Evidence map›Paper›PMID 36940412›Full record

ArticleTranslational behavioral medicine2023

Implementation planning for equitable tobacco treatment services: a mixed methods assessment of contextual facilitators and barriers in a large comprehensive cancer center.

Jennifer Tsui, Kylie Sloan, Rajiv Sheth, Esthelle Ewusi Boisvert, Jorge Nieva, Anthony W Kim, Raina D Pang, Steve Sussman, Matthew Kirkpatrick

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational behavioral medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

9 authors at 1 institution in 1 country.

Jennifer TsuiDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0002-5616-9636
Kylie SloanDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Rajiv ShethDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Esthelle Ewusi BoisvertDepartment of Psychology, University of Southern California, Los Angeles, CA, USA.
Jorge NievaNorris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
Anthony W KimNorris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
Raina D PangDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Steve SussmanDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Matthew KirkpatrickDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
University of Southern California · US

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
NCI NIH HHS P30 CA014089
6 · The paper itself

Abstract

Tobacco use among cancer patients is associated with an increased mortality and poorer outcomes, yet two-thirds of patients continue using following diagnosis, with disproportionately higher use among racial/ethnic minority and low socioeconomic status patients. Tobacco treatment services that are effectively tailored and adapted to population characteristics and multilevel context specific to settings serving diverse patients are needed to improve tobacco cessation among cancer patients. We examined tobacco use screening and implementation needs for tobacco treatment services to inform equitable and accessible delivery within a large comprehensive cancer center in the greater Los Angeles region. We conducted a multi-modal, mixed methods assessment using electronic medical records (EMR), and clinic stakeholder surveys and interviews (guided by the Consolidated Framework for Implementation Research). Approximately 45% of patients (n = 11,827 of 26,030 total) had missing tobacco use history in their EMR. Several demographic characteristics (gender, age, race/ethnicity, insurance) were associated with greater missing data prevalence. In surveys (n = 32), clinic stakeholders endorsed tobacco screening and cessation services, but indicated necessary improvements for screening/referral procedures. During interviews (n = 13), providers/staff reported tobacco screening was important, but level of priority differed as well as how often and who should screen. Several barriers were noted, including patients' language/cultural barriers, limited time during visits, lack of smoking cessation training, and insurance coverage. While stakeholders indicated high interest in tobacco use assessment and cessation services, EMR and interview data revealed opportunities to improve tobacco use screening across patient groups. Implementing sustainable system-level tobacco cessation programs at institutions requires leadership support, staff training, on routine screening, and intervention and referral strategies that meet patients' linguistic/cultural needs.

Indexed as

NeoplasmsSmoking CessationTobacco Use CessationEthnicityHumansMinority GroupsHealth equityImplementation planningMixed methodsTobacco cessation

Identifiers

PMID36940412
PMCPMC10848232
OpenAlexW4327912919

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.