Does Messaging for Reducing Breast Cancer Overscreening in Older Women Have Differential Responses among Medical Minimizers and Maximizers?

BackgroundMessaging strategies hold promise to reduce breast cancer overscreening. However, it is not known whether they may have differential effects among medical maximizers who prefer to take action about their health versus medical minimizers who prefer to wait and see.MethodsIn a randomized controlled survey experiment that included 2 sequential surveys with 3,041 women aged 65+ y from a US population-based online panel, we randomized participants to 1) no messages, 2) single exposure to a screening cessation message, or 3) 2 exposures over time to the screening cessation message. We assessed support for stopping screening in a hypothetical patient and intention to stop screening oneself on 7-point scales, where higher values indicated stronger support and intentions to stop screening. We conducted stratified analyses by medical-maximizing preference and moderation analysis.ResultsOf the women, 40.7% (<i>n</i> = 1,238) were medical maximizers; they had lower support and intention for screening cessation in all groups compared with the medical minimizers. Two message exposures increased support for screening cessation among medical maximizers, with a mean score of 3.68 (95% confidence interval [CI] 3.51-3.85) compared with no message (mean score 2.20, 95% CI 2.00-2.39, <i>P</i> < 0.001). A similar pattern was seen for screening intention. Linear regression models showed no differential messaging effect by medical-maximizing preference.ConclusionsMedical maximizers, although less likely to support screening cessation, were nonetheless responsive to messaging strategies designed to reduce breast cancer overscreening.HighlightsIt is not known if a message on rationales for stopping breast cancer screening would have differential effects among medical maximizers who prefer to take action when it comes to their health versus medical minimizers who prefer to wait and see.In a 2-wave randomized controlled survey experiment with 3,041 older women, we found that medical maximizers, although less likely to support screening cessation compared with medical minimizers, were nonetheless responsive to the messaging intervention, and the magnitude of the intervention effect was similar between maximizers and minimizers.Medical maximizers reported higher levels of worry and annoyance after reading the message compared with the minimizers, but the absolute levels of worry and annoyance were low.Our findings suggest that messaging can be a useful tool for reducing overscreening even in a highly reluctant population.

Authors

Institutions

Publication Details

Journal
Medical Decision Making
Published
2025-09-29
DOI
https://doi.org/10.1177/0272989x251377458
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Does Messaging for Reducing Breast Cancer Overscreening in Older Women Have Differential Responses among Medical Minimizers and Maximizers?

Qian‐Li Xue, Craig Evan Pollack, Cynthia M. Boyd, Yaldah Mohammad Nader et al.
Medical Decision Making
Global Cancer Incidence and Screening
article

Does Messaging for Reducing Breast Cancer Overscreening in Older Women Have Differential Responses among Medical Minimizers and Maximizers?

Qian‐Li Xue, Craig Evan Pollack, Cynthia M. Boyd, Yaldah Mohammad Nader, Rebekah H. Nagler, Mara A. Schonberg, Sarah E. Gollust, Nancy L. Schoenborn
article en

Abstract

BackgroundMessaging strategies hold promise to reduce breast cancer overscreening. However, it is not known whether they may have differential effects among medical maximizers who prefer to take action about their health versus medical minimizers who prefer to wait and see.MethodsIn a randomized controlled survey experiment that included 2 sequential surveys with 3,041 women aged 65+ y from a US population-based online panel, we randomized participants to 1) no messages, 2) single exposure to a screening cessation message, or 3) 2 exposures over time to the screening cessation message. We assessed support for stopping screening in a hypothetical patient and intention to stop screening oneself on 7-point scales, where higher values indicated stronger support and intentions to stop screening. We conducted stratified analyses by medical-maximizing preference and moderation analysis.ResultsOf the women, 40.7% (<i>n</i> = 1,238) were medical maximizers; they had lower support and intention for screening cessation in all groups compared with the medical minimizers. Two message exposures increased support for screening cessation among medical maximizers, with a mean score of 3.68 (95% confidence interval [CI] 3.51-3.85) compared with no message (mean score 2.20, 95% CI 2.00-2.39, <i>P</i> < 0.001). A similar pattern was seen for screening intention. Linear regression models showed no differential messaging effect by medical-maximizing preference.ConclusionsMedical maximizers, although less likely to support screening cessation, were nonetheless responsive to messaging strategies designed to reduce breast cancer overscreening.HighlightsIt is not known if a message on rationales for stopping breast cancer screening would have differential effects among medical maximizers who prefer to take action when it comes to their health versus medical minimizers who prefer to wait and see.In a 2-wave randomized controlled survey experiment with 3,041 older women, we found that medical maximizers, although less likely to support screening cessation compared with medical minimizers, were nonetheless responsive to the messaging intervention, and the magnitude of the intervention effect was similar between maximizers and minimizers.Medical maximizers reported higher levels of worry and annoyance after reading the message compared with the minimizers, but the absolute levels of worry and annoyance were low.Our findings suggest that messaging can be a useful tool for reducing overscreening even in a highly reluctant population.

Medical Decision MakingVol. 46(1)
University of Minnesota (US), Beth Israel Deaconess Medical Center (US), Johns Hopkins University (US), Johns Hopkins Medicine (US), Minnesota Department of Health (US)
Openalex Percentile: Top 64%
Global Cancer Incidence and Screening
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.