Evidence map›Paper›PMID 36339513›Full record

ArticleFrontiers in digital health2022

Using the participatory education and research into lived experience (PEARLE) methodology to localize content and target specific populations.

Ian David Aronson, Alex S Bennett, Mary-Andrée Ardouin-Guerrier, German J Rivera-Castellar, Brent E Gibson, Brittney Vargas-Estrella

Abstract read
In one paragraph

Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
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

6 authors.

Ian David AronsonTechnology-Based Education for Community Health (TECH) Lab, Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, United States.
Alex S BennettTechnology-Based Education for Community Health (TECH) Lab, Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, United States.
Mary-Andrée Ardouin-GuerrierTechnology-Based Education for Community Health (TECH) Lab, Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, United States.
German J Rivera-CastellarTechnology-Based Education for Community Health (TECH) Lab, Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, United States.
Brent E GibsonOnPoint NYC, New York, NY, United States.
Brittney Vargas-EstrellaOnPoint NYC, New York, NY, United States.

Funding

Transdisciplinary Theoretical Svnthesis and Development CoreP30DA011041 · NIDA · NEW YORK UNIVERSITY · PI Holly Hagan · 1998 to 2026
$38.9M
Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
Community Developed Technology-Based Messaging to Increase SARS-CoV-2 Vaccine Uptake Among People Who Inject DrugsR01DA054990 · NIDA · NEW YORK UNIVERSITY · PI ARONSON, IAN DAVID · 2021 to 2024
$2.4M
Social Determinants of HIVT32MH128395 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Gina Maria Wingood · 2021 to 2026
$1.4M
NIDA NIH HHS P30 DA011041NIDA NIH HHS P30 DA029926NIDA NIH HHS R01 DA054990NIDA NIH HHS R01DA054990NIMH NIH HHS T32 MH128395
6 · The paper itself

Abstract

Technology-based behavioral health interventions offer potentially limitless opportunities to localize content and target specific populations. However, this ability to customize requires developers to make a wide range of decisions not only about who should appear on screen, but how each message should be refined to most effectively reach a particular group of intervention recipients. These issues become especially salient as interventions are scaled for delivery to multiple populations in different geographical locations or settings (e.g., a hospital emergency department versus the drop-in center of a community-based clinic), and in more than one language. To facilitate evidence-based development of customized, targeted intervention content, our team created a multi-step methodology over a series of NIH-funded research projects. The resulting Participatory Education and Research into Lived Experience (PEARLE) Methodology entails formative qualitative interviews to examine why members of a given population do not enact a specific health behavior such as HIV/HCV testing or vaccinating against COVID-19 (this step includes identifying potential gaps in related health literacy), followed by iterative evaluations of draft content designed to address these barriers, and extensive discussions with a Community Advisory Board. The final step is a clinical trial. PEARLE is designed to be highly flexible, adaptable to a variety of behavioral outcomes in clinical and community settings, and to create content in more than one language depending on the needs or preferences of a population. The current paper discusses how our team employed PEARLE to develop content in English and Spanish for our latest project, which is intended to increase COVID-19 vaccination uptake among people who inject drugs.

Indexed as

communityCOVID-19injectioninterventionmethodologyopioidssubstance usetechnology

Identifiers

PMID36339513
PMCPMC9634163

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.