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Recent prevalence data indicates that Pacific Islanders living in the United States have disproportionately high smoking rates when compared to the general populace. However, little is known about the factors contributing to tobacco use in this at-risk population. Moreover, few studies have attempted to determine these factors utilizing technology-based assessment techniques.
The objective was to develop a customized Internet-based Ecological Momentary Assessment (EMA) system capable of measuring cigarette use among Pacific Islanders in Southern California. This system integrated the ubiquity of text messaging, the ease of use associated with mobile phone apps, the enhanced functionality offered by Internet-based Cell phone-optimized Assessment Techniques (ICAT), and the high survey completion rates exhibited by EMA studies that used electronic diaries. These features were tested in a feasibility study designed to assess whether Pacific Islanders would respond to this method of measurement and whether the data gathered would lead to novel insights regarding the intrapersonal, social, and ecological factors associated with cigarette use.
20 young adult smokers in Southern California who self-identified as Pacific Islanders were recruited by 5 community-based organizations to take part in a 7-day EMA study. Participants selected six consecutive two-hour time blocks per day during which they would be willing to receive a text message linking them to an online survey formatted for Web-enabled mobile phones. Both automated reminders and community coaches were used to facilitate survey completion.
720 surveys were completed from 840 survey time blocks, representing a completion rate of 86%. After adjusting for gender, age, and nicotine dependence, feeling happy (P=<.001) or wanting a cigarette while drinking alcohol (P=<.001) were positively associated with cigarette use. Being at home (
The results of the feasibility study indicate that customized systems can be used to conduct technology-based assessments of tobacco use among Pacific Islanders. Such systems can foster high levels of survey completion and may lead to novel insights for future research and interventions.
Pacific Islander refers to Chamorros, Marshallese, Native Hawaiians, Samoans, Tongans, and other related groups who share a common origin, culture, and customs. These communities face a wide range of social, economic, and health-related challenges. Educational attainment among Pacific Islanders residing in the United States is low, with only 14.4% obtaining bachelor’s degrees as compared to the national average of 27.9% [
One promising assessment technique that may lead to an improved understanding of the factors that contribute to tobacco use among this population is Ecological Momentary Assessment (EMA). Prior tobacco use research has demonstrated that EMA can generate novel insights for future research and interventions [
EMA is a technique that involves the repeated sampling of participants’ behaviors and experiences in real time within their natural environment [
In 2011, the Weaving an Islander Network for Cancer Awareness, Research, and Training (WINCART) Center set out to create a customized EMA system that integrated the ubiquity of text messaging, the ease of use associated with mobile phone apps, the enhanced functionality offered by ICAT systems, and the high survey completion rates exhibited by EMA studies that utilized electronic diaries. The WINCART Center is a community-based participatory research [
Geographic distribution of Pacific Islanders in Southern California.
Using strategies employed in prior studies [
Due to the potential burden placed on community coaches tasked with ensuring EMA survey completion during the 7-day feasibility study, the members of the WINCART Center voted to restrict enrollment to 20 participants (see
Descriptive statistics for demographics and tobacco use from 20 participants.
