Evidence map›Paper›PMID 29576816›Full record

ArticleThe open AIDS journal2018

Why it Worked: Participants' Insights into an mHealth Antiretroviral Therapy Adherence Intervention in China.

Lora L Sabin, Lauren Mansfield, Mary Bachman DeSilva, Taryn Vian, Zhong Li, Xie Wubin, Allen L Gifford, Yiyao Barnoon, Christopher J Gill

Abstract read
In one paragraph

Article in The open AIDS journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lora L SabinDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Crosstown, 3rd floor, Boston, MA, 02118, USA.
Lauren MansfieldDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Crosstown, 3rd floor, Boston, MA, 02118, USA.
Mary Bachman DeSilvaUniversity of New England, 716 Stevens Ave, Portland, ME, 04103, USA.
Taryn VianDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Crosstown, 3rd floor, Boston, MA, 02118, USA.
Zhong LiFHI 360, Room B110, Floor 4, Building 1, No.15, Guanghua Road, Chaoyang District, Beijing, 100026, China.
Xie WubinDepartment of Global Health, Milken Institute School of Public Health, George Washington University, 2121 I St NW, Washington, D.C., 20052, USA.
Allen L GiffordCenter for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave, Boston, MA, 02130, USA.
Yiyao BarnoonBoston Children's Hospital, 300 Longwood Ave, Boston, MA, 02115, USA.
Christopher J GillDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Crosstown, 3rd floor, Boston, MA, 02118, USA.

Funding

China Adherence through Technology Study (CATS)R34DA032423 · NIDA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI SABIN, LORA L · 2012 to 2014
$670k
NIDA NIH HHS R34 DA032423
6 · The paper itself

Abstract

backgroundFew Antiretroviral Therapy (ART) adherence trials investigate the reasons for intervention success or failure among HIV-positive individuals.

objectivesTo conduct qualitative research to explore the reasons for effectiveness of a 6-month mHealth (mobile health) trial that improved adherence among ART patients in China. The intervention utilized Wireless Pill Containers (WPCs) to provide, real-time SMS reminders, WPC-generated adherence reports, and report-informed counseling.

methodsWe conducted in-depth interviews with 20 intervention-arm participants immediately following the trial. Sampling was purposeful to ensure inclusion of participants with varied adherence histories. Questions covered adherence barriers and facilitators, and intervention experiences. We analyzed data in nVivo using a thematic approach.

resultsOf participants, 14 (70%) were male; 7 (35%) had used injectable drugs. Pre-intervention, 11 were optimal adherers and 9 were suboptimal adherers, using a 95% threshold. In the final intervention month, all but 3 (85%) attained optimal adherence. Participants identified a range of adherence barriers and facilitators, and described various mechanisms for intervention success. Optimal adherers at baseline were motivated by positive adherence reports at monthly clinic visits-similar to receiving A+ grades. For suboptimal adherers, reminders facilitated the establishment of adherence-promoting routines; data-guided counseling helped identify strategies to overcome specific barriers.

conclusionDifferent behavioral mechanisms appear to explain the success of an mHealth adherence intervention among patients with varying adherence histories. Positive reinforcement was effective for optimal adherers, while struggling patients benefitted from reminders and data-informed counseling. These findings are relevant for the design and scalability of mHealth interventions and warrant further investigation.

Indexed as

ART adherenceBehavior changeChinaHIV treatmentIntervention trialmHealth

Identifiers

PMID29576816
PMCPMC5850484

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.