility criteria were then asked
on a first come first serve basis to review the consent form and those who agreed and signed
were invited to participate in the study. All study procedures were approved by the University
Institutional Review Board.
Recruitment
Participants were recruited using social media, word of mouth, and study advertising materials.
The most common approach was the direct recruitment of participants either by the research
assistants approaching potential participants in public spaces or through referrals from other
people who knew about our study or by the participants themselves. Majority of our participants
were recruited via direct recruitment. The second most common approach was by the use of
advertisement by posting and leaving IRB approved flyers and cards in public spaces where a lot
of KAEA gathered such as cafes. On the advertisements were basic information about the study,
eligibility requirement, and contact information. In addition to the physical advertisement, we
also utilized the social network site Facebook by to create a page which included a picture of the
Institutional Review Board approved flyer and information about the study.
Sample Size
A total of 126 people were assessed for eligibility. A total of 15 people were excluded because
they did not meet the age requirement, 4 did not meet the ethnicity requirement, 2 resided outside
of the Los Angeles County or Orange County, 1 was not a daily smoker, and 3 did not possess
phones that were compatible with the required software to be used. Out of the 111 people who
met the eligibility criteria, 12 were unresponsive when contacted again, 9 were lost during the
wait period to fix a bug on the software, and 3 changed their minds to participate in the study.
9
Ultimately, 87 participants were enrolled into the study. During the study, 8 participants were
dropped due to little participation or lost interest in participating. Data were collected from 79
participants but analysis was done on 78 participants (level-2) due to 1 participant having poor
compliance. An illustration demonstrating the flow of attaining the final analytical sample size is
shown in Figure 1. From the 78 participants, a possible total of 546 observations were collected
because each participant provided daily data through surveys for 7 days. For this study, analysis
involved 503 observations (level-1) due to few missed surveys by participants.
Measurement
Baseline survey was taken on their mobile phone devices at the initial meeting. The day after the
baseline survey was taken, five random surveys were delivered to participant’s phone for 7 days
between the hours of 8am and 11pm and were given 15 minutes to complete. In addition, a
reminder alert was sent to the phone every 5 minutes for 15 minutes from the original when
surveys were unanswered. User initiated surveys were taken while smoking to capture current
emotion and situation during the smoking event. Therefore, participants were encouraged to take
these surveys every time they smoked, but only a minimum of four was required. The end of the
day survey asked about the day’s overall cigarettes use and was delivered once per day at 10pm
and given three hours to complete.
Variables
Demographic Variables
The demographic variables birth of origin, age, sex, education level, current occupation, attempts
to quit smoking, and other smoking related questions were collected from each individual’s
baseline survey.
10
Nicotine Dependence (FTND)
Participant’s level of nicotine dependence was assessed using the Fagerström test for nicotine
dependence (FTND) scale (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991). The FTND
scale consisted of six questions where each question had a score that ranged from 0 to 3 based on
the answer. The scores were then summed to yield a total of 0-10 with higher the value meaning
stronger the dependence. All of the six questions were part of the baseline survey. FTND was
controlled for because it was possible the association between confidence to quit smoking and
number of cigarettes smoked could differ depending on how dependent someone was on
nicotine.
Daily Absolute Confidence to Quit Smoking
Participant’s daily absolute confidence to quit smoking was collected from the end of the day
survey asking participants how confident they were quitting cigarettes on a range of 1-10.
Number of Cigarettes Smoked
The daily number of cigarettes smoked was collected from the end of the day survey in which
participants were asked to type in the total number of cigarettes smoked that day.
Data Analysis
Descriptive statistics were calculated for level-2 sample characteristics. Multilevel modeling
(MLM) was performed to assess the association between daily self-confidence to quit and the
number of cigarettes smoked per day, controlling for gender, FTND, past attempts at quitting,
and day of the week. MLM was used to analyze the data because the variables confidence to quit
and the number of cigarettes smoked were collected repeatedly, specifically once every day for
seven days. Main predictors of interest were partitioned into between person and within person
11
levels to observe change in outcome within an individual and between individual levels (Curran
& Bauer, 2011).
Using MLM, two general linear mixed models were constructed to explore the
directionality and association of the relationship. The first model (Figure 2a) was used to
evaluate whether daily number of cigarettes was a predictor of daily confidence to quit smoking.