General characteristics | Male |
Female |
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Chamorro | 2 (16.7) | 0 (0) |
Native Hawaiian | 1 (8.3) | 0 (0) | |
Marshallese | 0 (0) | 0 (0) | |
Samoan | 5 (41.7) | 2 (25) | |
Tongan | 4 (33.3) | 5 (62.5) | |
Other Pacific Islander | 0 (0) | 1 (12.5) | |
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18-20 | 1 (11.2) | 0 (0) |
21-23 | 2 (22.2) | 1 (16.7) | |
24-26 | 2 (22.2) | 2 (33.3) | |
27-30 | 4 (44.4) | 3 (50) | |
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Less than high school | 0 (0) | 0 (0) |
High school or GED | 8 (72.7) | 4 (50) | |
Some college/trade school | 1 (9.1) | 3 (37.5) | |
2-year college | 1 (9.1) | 1 (12.5) | |
4-year college or above | 1 (9.1) | 0 (0) | |
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Employed | 7 (58.3) | 4 (57.1) |
Unemployed | 5 (41.7) | 3 (42.9) | |
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0 days | 0 (0) | 0 (0) |
1 or 2 days | 0 (0) | 0 (0) | |
3 to 5 days | 1 (9.1) | 1 (12.5) | |
6 to 9 days | 0 (0) | 0 (0) | |
10 to 19 days | 0 (0) | 0 (0) | |
20 to 29 days | 3 (27.3) | 1 (12.5) | |
All 30 days |
7 (63.6) | 6 (75) | |
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Less than 1 cig | 0 (0) | 0 (0) |
1 cig | 0 (0) | 0 (0) | |
2-5 cig | 3 (25) | 2 (25) | |
6-10 cig | 2 (16.7) | 2 (25) | |
11-20 cig | 5 (41.7) | 4 (50) | |
More than 20 cig | 2 (16.7) | 0 (0) | |
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Low (<=5) | 12 (60) | 8 (40) |
High (>=6) | 0 (0) | 0 (0) | |
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Hookah | 8 (72.7) | 6 (75) |
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Cigars | 8 (72.7) | 4 (50) |
Pipe | 4 (36.4) | 1 (12.5) | |
Smokeless (chew, betel nut, etc.) | 4 (36.4) | 1 (12.5) | |
Cloves | 3 (27.3) | 0 (0) | |
Bidis | 1 (9.1) | 1 (12.5) | |
Kreteks | 0 (0) | 0 (0) | |
Other | 0 (0) | 1 (12.5) | |
None of the above | 2 (18.2) | 1 (12.5) |
Each of the twenty participants enrolled in the EMA study attended a one-on-one, follow-up appointment at which the customized system was presented. Surveys were initiated by sending a text message to the participant. This text message contained a link to a secure SQL Server hosting a real-time, Web-based survey system formatted to work on any Web-enabled mobile phone (see
The Web-based survey was programmed so that if a participant did not complete the first question within 15 minutes of the first text message being sent another text message was delivered. This process was repeated every 15 minutes for up to one hour (see
After watching the animated videos, the participant selected six consecutive two-hour time blocks during which they would be willing to receive automated text messages each day. These text messages were delivered on even-numbered hours (2:00 PM, 4:00 PM, 6:00 PM, etc.) and asked the participant to report their cigarette use since the last time a survey was completed. Text messages were delivered to a Web-enabled mobile phone either owned by the participant or provided to the participant for the duration of the study. The videos informed the participant that 6 surveys would be administered each day for a period of 9 days. The first 2 days were designed to help the participant acclimate to the process of completing the surveys and to resolve any technical problems encountered. The 7 days after that were the critical test days. At the end of this 9-day period, research staff provided each participant with a US $75 gift card to compensate them for their time and travel.
Web-based survey formatted for Web-enabled mobile phones, tablets, and computers.
Items for the EMA survey were developed based on data gathered from the computer-based questionnaire and the semi-structured interview. The EMA survey included measures of cigarette use, craving, location, social environment, mood, and rationale for deciding whether or not to smoke. The resulting items were then refined in consultation with the 5 community-based organizations. This process resulted in items that, while unconventional when compared to traditional EMA studies, were more appropriate for the Pacific Islander community.
Participants initially responded to a single question inquiring if they had smoked since the last time they entered a response that day. If they had smoked, the survey asked the number of cigarettes they had (“How many cigarettes have you had since {time of last entered response}?”). This question was designed so that all responses in a single day could be tabulated and compared to self-report measures of daily cigarette use. The question also facilitated the analytic approach which focused on the average number of cigarettes smoked across time blocks within each day. A follow-up question determined when the participant smoked (“When did you smoke?”) utilizing four response categories (“<30 mins ago,” “30-60 mins ago,” “60-90 mins ago,” and “90-120 mins ago”). This question did not ascertain the number of cigarettes smoked in each 30-minute sub-block but was instead used to gauge how much time had passed since the last instance in which the participant smoked. The remaining questions asked the participant to reflect on this instance (“Now, please think about the last time you smoked...”).
