Open AccessPrevious dropout from diabetic care as a predictor of patients' willingness to use mobile applications for self‐management: A cross‐sectional study
Author(s) -
Yamaguchi Satoko,
Waki Kayo,
Tomizawa Nobuko,
Waki Hironori,
Nannya Yasuhito,
Nangaku Masaomi,
Kadowaki Takashi,
Ohe Kazuhiko
Publication year - 2017
Publication title -
journal of diabetes investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.089
H-Index - 50
eISSN - 2040-1124
pISSN - 2040-1116
DOI - 10.1111/jdi.12613
Subject(s) - medicine , mhealth , glycemic , odds ratio , logistic regression , dropout (neural networks) , multivariate analysis , type 2 diabetes , odds , diabetes mellitus , medical record , cross sectional study , diabetes management , confounding , family medicine , psychological intervention , nursing , endocrinology , pathology , machine learning , computer science
Abstract Aims/Introduction Preventing dropout is crucial in managing diabetes. Accordingly, we investigated whether patients who had dropped out of diabetic care are suitable candidates for the use of mobile technologies – such as smartphone applications – to support self‐management ( mH ealth), which might help prevent dropout. Materials and Methods We carried out a cross‐sectional study in Tokyo, Japan. Patients aged 20 years or older who were clinically diagnosed as diabetic and who regularly visited the outpatient unit at the University of Tokyo Hospital were recruited between August 2014 and March 2015. Data were collected through face‐to‐face structured interviews, physical measurements and medical records. Participants were asked whether they were willing to use mH ealth after being shown DialBetics – an mH ealth application for diabetics – as an example, and about their history of dropout and previous mH ealth experience. Data were analyzed by multivariate logistic regression models. Results Of 307 patients with type 1 and type 2 diabetes, 34 (11.1%) had previously dropped out from diabetic care. Multivariate analysis identified previous mH ealth experience as a negative predictor of dropout (odds ratio 0.211, P = 0.023). Of those 34 patients, 27 (79.4%) expressed willingness to use mH ealth, a significantly higher percentage than for those who had never dropped out (51.5%, P = 0.002). After adjusting for confounders, history of dropout remained a strong predictor of willingness (odds ratio 3.870, P = 0.004). Conclusions Patients who previously dropped out of diabetic care are suitable candidates for mH ealth. Future studies must evaluate whether mH ealth is effective for preventing repeated dropout and improving glycemic control among this population.