Evidence map›Paper›PMID 29566717›Full record

ArticleImplementation science : IS2018

Toward optimal implementation of cancer prevention and control programs in public health: a study protocol on mis-implementation.

Margaret Padek, Peg Allen, Paul C Erwin, Melissa Franco, Ross A Hammond, Benjamin Heuberger, Matt Kasman, Doug A Luke, Stephanie Mazzucca, Sarah Moreland-Russell and 1 more

Abstract read
In one paragraph

Article in Implementation science : IS, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Implementation science: why should we care?Journal of the Medical Library Association : JMLA · 2024
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  6. Program adaptation by health departments.Frontiers in public health · 2022
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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

11 authors.

Margaret PadekPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA. mpadek@wustl.edu.ORCID 0000-0002-9825-4513
Peg AllenPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA.
Paul C ErwinDepartment of Public Health, University of Tennessee, Knoxville, TN, USA.
Melissa FrancoPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA.
Ross A HammondCenter on Social Dynamics and Policy, The Brookings Institution, Washington DC, USA.
Benjamin HeubergerCenter on Social Dynamics and Policy, The Brookings Institution, Washington DC, USA.
Matt KasmanCenter on Social Dynamics and Policy, The Brookings Institution, Washington DC, USA.
Doug A LukeCenter for Public Health System Science, Brown School at Washington University in St Louis, St. Louis, MO, USA.
Stephanie MazzuccaPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA.
Sarah Moreland-RussellPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA.
Ross C BrownsonPrevention Research Center in St. Louis, Brown School at Washington University in St. Louis, 1 Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA.

Funding

Mis-Implementation in Cancer Prevention and ControlR01CA214530 · NCI · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C · 2017 to 2021
$2.7M
NCI NIH HHS 1R01CA214530-01NCI NIH HHS R01 CA214530
6 · The paper itself

Abstract

backgroundMuch of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes.

methodsThis is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. DISCUSSION: This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas.

Indexed as

Public HealthDelivery of Health CareHumansLeadershipNeoplasmsAgent-based modelsCancer controlMis-implementation

Identifiers

PMID29566717
PMCPMC5865376

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.