Evidence map›Paper›PMID 24509033›Full record

ArticleJournal of health care for the poor and underserved2014

Impact of depression on the intensity of patient navigation for women with abnormal cancer screenings.

Ignacio I De La Cruz, Karen M Freund, Tracy A Battaglia, Clara A Chen, Sharon Bak, Richard Kalish, Barbara Lottero, Patrick Egan, Tim Heeren, Andrea C Kronman

Abstract readMulticenter Study
In one paragraph

Article in Journal of health care for the poor and underserved, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 46% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
  2. 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

10 authors at 4 institutions in 2 countries.

Ignacio I De La Cruz
Karen M Freund
Tracy A Battaglia
Clara A Chen
Sharon Bak
Richard Kalish
Barbara Lottero
Patrick Egan
Tim Heeren
Andrea C Kronman
Boston University · USTufts Medical Center · USWomen's Health Research Institute · CATufts University · US

Funding

"Patient Navigation in the SafetyNet: CONNECTeDD"U01CA116892 · NCI · BOSTON MEDICAL CENTER · PI FREUND, KAREN · 2005 to 2010
$4.3M
NCI NIH HHS U01 CA116892
6 · The paper itself

Abstract

Patient navigation is increasingly being used to support vulnerable patients to receive timely and quality medical care. We sought to understand whether patients with depression utilize additional patient navigation services after abnormal cancer screening. We compared depressed and non-depressed women using three different measures of intensity of patient navigation: number of patient-navigator encounters, encounter time, and number of unique barriers to care. The study population consisted of 1,455 women who received navigation after abnormal screening for breast or cervical cancer at one of six community health centers in Boston. Navigators spent a median of 60-75 minutes over one or two encounters per participant, with 49% of participants having one or more documented barrier to care. Depressed women did not differ in total numbers of encounters, encounter time, or unique barriers compared with non-depressed women. Our findings suggest that pre-existing depression does not predict which women will utilize additional navigation services.

Indexed as

Patient NavigationAdultAgedBostonBreast NeoplasmsCommunity Health CentersDepressionFemaleHumansMiddle AgedUterine Cervical Neoplasms

Identifiers

PMID24509033
PMCPMC4184058
OpenAlexW2072593562

What OpenQuestion holds

Textmetadata
LicenceTDM
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.