↓ Skip to main content

A qualitative analysis to optimize a telemonitoring intervention for heart failure patients from disparity communities

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

policy
1 policy source
twitter
4 X users
facebook
1 Facebook page

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
130 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A qualitative analysis to optimize a telemonitoring intervention for heart failure patients from disparity communities
Published in
BMC Medical Informatics and Decision Making, June 2016
DOI 10.1186/s12911-016-0300-9
Pubmed ID
Authors

R. Pekmezaris, R. M. Schwartz, T. N. Taylor, P. DiMarzio, C. N. Nouryan, L. Murray, G. McKenzie, D. Ahern, S. Castillo, K. Pecinka, L. Bauer, T. Orona, A.N. Makaryus

Abstract

The use of telemonitoring is a promising approach to optimizing outcomes in the treatment of heart failure (HF) for patients living in the community. HF telemonitoring interventions, however, have not been tested for use with individuals residing in disparity communities. The current study describes the results of a community based participatory research approach to adapting a telemonitoring HF intervention so that it is acceptable and feasible for use with a lower-income, Black and Hispanic patient population. The study uses the ADAPT-ITT framework to engage key community stakeholders in the process of adapting the intervention in the context of two consecutive focus groups. In addition, data from a third focus group involving HF telemonitoring patient participants was also conducted. All three focus group discussions were audio recorded and professionally transcribed and lasted approximately two hours each. Structural coding was used to mark responses to topical questions in the interview guide. This is the first study to describe the formative process of a community-based participatory research study aimed at optimizing telehealth utilization among African-American and Latino patients from disparity communities. Two major themes emerged from qualitative analyses of the focus group data. The first theme that arose involved suggested changes to the equipment that would maximize usability. Subthemes identified included issues that reflect the patient populations targeted, such as Spanish translation, font size and medical jargon. The second theme that arose involved suggested changes to the RCT study structure in order to maximize participant engagement. Subthemes also identified issues that reflect concerns of the targeted patient populations, such as the provision of reassurances regarding identity protection to undocumented patients in implementing an intervention that utilizes a camera, and that their involvement in telehealth monitoring would not replace their clinic care, which for many disparity patients is their only connection to medical care. The adaptation, based on the analysis of the data from the three focus groups, resulted in an intervention that is acceptable and feasible for HF patients residing in disparity communities. NCT02196922 ; ClinicalTrials.gov (US National Institutes of Health).

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 15%
Researcher 18 14%
Student > Ph. D. Student 16 12%
Student > Bachelor 10 8%
Professor > Associate Professor 6 5%
Other 25 19%
Unknown 35 27%
Readers by discipline Count As %
Medicine and Dentistry 33 25%
Nursing and Health Professions 21 16%
Social Sciences 10 8%
Computer Science 5 4%
Psychology 4 3%
Other 19 15%
Unknown 38 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 December 2021.
All research outputs
#4,935,366
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#447
of 2,030 outputs
Outputs of similar age
#85,402
of 356,691 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#6
of 35 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 78% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 356,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.