Cited by 4,021Health Policy Implementation ScienceGlobal Cancer Incidence and ScreeningEvaluation and Performance Assessment

The DOI matches its Crossref record; 12 of the 15 references it cites were found in a registry or an index; none of the 1 sources its claims cite is checked for support yet.

How We Design Feasibility Studies

Open access

Abstract

Public health is moving toward the goal of implementing evidence-based interventions. To accomplish this, there is a need to select, adapt, and evaluate intervention studies. Such selection relies, in part, on making judgments about the feasibility of possible interventions and determining whether comprehensive and multilevel evaluations are justified. There exist few published standards and guides to aid these judgments. This article describes the diverse types of feasibility studies conducted in the field of cancer prevention, using a group of recently funded grants from the National Cancer Institute. The grants were submitted in response to a request for applications proposing research to identify feasible interventions for increasing the utilization of the Cancer Information Service among underserved populations.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.amepre.2009.02.002

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

14 Own interpretation · 1 Sources not found · 1 No basis given

Show all 6 claims

  • Probably not a substantial claim. 8
  • It may state two separate claims as one. 2
10 of 10
  • The paper relies on this without support.

    Published standards and guides for judging feasibility and for designing and evaluating feasibility studies are lacking.

    “There exist few published standards and guides to aid these judgments.”
    “The published literature does not propose standards to guide the design and evaluation of feasibility studies.”
  • The paper relies on this without support.

    Feasibility studies are expected to yield findings that inform decisions about recommending an intervention for efficacy testing.

    “Feasibility studies are relied on to produce a set of findings that help determine whether an intervention should be recommended for efficacy testing.”
  • The paper relies on this without support.

    Feasibility studies help decide if an intervention merits further testing and if the underlying ideas and results can be made relevant and sustainable.

    “Feasibility studies are used to determine whether an intervention is appropriate for further testing; in other words, they enable researchers to assess whether or not the ideas and findings can be shaped to be relevant and sustainable.”
  • The authors state this as an assumption.

    Which design is best varies with the chosen focus, both in feasibility work and in other research.

    “The choice of an optimal research design depends upon the selected area of focus. This premise holds equally for feasibility studies and for other kinds of research.”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 15 references

Research works printed but not linked: 1

  1. Green, 1994, Study of participatory research in health promotion: review and recommendations for the development of participatory research in health promotion in Canada

Cited by

Sorted by citations

Items 1,501–1,600 of 3,693

Metadata

Authors
Bowen, D. J., Kreuter, M., Spring, B., Cofta-Woerpel, L., Linnan, L., Weiner, D., Bakken, S., Kaplan, C. P., Squiers, L., Fabrizio, C., & Fernandez, M.
Affiliations
  • Boston University (US)
  • Saint Louis University (US)
  • Northwestern University (US)
  • The University of Texas MD Anderson Cancer Center (US)
  • Mashantucket Pequot Tribal Nation (US)
  • University of California, San Francisco (US)
  • National Institutes of Health (US)
  • Yale Cancer Center (US)
Corresponding author
Bowen, Deborah J.
Venue
American Journal of Preventive Medicine
Publisher
Elsevier BV
Published
2009-05
Volume
36
Issue
5
Pages
452-457
ISSN
0749-3797 (ISSN-L)
OpenAlex
W2014261733
Cited by
4,021
References
15
Citations by year
2026: 471 · 2025: 483 · 2024: 482 · 2023: 467 · 2022: 409 · 2021: 370 · 2020: 332 · 2019: 255 · 2018: 231 · 2017: 180 · 2016: 120 · 2015: 97 · 2014: 70 · 2013: 21 · 2012: 17
FWCI
15.44
Type
journal article
Language
en
Open access
Locations
  • American Journal of Preventive Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
  • The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
  • UNC Libraries
Funders
  • National Institutes of Health (5r21ca126390-02, 5r21ca126373-02, 1r21ca126321-01, 7r21ca126326-03)
  • National Cancer Institute (R21-CA126326, R21 CA126321, 1R21CA126373-01, 1R21CA126321-01, R21 CA126390, R21CA126450, 1R21CA126390-01, R21CA126325, 1R21CA126326-01, R21 CA126373)
  • National Center for Research Resources (UL1RR025741)
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
  • Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
  • Social Sciences › Public Administration › Evaluation and Performance Assessment
Keywords
feasibility study, cancer prevention, evidence-based interventions, intervention selection, multi-level evaluation, cancer information services, underserved populations
MeSH terms
Feasibility Studies, Financing, Government, Humans, Medically Underserved Area, Neoplasms, Preventive Medicine, Public Health, Research Design, Research Support as Topic, United States, National Cancer Institute (U.S.)

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).

A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

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