Evidence map›Paper›PMID 37150823›Full record

ArticleAIDS research and therapy2023

Assessing behavioral economic biases among young adults who have increased likelihood of acquiring HIV: a mixed methods study in Baltimore, Maryland.

Larissa Jennings Mayo-Wilson, Jessica Coleman Lewis, Sarah MacCarthy, Sebastian Linnemayr

Open access · goldAbstract read
In one paragraph

Article in AIDS research and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 34% 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.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 4 institutions in 1 country.

Larissa Jennings Mayo-WilsonDepartment of Health Behavior, Department of Maternal and Child Health, University of North Carolina at Chapel Hill Gillings School of Global Public Health, 310 Rosenau Hall CB #7400, 135 Dauer Drive, Chapel Hill, NC, 27599, USA. ljennings.mayowilson@unc.edu.
Jessica Coleman LewisDepartment of International Health, Social and Behavioral Interventions Program, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205, USA.
Sarah MacCarthyDepartment of Health Behavior, University of Alabama at Birmingham School of Public Health, 1665 University Boulevard, Birmingham, AL, USA.
Sebastian LinnemayrRAND Corporation, 1776 Main Street, Santa Monica, CA, 90401, USA.
Johns Hopkins University · USRAND Corporation · USUniversity of Alabama at Birmingham · USUniversity of North Carolina at Chapel Hill · US

Funding

Integrating Microenterprise and Behavioral Economics for HIV Prevention in African-American Young AdultsK01MH107310 · NIMH · TRUSTEES OF INDIANA UNIVERSITY · PI JENNINGS MAYO-WILSON, LARISSA · 2015 to 2019
$848k
NIMH NIH HHS K01 MH107310NIMH NIH HHS K01MH107310
6 · The paper itself

Abstract

backgroundBehavioral economic (BE) biases have been studied in the context of numerous health conditions, yet are understudied in the field of HIV prevention. This aim of this study was to quantify the prevalence of four common BE biases-present bias, information salience, overoptimism, and loss aversion-relating to condom use and HIV testing in economically-vulnerable young adults who had increased likelihood of acquiring HIV. We also qualitatively examined participants' perceptions of these biases.

methods43 participants were enrolled in the study. Data were collected via interviews using a quantitative survey instrument embedded with qualitative questions to characterize responses. Interviews were transcribed and analyzed using descriptive statistics and deductive-inductive content analyses.

results56% of participants were present-biased, disproportionately discounting future rewards for smaller immediate rewards. 51% stated they were more likely to spend than save given financial need. Present-bias relating to condom use was lower with 28% reporting they would engage in condomless sex rather than wait one day to access condoms. Most participants (72%) were willing to wait for condom-supported sex given the risk. Only 35% knew someone living with HIV, but 67% knew someone who had taken an HIV test, and 74% said they often think about preventing HIV (e.g., high salience). Yet, 47% reported optimistically planning for condom use, HIV discussions with partners, or testing but failing to stick to their decision. Most (98%) were also averse (b = 9.4, SD  ±.9) to losing their HIV-negative status. Qualitative reasons for sub-optimal condom or testing choices were having already waited to find a sex partner, feeling awkward, having fear, or not remembering one's plan in the moment. Optimal decisions were attributed qualitatively to self-protective thoughts, establishing routine care, standing on one's own, and thinking of someone adversely impacted by HIV. 44% of participants preferred delayed monetary awards (e.g., future-biased), attributed qualitatively to fears of spending immediate money unwisely or needing time to plan.

conclusionMixed methods BE assessments may be a valuable tool in understanding factors contributing to optimal and sub-optimal HIV prevention decisions. Future HIV prevention interventions may benefit from integrating savings products, loss framing, commitment contracts, cues, or incentives.

Indexed as

Acquired Immunodeficiency SyndromeHIV InfectionsBaltimoreCondomsEconomics, BehavioralHumansSexual BehaviorYoung AdultAfrican-AmericanBaltimoreBehavioral economicsHIVHomelessnessMixed methodsPreventionQualitativeYoung adults

Identifiers

PMID37150823
PMCPMC10165802
OpenAlexW4375855817

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.