Evidence map›Paper›PMID 26684298›Full record

ArticlePloS one2015

Time Preferences Predict Mortality among HIV-Infected Adults Receiving Antiretroviral Therapy in Kenya.

Harsha Thirumurthy, Kami Hayashi, Sebastian Linnemayr, Rachel C Vreeman, Irwin P Levin, David R Bangsberg, Noel T Brewer

Abstract read
In one paragraph

Article in PloS one, 2015. 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
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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

7 authors.

Harsha ThirumurthyDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Kami HayashiDepartment of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Sebastian LinnemayrRAND Corporation, Santa Monica, CA, United States of America.
Rachel C VreemanDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, United States of America.
Irwin P LevinDepartment of Psychology, University of Iowa, Iowa City, IA, United States of America.
David R BangsbergCenter for Global Health, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America.
Noel T BrewerDepartment of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
Preferences, expectations, and the prediction of health and economic behaviorK01HD061605 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THIRUMURTHY, HARSHA · 2011 to 2015
$638k
NICHD NIH HHS K01 HD061605NICHD NIH HHS K01HD061605NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

backgroundIdentifying characteristics of HIV-infected adults likely to have poor treatment outcomes can be useful for targeting interventions efficiently. Research in economics and psychology suggests that individuals' intertemporal time preferences, which indicate the extent to which they trade-off immediate vs. future cost and benefits, can influence various health behaviors. While there is empirical support for the association between time preferences and various non-HIV health behaviors and outcomes, the extent to which time preferences predict outcomes of those receiving antiretroviral therapy (ART) has not been examined previously.

methodsHIV-infected adults initiating ART were enrolled at a health facility in Kenya. Participants' time preferences were measured at enrollment and used to classify them as having either a low or high discount rate for future benefits. At 48 weeks, we assessed mortality and ART adherence, as measured by Medication Event Monitoring System (MEMS). Logistic regression models adjusting for socio-economic characteristics and risk factors were used to determine the association between time preferences and mortality as well as MEMS adherence ≥90%.

resultsOverall, 44% (96/220) of participants were classified as having high discount rates. Participants with high discount rates had significantly higher 48-week mortality than participants with low discount rates (9.3% vs. 3.1%; adjusted odds ratio 3.84; 95% CI 1.03, 14.50). MEMS adherence ≥90% was similar for participants with high vs. low discount rates (42.3% vs. 49.6%, AOR 0.70; 95% CI 0.40, 1.25).

conclusionHigh discount rates were associated with significantly higher risk of mortality among HIV-infected patients initiating ART. Greater use of time preference measures may improve identification of patients at risk of poor clinical outcomes. More research is needed to further identify mechanisms of action and also to build upon and test the generalizability of this finding.

Indexed as

AdultAnti-HIV AgentsFemaleHealth Knowledge, Attitudes, PracticeHIV InfectionsHumansKenyaMaleMedication AdherencePatient PreferenceRandomized Controlled Trials as TopicTime FactorsAnti-HIV Agents

Identifiers

PMID26684298
PMCPMC4684319

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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.