Alison K Brinson, Hannah R Jahnke, Natalie Henrich, Smriti Karwa, Christa Moss, Neel Shah
{"title":"孕期使用数字医疗与早产的可能性。","authors":"Alison K Brinson, Hannah R Jahnke, Natalie Henrich, Smriti Karwa, Christa Moss, Neel Shah","doi":"10.1177/20552076241277037","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth.</p><p><strong>Methods: </strong>Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions.</p><p><strong>Results: </strong>Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; <i>p</i> < 0.001). For every 1 h of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [adjusted odds ratio (AOR) (95% confidence interval (CI)) = 0.98 (0.95, 0.998), <i>p</i> = 0.04]. Among individuals who developed gestational conditions, every 1 h increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), <i>p</i> = 0.037]. There was no statistically significant association between Maven use and preterm birth in individuals without gestational conditions.</p><p><strong>Conclusion: </strong>Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11372763/pdf/","citationCount":"0","resultStr":"{\"title\":\"Digital health utilization during pregnancy and the likelihood of preterm birth.\",\"authors\":\"Alison K Brinson, Hannah R Jahnke, Natalie Henrich, Smriti Karwa, Christa Moss, Neel Shah\",\"doi\":\"10.1177/20552076241277037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth.</p><p><strong>Methods: </strong>Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions.</p><p><strong>Results: </strong>Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; <i>p</i> < 0.001). For every 1 h of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [adjusted odds ratio (AOR) (95% confidence interval (CI)) = 0.98 (0.95, 0.998), <i>p</i> = 0.04]. Among individuals who developed gestational conditions, every 1 h increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), <i>p</i> = 0.037]. There was no statistically significant association between Maven use and preterm birth in individuals without gestational conditions.</p><p><strong>Conclusion: </strong>Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.</p>\",\"PeriodicalId\":51333,\"journal\":{\"name\":\"DIGITAL HEALTH\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11372763/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DIGITAL HEALTH\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/20552076241277037\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076241277037","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Digital health utilization during pregnancy and the likelihood of preterm birth.
Objective: Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth.
Methods: Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions.
Results: Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; p < 0.001). For every 1 h of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [adjusted odds ratio (AOR) (95% confidence interval (CI)) = 0.98 (0.95, 0.998), p = 0.04]. Among individuals who developed gestational conditions, every 1 h increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), p = 0.037]. There was no statistically significant association between Maven use and preterm birth in individuals without gestational conditions.
Conclusion: Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.