Evidence map›Paper›PMID 32766864›Full record

ArticleTranslational behavioral medicine2020

Collaborative care clinician perceptions of computerized cognitive behavioral therapy for depression in primary care.

Lucinda B Leung, Karen E Dyer, Elizabeth M Yano, Alexander S Young, Lisa V Rubenstein, Alison B Hamilton

Open access · greenAbstract read
In one paragraph

Article in Translational behavioral medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 34% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Primary care provider perspectives on virtual and in-person depression management during the COVID-19 pandemic.Families, systems & health : the journal of collaborative family healthcare · 2023
    Article
  7. 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

6 authors at 5 institutions in 1 country.

Lucinda B LeungCenter for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Karen E DyerCenter for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Elizabeth M YanoCenter for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Alexander S YoungCenter for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Lisa V RubensteinDivision of General Internal Medicine and Health Services Research, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.
Alison B HamiltonCenter for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Neurobehavioral Systems · USCenter for the Study of Healthcare Provider Behavior · USRAND Corporation · USUCLA Health · USUniversity of California, Los Angeles · US

Funding

Improving Depression Management in Primary CareIK2HX002867 · VA · VA GREATER LOS ANGELES HEALTHCARE SYSTEM · PI LEUNG, LUCINDA B · 2020 to 2025
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HSR&D Merit Review Research Career Scientist (RCS) Award (IK6)IK6HX002836 · VA · VA GREATER LOS ANGELES HEALTHCARE SYSTEM · PI ELIZABETH M YANO · 2020 to 2026
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HSRD VA IK2 HX002867HSRD VA IK6 HX002836
6 · The paper itself

Abstract

In Veterans Health Administration's (VA) Primary Care-Mental Health Integration (PC-MHI) models, primary care providers, care managers, and mental health clinicians collaboratively provide depression care. Primary care patients, however, still lack timely, sufficient access to psychotherapy treatment. Adapting PC-MHI collaborative care to improve uptake of evidence-based computerized cognitive behavioral therapy (cCBT) may be a potential solution. Understanding primary care-based mental health clinician perspectives is crucial for facilitating adoption of cCBT as part of collaborative depression care. We examined PC-MHI mental health clinicians' perspectives on adapting collaborative care models to support cCBT for VA primary care patients. We conducted 16 semi-structured interviews with PC-MHI nurse care managers, licensed social workers, psychologists, and psychiatrists in one VA health-care system. Interviews were audio-recorded, transcribed, coded using the constant comparative method, and analyzed for overarching themes. Although cCBT awareness and knowledge were not widespread, participants were highly accepting of enhancing PC-MHI models with cCBT for depression treatment. Participants supported cCBT delivery by a PC-MHI care manager or clinician and saw it as an additional tool to engage patients, particularly younger Veterans, in mental health treatment. They commented that current VA PC-MHI models did not facilitate, and had barriers to, use of online and mobile treatments. If effectively implemented, however, respondents thought it had potential to increase the number of patients they could treat. There is widespread interest in modernizing health systems. VA PC-MHI mental health clinicians appear open to adapting collaborative care to increase uptake of cCBT to improve psychotherapy access.

Indexed as

Cognitive Behavioral TherapyDelivery of Health Care, IntegratedMental Health ServicesDepressionHumansPerceptionPrimary Health CareUnited StatesUnited States Department of Veterans Affairse-TechnologyImplementationPrimary carePsychiatric disorders/mental healthTeam science and practice

Identifiers

PMID32766864
PMCPMC8018828
OpenAlexW3047996180

What OpenQuestion holds

Textmetadata
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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.