Evidence map›Paper›PMID 41533380›Full record

Trial reportJAMA network open2026

Electronic Intervention for Patient-Managed Benzodiazepine Tapering: A Randomized Clinical Trial.

Keith Humphreys, Hildi Hagedorn, Xiaotong Han, Lakiesha Kemp, Nichols Poitra, Michael A Cucciare

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2026. 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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

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

6 authors.

Keith HumphreysCenter for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, California.
Hildi HagedornCenter for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, Minnesota.
Xiaotong HanCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock.
Lakiesha KempCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock.
Nichols PoitraCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock.
Michael A CucciareCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Affairs Healthcare System, North Little Rock.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: More than 30 million people in the US take prescribed benzodiazepines, which, when taken long-term, carry risks of falls, cognitive decline, and dependence. A previous trial showed that a patient-focused self-management intervention (Eliminating Medications Through Patient Ownership of End Results; EMPOWER) can reduce long-term benzodiazepine dependence use and the risks that accompany it. Objective: To replicate the finding of the EMPOWER trial after converting the intervention from printed materials to electronic format. Design, Setting, and Participants: This 2-arm, individually randomized clinical trial with a 6-month follow-up was conducted at US Veterans Health Administration primary care clinics in 2 Veterans Affairs health care systems. Participants included 161 primary care patients taking benzodiazepines for 3 or more months and having access to a smartphone, tablet, or desktop computer. Recruitment occurred from June 1, 2022, to January 31, 2024. Intervention: Participants were randomized to either the electronically delivered EMPOWER (EMPOWER-ED) protocol or asked to continue to follow clinician recommendations regarding their benzodiazepine use (treatment as usual). Main Outcomes and Measures: Preregistered primary outcomes were complete benzodiazepine cessation and at least 25% dose reduction at 6-month follow-up, assessed using pharmacy data. Secondary outcomes were self-reported anxiety symptoms, sleep quality, and overall health and quality of life. Analysis was performed on an intent-to-treat basis. Results: The 161 participants had a mean (SD) age of 61.9 (13.7) years and were mostly male (134 [83.2%]). Individuals assigned to the EMPOWER-ED group had a significantly greater likelihood of complete benzodiazepine cessation (odds ratio [OR], 5.31 [95% CI, 1.12-25.12]). There was no likelihood of at least a 25% dose reduction in the EMPOWER-ED group relative to the control group (OR, 2.51 [95% CI, 0.91-6.90]). No statistically significant difference was found between the 2 groups for the secondary outcomes. Conclusions and Relevance: This randomized clinical trial found a large effect of a low-cost, self-administered electronic intervention for reducing benzodiazepine use among long-term users. Findings from this replicated clinical trial are encouraging given the prevalence of benzodiazepine dependence and the constraints on clinician time available to address it. Dissemination of this intervention-which is in the public domain-by health care and public health systems seems warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT04572750.

Indexed as

BenzodiazepinesDrug TaperingSelf-ManagementSubstance-Related DisordersAgedFemaleHumansMaleMiddle AgedUnited StatesVeteransBenzodiazepines

Identifiers

PMID41533380
PMCPMC12805446

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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.