Evidence map›Paper›PMID 28634539›Full record

ArticleSAGE open medicine2017

Using mHealth technologies to improve the identification of behavioral health problems in urban primary care settings.

Martha Staeheli, Robert H Aseltine, Elizabeth Schilling, Daren Anderson, Bruce Gould

Abstract read
In one paragraph

Article in SAGE open medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

5 authors.

Martha StaeheliProgram for Recovery and Community Health, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
Robert H AseltineDivision of Behavioral Sciences and Community Health and Center for Public Health and Health Policy, University of Connecticut Health Center, Farmington, CT, USA.
Elizabeth SchillingDivision of Behavioral Sciences and Community Health and Center for Public Health and Health Policy, University of Connecticut Health Center, Farmington, CT, USA.
Daren AndersonWeitzman Institute, Community Health Center, Inc., Middletown, CT, USA.
Bruce GouldDivision of Behavioral Sciences and Community Health and Center for Public Health and Health Policy, University of Connecticut Health Center, Farmington, CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBehavioral health disorders remain under recognized and under diagnosed among urban primary care patients. Screening patients for such problems is widely recommended, yet is challenging to do in a brief primary care encounter, particularly for this socially and medically complex patient population.

methodsIn 2013, intervention patients at an urban Connecticut primary clinic were screened for post-traumatic stress disorder, depression, and risky drinking (n = 146) using an electronic tablet-based screening tool. Screening data were compared to electronic health record data from control patients (n = 129) to assess differences in the prevalence of behavioral health problems, rates of follow-up care, and the rate of newly identified cases in the intervention group.

resultsResults from logistic regressions indicated that both groups had similar rates of disorder at baseline. Patients in the intervention group were five times more likely to be identified with depression (p < 0.05). Post-traumatic stress disorder was virtually unrecognized among controls but was observed in 23% of the intervention group (p < 0.001). The vast majority of behavioral health problems identified in the intervention group were new cases. Follow-up rates were significantly higher in the intervention group relative to controls, but were low overall.

conclusionThis tablet-based electronic screening tool identified significantly higher rates of behavioral health disorders than have been previously reported for this patient population. Electronic risk screening using patient-reported outcome measures offers an efficient approach to improving the identification of behavioral health problems and improving rates of follow-up care.

Indexed as

behavioral healthmHealthprimary careRisk screeningtechnologyurban health

Identifiers

PMID28634539
PMCPMC5467966

What OpenQuestion holds

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Registered trials

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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.