Emotion sharing in remote patient monitoring of patients with chronic kidney disease

被引:8
|
作者
Huang, Robin [1 ]
Liu, Na [1 ]
Nicdao, Mary Ann [2 ]
Mikaheal, Mary [2 ]
Baldacchino, Tanya [2 ]
Albeos, Annabelle [2 ]
Petoumenos, Kathy [3 ]
Sud, Kamal [2 ,4 ,5 ]
Kim, Jinman [1 ]
机构
[1] Univ Sydney, Sch Comp Sci, J12, Camperdown, NSW 2006, Australia
[2] Blacktown Hosp, Reg Dialysis Ctr, Home Hemodialysis Unit, Sydney, NSW, Australia
[3] UNSW Sydney, Kirby Inst, Sydney, NSW, Australia
[4] Nepean Hosp, Dept Renal Med, Sydney, NSW, Australia
[5] Univ Sydney, Med Sch, Sydney, NSW, Australia
关键词
remote monitoring; emoticon sharing; sentiment analysis; mHealth; mobile health; data collection; STAGE RENAL-DISEASE; HOME HEMODIALYSIS; MANAGEMENT; SENTIMENT; INFORMATION; CARE; TECHNOLOGIES; TELEHEALTH; EMOTICONS; IMPROVE;
D O I
10.1093/jamia/ocz183
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective: To investigate the relationship between emotion sharing and technically troubled dialysis (TTD) in a remote patient monitoring (RPM) setting. Materials and Methods: A custom software system was developed for home hemodialysis patients to use in an RPM setting, with focus on emoticon sharing and sentiment analysis of patients' text data. We analyzed the outcome of emoticon and sentiment against TTD. Logistic regression was used to assess the relationship between patients' emotions (emoticon and sentiment) and TTD. Results: Usage data were collected from January 1, 2015 to June 1, 2018 from 156 patients that actively used the app system, with a total of 31 159 dialysis sessions recorded. Overall, 122 patients (78%) made use of the emoticon feature while 146 patients (94%) wrote at least 1 or more session notes for sentiment analysis. In total, 4087 (13%) sessions were classified as TTD. In the multivariate model, when compared to sessions with self-reported very happy emoticons, those with sad emoticons showed significantly higher associations to TTD (aOR 4.97; 95% CI 4.13-5.99; P = < .001). Similarly, negative sentiments also revealed significant associations to TTD (aOR 1.56; 95% CI 1.22-2; P=.003) when compared to positive sentiments. Discussion: The distribution of emoticons varied greatly when compared to sentiment analysis outcomes due to the differences in the design features. The emoticon feature was generally easier to understand and quicker to input while the sentiment analysis required patients to manually input their personal thoughts. Conclusion: Patients on home hemodialysis actively expressed their emotions during RPM. Negative emotions were found to have significant associations with TTD. The use of emoticons and sentimental analysis may be used as a predictive indicator for prolonged TTD.
引用
收藏
页码:185 / 193
页数:9
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