Evidence map›Paper›PMID 24158242›Full record

ArticleJournal of clinical psychology in medical settings2014

Health-related outcomes associated with patterns of risk factors in primary care patients.

Jennifer S Funderburk, Stephen A Maisto, Allison K Labbe

Abstract read
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In one paragraph

Article in Journal of clinical psychology in medical settings, 2014. 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 30% 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

3 authors at 3 institutions in 1 country.

Jennifer S FunderburkVA Center for Integrated Healthcare, Syracuse Veterans Affairs Medical Center, 800 Irving Ave., (116C), Syracuse, NY, 13210, USA, Jennifer.Funderburk@va.gov.
Stephen A Maisto
Allison K Labbe
SUNY Upstate Medical University · USSyracuse University · USSyracuse VA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is important to find ways to identify prevalent co-occurring health risk factors to help facilitate treatment programming. One method is to use electronic medical record (EMR) data. Funderburk et al. (J Behav Med 31:525-535, 2008) used such data and latent class analysis to identify three classes of individuals based on standard health screens administered in Veterans Affairs primary care clinics. The present study extended these results by examining the health-related outcomes for each of these identified classes. Follow-up data were collected from a subgroup of the original sample (N = 4,132). Analyses showed that class assignment predicted number of diagnoses associated with the diseases that the health screens target and number of primary care behavioral health, and emergency room encounters. The findings illustrate one way an EMR can be used to identify clusters of individuals presenting with multiple health risk factors and where the healthcare system comes in contact with them.

Indexed as

Health BehaviorHealth StatusAlcoholismBlood PressureBody Mass IndexCardiovascular DiseasesCausalityComorbidityDepressive DisorderDiabetes MellitusElectronic Health RecordsEmergency Service, HospitalFemaleFollow-Up StudiesHumansHypertension

Identifiers

PMID24158242
OpenAlexW2029583348

What OpenQuestion holds

Textmetadata
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.