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181 results on '"Lee, Ching‐Fang"'

9. Recurrent Neural Networks for Analysis and Automated Air Pollution Forecasting

Author

Lee, Ching-Fang, Yang, Chao-Tung, Kristiani, Endah, Tsan, Yu-Tse, Chan, Wei-Cheng, Huang, Chin-Yin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Hung, Jason C., editor, Yen, Neil Y., editor, and Hui, Lin, editor

Published
2019
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35. Effectiveness of a nurse‐led mHealth app to prevent excessive gestational weight gain among overweight and obese women: A randomized controlled trial.

Author

Chen, Hung‐Hui, Lee, Ching‐Fang, Huang, Jian‐Pei, Hsiung, Yvonne, and Chi, Li‐Kang

Subjects
*OBESITY, *WEIGHT gain in pregnancy, *CONFIDENCE intervals, *MOBILE apps, *FIRST trimester of pregnancy, *THIRD trimester of pregnancy, *DIET, *WEARABLE technology, *RANDOMIZED controlled trials, *PHYSICAL activity, *RESEARCH funding, *STATISTICAL sampling, *SECOND trimester of pregnancy, *TELEMEDICINE, *NURSING interventions
Abstract

Objective: To explore the effectiveness of a nurse‐led mobile health (mHealth) intervention to prevent excessive gestational weight gain (GWG) in overweight and obese women. Methods: A randomized controlled trial with an experimental study design. Ninety‐two pregnant women with body mass index (BMI) ≥25 kg/m2 at less than 17 weeks gestation were recruited from two prenatal clinics in northern Taiwan from January to June 2020. The experimental group used the MyHealthyWeight (MHW) app and a wearable activity tracker (WAT), and the controls received standard antenatal treatments with no mHealth‐based elements. Two hospital follow‐up visits were scheduled at 24–26 weeks in the second trimester and 34–36 weeks in the third trimester. A generalized estimating equation (GEE) was used to examine the trajectories and the effectiveness of mHealth on GWG. Results: No difference in GWG was found between the intervention and control groups at baseline (p > 0.05). The GWG trajectory in the entire cohort of women with obesity exhibited a quadratic pattern (ß = 1.8, 95% confidence interval [CI] = 1.27–2.32), and intervention participants' weekly GWG was gained significantly lower than their controls in the second trimester (p < 0.05). Throughout the pregnancy, the mHealth intervention group had a significantly lower proportion of individuals who exceeded their GWG in both total (21.6% vs. 32.6%) and weekly weight gain (first trimester = 58.7% vs. 65.2%; second trimester = 45% vs. 67.4%; third trimester = 48.6% vs. 55.1%). In particular, among obese women in the third trimester, those in the intervention group gained less gestational weight than their controls. The adjusted body weight difference was 5.44 kg (p = 0.023), signifying the total GWG difference (3.30 vs. 8.74 kg) between the means of the two groups. The GEE model indicated that obese women who were aged 35 years, had prepregnancy exercise habits, perceived self‐efficacy of diet, and more physical activity tended to have low GWG (p < 0.05). Conclusions: The nurse‐led mHealth‐based intervention shows promising results in significantly preventing excessive GWG among high‐BMI women. More effectiveness was found among the obese subgroup. Clinical relevance: The mHealth‐based intervention would be successfully implemented by nurses to help high‐BMI women maintain their optimal body weight and promote healthy behavioral changes, particularly in diet and physical activity during pregnancy. [ABSTRACT FROM AUTHOR]

Published
2023
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