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iMedicalApps and JMIR Publications have partnered to help disseminate interesting & innovative digital health research being done worldwide. Each article in this series will feature summaries of interesting studies to help you keep up to date on the latest in digital health research. We invite you to share your thoughts on the study in the comments section.

Developing an Internet-Based Ecological Momentary Assessment System to Measure Cigarette Use Among Pacific Islanders

1. What was the motivation behind your study?

Recent prevalence data indicates that Pacific Islanders living in the United States have disproportionately high smoking rates of 21.5% for males and 18.4% for females compared with respective averages for the general population of 15.7% and 12.8%. However, little is known about the factors contributing to tobacco use in this at-risk population. Our goal was to uncover these factors by developing a customized, Internet-based system capable of using mobile phones to measure cigarette use among young adult Pacific Islanders.

2. Describe your study.

With the help of five community-based organizations in Southern California, 20 young adult, Pacific Islander smokers were recruited for a 7-day study. At the beginning of the 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. Each participant was then asked to use their phone to complete 42 five-minute surveys that measured the intrapersonal, social, and ecological factors associated with their cigarette use.

3. What were the results of the study?

After adjusting for gender, age, and nicotine dependence, analyses indicated that wanting a cigarette while drinking alcohol and feeling happy were each positively associated with the total number of cigarettes smoked (P< .05). In contrast, being at home and being around people who are not smoking were negatively associated with the total number of cigarettes smoked (P<.05). It is also worth noting that survey completion rates (86%) were relatively high when compared to other studies that conducted repeated assessments using Web-enabled mobile phones.

4. What is the main point that readers should take away from this study?

The primary takeaway from the study is that smoking cessation programs developed for Pacific Islanders may be strengthened by capitalizing on the unique intrapersonal, social, and ecological factors that influence cigarette use in the Pacific Islander community. For example, the protective effect of non-smokers suggests that such individuals may function as an effective deterrent. Future interventions may benefit by encouraging Pacific Islander smokers to enlist support from non-smoking friends and family when they are in social situations that stimulate their desire for a cigarette.

5. What was the most surprising finding from your study?

The most surprising finding was the comparatively high survey completion rate (86%). This may be attributable to the fact that all facets of the Internet-based system were customized for Pacific Islanders, including the language used within survey, the orientation materials provided (vimeo), and the functionality of the system. The high level of engagement resulting from this approach suggests that developers of healthcare apps may need to consider tailoring their apps to address the needs of at-risk subgroups as opposed to attempting to satisfy all potential users.

6. What are the next steps? How do you envision this work ultimately translating into clinical practice or affecting R&D?

The methodology developed for this study provides a framework for conducting future research that examines other health disparities evident within the Pacific Islander community, such as obesity, diabetes, and mental health. The technology developed may also be used to craft novel phone-based interventions that use participant responses to provide individualized, situationally-relevant health information. Such interventions could improve health outcomes by targeting moments where an individual is prone to make an unhealthy choice due to specific intrapersonal, social, or ecological factors.

JamesPikeThis Q&A was submitted by James Pike. James is a research center manager and multimedia technologist at the School of Community and Global Health at Claremont Graduate University. He is a graduate of the School of Cinematic Arts at the University of Southern California and a current student in the Executive MBA program at Claremont Graduate University’s Peter F. Drucker and Masatoshi Ito Graduate School of Management. For more than a decade, James has specialized in conducting advanced behavioral research using technology-based assessment methods.