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Assessing the perspectives of users and beneficiaries of a community health worker mHealth tracking system for mothers and children in Rwanda

Overview of attention for article published in PLOS ONE, June 2018
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Title
Assessing the perspectives of users and beneficiaries of a community health worker mHealth tracking system for mothers and children in Rwanda
Published in
PLOS ONE, June 2018
DOI 10.1371/journal.pone.0198725
Pubmed ID
Authors

Angele Musabyimana, Hinda Ruton, Erick Gaju, Atakilt Berhe, Karen A. Grépin, Joseph Ngenzi, Emmanuel Nzabonimana, Celestin Hategeka, Michael R. Law

Abstract

Mobile Health (mHealth) programs have increasingly been used to tackle maternal and child health problems in low and middle income countries. However, few studies have evaluated how these programs have been perceived by intended users and beneficiaries. Therefore, we explored perceptions of healthcare officials and beneficiaries regarding RapidSMS Rwanda, an mHealth system used by Community Health Workers (CHWs) that was scaled up nationwide in 2013. We conducted key informant interviews and focus group discussions with key stakeholders, providers, and beneficiaries of maternal and child health services at both the national and community levels. Semi-structured interviews were used to assess perceptions about the impact of and challenges facing the RapidSMS system. Interviews and focus group discussions were recorded (with the exception of one), transcribed verbatim, and analyzed. We conducted a total of 28 in-depth interviews and 10 focus group discussions (93 total participants). A majority of respondents believed that RapidSMS contributed to reducing maternal and child mortality rates. RapidSMS was generally accepted by both CHWs and parents. Participants identified insufficient training, a lack of equipment, and low CHW motivation as the main challenges facing RapidSMS. Our findings suggest that an mHealth program can be well accepted by both policymakers, health providers, and the community. We also found significant technical challenges that have likely reduced its impact. Addressing these challenges will serve to strengthen future mHealth programs.

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The data shown below were collected from the profiles of 3 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 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 165 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 38 23%
Researcher 19 12%
Student > Bachelor 13 8%
Student > Doctoral Student 11 7%
Student > Ph. D. Student 10 6%
Other 22 13%
Unknown 52 32%
Readers by discipline Count As %
Medicine and Dentistry 32 19%
Nursing and Health Professions 23 14%
Social Sciences 15 9%
Agricultural and Biological Sciences 6 4%
Computer Science 5 3%
Other 27 16%
Unknown 57 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 June 2018.
All research outputs
#14,620,068
of 23,511,526 outputs
Outputs from PLOS ONE
#122,469
of 201,404 outputs
Outputs of similar age
#186,570
of 330,371 outputs
Outputs of similar age from PLOS ONE
#1,908
of 3,253 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 201,404 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 330,371 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,253 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.