Midlife women's symptom cluster heuristics: evaluation of an iPad application for data collection.
Midlife women's symptom cluster heuristics: evaluation of an iPad application for data collection.
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中年女性症状群启发法：对用于数据收集的 iPad 应用程序的评估。
DOI：
10.1097/gme.0000000000000429
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Macpherson,CatherineFiona
中科院分区：
文献类型：
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作者：
Woods,NancyFugate;Ismail,Rita;Linder,LauriA;Macpherson,CatherineFiona
目的：本研究旨在通过更年期计算机化症状捕获工具 (C-SCAT M) 识别中年女性对她们所经历的症状群的启发。方法：通过在校园和诊所张贴传单，招募经历与更年期相关症状的 40 至 60 岁女性。女性使用 iPad 完成了 C-SCAT M 应用程序 (app)，通过识别和绘制过去 24 小时内经历的症状群、表明症状之间的关系、对症状群和症状进行优先排序、进行因果归因以及识别恶化和改善因素。他们被要求对集群和每个集群中的症状进行优先排序。当女性完成该应用程序时，她们被要求“大声思考”自己使用该应用程序的体验。 C-SCAT M 应用程序生成的数据被安全地传输到 Amazon Web Services 帐户，并保存为屏幕图像和 Excel 文件，以保留从应用程序中获取的图形图像和文本。定性数据以逐字记录形式保存。使用常规内容分析来分析定性数据。结果：30 名女性完成了该应用程序。大多数女性（77%）表示，最终图表在描述她们的症状及其联系方面非常/极其准确。女性报告了 1 到 22 种症状（中位数为 11 种）。潮热、夜间醒来、盗汗和清晨醒来是最常见的症状。女性将潮热视为最令人烦恼的症状，其次是夜间醒来和疲劳。他们报告了症状之间的 300 多种不同的双变量关系和 150 多种独特的因果路径。他们认为潮热会引起多种症状，尤其是睡眠障碍，而且大多数症状都能描述其症状的时间顺序。女性报告了由 2 至 18 种症状组成的集群。女性还根据她们对症状的反应（“真的很烦人”）、发生时间（“夜间问题”）和集群中包含的症状（“潮热”）来命名每个集群。他们将这些症状归因于更年期、生活需求和其他症状等原因。女性使用的管理策略包括非处方制剂、睡眠、休息和其他生活方式的改变。一些女性要求获得最终症状聚类图的副本，以便与她们的医疗保健提供者讨论。 结论：使用 C-SCAT M 为女性提供了一个机会来描述她们的症状和聚类以及它们之间的关系，并提供有关她们启发法的叙述性数据。女性主动提出关于使用聚类图促进与医疗保健提供者对话（关于其症状）的评论，这表明修改 C-SCAT M 并评估其在医疗保健环境中的使用的潜在价值。
Objective:This study aims to elicit midlife women's heuristics about symptom clusters they were experiencing, as identified by the Computerized Symptom Capture Tool for Menopause (C-SCAT M).Methods:Women aged 40 to 60 years who were experiencing symptoms that they associated with menopause were recruited through flyers posted on campus and in clinics. Women completed the C-SCAT M application (app), using an iPad, by identifying and drawing symptom clusters they experienced during the last 24 hours, indicating relationships among symptoms, prioritizing the clusters and symptoms within them, making causal attributions, and identifying exacerbating and ameliorating factors. They were asked to prioritize the clusters and a symptom within each cluster. While women were completing the app, they were asked to “think aloud” about their experience using the app. Data generated from the C-SCAT M app were transmitted securely to an Amazon Web Services account and saved as screen images and Excel files to preserve both graphical images and text elicited from the app. Qualitative data were saved in verbatim phrases. Conventional content analysis was used to analyze qualitative data.Results:Thirty women completed the app. Most women (77%) stated that the final diagrams were very/extremely accurate in depicting their symptoms and their connections. Women reported between 1 and 22 symptoms (median, 11). Hot flashes, waking up during the night, night sweats, and early morning awakening were the most commonly reported symptoms. Women rated hot flashes as their most bothersome symptom, followed by waking up during the night and fatigue. They reported more than 300 different bivariate relationships between their symptoms and more than 150 unique causal paths. They believed that hot flashes caused several symptoms, especially sleep disruption, and most could describe the time order of their symptoms. Women reported clusters consisting of 2 to 18 symptoms. Women also named each cluster based on their response to their symptoms (“really annoying”), time of occurrence (“night problem”), and symptoms included in the cluster (“hot flash”). They attributed their clusters to menopause, life demands, and other symptoms, among other causes. Management strategies that women used included over-the-counter preparations, sleep, rest, and other lifestyle changes. Some women requested for a copy of their final symptom cluster diagram to discuss with their healthcare providers.Conclusions:Use of the C-SCAT M affords women an opportunity to depict their symptoms and clusters and the relationships between them and to provide narrative data about their heuristics. Women's unsolicited comments about using the cluster diagram to facilitate conversations (about their symptoms) with their healthcare providers suggest the potential value of modifying the C-SCAT M and evaluating its use in a healthcare setting.