The reason for looking at this association concurrently on the same day was because confidence
about one’s ability to quit smoking was asked at the end of the day, and logically it made sense
that most people would reflect on their current day’s smoking behavior to answer the question.
Also, because we were interested in the relationship between daily confidence to quit relative to
the change in the number of cigarettes within person and between person, the primary variable of
interest, number of cigarettes, was centered around each individual’s own mean (i.e., within-
person) as well as around the grand sample mean (i.e., between-person) to discern within- and
between-person effects (Curran & Bauer, 2011). The second model (Figure 2b) was used to
evaluate whether daily confidence to quit was a predictor of next day’s number of cigarettes
smoked. The reason for observing the following day’s number of cigarettes was because daily
confidence to quit was always collected at the end of the night, and we wanted to see how the
overall confidence felt the night before would affect the number of cigarettes smoked the
following day. In order to explore the relationship between previous day’s confidence to quit
and current day’s number of cigarettes smoked, the variable current day’s confidence to quit had
to be lagged relative to the number of cigarette smoked on a specific day because only current
day’s information was collected. The lagged confidence to quit variable was created simply by
examining whether previous day’s confidence to quit value would be associated with current
day’s number of cigarettes smoked, adjusting the confidence to quit variable. And again, because
12
we were interested in within person and between person variations, the variable confidence to
quit was centered around each individual’s own mean as well as the grand sample mean (Curran
& Bauer, 2011). The variables FTND, gender, history of quit attempts, and day were included as
controls in both models.
Using MLM, for each model, the within and between person levels can be expressed as:
Level 1 (within person trajectory) equation
yti = β0i + β1ixti+rti,
where yti represents the repeated measure observed at time point t for individual i, B0i and B1i
represents the intercept and linear slope for individual i, xti is the observed value of time at
assessment t for individual i, and rti is the time and individual specific residual (Curran & Bauer,
2011)
Level 2 (between person trajectory) equation
β0i = γ00 + γ01wi + u0i
β1i = γ10 + γ11wi +u1i ,
where γ00 and γ10 are the overall mean intercept and slope, γ01 and γ11 represent the fixed effect
regression of the random intercept and slopes components of the time-invariant covariates, wi
represents a single time-invariant covariate, u0i and u1i are the individual specific deviations from
the overall mean (Curran & Bauer, 2011) By substituting level 2 equation to level 1 equation, the
reduced form of the equation for the model can be expressed as (Curran & Bauer, 2011):
yti = (γ00 + γ01wi + (γ10 + γ11wi )xti)+(rti+ u0i+ u1ixti ).
Applied to the current study, model 1 can be expressed as
yti = [γ00 + γ01(bpnumcig)i + γ02(FTND)i + γ03(male)i + γ04(hisquit)i + γ05(day)i + u0i] + [(γ10 +
γ11(bpnumcig)i + γ12(FTND)i + γ13(male)i + γ14(hisquit)i + γ15(day) I + u1i)(wpnumcig)ti] + rti,
13
and model 2 can be expressed as
yti = [γ00 + γ01(bpabsconf)i + γ02(FTND)i + γ03(male)i + γ04(hisquit)i + γ05(day)i + u0i] + [(γ10 +
γ11(bpnumcig)i + γ12(FTND)i + γ13(male)i + γ14(hisquit)i + γ15(day)i + u1i)(wpabsconf)ti] + rti
Results
Demographics of the Sample
Our sample consisted of 78 Korean descendant subjects, 63% were born in the United States, the
average age was 22.4 years old, and more than half (72%) were males. Majority of the subjects
had the highest education level of high school or equivalent (38.5%), 2-year junior or community
college (21.8%), or 4-year college or university (35.9%). Currently, most of the subjects were
either employed full time (32.1%) or were in school either part time or full time (51.3%). Few
participants (37.2%) claimed they have attempted to quit cigarettes in the past 12 months. The
mean nicotine dependence was very low with an average FTND score of 2.10. Participants
reported smoking 6.9 cigarettes per day, on average, and had a fairly moderate level of
confidence to quit with an average of 4.8 out of 10. Table 1 provides a summary of the
demographic and smoking history/behavior characteristics of the sample.
Association and Direction
Figures 3 and 4 provide a graphical representation of the change in confidence to quit cigarettes
and the number of cigarettes smoked within each individual plotted over a 7 day period. The ‘0’
on Figures 3 and 4 represent individual means (i.e, an individual was at their average confidence
or smoked their average number of cigarettes). A few individuals were fairly consistent
throughout the week, but majority fluctuated. Figures 5 and 6 are a subset of some of the
individual subject’s plots of their change in confidence to quit cigarettes and the number of
cigarettes smoked over a 7-day period.
