将自然语言处理和情感分析方法应用于老年人干预：对健康与技术的积极认知
Adapting natural language processing and sentiment analysis methods for an intervention in older adults: Positive perceptions of health and technology.
作者信息
Petersen Curtis L, Li Xingyi, Stevens Courtney J, Gooding Tyler L, Carpenter-Song Elizabeth A, Batsis John A
机构信息
The Dartmouth Institute for Health Policy, Dartmouth College, Hanover, NH, USA.
Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH, USA.
出版信息
Gerontechnology. 2023 Mar 17;22(1). doi: 10.4017/gt.2023.22.1.824.06.
BACKGROUND
Older adults frequently participate in behavior change studies, yet it is not clear how to quantify a potential relationship between their perception of the intervention and its efficacy.
RESEARCH AIM
We assessed the relationship between participant sentiment toward the intervention from follow-up interviews with physical activity and questionnaires for the perception of health.
METHODS
Sentiment was calculated using the transcripts of exit interviews through a bag of words approach defined as the sum of positive and negative words in 28 older adults with obesity (body mass index ≥30kg/m).
RESULTS
Mean age was 73 years (82% female), and 54% lost ≥5% weight loss. Through linear regression we describe a significant association between positive sentiment about the intervention and weight loss; positive sentiment on technology and change in PROMIS-10 physical health and reduced physical activity time, while controlling for sex and age.
CONCLUSIONS
This analysis demonstrates that sentiment analysis and natural language processing in program review identified an association between perception and topics with clinical outcomes.
背景
老年人经常参与行为改变研究，但尚不清楚如何量化他们对干预措施的认知与其效果之间的潜在关系。
研究目的
我们通过对体育活动的随访访谈记录以及健康认知问卷，评估了参与者对干预措施的看法之间的关系。
方法
通过词袋法，利用退出访谈的文字记录计算情感得分，该方法定义为28名肥胖老年人（体重指数≥30kg/m）中积极词汇和消极词汇的总和。
结果
平均年龄为73岁（82%为女性），54%的人体重减轻了≥5%。通过线性回归，我们描述了对干预措施的积极看法与体重减轻之间的显著关联；在控制性别和年龄的同时，对技术的积极看法以及PROMIS-10身体健康状况的变化和体育活动时间的减少。
结论
该分析表明，项目评估中的情感分析和自然语言处理确定了认知与临床结果主题之间的关联。
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