After recalling the last instance in which they smoked, the participant answered one question about the extent to which they craved a cigarette beforehand (“How much were you craving a cigarette?”). Responses were rated on a 4-point Likert scale ranging from “1=Not at all” to “4=A lot” (see
Example timeline of survey reminders.
Cigarette use was reported in 534 time blocks. The analysis focused on the total and average number of cigarettes smoked during each time block. Repeated assessments of factors associated with the most recent cigarette consumed were aggregated by taking the average of these assessments across time blocks within each day. This produced a two-level hierarchical analysis dataset with data on each day (i.e. level-1 data) nested within individual participants (i.e. level-2 data). Multilevel models with both fixed and random effects were then used to quantify between and within subject variability across repeated measurement points [
Variables were created for the associational analysis. These variables included the total number of cigarettes smoked during time blocks per day, the proportion of time blocks per day in which 4 or more cigarettes were smoked, and the proportion of time blocks per day in which the participant reported an intrapersonal, social, or ecological factor related to cigarette use. Multilevel regression models were conducted using SAS Proc Mixed procedure with the participants’ age, gender, and nicotine dependence being adjusted in the analysis as covariates [
Surveys in which the participant failed to respond to all questions within two hours of the first text message prompt were classified as missed. In total, 20 participants completed 720 surveys from 840 prompted survey time blocks, representing a prompt-based survey completion rate of 86%. Nineteen (95%) participants completed all surveys on the first five days. Sixteen (80%) participants completed all surveys on the sixth day and fifteen (75%) participants completed all surveys on the seventh day. Participants reported smoking in 535 (74%) of the 720 two-hour time blocks with completed surveys. The average total number of cigarettes smoked per day was 13.96 (SD 9.19) which is 18.3% higher than the recoded estimates reported in the computer-based questionnaire.
For each time block in which smoking was reported, participants had an average of 3.07 cigarettes (SD 1.44). Home was the most common smoking location and attempting to relax was the most commonly cited reason for choosing to smoke (see
Proportions of responses per day during time blocks in which smoking was reported.
Question | Response option | Mean of proportion (SD) |
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At home | 0.61 (0.37) | |
In a car | 0.20 (0.28) | |
At work | 0.13 (0.28) | |
Around church | 0.07 (0.23) | |
At restaurant/bar | 0.05 (0.12) | |
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At school | 0.01 (0.07) |
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Alone | 0.54 (0.35) | |
With people who are not smoking | 0.41 (0.36) | |
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With people who are smoking | 0.23 (0.29) |
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Fine | 0.51 (0.39) | |
Relaxed | 0.37 (0.37) | |
Happy | 0.18 (0.30) | |
Stressed out | 0.16 (0.31) | |
Bored | 0.10 (0.17) | |
Anxious | 0.09 (0.20) | |
Angry | 0.03 (0.13) | |
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Sad | 0.02 (0.11) |
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To relax or calm down | 0.55 (0.35) | |
Wanted a cigarette after eating | 0.26 (0.29) | |
Someone was smoking around me | 0.15 (0.26) | |
Someone offered me a cig | 0.11 (0.25) | |
To concentrate/focus | 0.11 (0.24) | |
Have a good time/celebrate | 0.09 (0.20) | |
Wanted a cigarette while drinking alcohol | 0.05 (0.14) | |
Wanted a cigarette while drinking coffee | 0.03 (0.09) | |
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To eat less | 0.03 (0.10) |
After adjusting for gender, age, and nicotine dependence, analyses indicated that a one score increase of craving resulted in 3.8 more cigarettes smoked per day on average (
Associations with total number of cigarettes smoked per day.
