Evidence map›Paper›PMID 35254270›Full record

ArticleJMIR research protocols2022

mHealth Intervention to Improve Treatment Outcomes Among People With HIV Who Use Cocaine: Protocol for a Pilot Randomized Controlled Trial.

Yerina S Ranjit, Archana Krishnan, Debarchana Ghosh, Claire Cravero, Xin Zhou, Frederick L Altice

Erratum issued Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT04418076 (Improving Antiretroviral Adherence and Persistence Using mHealth Tools in HIV-infected Cocaine Users), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 45% of its field
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.

NCT04418076 nacompletednot on this map

Improving Antiretroviral Adherence and Persistence Using mHealth Tools in HIV-infected Cocaine Users

TypeinterventionalSponsorYale UniversityRan2017 to 2020Enrolled78ConditionsHIV/AIDS, Cocaine UseArmsGroup A_No feedback, Group B_Automated feedback, Group C_Automated feedback + Clinician feedback, Group D_Automated feedback + Social Network feedback
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 1 country.

Yerina S RanjitDepartment of Communication, University of Missouri, Columbia, MO, United States.ORCID 0000-0002-4361-7508
Debarchana GhoshDepartment of Geography, University of Connecticut, Storrs, CT, United States.ORCID 0000-0002-9181-1524
Claire CraveroHarvard T H Chan School of Public Health, Harvard University, Boston, MA, United States.ORCID 0000-0002-0590-5920
Xin ZhouDepartment of Internal Medicine, Section of Infectious Diseases, Yale University, New Haven, CT, United States.ORCID 0000-0003-2852-1468
Frederick L AlticeDepartment of Internal Medicine, Section of Infectious Diseases, Yale University, New Haven, CT, United States.ORCID 0000-0002-7860-693X
Yale University · USAlbany State University · USHarvard University · USUniversity of Connecticut · USUniversity of Missouri · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

backgroundAntiretroviral therapy is effective in reducing HIV-related morbidity, mortality, and transmission among people with HIV. However, adherence and persistence to antiretroviral therapy are crucial for successful HIV treatment outcomes. People with HIV who use cocaine have poor access to HIV services and lower retention in care.

objectiveThe primary goal of this paper is to provide a detailed description of a mobile health intervention. This study is designed to improve medication adherence among people with HIV who use cocaine. A secondary goal is to list the important challenges and adaptations incorporated in the study design.

methodsThis study, titled Project SMART, used a wireless technology-based intervention, including cellular-enabled electronic pillboxes called TowerView Health and smartphones, to provide reminders and feedback on adherence behavior. The intervention design was based on the theoretical frameworks provided by the self-determination theory and the Motivation Technology Model. The 12-week pilot randomized controlled trial with four arms provided three types of feedback: automated feedback, automated+clinician feedback, and automated feedback+social network feedback.

resultsThe study was funded by the National Institute of Drug Abuse (R21DA039842) on August 1, 2016. The institutional review board for the study was approved by Yale University on March 21, 2017. Data collection lasted from June 2017 to January 2020. The final enrollment was 71 participants, of whom 57 (80%) completed the study. The data are currently undergoing analysis, and the manuscript is being developed for publication in early 2022.

conclusionsImplementing complex mobile health interventions for high-risk and marginalized populations with multicomponent interventions poses certain challenges, such as finding companies with adequate technology for clients and financial stability and minimizing the research-related burden for the study population. Conducting feasibility studies is important to recognize these challenges and the opportunity to address these challenges with solutions while keeping the design of a randomized controlled trial as true as possible.

trial registrationClinicaltrials.gov NCT04418076; https://clinicaltrials.gov/ct2/show/NCT04418076. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28332.

Indexed as

antiretroviral therapycocaine usedescription of feasibility and acceptabilitymHealth interventionmobile phonepeople with HIVsmartphonesmart pillbox

Identifiers

PMID35254270
PMCPMC8938831
OpenAlexW3215534812

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.