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mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial

Overview of attention for article published in Reproductive Health, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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6 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

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48 Dimensions

Readers on

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328 Mendeley
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Title
mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial
Published in
Reproductive Health, July 2018
DOI 10.1186/s12978-018-0554-z
Pubmed ID
Authors

Boris Martinez, Enma Coyote Ixen, Rachel Hall-Clifford, Michel Juarez, Ann C. Miller, Aaron Francis, Camilo E. Valderrama, Lisa Stroux, Gari D. Clifford, Peter Rohloff

Abstract

Guatemala's indigenous Maya population has one of the highest perinatal and maternal mortality rates in Latin America. In this population most births are delivered at home by traditional birth attendants (TBAs), who have limited support and linkages to public hospitals. The goal of this study was to characterize the detection of maternal and perinatal complications and rates of facility-level referral by TBAs, and to evaluate the impact of a mHealth decision support system on these rates. A pragmatic one-year feasibility trial of an mHealth decisions support system was conducted in rural Maya communities in collaboration with TBAs. TBAs were individually randomized in an unblinded fashion to either early-access or later-access to the mHealth system. TBAs in the early-access arm used the mHealth system throughout the study. TBAs in the later-access arm provided usual care until crossing over uni-directionally to the mHealth system at the study midpoint. The primary study outcome was the monthly rate of referral to facility-level care, adjusted for birth volume. Forty-four TBAs were randomized, 23 to the early-access arm and 21 to the later-access arm. Outcomes were analyzed for 799 pregnancies (early-access 425, later-access 374). Monthly referral rates to facility-level care were significantly higher among the early-access arm (median 33 referrals per 100 births, IQR 22-58) compared to the later-access arm (median 20 per 100, IQR 0-30) (p = 0.03). At the study midpoint, the later-access arm began using the mHealth platform and its referral rates increased (median 34 referrals per 100 births, IQR 5-50) with no significant difference from the early-access arm (p = 0.58). Rates of complications were similar in both arms, except for hypertensive disorders of pregnancy, which were significantly higher among TBAs in the early-access arm (RR 3.3, 95% CI 1.10-9.86). Referral rates were higher when TBAs had access to the mHealth platform. The introduction of mHealth supportive technologies for TBAs is feasible and can improve detection of complications and timely referral to facility-care within challenging healthcare delivery contexts. Clinicaltrials.gov NCT02348840 .

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 328 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 328 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 49 15%
Researcher 36 11%
Student > Bachelor 34 10%
Student > Ph. D. Student 28 9%
Student > Doctoral Student 15 5%
Other 44 13%
Unknown 122 37%
Readers by discipline Count As %
Nursing and Health Professions 61 19%
Medicine and Dentistry 59 18%
Social Sciences 22 7%
Computer Science 11 3%
Arts and Humanities 8 2%
Other 37 11%
Unknown 130 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 25 August 2021.
All research outputs
#4,481,180
of 24,898,480 outputs
Outputs from Reproductive Health
#534
of 1,534 outputs
Outputs of similar age
#79,649
of 333,746 outputs
Outputs of similar age from Reproductive Health
#24
of 46 outputs
Altmetric has tracked 24,898,480 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,534 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. This one has gotten more attention than average, scoring higher than 65% 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 333,746 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 46 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.