14
Results (table 2) show that smoking more than one’s usual self that day (within-person)
was associated with lower levels of confidence to quit cigarettes, but this relationship was
not statistically significant (p=0.18). However, being a heavier smoker than average (between-
person) was significantly associated with lower levels of confidence to quit smoking (est = -.03,
p=0.02). Other predictors that were found to have statistically significant influence on confidence
to quit smoking were nicotine dependence as measured by the FTND scale (est= -0.38, p=0.03),
and gender (est=1.73, p=0.01). Higher levels of FTND was associated with lower levels of
confidence to quit cigarettes, and males had higher level of confidence to quit cigarettes than
females. Attempts to quit cigarettes in the past 12 months was not a significant predictor of one’s
confidence to quit (p=0.14).
Similar to the results of the first model, the second model (table 3) shows that having
higher confidence to quit smoking than one’s usual confidence level (within-person) was not
significantly associated with next day’s number of cigarettes smoked (p=0.95), but being a
smoker with higher confidence to quit than the average (between-person) was significantly
related to lower numbers of number of cigarettes smoked the next day (est=-0.19, p=0.04). Other
predictor that was found to have statistically significant influence on the number of cigarettes
smoked the next day was nicotine dependence measured as FTND (est= 0.56, p<0.001). Higher
levels of FTND was associated with an increase in the number of cigarettes smoked the next day.
The variables gender (p=0.083) and attempts to quit in the past 12 months (p=0.36) were not
significant predictors of number of cigarettes smoked the next day.
Discussion
The current study examined the association between number of cigarettes smoked and the
confidence to quit cigarettes in Korean Americans between the ages of 18 and 25 years using
15
daily diary data. Social cognitive theory suggests increased confidence to quit smoking leads to
smoking reduction; in contrast, the behavioral theory suggests it is the smoking reduction that
leads to increased confidence to quit smoking. Two models were created to assess the two
theories between confidence to quit smoking and number of cigarettes smoked in KAEA using
MLM. The first model modeled number of cigarettes as a predictors of one’s confidence level to
quit cigarettes, and the second model modeled one’s confidence to quit cigarettes as a predictor
of next day’s number of cigarettes smoked. The main predictors were disaggregated into within
person and between person levels to appropriately disaggregate the effects into two level to
explore the relationship within a person as well as relationships that hold across persons to
ultimately gain more comprehensive understanding of the relationship. This was possible
because the study was a longitudinal study.
Our results were very interesting because the associations found on a between person
level was not replicated at the within person level. Results indicated that in Korean American
emerging adults, heavier smokers have less confidence to quit cigarettes than the average
smokers and smokers with higher than average confidence in quitting their smoking smoked less
cigarettes (i.e., between-person effect). However, this same association could not be produced at
a within person level. Results showed that smoking more than one’s usual amount did not
significantly lower one’s confidence to quit cigarettes and having more confidence to quit than
usual did not significantly decrease the number of cigarettes smoked the next day (i.e., within-
person effect). Furthermore, based on our results we did not have enough evidence to support
either the social learning theory or the behavioral theory on a within person level, but on a
between person level, the association between number of cigarettes smoked and one’s
confidence to quit was negative and bidirectional and supported both theories. We can deduce
16
that in general amongst KAEA, heavier smokers have less confidence to quit smoking than light
smokers, but we cannot determine whether changing one’s smoking behavior or increasing self-
confidence within an individual would cause an individual’s cessation confidence or smoking
behavior to change.
However, it is possible that there were no significant associations found on a within
person level due to some limitations of our study. A possible limitation could have been that we
did not encourage or implement smoking cessation, but was more focused in self-efficacy in
relation to everyday continued cigarette use, so there was not a lot of change within individuals.
Another limitation could have been that our sample consisted of light smokers who smoked an
average of about 7 cigarettes per day and were not very heavily dependent on nicotine (FTND =
2.10).
Regardless, these results are helpful in showing that Korean American emerging adults
share similar smoking behavior patterns as other smokers in which those who smoke more have
less confidence in their ability to quit smoking and those with higher confidence to quit generally
smoke less. More work is needed to better understand the within person association between
number of cigarettes smoked and one’s confidence to quit.