Question | Response option | β | SE |
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At home | -0.72 | 0.31 | .02 | |
In a car | -0.02 | 0.42 | .96 | |
At work | 0.49 | 0.44 | .27 | |
Around church | 0.79 | 0.85 | .36 | |
At restaurant/bar | 0.17 | 0.71 | .82 | |
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At school | 1.51 | 1.16 | .20 |
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Alone | 0.54 | 0.29 | .06 | |
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With people who are not smoking | -0.76 | 0.28 | .01 |
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With people who are smoking |
0.65 | 0.35 | .07 |
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Fine | 0.31 | 0.29 | .30 | |
Relaxed | 0.19 | 0.37 | .60 | |
Happy | 1.41 | 0.37 | < .001 | |
Stressed out | 0.13 | 0.43 | .76 | |
Bored | -0.85 | 0.54 | .12 | |
Anxious | 0.9 | 0.55 | .11 | |
Angry | 0.88 | 0.71 | .22 | |
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Sad | 0.03 | 0.84 | .97 |
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To relax or calm down | 0.41 | 0.32 | .22 | |
Wanted a cigarette after eating | 0.26 | 0.39 | .50 | |
Someone was smoking around me | 0.15 | 0.43 | .72 | |
Someone offered me a cig | 0.72 | 0.47 | .13 | |
To concentrate/focus | -0.52 | 0.53 | .33 | |
Have a good time/celebrate | 0.46 | 0.55 | .41 | |
Wanted a cigarette while drinking alcohol | 2.31 | 0.63 | <.001 | |
Wanted a cigarette while drinking coffee | 1.85 | 1.08 | .09 | |
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To eat less | -1.32 | 1.25 | .29 |
Associations with proportion of time blocks per day with four or more cigarettes.
Question | Response option | β | SE |
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At home | -0.19 | 0.08 | .02 | |
In a car | 0.06 | 0.11 | .59 | |
At work | 0.09 | 0.11 | .40 | |
Around church | 0.07 | 0.20 | .74 | |
At restaurant/bar | 0.00 | 0.19 | .99 | |
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At school | 0.91 | 0.29 | .003 |
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Alone | 0.09 | 0.07 | .23 | |
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With people who are not smoking | -0.17 | 0.07 | .03 |
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With people who are smoking | 0.17 | 0.09 | .06 |
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Fine | 0.01 | 0.08 | .92 | |
Relaxed | 0.08 | 0.09 | .42 | |
Happy | 0.29 | 0.10 | .003 | |
Stressed out | 0.14 | 0.11 | .19 | |
Bored | -0.32 | 0.14 | .02 | |
Anxious | 0.24 | 0.14 | .10 | |
Angry | 0.37 | 0.18 | .05 | |
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Sad | -0.01 | 0.22 | .95 |
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To relax or calm down | 0.09 | 0.08 | .28 | |
Wanted a cigarette after eating | 0.12 | 0.10 | .23 | |
Someone was smoking around me | -0.04 | 0.11 | .75 | |
Someone offered me a cig | 0.09 | 0.12 | .44 | |
To concentrate/focus | -0.21 | 0.14 | .12 | |
Have a good time/celebrate | 0.19 | 0.14 | .19 | |
Wanted a cigarette while drinking alcohol | 0.38 | 0.17 | .03 | |
Wanted a cigarette while drinking coffee | 0.77 | 0.27 | .01 | |
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To eat less | -0.73 | 0.31 | .02 |
This is the first study, of which we are aware, in which a customized EMA system assessed factors associated with tobacco use among young, adult Pacific Islanders. Prior EMA studies of tobacco use that utilized electronic diaries reported prompt-based survey completion rates of 65% [
Prior research has suggested that while EMA measures sometimes mirror the results of recall measures they often gather data with less noise and greater sensitivity [
An analysis of the EMA data also offers new insight into the intrapersonal, social, and ecological factors associated with cigarette use among young, adult Pacific Islanders. Previous studies have identified the home as a place where smoking frequently occurs [
