Beenhakker Lian, Wijlens Kim A E, Bode Christina, Vollenbroek-Hutten Miriam M R, Siesling Sabine, van Til Janine A, Witteveen Annemieke
Department of Biomedical Signals and Systems, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
Department of Psychology, Health and Technology, University of Twente, Enschede, The Netherlands.
MDM Policy Pract. 2025 Jan 13;10(1):23814683241309676. doi: 10.1177/23814683241309676. eCollection 2025 Jan-Jun.
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. 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. 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 highest. Next to , and 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%. 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. 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.
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.
许多乳腺癌幸存者经历过癌症相关疲劳（CRF），并且有几种治疗CRF的干预措施。根据患者偏好量身定制干预建议是一种方法。在本研究中，我们探讨了属性间偏好和属性内偏好的异质性。此外，我们提出了简单的决策规则，以使偏好与干预措施相匹配。九个属性被纳入，其水平被二分。参与者为每个属性选择他们偏好的水平，并使用最佳-最差尺度对属性进行排序。确定了属性间和属性内的偏好及其异质性。使用决策规则，计算了一种假设干预措施的匹配分数。67名乳腺癌幸存者完成了调查。他们的平均年龄为52岁，诊断后4.5年，在身体、心理和情感三个维度上经历CRF（6.5 - 7.2/10），43%的人已经在接受CRF干预。总体而言，参与者将[具体内容未给出]排在最高位。其次，[具体内容未给出]和[具体内容未给出]也经常排在首位。只有13名参与者（19%）具有最常见的偏好模式，即干预时间较短、每日进行、每次会话时间较短、采用心理社会干预、不匿名以及与治疗师和同伴接触。与总体属性内偏好相对应的具有特定属性的假设干预措施的匹配分数在44%至100%之间变化。研究表明乳腺癌幸存者对CRF干预属性的偏好存在很大异质性。使用简单的决策规则，证明了这种异质性对将偏好与具有匹配分数的干预措施相联系的影响。由于偏好异质性，干预建议的个性化是必要的。量身定制的建议可以使患者更多地参与决策、提高干预依从性和满意度，进而可能提高乳腺癌后的生活质量。
许多乳腺癌幸存者经历癌症相关疲劳，对此有多种干预措施。我们的结果显示乳腺癌患者对电子健康干预属性的偏好存在很大异质性。基于这种偏好异质性，乳腺癌后癌症相关疲劳的干预建议可以个性化，最终改善乳腺癌后的生活质量。
