Evidence map›Paper›PMID 36111174›Full record

ArticleContemporary clinical trials communications2022

Promoting benzodiazepine cessation through an electronically-delivered patient self-management intervention (EMPOWER-ED): Randomized controlled trial protocol.

Michael A Cucciare, Hildi J Hagedorn, Mark Bounthavong, Traci H Abraham, Carolyn J Greene, Xiaotong Han, Lakiesha Kemp, Kathy Marchant, Penny White, Keith Humphreys

Registry-linked trialAbstract read
In one paragraph

Article in Contemporary clinical trials communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04572750 (Promoting Benzodiazepine Cessation Through an Electronically-delivered Patient Self-management Intervention), which is not on this 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
–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.

NCT04572750 nacompletednot on this map

Promoting Benzodiazepine Cessation Through an Electronically-delivered Patient Self-management Intervention

TypeinterventionalSponsorVA Office of Research and DevelopmentRan2022 to 2024Enrolled170ConditionsTaking Benzodiazepines for Any Reason for 3 Months, Benzodiazepine DependenceArmsEMPOWER-ED
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Trial
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.

Michael A CucciareCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock, AR, 72205, USA.
Hildi J HagedornCenter for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, 55417, USA.
Mark BounthavongHealth Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, CA, 94025, USA.
Traci H AbrahamCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock, AR, 72205, USA.
Carolyn J GreeneDepartment of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA.
Xiaotong HanCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock, AR, 72205, USA.
Lakiesha KempCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock, AR, 72205, USA.
Kathy MarchantCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock, AR, 72205, USA.
Penny WhiteVeterans Affairs South Central Mental Illness Research, Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock, AR, 72205, USA.
Keith HumphreysCenter for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, CA, 94025, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Long-term benzodiazepine dependence carries significant health risks which might be reduced with low-cost patient self-management interventions. A booklet version of one such intervention (Eliminating Medications Through Patient Ownership of End Results; EMPOWER) proved effective in a Canadian clinical trial with older adults. Digitizing such an intervention for electronic delivery and tailoring it to different populations could expand its reach. Accordingly, this article describes the protocol for a randomized controlled trial to test the effectiveness of an electronically-delivered, direct-to-patient benzodiazepine cessation intervention tailored to U.S. military veterans. Methods: Design: Two-arm individually randomized controlled trial. Setting: US Veterans Health Administration primary care clinics. Participants: Primary care patients taking benzodiazepines for three or more months and having access to a smartphone, tablet or desktop computer. Intervention and comparator: Participants will be randomized to receive either the electronically-delivered EMPOWER (EMPOWER-ED) protocol or asked to continue to follow provider recommendations regarding their benzodiazepine use (treatment-as-usual). Measurements: The primary outcomes are complete benzodiazepine cessation and 25% dose reduction, assessed using administrative and self-report data, between baseline and six-month follow-up. Secondary outcomes are self-reported anxiety symptoms, sleep quality, and overall health and quality of life, measured at baseline and 6-month follow-up, and benzodiazepine cessation at 12-month follow-up. Comments: This randomized controlled trial will evaluate whether the accessibility and effectiveness of a promising intervention for benzodiazepine cessation can be improved through digitization and population tailoring.

Indexed as

Benzodiazepine dependenceDigitalProtocolSelf-managementSmartphone appVeterans

Identifiers

PMID36111174
PMCPMC9468353

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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.