Literature DB >> 30221166

Smartphone ownership and perspectives on health apps among a vulnerable population in East Harlem, New York.

Nita Vangeepuram1, Victoria Mayer1, Kezhen Fei1, Emily Hanlen-Rosado1, Cesar Andrade1, Shari Wright1, Carol Horowitz1.   

Abstract

BACKGROUND: Individuals from low-income and racial/ethnic minority backgrounds have traditionally had less access to mobile health (mHealth) technologies, but there is evidence that this gap has been rapidly narrowing. Given the increase in access to mobile technologies recently seen in vulnerable populations, mHealth has been championed as a strategy for improving population health and reducing health disparities. However, members of low-income and racial/ethnic minority populations have had a limited role in the development and implementation of mHealth interventions designed to impact them.
METHODS: We used community-based participatory research (CBPR), a research approach that is frequently employed to help reach communities that are disproportionately affected by illness but are difficult to engage. Our community-academic collaboration, the East Harlem Partnership for Diabetes Prevention, sought to create a mobile technology platform that would allow adults in East Harlem, New York to improve their own health and promote the health of the broader community. As a first step, we developed and conducted a survey of community residents to better understand access to, usage of, and attitudes towards mobile technologies among diverse, low-income adults. We administered the cross-sectional survey to a convenience sample of adults who utilized a variety of community-based organizations in East Harlem. We examined frequencies for each survey item and then used chi-square tests (or Fisher's exact tests) and multivariate logistic regression to evaluate relationships between these outcomes and sociodemographic factors.
RESULTS: We approached 154 people, of whom 104 (68%) agreed to participate. The majority of respondents were of Black and/or Hispanic/Latino descent with a mean age of 37 years. Our sample displayed a high percentage of smartphone ownership (82% of the participants reported that they owned a cell phone, and 88% of owners reported that their cell phone was a smartphone). We found lower rates of ownership among individuals who were older, self-identified as Latino, insured by Medicare, and had a household income of less than $30,000 per year. Multivariate logistic regression showed that after adjusting for age, gender and race, those with at least a high school education were seven times more likely to use health apps than those with less than a high school education (OR 6.8, 95% CI: 1.7-27.1). Participants expressed interest in health promoting apps that provide interactive, individualized diet, exercise and weight loss tools and offer information about local health resources and events.
CONCLUSIONS: Despite some notable disparities, our study results suggest that the digital divide is narrowing in the East Harlem community with relatively high rates of smartphone ownership and use, even among individuals from low-income, low education backgrounds and those without health insurance. Based on study results, our partnership developed an app supporting healthy lifestyle and diabetes prevention tailored to the East Harlem community.

Entities:  

Keywords:  Mobile health (mHealth); community-based participatory research (CBPR); mobile apps; type 2 diabetes

Year:  2018        PMID: 30221166      PMCID: PMC6131491          DOI: 10.21037/mhealth.2018.07.02

Source DB:  PubMed          Journal:  Mhealth        ISSN: 2306-9740


  12 in total

1.  Exploring the potential of Web 2.0 to address health disparities.

Authors:  M Chris Gibbons; Linda Fleisher; Rachel E Slamon; Sarah Bass; Venk Kandadai; J Robert Beck
Journal:  J Health Commun       Date:  2011

2.  Exploring digital divides: an examination of eHealth technology use in health information seeking, communication and personal health information management in the USA.

Authors:  Mia Liza A Lustria; Scott Alan Smith; Charles C Hinnant
Journal:  Health Informatics J       Date:  2011-09       Impact factor: 2.681

3.  Results of a pilot diabetes prevention intervention in East Harlem, New York City: Project HEED.

Authors:  Punam Parikh; Ellen P Simon; Kezhen Fei; Helen Looker; Crispin Goytia; Carol R Horowitz
Journal:  Am J Public Health       Date:  2010-02-10       Impact factor: 9.308

4.  A short message service (SMS) intervention to prevent diabetes in Chinese professional drivers with pre-diabetes: a pilot single-blinded randomized controlled trial.

Authors:  Carlos K H Wong; Colman S C Fung; S C Siu; Yvonne Y C Lo; K W Wong; Daniel Y T Fong; Cindy L K Lam
Journal:  Diabetes Res Clin Pract       Date:  2013-12       Impact factor: 5.602

5.  Text4Diet: a randomized controlled study using text messaging for weight loss behaviors.

Authors:  Jennifer R Shapiro; Tina Koro; Neal Doran; Sheri Thompson; James F Sallis; Karen Calfas; Kevin Patrick
Journal:  Prev Med       Date:  2012-08-27       Impact factor: 4.018

6.  Fruit and vegetable intake and eating behaviors mediate the effect of a randomized text-message based weight loss program.

Authors:  Gregory J Norman; Julia K Kolodziejczyk; Marc A Adams; Kevin Patrick; Simon J Marshall
Journal:  Prev Med       Date:  2012-10-22       Impact factor: 4.018

7.  Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial.

