Evidence map›Paper›PMID 31846482›Full record

ArticlePloS one2019

Recall accuracy of weekly automated surveys of health care utilization and infectious disease symptoms among infants over the first year of life.

Catherine Ley, Lauren Willis, Maria de la Luz Sanchez, Julie Parsonnet

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 77% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Catherine LeyDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford School of Medicine, Stanford, CA, United States of America.ORCID 0000-0002-8424-7873
Lauren WillisDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford School of Medicine, Stanford, CA, United States of America.
Maria de la Luz SanchezDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford School of Medicine, Stanford, CA, United States of America.
Julie ParsonnetDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford School of Medicine, Stanford, CA, United States of America.
Stanford Medicine · US

Funding

Childhood infection and prevention of obesityR01HD063142 · NICHD · STANFORD UNIVERSITY · PI PARSONNET, JULIE · 2009 to 2013
$3.7M
Longitudinal investigations of the infant virome and its associations with obesityR01HD088837 · NICHD · STANFORD UNIVERSITY · PI PARSONNET, JULIE · 2017 to 2020
$2.2M
Household Triclosan and Triclocarban Use and the Developing Infant MicrobiomeR21ES023371 · NIEHS · STANFORD UNIVERSITY · PI PARSONNET, JULIE · 2014 to 2016
$974k
NICHD NIH HHS R01 HD063142NICHD NIH HHS R01 HD088837NIEHS NIH HHS R21 ES023371
6 · The paper itself

Abstract

Automated surveys, by interactive voice response (IVR) or email, are increasingly used for clinical research. Although convenient and inexpensive, they have uncertain validity. We sought to assess the accuracy of longitudinally-collected automated survey responses compared to medical records. Using data collected from a well-characterized, prospective birth cohort over the first year of life, we examined concordance between guardians' reports of their infants' health care visits ascertained by weekly automated survey (IVR or email) and those identified by medical chart review. Among 180 survey-visit pairs, concordance was 51%, with no change as number of visits per baby increased. Accuracy of recall was higher by email compared to IVR (61 vs. 43%; adjusted OR = 2.5 95% CI: 1.3-4.8), did not vary by health care encounter type (hospitalization: 50%, ER: 64%, urgent care: 44%, primary care: 52%; p = 0.75), but was higher for fever (77%, adjusted OR = 5.1 95%CI: 1.5-17.7) and respiratory illness (58%, adjusted OR = 2.9 95%CI: 1.5-5.8) than for other diagnoses. For the 75 mothers in these encounters, 69% recalled at least one visit; among 41 mothers with two or more visits, 85% recalled at least one visit. Predictors of accurate reporting by mothers after adjusting for illness in the baby included increased age and increased years of education (age per year, β = 0.05, p = 0.03; education per year, β = 0.08, p = 0.04). Additional strategies beyond use of automated surveys are needed to ascertain accurate health care utilization in longitudinal cohort studies, particularly in healthy populations with little motivation for accurate reporting.

Indexed as

AdultAutomationCommunicable DiseasesElectronic MailFemaleHumansInfantInfant, NewbornMaleMedical RecordsMental RecallMothersPatient Acceptance of Health CareReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID31846482
PMCPMC6917293
OpenAlexW2996226192

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.