Can digital health technologies exacerbate the health gap? A clustering analysis of mothers' opinions toward digitizing the maternal and child health handbook

被引:10
作者
Goto, Ryunosuke [1 ]
Watanabe, Yoko [2 ]
Yamazaki, Ako [3 ]
Sugita, Masatoshi [4 ]
Takeda, Satoru [5 ,6 ]
Nakabayashi, Masao [3 ]
Nakamura, Yasuhide [7 ]
机构
[1] Univ Tokyo Hosp, Dept Pediat, Bunkyo Ku, 7-3-1 Hongo, Tokyo 1138655, Japan
[2] Hachi City Publ Hlth Ctr, 13-18 Asahicho, Hachioji, Tokyo 1920083, Japan
[3] Imperial Gift Fdn, Aiiku Maternal & Child Hlth Ctr, Minato Ku, 5-6-8 Minami Azabu, Tokyo 1068580, Japan
[4] NTT Med Ctr Tokyo, Dept Obstet & Gynecol, Shinagawa Ku, 5-9-22 Higashi Gotanda, Tokyo 1418625, Japan
[5] Juntendo Univ, Fac Med, Dept Obstet & Gynecol, Bunkyo Ku, 2-1-1 Hongo, Tokyo 1138421, Japan
[6] Imperial Gift Fdn, Aiiku Maternal & Child Hlth Ctr, Aiiku Res Inst Maternal Child Hlth & Welf, Minato Ku, 5-6-8 Minami Azabu, Tokyo 1068580, Japan
[7] Friends WHO Japan, Chuo Ku, 2-8 Honmachibashi, Osaka 5400029, Japan
关键词
Social determinants of health; Maternal and child health; Health inequity; Digital; Health; Digital divide; DISPARITIES;
D O I
10.1016/j.ssmph.2021.100935
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The use of mobile health has increased worldwide, but along with its increased utilization comes the risk of the digital divide, inequity in access to information and communications technologies, exerting greater influence on health inequity caused by socioeconomic determinants of health. There is a growing need to investigate whether the digitization of existing health interventions has a risk of worsening the health gap. Methods: We investigated the attitudes of mothers and pregnant women toward digitization of the Maternal and Child Health Handbook (MCHH), a popular personal health record (PHR) used by almost every pregnant woman or mother in Japan, using a cross-sectional survey. We determined sociodemographic factors associated with favorable opinions toward digitization using a multivariate regression model. We then grouped the participants using partitioning around medoids clustering, a machine-learning approach, to interpret their varying attitudes toward digitization in light of their sociodemographic characteristics as well as their affinity toward the paper MCHH. Findings: Higher income and educational level, older age, and less reliance on the MCHH were significantly associated with favorable opinion toward digitization. Clustering analysis identified four latent clusters. The cluster with the highest socioeconomic status (SES) was the most favorable toward digitization, while two clusters with the lowest SES, one of which relied heavily on the paper MCHH, were less favorable of digitization compared to the high SES cluster. The final cluster was comprised of mothers with the experience of raising multiple children and did not rely heavily on the MCHH. Interpretation: Our study identified a socioeconomic divide in opinions toward digitization of an existing health intervention. A hasty digitization may result in an unbalanced uptake of the digitized health intervention among different social classes.
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页数:6
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