Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning.
Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning.
复制标题
DOI：
10.1186/s12885-021-08438-8
复制
发表时间：
2021-06-27
期刊：
影响因子：
3.8
通讯作者：
Jung M
中科院分区：
文献类型：
--
作者：
Yang K;Kim J;Chun M;Ahn MS;Chon E;Park J;Jung M
根据患者报告的调查和医疗保健提供者的个人访谈，我们试图通过机器学习技术的文本分析来确定与癌症幸存者的痛苦和疲劳改善相关的重要因素，作为使用韩国癌症幸存中心试点项目的单一研究所数据的二次分析。对322名癌症幸存者的调查和深入访谈进行了分析，以确定他们的需求和关注点。在调查的关键词中，包括EQ-VAS、苦恼、疲劳、疼痛、失眠、焦虑和抑郁，苦恼和疲劳是重点。根据调查中使用的关键词，通过基于韩语的文本分析和机器学习技术对采访记录进行了分析。词被生成为向量，相似度得分通过与文本的关键字和频率相关的距离来计算。然后，根据相似度为每个关键词选择10个高排名的词，绘制网络图。大多数参与者是50岁以下的健康女性，患有乳腺癌，完成治疗不到6个月。作为1个月的随访调查结果，患者的痛苦和疲劳评分分别为56.5%和58.4%。对于痛苦的改善，消化不良（p = 0.006）和痛苦，疲劳，焦虑和抑郁的初始评分（分别为p < 0.001，< 0.001，0.043和0.013）显著相关。对于疲劳的改善，经济状况（p = 0.021），康复需求（p = 0.035），疲劳初始评分（p < 0.001），任何干预（p = 0.017）和参与家庭护理计划（p = 0.022）具有显著性。对于文本分析，压力和疲劳被放置在关键词网络图的中心，单词被错综复杂地连接起来。从回归分析结合调查分数和定量变量的文本分析，参与家庭护理计划和提到家庭相关的词与疲劳改善（p = 0.033）。在调查中，常见症状和实际问题与痛苦和疲劳有关。但通过文本分析，我们发现，诸如家庭问题等具体问题及其关系更为复杂。尽管进一步的研究需要探索癌症患者中隐藏的问题，但本研究使用访谈等个性化方法是有意义的。在线版本包含补充材料，可通过10.1186/s12885-021-08438-8获得。
From patient-reported surveys and individual interviews by health care providers, we attempted to identify the significant factors related to the improvement of distress and fatigue for cancer survivors by text analysis with machine learning techniques, as the secondary analysis using the single institute data from the Korean Cancer Survivorship Center Pilot Project. Surveys and in-depth interviews from 322 cancer survivors were analyzed to identify their needs and concerns. Among the keywords in the surveys, including EQ-VAS, distress, fatigue, pain, insomnia, anxiety, and depression, distress and fatigue were focused. The interview transcripts were analyzed via Korean-based text analysis with machine learning techniques, based on the keywords used in the survey. Words were generated as vectors and similarity scores were calculated by the distance related to the text’s keywords and frequency. The keywords and selected high-ranked ten words for each keyword based on the similarity were then taken to draw a network map. Most participants were otherwise healthy females younger than 50 years suffering breast cancer who completed treatment less than 6 months ago. As the 1-month follow-up survey’s results, the improved patients were 56.5 and 58.4% in distress and fatigue scores, respectively. For the improvement of distress, dyspepsia (p = 0.006) and initial scores of distress, fatigue, anxiety, and depression (p < 0.001, < 0.001, 0.043, and 0.013, respectively) were significantly related. For the improvement of fatigue, economic state (p = 0.021), needs for rehabilitation (p = 0.035), initial score of fatigue (p < 0.001), any intervention (p = 0.017), and participation in family care program (p = 0.022) were significant. For the text analysis, Stress and Fatigue were placed at the center of the keyword network map, and words were intricately connected. From the regression anlysis combined survey scores and the quantitative variables from the text analysis, participation in family care programs and mention of family-related words were associated with the fatigue improvement (p = 0.033). Common symptoms and practical issues were related to distress and fatigue in the survey. Through text analysis, however, we realized that the specific issues and their relationship such as family problem were more complicated. Although further research needs to explore the hidden problem in cancer patients, this study was meaningful to use personalized approach such as interviews. The online version contains supplementary material available at 10.1186/s12885-021-08438-8.
登录
查看更多内容
DOI：
10.1136/bmj.e70
发表时间：
2012-01-30
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Fong DY;Ho JW;Hui BP;Lee AM;Macfarlane DJ;Leung SS;Cerin E;Chan WY;Leung IP;Lam SH;Taylor AJ;Cheng KK
通讯作者：
Cheng KK
影响因子：
6.2
作者：
Minton, Ollie;Berger, Ann;Stone, Patrick C.
通讯作者：
Stone, Patrick C.
DOI：
10.1093/jnci/djy177
发表时间：
2018-12-01
期刊：
Journal of the National Cancer Institute
影响因子：
--
作者：
Carreira H;Williams R;Müller M;Harewood R;Stanway S;Bhaskaran K
通讯作者：
Bhaskaran K
影响因子：
5.9
作者：
Ebede, Chidinma C.;Jang, Yongchang;Escalante, Carmen P.
通讯作者：
Escalante, Carmen P.
DOI：
10.2190/eufn-rv1k-y3tr-fk0l
发表时间：
2006-01-01
影响因子：
2
作者：
Osborn, Robyn L.;Demoncada, Angelique C.;Feuerstein, Michael
通讯作者：
Feuerstein, Michael