Evidence map›Paper›PMID 37707597›Full record

ArticleJNCI cancer spectrum2023

Advancing the science of integrating multiple interventions by blending and bundling.

Aubrey Villalobos, David A Chambers

Abstract read
In one paragraph

Article in JNCI cancer spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. The Effectiveness ofCancers · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. 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.

Aubrey VillalobosDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.ORCID 0000-0002-3588-2678
David A ChambersDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer prevention and control research has produced a variety of effective interventions over the years, though most are single disease focused. To meet the Cancer Moonshot goal to reduce the cancer death rate by 50% by 2047, it may be necessary to overcome the limitations of siloed interventions that do not meet people's multiple needs and limitations in system capacity to deliver the increasing number of interventions in parallel. In this article, we propose integrating multiple evidence-based interventions as a potential solution. We define 2 types of integrated interventions, blended and bundled, and provide examples to illustrate each. We then offer a schematic and outline considerations for how to assemble blended or bundled interventions including looking at the intervention need or opportunity along the cancer continuum as well as co-occurring behaviors or motivations. We also discuss delivery workflow integration considerations including social-ecological level(s), context or setting, implementer, and intended beneficiary. Finally, in assembling integrated interventions, we encourage consideration of practice-based expertise and community and/or patient input. After assembly, we share thoughts related to implementation and evaluation of blended or bundled interventions. To conclude the article, we present multiple research opportunities in this space. With swift progress on these research directions, cancer prevention and control interventionists and implementation scientists can contribute to achieving the promise of the reignited Cancer Moonshot.

Indexed as

MotivationNeoplasmsHumans

Identifiers

PMID37707597
PMCPMC10587993

What OpenQuestion holds

Textmetadata
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.