Evidence map›Paper›PMID 40961384›Full record

ArticleJMIR formative research2025

Previsit Preparation for Shared Decision-Making in Lung Cancer Screening in Primary Care Using a Paper Decision Aid and an Automated Text Messaging Program: Quasi-Experimental Pilot Study.

Mayuko Ito Fukunaga, Renda Soylemez Wiener, Shaun Toomey, Joann Wagner, Qiming Shi, Kavitha Balakrishnan, Alexandra Nguyen, Dan Nguyen, M Diane McKee, Alexander A Bankier and 5 more

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Mayuko Ito FukunagaDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0003-4325-3959
Renda Soylemez WienerCenter for Health Optimization and Implementation Research, VA Boston Healthcare System, Boston, MA, United States.ORCID 0000-0001-7712-2135
Shaun ToomeyDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0009-0002-5854-3684
Joann WagnerDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0009-0009-3906-2798
Qiming ShiCenter for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0001-5829-4345
Kavitha BalakrishnanDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0009-0005-8170-5604
Alexandra NguyenDepartment of Obstetrics and Gynecology, University of Arizona, Tucson, AZ, United States.ORCID 0009-0007-3195-2759
Dan NguyenUniversity of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0009-0002-0661-0574
M Diane McKeeDepartment of Family Medicine and Community Health, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0002-1228-718X
Alexander A BankierDepartment of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0009-0006-1113-7821
Rajani S SadasivamDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0001-8406-6207
Sybil L CrawfordTan Chingfen Graduate School of Nursing, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0001-6621-0439
Paul Kj HanCenter for Outcomes Research and Evaluation, Maine Medical Center, Portland, ME, United States.ORCID 0000-0003-0165-1940
Thomas K HoustonDepartment of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States.ORCID 0000-0002-2909-4018
Kathleen M MazorDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0002-9491-9872

Funding

University of Massachusetts Center for Clinical Science and Translational SupplementUL1TR001453 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2015 to 2024
$39.0M
K12 Cardiopulmonary Implementation Science Scholars ProgramK12HL138049 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LEMON, STEPHENIE C., LINDENAUER, PETER KYLE · 2017 to 2021
$2.7M
Facilitation of Information Exchange for Shared Decision Making for Lung Cancer ScreeningK08CA283304 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Mayuko Ito Fukunaga · 2023 to 2026
$995k
NCATS NIH HHS UL1 TR001453NCI NIH HHS K08 CA283304NHLBI NIH HHS K12 HL138049
6 · The paper itself

Abstract

Background: Patient-provider discussions and shared decision-making (SDM) are essential for tailoring lung cancer screening (LCS) decisions to individual patients. However, the implementation of SDM in primary care settings is challenging. Innovative approaches are needed to reach and prepare patients eligible for LCS for SDM in primary care settings and increase LCS uptake. Objective: We piloted previsit preparation comparing 2 strategies: a paper decision aid (DA; DA group) and an enhanced comparator strategy consisting of the paper DA plus an automated text message program (DA+TM group) designed to promote patient-provider LCS discussions. We explored feasibility and gathered preliminary data on its potential effects on LCS discussions, decision-making, and LCS uptake in primary care settings. Methods: In a sequential quasi-experimental pilot study, we recruited patients who were eligible for LCS in a single academic health care system. Prior to an upcoming visit, participants in both groups received a paper-based DA by mail. In the DA+TM group, participants also received a series of automated text messages to help them prepare for their LCS discussions. We monitored participant recruitment and retention, as well as patient engagement in DA and text messages. In exploratory analyses, we assessed patient-provider discussion of LCS, SDM, patient knowledge, decision conflict at baseline and in follow-up telephone surveys, and LCS completion measured by electronic health records. Results: We enrolled and included 48 participants (DA group=19 and DA+TM group=29) in the final analysis. Participants were predominantly White, with a median age of 61.0 (IQR, 57.0-65.0), and 58% (28/48) of them were female. Engagement was high in both groups. LCS knowledge significantly improved in the DA+TM group (4.5 baseline vs 6.0 follow-up; P=.003), while there was no change in the DA group (5.0 baseline vs 5.0 follow-up, P=.23). Median LCS knowledge change from baseline to follow-up was 0.5 (IQR -1.0 to 2.5) in the DA group and 1.5 (IQR 0-3.0) in the DA+TM group (P=.24). Decision conflict in both groups significantly decreased (DA group: 37.5 baseline vs 0 follow-up, P<.001; DA+TM group: 50.0 baseline vs 20.0 follow-up, P=.003). The median SDM process score (a measure of SDM) was 3.0 (IQR 1.5-4.0) in the DA group and 2.0 (IQR 1.0-3.0) in the DA+TM group (P=.11). The LCS completion rates were 5% (1/19) in the DA group and 31% (9/29) in the DA+TM group at 3 months (P=.07), and 26% (5/19) in the DA group and 34% (10/29) in the DA+TM group at 6 months (P=.75). Conclusions: Previsit preparation was feasible in primary care settings. An enhanced, text message-based strategy has the potential to reach and engage broader LCS-eligible populations and prepare patients for LCS discussions with their primary care providers, which may ultimately improve informed decision-making and LCS uptake.

Indexed as

Decision Making, SharedDecision Support TechniquesEarly Detection of CancerLung NeoplasmsText MessagingAgedFemaleHumansMaleMiddle AgedPatient ParticipationPilot ProjectsPrimary Health Carecancer screeningdecision-making, sharedhealthlung cancertelemedicinetext messaging

Identifiers

PMID40961384
PMCPMC12443356

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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.