Digital Technology Ownership, Usage, and Factors Predicting Downloading Health Apps Among Caucasian, Filipino, Korean, and Latino Americans: The Digital Link to Health Survey

Background Interventions using mobile health (mHealth) apps have been effective in promoting healthy lifestyle behavior change and hold promise in improving health outcomes to thereby reduce health disparities among diverse racial/ethnic populations, particularly Latino and Asian American subgroups (Filipinos and Koreans) at high risk for diabetes and cardiovascular disease. Latinos and Asian Americans are avid digital technology owners and users. However, limited datasets exist regarding digital technology ownership and use, especially among specific racial/ethnic subgroups. Such information is needed to inform development of culturally tailored mHealth tools for use with lifestyle interventions promoting healthy behaviors for these at-risk racial/ethnic populations. Objective The intent of the study was to examine (1) digital technology ownership and usage, and (2) factors predicting downloading health apps for Caucasian, Filipino, Korean, and Latino American subgroups. Methods A cross-sectional survey conducted in August 2013 through December 2013 recruited 904 participants (Caucasians n=172, Filipinos n=250, Koreans n=234, and Latinos n=248), age >18 years, from California community events, clinics, churches, and online. English, Spanish, and Korean surveys were administered via paper or online. Descriptive statistics characterized the sociodemographics and digital technology ownership/usage of the 904 participants. Differences among groups in categorical variables were examined using chi-square statistics. Logistic regression was used to determine factors predicting downloading health apps. Results Overall, mean age was 44 years (SD 16.1), with 64.3% (581/904) female. Only 44.7% (404/904) of all participants reported English as their primary language (Caucasian 98.3%, 169/172; Filipino 67.6%, 169/250; Korean 9.4%, 22/234, and Latino 17.7%, 44/248. Overall, mobile phone ownership was 92.8% (839/904). Compared to all groups, Koreans were more likely to own a mobile phone (82.8%, 194/234), computer (91.4%, 214/234), or tablet (55.2%, 129/234), whereas Latinos (67.5%, 167/248; 65.3%, 162/248; 24.4%, 61/248, respectively) were least likely. Internet access via mobile phones (90.5%, 818/904) was higher than computers (78.6%, 711/904). Odds of downloading health apps increased with college (OR 2.62, 95% CI 1.44-4.80) or graduate school (OR 2.93, 95% CI 1.43-6.00) compared to some high school; and family history of heart attack (OR 2.02, 95% CI 1.16-3.51). Odds of downloading health apps were reduced with: race/ethnicity, Latino (OR 0.37, 95% CI 0.20-0.69), and Korean (OR 0.52, 95% CI 0.31-0.88) compared to Caucasians; increasing age (OR 0.96, 95% CI 0.95-0.97); and completing paper surveys (OR 0.50, 95% CI 0.34-0.75). Conclusions This survey study uniquely targeted specific racial/ethnic subgroups. Results indicated that despite a narrowing racial/ethnic “digital divide”, some disparities still exist, particularly among racial/ethnic groups with less education and whose primary language is not English. Findings will be used to inform development and evaluation of culturally tailored mHealth apps for use with interventions promoting healthy behavior change for Filipinos, Koreans, and Latinos.

[1]  David Cella,et al.  A Comprehensive Method for the Translation and Cross-Cultural Validation of Health Status Questionnaires , 2005, Evaluation & the health professions.

[2]  C. Abraham,et al.  Self-Directed Interventions to Promote Weight Loss: A Systematic Review of Reviews , 2014, Journal of medical Internet research.

[3]  Katherine M Flegal,et al.  Obesity and socioeconomic status in adults: United States, 2005-2008. , 2010, NCHS data brief.

[4]  Guy S. Parcel,et al.  How individuals, environments, and health behaviors interact: Social cognitive theory. , 2008 .

[5]  C. Emslie,et al.  Are perceptions of a family history of heart disease related to health-related attitudes and behaviour? , 2000, Health education research.

[6]  Tom Baranowski,et al.  How individuals, environments, and health behavior interact : Social learning theory , 1990 .

[7]  K. Glanz,et al.  Health behavior and health education : theory, research, and practice , 1991 .

[8]  I. Ajzen The theory of planned behavior , 1991 .

[9]  Lora E Burke,et al.  Mobile applications for weight management: theory-based content analysis. , 2013, American journal of preventive medicine.

[10]  A. Haines,et al.  The Effectiveness of Mobile-Health Technology-Based Health Behaviour Change or Disease Management Interventions for Health Care Consumers: A Systematic Review , 2013, PLoS medicine.

[11]  Predictors of Hypertension Among Filipino Immigrants in the Northeast US , 2013, Journal of Community Health.

[12]  Hae-Ra Han,et al.  Implementation and success of nurse telephone counseling in linguistically isolated Korean American patients with high blood pressure. , 2010, Patient education and counseling.

[13]  Weon Sang Yoo,et al.  Is the Internet a primary source for consumer information search?: Group comparison for channel choices , 2009 .

[14]  Suzanne Bakken,et al.  Online Health Information Seeking Behaviors of Hispanics in New York City , 2013 .

[15]  Jerilyn K Allen,et al.  Mobile phone interventions to increase physical activity and reduce weight: a systematic review. , 2013, The Journal of cardiovascular nursing.

[16]  M. Becker,et al.  The Health Belief Model: A Decade Later , 1984, Health education quarterly.

[17]  E. Vittinghoff,et al.  Innovation to motivation--pilot study of a mobile phone intervention to increase physical activity among sedentary women. , 2010, Preventive medicine.

[18]  Yoshimi Fukuoka,et al.  Gender Differences in Lay Knowledge of Type 2 Diabetes Symptoms Among Community-dwelling Caucasian, Latino, Filipino, and Korean Adults - DiLH Survey , 2014, The Diabetes educator.

[19]  Yoshimi Fukuoka,et al.  Randomized controlled trial lifestyle interventions for Asian Americans: a systematic review. , 2014, Preventive medicine.

[20]  Thomas E Novotny,et al.  US Department of Health and Human Services: a need for global health leadership in preparedness and health diplomacy. , 2006, American journal of public health.

[21]  S MacRury,et al.  The use of technology to promote physical activity in Type 2 diabetes management: a systematic review , 2013, Diabetic medicine : a journal of the British Diabetic Association.

[22]  J. Prochaska,et al.  Stages and processes of self-change of smoking: toward an integrative model of change. , 1983, Journal of consulting and clinical psychology.

[23]  Tamara Sawyer The Office of Minority Health , 2013, Asian American and Pacific Islander journal of health.

[24]  Tung T. Nguyen,et al.  Using appropriate body mass index cut points for overweight and obesity among Asian Americans. , 2014, Preventive medicine.

[25]  J. Beck,et al.  Exploring the Potential of Web 2.0 to Address Health Disparities , 2011, Journal of health communication.

[26]  Charles C. Hinnant,et al.  Exploring digital divides: An examination of eHealth technology use in health information seeking, communication and personal health information management in the USA , 2011, Health Informatics J..

[27]  Wen-Ying Sylvia Chou,et al.  Predictors of eHealth Usage: Insights on The Digital Divide From the Health Information National Trends Survey 2012 , 2014, Journal of medical Internet research.

[28]  D. Bond,et al.  Review of Innovations in Digital Health Technology to Promote Weight Control , 2014, Current Diabetes Reports.

[29]  L. Wyatt,et al.  Awareness, Treatment and Control of Hypertension Among Filipino Immigrants , 2014, Journal of General Internal Medicine.