Evidence map›Paper›PMID 28559408›Full record

ArticleThe oncologist2017

Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators.

Christine M Gunn, Victoria A Parker, Sharon M Bak, Naomi Ko, Kerrie P Nelson, Tracy A Battaglia

Open access · bronzeAbstract read
In one paragraph

Article in The oncologist, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Experiences of caring for women with cervical cancer: A qualitative study among male partners in Dar es Salaam, Tanzania.Health expectations : an international journal of public participation in health care and health policy · 2024
    Article
  3. Article
  4. Exploring the social stressors and resources of husbands of women diagnosed with advanced breast cancer in their role as primary caregivers in Kumasi, Ghana.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  5. Article
  6. 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

6 authors at 2 institutions in 1 country.

Christine M GunnEvans Department of Medicine, Women's Health Unit, Boston University School of Medicine, Boston, Massachusetts, USA cgunn@bu.edu.
Victoria A ParkerDepartment of Health Law, Policy and Management, Boston University School of Public Health, Boston, Massachusetts, USA.
Sharon M BakWomen's Health Unit Section of General Internal Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, USA.
Naomi KoDepartment of Hematology and Oncology, Boston Medical Center, Boston, Massachusetts, USA.
Kerrie P NelsonDepartment of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.
Tracy A BattagliaDepartment of Hematology and Oncology, Boston Medical Center, Boston, Massachusetts, USA.
Boston University · USBoston Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMinority women in the U.S. continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models like patient navigation focus on social barriers, but evidence demonstrating how these models increase social capital is lacking. This pilot study describes the social networks of newly diagnosed breast cancer patients and explores the contributing role of patient navigators. MATERIALS AND

methodsTwenty-five women completed a one hour interview about their social networks related to cancer care support. Network metrics identified important structural attributes and influential individuals. Bivariate associations between network metrics, type of network, and whether the network included a navigator were measured. Secondary analyses explored associations between network structures and clinical outcomes.

resultsWe identified three types of networks: kin-based, role and/or affect-based, or heterogeneous. Network metrics did not vary significantly by network type. There was a low prevalence of navigators included in the support networks (25%). Network density scores were significantly higher in those networks without a navigator. Network metrics were not predictive of clinical outcomes in multivariate models.

conclusionPatient navigators were not frequently included in support networks, but provided distinctive types of support. If navigators can identify patients with poorly integrated (less dense) social networks, or who have unmet tangible support needs, the intensity of navigation services could be tailored. Services and systems that address gaps and variations in patient social networks should be explored for their potential to reduce cancer health disparities. IMPLICATIONS FOR PRACTICE: This study used a new method to identify the breadth and strength of social support following a diagnosis of breast cancer, especially examining the role of patient navigators in providing support. While navigators were only included in one quarter of patient support networks, they did provide essential supports to some individuals. Health care providers and systems need to better understand the contributions of social supports both within and outside of health care to design and tailor interventions that seek to reduce health care disparities and improve cancer outcomes.

Indexed as

Healthcare DisparitiesPatient NavigationBreast NeoplasmsFemaleHumansMinority GroupsPilot ProjectsQualitative ResearchSocial SupportUnited StatesBreast cancerCancer health disparitiesPatient navigationSocial networksSocial support

Identifiers

PMID28559408
PMCPMC5553958
OpenAlexW2617971940

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.