Authors:  Caroline Free; Rosemary Knight; Steven Robertson; Robyn Whittaker; Phil Edwards; Weiwei Zhou; Anthony Rodgers; John Cairns; Michael G Kenward; Ian Roberts
Journal:  Lancet       Date:  2011-07-02       Impact factor: 79.321

8.  Design and rationale of the tobacco, exercise and diet messages (TEXT ME) trial of a text message-based intervention for ongoing prevention of cardiovascular disease in people with coronary disease: a randomised controlled trial protocol.

Authors:  C K Chow; J Redfern; A Thiagalingam; S Jan; R Whittaker; M Hackett; N Graves; J Mooney; G S Hillis
Journal:  BMJ Open       Date:  2012-01-19       Impact factor: 2.692

9.  Digital technology ownership, usage, and factors predicting downloading health apps among caucasian, filipino, korean, and latino americans: the digital link to health survey.

Authors:  Melinda S Bender; JiWon Choi; Shoshana Arai; Steven M Paul; Prisila Gonzalez; Yoshimi Fukuoka
Journal:  JMIR Mhealth Uhealth       Date:  2014-10-22       Impact factor: 4.773

10.  Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012.

Authors:  Emily Kontos; Kelly D Blake; Wen-Ying Sylvia Chou; Abby Prestin
Journal:  J Med Internet Res       Date:  2014-07-16       Impact factor: 5.428

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  30 in total

Review 1.  Big Data From Small Devices: The Future of Smartphones in Oncology.

Authors:  Juhi M Purswani; Adam P Dicker; Colin E Champ; Matt Cantor; Nitin Ohri
Journal:  Semin Radiat Oncol       Date:  2019-10       Impact factor: 5.934

Review 2.  Digital health technologies: opportunities and challenges in rheumatology.

Authors:  Daniel H Solomon; Robert S Rudin
Journal:  Nat Rev Rheumatol       Date:  2020-07-24       Impact factor: 20.543

3.  Health Information-seeking Behaviors and Preferences of a Diverse, Multilingual Urban Cohort.

Authors:  Elaine C Khoong; Gem M Le; Mekhala Hoskote; Natalie A Rivadeneira; Robert A Hiatt; Urmimala Sarkar
Journal:  Med Care       Date:  2019-06       Impact factor: 2.983

4.  Effectiveness of a Brief Lifestyle Intervention in the Prenatal Care Setting to Prevent Excessive Gestational Weight Gain and Improve Maternal and Infant Health Outcomes.

Authors:  Franziska Krebs; Laura Lorenz; Farah Nawabi; Adrienne Alayli; Stephanie Stock
Journal:  Int J Environ Res Public Health       Date:  2022-05-11       Impact factor: 4.614

5.  "It closes the gap when the ball is dropped": patient perspectives of a novel smartphone app for regional care coordination after hospital encounters.

Authors:  Adriana Guzman; Tiffany Brown; David T Liss
Journal:  Mhealth       Date:  2022-04-20

6.  Identifying Mobile Health Technology Experiences and Preferences of Low-Income Pregnant Women with Diabetes.

Authors:  Karolina Leziak; Eleanor Birch; Jenise Jackson; Angelina Strohbach; Charlotte Niznik; Lynn M Yee
Journal:  J Diabetes Sci Technol       Date:  2021-02-19

7.  Remote patient monitoring sustains reductions of hemoglobin A1c in underserved patients to 12 months.

Authors:  Elizabeth B Kirkland; Justin Marsden; Jingwen Zhang; Samuel O Schumann; John Bian; Patrick Mauldin; William P Moran
Journal:  Prim Care Diabetes       Date:  2021-01-25       Impact factor: 2.567

Review 8.  Remote Monitoring of Patient- and Family-Generated Health Data in Pediatrics.

Authors:  Carolyn Foster; Dana Schinasi; Kristin Kan; Michelle Macy; Derek Wheeler; Allison Curfman
Journal:  Pediatrics       Date:  2022-02-01       Impact factor: 9.703

9.  Patient Demographics and Clinic Type Are Associated With Patient Engagement Within a Remote Monitoring Program.

Authors:  Elizabeth Kirkland; Samuel O Schumann; Andrew Schreiner; Marc Heincelman; Jingwen Zhang; Justin Marsden; Patrick Mauldin; William P Moran
Journal:  Telemed J E Health       Date:  2021-06-11       Impact factor: 5.033

10.  Designing an Information and Communications Technology Tool With and for Victims of Violence and Their Case Managers in San Francisco: Human-Centered Design Study.

Authors:  Devika Patel; Siavash Sarlati; Patrick Martin-Tuite; Joshua Feler; Lara Chehab; Michael Texada; Ruben Marquez; F Julia Orellana; Terrell L Henderson; Adaobi Nwabuo; Rebecca Plevin; Rochelle Ami Dicker; Catherine Juillard; Amanda Sammann
Journal:  JMIR Mhealth Uhealth       Date:  2020-08-24       Impact factor: 4.773

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