Evidence mapPaperPMID 41656239Full record

Trial reportImplementation science : IS2026

Testing normalization process theory in a randomized trial of mental health clinics implementing digital measurement-based care.

Nathaniel J Williams, Mimi Choy-Brown, Nallely Vega, Gregory A Aarons, Mark G Ehrhart, Steven C Marcus

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Implementation science : IS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04096274 (Randomized Trial of a Leadership and Organizational Change Strategy to Improve the Implementation and Sustainment of Digital Measurement-based Care in Youth Mental Health Services), 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.

NCT04096274 nacompletednot on this map

Randomized Trial of a Leadership and Organizational Change Strategy to Improve the Implementation and Sustainment of Digital Measurement-based Care in Youth Mental Health Services

TypeinterventionalSponsorBoise State UniversityRan2019 to 2022Enrolled686ConditionsImplementation, Behavioral SymptomsArmsLeadership for Organization Change and Implementation (LOCI), Training and Technical Assistance Only
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.

Nathaniel J WilliamsInstitute for the Study of Behavioral Health and Addiction, Boise State University, 1910 W. University Dr., Boise, ID, 83725, USA. natewilliams@boisestate.edu.ORCID 0000-0002-3948-7480
Mimi Choy-BrownSchool of Social Work, University of Minnesota - Twin Cities, St. Paul, MN, USA.
Nallely VegaInstitute for the Study of Behavioral Health and Addiction, Boise State University, 1910 W. University Dr., Boise, ID, 83725, USA.
Gregory A AaronsDepartment of Psychiatry, University of California, San Diego, CA, USA.
Mark G EhrhartDepartment of Psychology, University of Central Florida, Orlando, FL, USA.
Steven C MarcusSchool of Social Policy and Practice, University of Pennsylvania, Philadelphia, PA, USA.

Funding

NIDA NIH HHS R01 DA049891NIMH NIH HHS R01MH119127
6 · The paper itself

Abstract

backgroundNormalization process theory (NPT) is one of the most highly cited implementation theories that explains the mechanisms by which new complex health interventions become embedded and sustained in healthcare settings; however, few of its predictions have been subjected to inferential hypothesis testing. In this theory-driven, ancillary analysis of a large hybrid type 3 effectiveness-implementation trial, we tested two NPT predictions: (1) its generative mechanisms of coherence, cognitive participation, collective action, and reflexive monitoring are modifiable in response to deliberate change efforts, and (2) greater enactment of these mechanisms predicts greater future sustainment of complex health interventions.

methodsThe trial tested two strategies to improve the implementation and sustainment of digital measurement-based care in outpatient mental health clinics serving youth. Twenty-one clinics were randomized to either training and technical assistance alone (k = 10) or training and technical assistance plus the Leadership and Organizational Change for Implementation (LOCI) strategy, in which leaders received training, coaching, and consultation to support implementation (k = 11). Six months after implementation strategies concluded, clinicians (N = 144) in both arms completed the Normalization MeAsure Development (NoMAD) questionnaire to describe the extent to which NPT mechanisms were enacted in their clinics. The primary outcome was a monthly, clinic-level, binary indicator of measurement-based care sustainment, derived from automatically-generated system usage data, for 16 months after the NoMAD assessment.

resultsThe NPT mechanisms were highly responsive to the organizational implementation strategy, which had a large effect overall (NoMAD total score: d

conclusionsThe generative mechanisms proposed by NPT are modifiable in response to theoretically-aligned implementation strategies, and greater enactment of these mechanisms predicts greater sustainment of complex health interventions over 16 months.

trial registrationClinicalTrials.gov Identifier: NCT04096274 (Working to Implement and Sustain Digital Outcome Measures); Registered September 19, 2019; url: https://www. CLINICALTRIALS: gov/study/NCT04096274.

Indexed as

Implementation ScienceMental Health ServicesDigital HealthHumansLeadershipOrganizational InnovationComplex health interventionsEvidence-based practiceImplementation mechanismsLeadership and Organizational Change for ImplementationMeasurement-based careMental healthNormalization process theoryNPTSustainmentWISDOM trial

Identifiers

PMID41656239
PMCPMC12918388

What Socratic holds

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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 Socratic graph.