Evidence map›Paper›PMID 37089990›Full record

ArticleImplementation research and practice

Optimization Methods and Implementation Science: An Opportunity for Behavioral and Biobehavioral Interventions.

Kate Guastaferro, Linda M Collins

Abstract 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 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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.

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

29 citing papers in PubMed.

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  18. Article
  19. Enhancing Impact: A Call to Action for Equitable Implementation Science.Prevention science : the official journal of the Society for Prevention Research · 2024
    Article
  20. Using decision analysis for intervention value efficiency to select optimized interventions in the multiphase optimization strategy.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2024
    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

2 authors.

Kate GuastaferroDepartment of Human Development and Family Studies, The Pennsylvania State University.ORCID https://orcid.org/0000-0002-5616-9708
Linda M CollinsDepartments of Social and Behavioral Sciences and Biostatistics, School of Global Public Health, New York University.

Funding

STRATIFIED CLUSTER RANDOMIZED TRIAL (SCRT) OF A CLINICAL DECISION RULE (CDR) FOR ABUSIVE HEAD TRAUMA (AHT)P50HD089922 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI CHRISTIAN M CONNELL · 2017 to 2026
$16.9M
Optimization of behavioral and biobehavioral interventions: Building investigator capacity nationwideR25DA049699 · NIDA · NEW YORK UNIVERSITY · PI LINDA M COLLINS, Katelyn Guastaferro · 2020 to 2026
$1.3M
NICHD NIH HHS P50 HD089922NIDA NIH HHS R25 DA049699
6 · The paper itself

Abstract

This editorial introduces the multiphase optimization strategy (MOST), a principled framework for the development, optimization and evaluation of multicomponent interventions, to the field of implementation science. We suggest that MOST may be integrated with implementation science to advance the field, moving closer towards the ultimate goal of disseminating effective interventions to those in need. We offer three potential ways MOST may advance implementation science: (1) development of an effective and immediately scalable intervention; (2) adaptation of interventions to local contexts; and (3) optimization of the implementation of an intervention itself. Our goal is to inspire the integration of MOST with implementation science across a number of public health contexts.

Indexed as

implementation scienceinterventionmethodsmultiphase optimization strategy (MOST)optimization

Identifiers

PMID37089990
PMCPMC9978651

What OpenQuestion holds

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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.