COH611 Public Health Research Methods

Please write a 2-4 page introduction to your research proposal. In this section you will include the following information:

  1. Statement of the problem (What healthcare issues are you addressing in your research proposal)
  2. Significance of the topic and explanation of why this should be studied (supported with evidence and statistics)
  3. Target population (who are you studying)
  4. Proposed research question(s)
  5. At least 10 quality references related to your topic
  6. These must be recent (preferably in past 5 years, and not over 10 years old)
  7. These must be peer-reviewed journal articles of primary research
  8. Sources outside of peer-reviewed journals (government websites, etc.) are encouraged but DO NOT count toward your 10 sources.

In an Appendix, please provide the following:

  1. proposed research design (quantitative or qualitative)
  2. proposed method (survey, interviews, focus groups, ethnography)
  3. short explanation of why you chose this method (why and how does this design and method help you to answer your research question?)

Impact of Wearable Technology in Healthcare


With the Health Information Technology for Economic Clinical Health Act (HITECH), which was part of a stimulus package for the Affordable Care Act of 2009, providers were tasked with creating a patient-centric platform to improve engagement (Patient Protection and

Affordable Care Act, 2009). This was achieved most commonly through use of patient portals. In order to connect with these patient portals securely, and to meet patients where they are, many of these portals were integrated into mobile applications. Due to this, and the increased saturation of wearable technology in consumer markets, some health providers began to allow access of shared data collected by such devices. According to Krohn (2017), “doctor[s] can remotely monitor the patient’s vital signs, perform simple medical diagnosis tests…before the patient has even noticed any symptoms” (p. 45). This type of engagement has the potential to provide increased insight into diagnosis, treatment, and a variety of other medical relevancies. For patients as well as the industry, there is a delicate balance of providing the best care while respecting privacy. Because of that balance, determining the impact of this new data stream can be challenging due to the nature of early technology adoption and regulatory constraints from the Health Insurance Portability and Accountability Act (HIPAA). Additionally, determining which conditions and treatments might benefit most from such technology is likely to evolve over time. Chronic illnesses, for example, are commonly tracked conditions on such devices today and provide early case studies (Krohn, 2017). Therefore, specific treatments and diagnosis markers may be easier to explore as compared to other conditions. Yet, the potential to impact great portions of communities and populations exists and makes the effort of exploring the medium worthy of pursuit.

From a population health standpoint, particularly in dense and diverse populations in large metro areas, spikes in emergency room or acute care visits can be examined much differently. For example, when trying to understand why so many people were seeking treatment for illness in Flint, Michigan in 2015, Epic, an electronic health records system, was used to determine that the patients were localized around the same water source (Epic, 2016). By leveraging a localized data stream, health professionals could quickly address what was occurring and notify government officials. For wearable technologies, consider synthesizing the data pool to more than those who were seen by health professionals. Consider the alarm sounding before patients even arrived in the emergency room. Readiness and responsiveness could certainly improve and potentially save more lives. The increased potential to evaluate outbreaks or population health issues can be dramatically shifted with more information.


The purpose of this study is to assess the impact and effectiveness of health data collection through consumer wearable health sources such as watches, heart monitors, or other devices synced to smart phones and made available for physician or research examination.

Research Question

RQ1: What is the impact of health data collection through consumer wearable health sources such as watches, heart monitors, or other devices synced to smart phones and made available for physician or research examination?

RQ2: How effective is health data collection through consumer wearable health sources such as watches, heart monitors, or other devices synced to smart phones and made available for physician or research examination?


Arigo, D. (2015). Promoting physical activity among women using wearable technology and online social connectivity: A feasibility study. Health Psychology and Behavioral

Medicine, 3(1), 391-409.

Belsi, A., Papi, E., & McGregor, A. H. (2016). Impact of wearable technology on psychosocial factors of osteoarthritis management: A qualitative study. BMJ open, 6(2), e010064.

Bonacaro, A., & Sookhoo, D. (2017). The effectiveness and usability of wearable devices in the prevention of hospital readmission in patients with chronic conditions: a comprehensive literature review protocol.

Epic. (2016, February 22). Researcher Uses Epic to Expose Water Contamination. Retrieved from Epic: https://www.epic.com/epic/post/722

Krohn, R., Metcalf, D., & Salber, P. (2017). Connected Health: Improving Care, Safety, and

Efficiency with Wearables and IoT Solution. Productivity Press.

Millings, A., Morris, J., Rowe, A., Easton, S., Martin, J. K., Majoe, D., & Mohr, C. (2015). Can the effectiveness of an online stress management program be augmented by wearable sensor technology?. Internet Interventions, 2(3), 330-339.

Patient Protection and Affordable Care Act, H.R.3590 (111th Congress September 17, 2009).

Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016). The rise of consumer health wearables: Promises and barriers. PLoS medicine, 13(2).

Radhakrishnan, S., Duvvuru, A., & Kamarthi, S. V. (2014). Investigating discrete event simulation method to assess the effectiveness of wearable health monitoring devices.

Procedia Economics and Finance, 11(0), 838-856.

Ridgers, N. D., McNarry, M. A., & Mackintosh, K. A. (2016). Feasibility and effectiveness of using wearable activity trackers in youth: A systematic review. JMIR mHealth and uHealth, 4(4), e129.

Stephenson, A., McDonough, S. M., Murphy, M. H., Nugent, C. D., & Mair, J. L. (2017). Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: A systematic review and meta-analysis. International Journal of Behavioral

Nutrition and Physical Activity, 14(1), 105.

Zhang, M., Luo, M., Nie, R., & Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97-109.


Research Design:

  • RQ1: Qualitative
  • RQ2: Quantitative

Research Method

  • RQ1: Semi-structured interviews; focus groups
  • RQ2: Online Survey

I chose a qualitative research design for research question 1. The mthod I will use is semistructured interviews and focus groups. I will use semi-structured interviews because this will allow me to talk to individuals who use wearable technology in order to understand their impact. I will use focus groups to do the same, but these will allow for people to interact with one another and therefore more information may be shared to better understand the impact of wearables.

I chose quantitative research design for research question 2. The method I will use is an online survey. In order to measure the effectiveness of wearables, I will survey a larger number of people (approx. 200-250) and use validated measures. This will allow me to generalize to the larger population.

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