17
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19
Figures and Tables:
Figure 1. Consort Diagram
Figure 2. Models of associations of interest
a. Model I: Number of cigarettes smoked as a predictor of confidence to quit smoking
b. Model II: Current day confidence to quit smoking as a predictor of next day’s number of
cigarettes smoked
Number of
cigarettes smoked
Confidence to quit
smoking
Current day’s confidence
to quit smoking
Number of cigarettes
smoked next day
20
Figure 3. Plot of change in within person confidence to quit smoking over 7 days.
Figure 4. Plot of change in within person number of cigarettes smoked over 7 days
21
Figure 5. Plot of change in within person confidence to quit smoking over 7 days on an
individual level (showing a subsample)
Figure 6. Plot of change in within person number of cigarettes smoked over 7 days on an
individual level (showing a subsample)
22
Table 1. Baseline Characteristics
Characteristic Participants (N=78)
Age, Mean (S.D.) 22.39 (1.76)
Sex, n (%)
Male 56 (71.8)
Female 22 (28.2)
Born in U.S., n (%) 49 (63)
Highest education, n (%)
High school or equivalent 30 (38.5)
2-year junior or community college 17 (21.8)
4-year college or university 28 (35.9)
Vocational, business, or trade school 1 (1.3)
Graduate or professional school 1 (1.3)
Current occupation, n (%)
Full-time student 17 (21.8)
Part time student, part time employed 12 (15.4)
Full time student, part time employed 11 (14.1)
Employed part time 5 (6.4)
Employed full time 25 (32.1)
Not employed, looking for work 8 (10.26)
Attempt to quit in past 12 months, n (%) 29 (37.2%)
FTND, Mean (S.D.) 2.10 (1.92)
Number of cigarettes smoked per day, Mean
(S.D.) 6.92 (3.02)*
Confidence to quit cigarettes, Mean (S.D.) 4.76 (3.21)*
* N=503 (based on daily responses)
23
Table 2. Within person and between person number of cigarettes as predictors of confidence to
quit smoking cigarettes
Effect Estimate SE DF t-value p-value
Intercept 9.19 1.59 73 5.8 <0.001
Wpnumcig -0.04 0.03 422 -1.34 0.18
Bpnumcig -0.3 0.13 422 -2.26 0.02
FTND -0.38 0.18 422 -2.13 0.03
Male 1.73 0.67 422 2.59 0.01
Hisquit 0.83 0.56 422 1.47 0.14
Day -0.05 0.03 422 -1.77 0.08
Table 3. Within person and between person confidence to quit smoking cigarettes as predictors
of next day smoking abstinence
Effect
Estimate SE DF t-value p-value
Intercept 7.44 1.36 73 5.47 <0.001
Wpabsconf -0.006 0.09 321 -0.07 0.95
Bpabsconf -0.19 0.09 321 -2.09 0.04
FTND 0.56 0.14 321 4.02 <0.001
Male 0.965 0.55 321 1.74 0.083
Hisquit -0.42 0.46 321 -0.91 0.36
Day -0.07 0.05 321 -1.33 0.19
Abstract (if available)
Abstract
Social cognitive theory and the behavioral theory have been used to explain the relationship between self-efficacy for abstaining from smoking and smoking behavior change. Social cognitive theory suggests increased perceived self-efficacy for abstaining from smoking leads to smoking reduction
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Asset Metadata
Creator
Yang, Katherine
(author)
Core Title
Exploring the association of number of cigarettes smoked and confidence to quit smoking in Korean American emerging adults: a multilevel modeling approach
School
Keck School of Medicine
Degree
Master of Science
Degree Program
Applied Biostatistics and Epidemiology
Publication Date
07/29/2015
Defense Date
07/28/2015
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Biostatistics,emerging adults,Epidemiology,Korean American,OAI-PMH Harvest,smoking
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Huh, Jimi (
committee chair
), Azen, Stanley P. (
committee member
), Chou, Chih Ping (
committee member
)
Creator Email
k.yang1216@gmail.com,yangkath@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c3-613071
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UC11304857
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etd-YangKather-3736.pdf (filename),usctheses-c3-613071 (legacy record id)
Legacy Identifier
etd-YangKather-3736-1.pdf
Dmrecord
613071
Document Type
Thesis
Format
application/pdf (imt)
Rights
Yang, Katherine
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
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The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
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Repository Location
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Tags
emerging adults
Korean American
smoking