Evidence map›Paper›PMID 37089123›Full record

ArticleImplementation research and practice

Evaluating agency-led adaptions to an evidence-based lifestyle intervention for adults with serious mental illness.

Kelly A Aschbrenner, Gary R Bond, Sarah I Pratt, Kenneth Jue, Gail Williams, Souvik Banerjee, Stephen J Bartels

Open access · goldAbstract read
In one paragraph

Article in Implementation research and practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 12% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

7 authors at 5 institutions in 1 country.

Kelly A AschbrennerDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Gary R BondWestat, Lebanon, NH, USA.
Sarah I PrattDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Kenneth JueKen Jue Consulting, Keene, NH, USA.
Gail WilliamsDartmouth Hitchcock Health System, Merrimack, NH, USA.
Souvik BanerjeeThe Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
Stephen J BartelsThe Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
Dartmouth–Hitchcock Medical Center · USDartmouth College · USHarvard University · USMassachusetts General Hospital · USWestat (United States) · US

Funding

RCT of a Learning Collaborative to Implement Health Promotion in Mental HealthR01MH102325 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BARTELS, STEPHEN J · 2014 to 2018
$3.7M
1/3 - Social Processes Initiative in Neurobiology of the Schizophrenia(s)R01MH102324 · NIMH · CENTRE FOR ADDICTION AND MENTAL HEALTH · PI VOINESKOS, ARISTOTLE NICHOLAS · 2014 to 2018
$1.4M
NIMH NIH HHS R01 MH102324NIMH NIH HHS R01 MH102325
6 · The paper itself

Abstract

Background: Limited empirical evidence exists on the impact of adaptations that occur in implementing evidence-based practices (EBPs) in real-world practice settings. The purpose of this study was to measure and evaluate adaptations to an EBP (InSHAPE) for obesity in persons with serious mental illness in a national implementation in mental health care settings. Methods: We conducted telephone interviews with InSHAPE provider teams at 37 (95%) of 39 study sites during 24-month follow-up of a cluster randomized trial of implementation strategies for InSHAPE at behavioral health organizations. Our team rated adaptations as fidelity-consistent or fidelity-inconsistent. Multilevel regression models were used to estimate the relationship between adaptations and implementation and participant outcomes. Results: Of 37 sites interviewed, 28 sites (76%) made adaptations to InSHAPE ( Conclusions: This research suggests that adaptations to an evidence-based lifestyle program were common during implementation in real-world mental health practice settings even when fidelity was monitored and reinforced through implementation interventions. Results suggest that adaptations, including those that are fidelity-inconsistent, can be positively associated with improved participant outcomes when they provide a potential practical advantage while maintaining the core function of the intervention. Plain language abstract: Treatments that have been proven to work in research studies are not always one-size-fits-all. In real-world clinical settings where people receive mental health care, sometimes there are good reasons to change certain things about a treatment. For example, a particular treatment might not fit well in a specific clinic or cultural context, or it might not meet the needs of specific patient groups. We studied adaptations to an evidence-based practice (InSHAPE) targeting obesity in persons with serious mental illness made by teams implementing the program in routine mental health care settings. We learned that adaptations to InSHAPE were common, and that an adaptation that model experts initially viewed as inconsistent with fidelity to the model turned out to have a positive impact on participant health outcomes. The results of this study may encourage researchers and model experts to work collaboratively with mental health agencies and clinicians implementing evidence-based practices to consider allowing for and guiding adaptations that provide a potential practical advantage while maintaining the core purpose of the intervention.

Indexed as

Adaptationbehavioral healthfidelityhealth promotionimplementationmeasurementmodification

Identifiers

PMID37089123
PMCPMC9978662
OpenAlexW3082516230

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.