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Content Provider | Directory of Open Access Journals (DOAJ) |
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Author | Sisi Su Xin Yang Qing Su Yang Zhao |
Abstract | The aim of this study was to assess menstrual blood loss (MBL) and knowledge of heavy menstrual bleeding (HMB) among the gynecology outpatients at Peking University People's Hospital, by scanning a WeChat (a social media application software developed by Tencent) QR Code using a mobile phone or tablet. This survey was conducted among outpatients who were treated at the Gynecology Department of Peking University People's Hospital between September 2016 and November 2016. All participants filled up the questionnaires and scales through WeChat: general information questionnaire, Pictorial Blood Loss Assessment Chart (PBAC), Menorrhagia Multi-Attribute Quality-of-Life Scale (MMAS), and HMB knowledge questionnaire. Menstrual blood volume was assessed by the PBAC and self-assessment. Among the 1152 patients who filled out the survey, 77.4% (892/1152) had normal menstrual cycle (assessed by the patients), 15.6% (180/1152) patients described themselves as HMB, whereas the results from PBAC showed that 58.0% (668/1152) had HMB (PBAC ≥100). Among patients with PBAC ≥100, only 26.8% (179/668) patients reported HMB through self-assessment. Regarding its impact on daily life, the MMAS scores of HMB patients (PBAC ≥100) were significantly lower compared to those with normal blood loss (P<0.001). Regarding the awareness to HMB, 63.2% (728/1152) of the patients were not familiar with HMB. HMB is a common abnormal uterine bleeding and is frequently found among Chinese gynecology outpatients. HMB has major impacts on a woman's quality of life, affecting both physical and emotional health domains. Since women generally have low levels of awareness and understanding of HMB, they could assess their blood loss using the PBAC, which they can forward to their health care provider using a mobile phone or tablet and the WeChat platform. This tool may be effortlessly used by the health care providers and patients to easily share HMB-related data. |
e-ISSN | 19326203 |
DOI | 10.1371/journal.pone.0229123 |
Journal | PLoS ONE |
Issue Number | 4 |
Volume Number | 15 |
Language | English |
Publisher | Public Library of Science (PLoS) |
Publisher Date | 2020-01-01 |
Publisher Place | United States |
Access Restriction | Open |
Subject Keyword | Medicine Science |
Content Type | Text |
Resource Type | Article |
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