Evidence map›Paper›PMID 30016520›Full record

ReviewTranslational behavioral medicine2018

A conceptual model of social networks and mechanisms of cancer mortality, and potential strategies to improve survival.

Candyce H Kroenke

Abstract readReview
In one paragraph

Review in Translational behavioral medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Neighborhood Collective Efficacy: A Longitudinal Social Determinant of Access to Medical Care Among Recently Immigrated Latina Young Adults.Hispanic health care international : the official journal of the National Association of Hispanic Nurses · 2024
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  19. The Integration of Value Assessment and Social Network Methods for Breast Health Navigation Among African Americans.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2023
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Candyce H KroenkeDivision of Research, Kaiser Permanente Northern California, Oakland, CA, USA.

Funding

Social networks, breast cancer treatment, and survivalK07CA187403 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI KROENKE, CANDYCE H · 2015 to 2019
$914k
NCI NIH HHS K07 CA187403
6 · The paper itself

Abstract

Women with larger personal social networks have better breast cancer survival and a lower risk of mortality. However, little work has examined the mechanisms through which social networks influence breast cancer outcomes and cancer outcomes more generally, potentially limiting the development of feasible, clinically effective interventions. In fact, much of the emphasis in cancer research regarding the influence of social relationships on cancer outcomes has focused on the benefits of the provision of social support to patients, especially through peer support groups, and only more recently through patient navigation. Though critically important, there are other ways through which social relationships might influence outcomes, around which interventions might be developed. In addition to social support, these include social resources, social norms, social contagion, social roles, and social burdens and obligations. This narrative review addresses how social networks may influence cancer outcomes and discusses potential strategies for improving outcomes given these relationships. The paper (a) describes background and limitations of previous research, (b) outlines terms and provides a conceptual model that describes interrelationships between social networks and relevant variables and their hypothesized influence on cancer outcomes, (c) clarifies social and psychosocial mechanisms through which social networks affect downstream factors, (d) describes downstream behavioral, treatment, and physiological factors through which these subsequently influence recurrence and mortality, and (e) describes needed research and potential opportunities to enhance translation. Though most literature in this area pertains to breast cancer, this review has substantial relevance for cancer outcomes generally. Further clarification and research regarding potential mechanisms are needed to translate epidemiological findings on social networks into clinical and community strategies to improve cancer outcomes.

Indexed as

Models, TheoreticalSocial NetworkingHumansNeoplasmsSocial Support

Identifiers

PMID30016520
PMCPMC6065533

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.