Letter to the Editor in response to Greidanus et al., June 2020, “The Successful Return-To-Work Questionnaire for Cancer Survivors (I-RTW_CS): Development, Validity and Reproducibility”
Letter to the Editor in response to Greidanus et al., June 2020, “The Successful Return-To-Work Questionnaire for Cancer Survivors (I-RTW_CS): Development, Validity and Reproducibility”
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致编辑回复 Greidanus 等人的信，2020 年 6 月，“癌症幸存者成功重返工作岗位问卷 (I-RTW_CS)：开发、有效性和可重复性”
DOI：
10.1007/s40271-020-00470-3
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Ogata Ayako
中科院分区：
文献类型：
--
作者：
Kobayashi Masamitsu;Kako Jun;Kajiwara Kohei;Ogata Ayako
我们饶有兴趣地阅读了Greidanus等人撰写的题为“癌症幸存者成功重返工作岗位问卷（I-RTW_CS）：开发、有效性和可重复性”的论文。[1]的文件。作者开发了一种反映就业癌症幸存者观点的重返工作（RTW）结果指标，包括可能受雇主影响的项目，并评估了其结构效度和可重复性。最近这篇文章的作者描述说，现有RTW评估中使用的“就业状况”标准不足以全面客观地评估患者及其雇主的准备和经验。除了Greidanus等人在引言中描述的工具外，许多先前的研究还测量了次要结局，如生活质量、心理困扰、认知功能和疾病以及满意度[2-4]。此外，应用稍微更广泛的概念，开发了社会困难清单（SDI）来衡量癌症患者的社会影响，如先前研究所述[5，6]。我们支持作者的工作，并同意I-RTW_CS将是衡量RTW结果的有用工具;然而，我们想强调一些关于该研究的额外讨论点。作者使用焦点小组访谈和德尔菲设计来开发I-RTW_CS。招募癌症幸存者作为本研究的研究参与者。招募癌症幸存者作为研究对象可能对以患者为中心的护理非常有益。然而，从焦点小组访谈和德尔菲中提取的所有项目都来自参与的癌症幸存者;因此，所包含的项目可能取决于参与患者的背景。我们认为，如果RTW专家被纳入研究人群，结果会更有用。此外，目标人群的背景可能存在偏见，包括教育水平。我们认为教育水平是一个重要因素，因为以前的研究报告说，这些特征影响RTW [7]。此外，以前的研究报告说，症状的严重程度，癌症类型，预期寿命和工作类型是影响癌症存活者RTW的因素[7-9]。因此，如果在选择目标人群时考虑这些项目，则可能招募更多同等质量的受试者。焦点小组访谈有14名参与者，考虑到参与者背景的异质性，增加研究人群的数量可能会更好。或者，由于目标人口的质量相同，选择参与者的更严格标准可能会产生丰富的数据。
We read with great interest the paper titled “The Suc‑cessful Return‑To‑Work Questionnaire for Cancer Survi‑vors (I‑RTW_CS): Development, Validity and Reproduc‑ibility,” by Greidanus et al.[1]. The authors developed a return‑to‑work (RTW) outcome measure that reflects employed cancer survivors’ perspectives, including items that could be influenced by an employer, and assessed its construct validity and reproducibility. The authors of the recent article describe that the criteria around “employment status” used in existing RTW instru‑ments are not sufficient to fully and objectively evaluate the readiness and experience of patients and their employers. In addition to the instruments described in the Greidanus et al. in their introduction, many previous studies have measured secondary outcomes such as quality of life, psychological distress, cognitive functioning and illness, and satisfaction [2–4]. Also, applying a slightly broader concept, the Social Difficulties Inventory (SDI) was developed to measure the social impacts of cancer in cancer patients, as described in previous studies [5, 6]. We support the work of the authors and agree that the I‑RTW_CS will be a useful tool for meas‑uring RTW outcomes; however, we would like to highlight some additional points of discussion regarding the study. The authors used focus group interviews and a Delphi design to develop the I‑RTW_CS. Cancer survivors were recruited as study participants for this study. Recruiting can‑cer survivors as research subjects may be very beneficial for patient‑centered care. However, all items extracted from the focus group interviews and Delphi are from the cancer survi‑vors who participated; thus, the items included may depend on the participating patients’ backgrounds. We believe that the results would have been more useful if RTW experts had been included in the study population. Also, there may have been biases in the background of the target popula‑tion, including level of education. We consider the level of education to be an important factor, as previous studies have reported that these characteristics affect RTW [7]. Additionally, previous studies have reported that the severity of symptoms, type of cancer, life expectancy, and type of work are factors that influence RTW in cancer sur‑vivors [7–9]. Therefore, it may be possible to recruit more equal‑quality subjects if these items can be considered in the selection of the target population. There were 14 participants in the focus group interviews, and given the heterogeneity of the participants’ backgrounds, it might have been better to increase the number of the study population. Alternatively, stricter criteria for the selection of participants could have yielded rich data because of the equal quality of the target population.
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