A technological innovation within the current study, the creation of tailored survey questions based on participant responses entered earlier in the day, hints at new opportunities for additional research. Future studies may choose to capitalize on this feature by administering brief, tailored surveys to multiple, linked individuals within the Pacific Islander community each time one individual reports smoking behavior in a prior assessment. Such investigations may lead to an improved understanding of friend and familial perceptions of Pacific Islander tobacco use, which previous research has suggested is highly relevant in explaining both past and current smoking among Native Hawaiian youth [
The correlation between increased tobacco craving and increased cigarette use parallels previous findings that cravings precipitate smoking [
There are several limitations to the current study. Perhaps the most relevant is the small sample size and homogeneity of the participants. Specifically, the generalizability of the sample to other Pacific Islander communities may be limited by the fact that all participants were identified via nonprobability sampling. Moreover, key subgroups, including female Chamorros, Native Hawaiians, and Marshallese, were not represented nor were Pacific Islanders over the age of thirty. The small sample size also prohibited analytic techniques that have generated valuable insights in prior EMA research. Examples include explorations of how situational and mood factors differ between light and heavy smokers [
Another limitation within the current study is the focus on regular cigarettes. With the advent of electronic cigarettes, as well as the common usage of alternative forms of tobacco within the Pacific Islander community [
An additional limitation is that all surveys were initiated on even-numbered hours and only assessed factors associated with the most recent cigarette smoked. Future studies should consider initiating surveys at random intervals within time blocks to avoid potential time-based covariates. Such methods will help clarify the causal relationship between cigarette use and the factors associated with it. Nevertheless, future interventions may still consider applying the current findings even if their causal relationship remains unclear [
This feasibility study provides new insights on factors that contribute to cigarette use among young, adult Pacific Islanders. It suggests new directions for conducting advanced, technology-based research aimed at understanding tobacco use within the Pacific Islander community and offers new possibilities for crafting culturally-tailored interventions, which past research has demonstrated is often more effective within this population [
Introduction to the ecological momentary assessment study.
Using an iPhone.
Accessing a Web-based survey with an iPhone.
Completing a Web-based survey with an iPhone.
Accessing a Web-based survey after receiving a text message.
Selecting times to receive text message survey reminders.
Receiving text message survey reminders.
Contacting technical support.
Ecological Momentary Assessment
Internet-Based Cell Phone-Optimized Assessment Technique
National Cancer Institute Center to Reduce Cancer Health Disparities
Structured Query Language
Weaving an Islander Network for Cancer Awareness, Research, and Training
This research was supported by the Weaving an Islander Network for Cancer Awareness, Research, and Training (WINCART) Center funded by Grant Number U54CA153458 from the National Cancer Institute (NCI), Center to Reduce Cancer Health Disparities (CRCHD). The authors thank the directors, community and academic researchers, and project staff at the Guam Communications Network, Pacific Islander Health Partnership, Samoan National Nurses Association, Tongan Community Service Center/Special Services for Groups, Union of Pan Asian Communities, Orange County Asian Pacific Islander Community Alliance, Orange County Health Care Agency, California State University, Fullerton, St. Joseph Hospital of Orange, University of Southern California, and Claremont Graduate University for their contributions. The contents are solely the responsibility of the authors and do not necessarily represent the official views of the NCI CRCHD.
JRP and BX conceived and drafted the manuscript. BX performed the analyses with support from NT and MAR. NT, MDS, AO, TT, SC, VM, CL, VKP, MAR, DESV, JTL, SPT, and PHP edited the manuscript for content. All authors reviewed and approved the final version of the manuscript.
None declared.