Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue

Introduction. Many breast cancer survivors experience cancer-related fatigue (CRF), and several interventions to treat CRF are available. One way to tailor intervention advice is based on patient preferences. In this study, we explore preference heterogeneity regarding between-attribute and within-a...

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Main Authors: Lian Beenhakker, Kim A. E. Wijlens, Christina Bode, Miriam M. R. Vollenbroek-Hutten, Sabine Siesling, Janine A. van Til, Annemieke Witteveen
Format: Article
Language:English
Published: SAGE Publishing 2025-01-01
Series:MDM Policy & Practice
Online Access:https://doi.org/10.1177/23814683241309676
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author Lian Beenhakker
Kim A. E. Wijlens
Christina Bode
Miriam M. R. Vollenbroek-Hutten
Sabine Siesling
Janine A. van Til
Annemieke Witteveen
author_facet Lian Beenhakker
Kim A. E. Wijlens
Christina Bode
Miriam M. R. Vollenbroek-Hutten
Sabine Siesling
Janine A. van Til
Annemieke Witteveen
author_sort Lian Beenhakker
collection DOAJ
description Introduction. Many breast cancer survivors experience cancer-related fatigue (CRF), and several interventions to treat CRF are available. One way to tailor intervention advice is based on patient preferences. In this study, we explore preference heterogeneity regarding between-attribute and within-attribute preferences. In addition, we propose simple decision rules to match preferences to interventions. Methods. Nine attributes were included with dichotomized levels. Participants selected their preferred level per attribute and ranked the attributes using best-worst scaling. Between-attribute and within-attribute preferences were determined, together with their heterogeneity. Using decision rules, matching scores were calculated for a hypothetical intervention. Results. Sixty-seven breast cancer survivors completed the survey. They were on average 52 y old, 4.5 y after diagnosis, experienced CRF (6.5–7.2/10) on 3 dimensions (physical, mental, and emotional), and 43% already followed an intervention for CRF. Overall, participants ranked costs highest. Next to costs , proven effectiveness and type of intervention were also frequently ranked first. Only 13 participants (19%) shared the most common preference pattern of shorter interventions, daily sessions, shorter session time, a psychosocial intervention, no anonymity, and contact with a therapist and peers. Matching scores for a hypothetical intervention with attributes corresponding with the overall within-attribute preferences varied from 44% to 100%. Conclusion. A large heterogeneity in preferences of breast cancer survivors for CRF intervention attributes was demonstrated. Using simple decision rules, the effect of this heterogeneity on linking preferences to interventions with matching scores was demonstrated. Implications. Personalization of intervention advice is necessary due to preference heterogeneity. Tailored advice can result in higher involvement of patients in decision making, intervention adherence and satisfaction, and subsequently a potential higher quality of life after breast cancer. Highlights Many breast cancer survivors experience cancer-related fatigue for which many interventions exist. Our results show large preference heterogeneity in breast cancer patients’ preferences for attributes of eHealth interventions. Based on this preference heterogeneity, intervention advice for cancer-related fatigue after breast cancer can be personalized, ultimately improving quality of life after breast cancer.
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spelling doaj-art-e521fe4c689c49e7b926bdfa100d203e2025-01-13T12:03:19ZengSAGE PublishingMDM Policy & Practice2381-46832025-01-011010.1177/23814683241309676Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related FatigueLian BeenhakkerKim A. E. WijlensChristina BodeMiriam M. R. Vollenbroek-HuttenSabine SieslingJanine A. van TilAnnemieke WitteveenIntroduction. Many breast cancer survivors experience cancer-related fatigue (CRF), and several interventions to treat CRF are available. One way to tailor intervention advice is based on patient preferences. In this study, we explore preference heterogeneity regarding between-attribute and within-attribute preferences. In addition, we propose simple decision rules to match preferences to interventions. Methods. Nine attributes were included with dichotomized levels. Participants selected their preferred level per attribute and ranked the attributes using best-worst scaling. Between-attribute and within-attribute preferences were determined, together with their heterogeneity. Using decision rules, matching scores were calculated for a hypothetical intervention. Results. Sixty-seven breast cancer survivors completed the survey. They were on average 52 y old, 4.5 y after diagnosis, experienced CRF (6.5–7.2/10) on 3 dimensions (physical, mental, and emotional), and 43% already followed an intervention for CRF. Overall, participants ranked costs highest. Next to costs , proven effectiveness and type of intervention were also frequently ranked first. Only 13 participants (19%) shared the most common preference pattern of shorter interventions, daily sessions, shorter session time, a psychosocial intervention, no anonymity, and contact with a therapist and peers. Matching scores for a hypothetical intervention with attributes corresponding with the overall within-attribute preferences varied from 44% to 100%. Conclusion. A large heterogeneity in preferences of breast cancer survivors for CRF intervention attributes was demonstrated. Using simple decision rules, the effect of this heterogeneity on linking preferences to interventions with matching scores was demonstrated. Implications. Personalization of intervention advice is necessary due to preference heterogeneity. Tailored advice can result in higher involvement of patients in decision making, intervention adherence and satisfaction, and subsequently a potential higher quality of life after breast cancer. Highlights Many breast cancer survivors experience cancer-related fatigue for which many interventions exist. Our results show large preference heterogeneity in breast cancer patients’ preferences for attributes of eHealth interventions. Based on this preference heterogeneity, intervention advice for cancer-related fatigue after breast cancer can be personalized, ultimately improving quality of life after breast cancer.https://doi.org/10.1177/23814683241309676
spellingShingle Lian Beenhakker
Kim A. E. Wijlens
Christina Bode
Miriam M. R. Vollenbroek-Hutten
Sabine Siesling
Janine A. van Til
Annemieke Witteveen
Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
MDM Policy & Practice
title Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
title_full Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
title_fullStr Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
title_full_unstemmed Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
title_short Working toward Personalized Intervention Advice: A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
title_sort working toward personalized intervention advice a survey study on preference heterogeneity in patients with breast cancer related fatigue
url https://doi.org/10.1177/23814683241309676
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