Evidence map›Paper›PMID 37917476›Full record

ArticlePsychological services2024

Identifying predictors of the amount of veteran participation in cognitive behavioral therapy for insomnia in the Veterans Affairs health care system.

Caitlan A Tighe, Gregory S Berlin, Elaine M Boland, Katherine E Miller, Adam D Bramoweth

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Psychological services, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03974503 (Characterization of Sleep With Trauma Nightmares Using Ambulatory Sleep Measurement), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 31% 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.

NCT03974503 nacompletednot on this map

Characterization of Sleep With Trauma Nightmares Using Ambulatory Sleep Measurement

TypeinterventionalSponsorVA Office of Research and DevelopmentRan2019 to 2025Enrolled48ConditionsNightmares, Stress Disorders, Post-Traumatic, Actigraphy, Respiratory Sinus ArrhythmiaArmsExposure, Relaxation, and Rescripting Therapy, Sleep and Nightmare Management
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

5 authors at 3 institutions in 1 country.

Caitlan A TigheMental Illness Research, Education and Clinical Center, VA Pittsburgh Healthcare System.ORCID 0000-0003-0592-4213
Gregory S BerlinBehavioral Health Service Line, VA Pittsburgh Healthcare System.ORCID 0000-0002-5128-8046
Elaine M BolandDepartment of Psychiatry, University of Pennsylvania.ORCID 0000-0002-3532-6380
Katherine E MillerMental Illness Research, Education and Clinical Center, Corporal Michael J. Crescenz Veterans Affairs Medical Center.ORCID 0000-0003-1108-2630
Adam D BramowethMental Illness Research, Education and Clinical Center, VA Pittsburgh Healthcare System.ORCID 0000-0002-3535-0292
VA Pittsburgh Healthcare System · USUniversity of Pennsylvania · USVeterans Health Administration · US

Funding

Enhancing Access to Insomnia Care (EASI Care): Implementing Brief Behavioral Treatment for Insomnia in Primary Care Mental Health Integration ClinicsI01HX003096 · VA · VETERANS HEALTH ADMINISTRATION · PI BRAMOWETH, ADAM DANIEL · 2020 to 2025
–
SEdative-Hypnotic Deprescribing Assisted by a Technology-Driven Insomnia InterVEntion (SEDATIVE)I21RX003732 · VA · VETERANS HEALTH ADMINISTRATION · PI BRAMOWETH, ADAM DANIEL · 2022 to 2024
–
The Role of Effort Discounting in the Link between Insomnia and DepressionIK2CX001501 · VA · PHILADELPHIA VA MEDICAL CENTER · PI BOLAND, ELAINE M · 2017 to 2022
–
Characterization of sleep with trauma nightmares using ambulatory sleep measurementIK2CX001874 · VA · PHILADELPHIA VA MEDICAL CENTER · PI MILLER, KATHERINE ELIZABETH · 2019 to 2024
–
Optimizing Cardiac Rehabilitation by Integrating Sleep TherapeuticsIK2RX003393 · VA · VETERANS HEALTH ADMINISTRATION · PI TIGHE, CAITLAN ANN · 2020 to 2022
–
CSRD VA IK2 CX001501CSRD VA IK2 CX001874HSRD VA I01 HX003096RRD VA I21 RX003732RRD VA IK2 RX003393US Department of Veterans Affairs; Clinical Science Research and Development ServiceUS Department of Veterans Affairs; Clinical Sciences and Research Development ServiceUS Department of Veterans Affairs; Health Services Research and Development ServiceUS Department of Veterans Affairs; Rehabilitation Research and Development ServiceVA Pittsburgh Healthcare SystemVeterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center (VISN 4 MIRECC)
6 · The paper itself

Abstract

Insomnia is a prevalent and negatively impactful disorder among veterans. The Department of Veterans Affairs (VA) has committed significant resources to the development and dissemination of training related to cognitive behavioral therapy for insomnia (CBT-I), the recommended first-line intervention for chronic insomnia disorder. It has been established that VA clinicians can be effectively trained to deliver high fidelity CBT-I and that treatment results in significant improvements in insomnia. However, there is a paucity of research examining rates and predictors of veterans' participation in CBT-I in routine VA clinical care. In this study, we conducted a secondary analysis of data from VA electronic health records (EHR) to determine individual predisposing, enabling, and need factors associated with CBT-I participation. The sample included veterans who had at least one CBT-I templated note from the VA mid-Atlantic region of the United States (VISN4) between 2015 and 2019 in their chart (

Indexed as

Cognitive Behavioral TherapySleep Initiation and Maintenance DisordersUnited States Department of Veterans AffairsVeteransAdultAgedFemaleHumansMaleMiddle AgedPatient Acceptance of Health CareUnited States

Identifiers

PMID37917476
PMCPMC11063118
OpenAlexW4388280953

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.