BMC digital health最新文献

{"title":"Description of patient characteristics and medication adherence among medication access mobile application users and nonusers: a single-center questionnaire-based cross-sectional study","authors":"Ghadah Assiri, Dalal Alabdulkarim, Asrar Alanazi, Sarah Altamimi, Nadin Lafi Alanazi, Wael Khawagi","doi":"10.1186/s44247-023-00039-8","DOIUrl":"https://doi.org/10.1186/s44247-023-00039-8","url":null,"abstract":"Abstract Background In this study, we aimed to describe patient characteristics and medication adherence among medication access mobile application users and nonusers. Methods This was a cross-sectional study of a randomly selected sample of patients who refilled their medications either through the mobile application ‘MNG-HA Care’ or by phone call to a government-funded multispecialty hospital in Riyadh, Saudi Arabia. Data were collected through an online survey and filed either via WhatsApp or by phone call. Medication adherence was assessed using the five-item Medication Adherence Report Scale (MARS-5). Results A total of 280 respondents were recruited, and their mean age was 48.8 years (standard deviation (SD): 17.8). More than 75% of application users and nonusers were younger (18–64 years) and lived in urban areas, 58% were male, 37.5% held a bachelor’s degree, and 40% were unemployed. The number of respondents who accessed the mobile application (mobile application users) was 212, and 64.2% of them were adherent to their medications. Sixty-eight of the respondents used a phone call for refills (mobile application nonusers), and 77.9% of them were adherent to their medications. The most common self-reported reasons for using the application were to book an appointment and to request a medication refill. The most common self-reported reasons for not using the application were respondents’ lack of knowledge about the availability of the application and preference for speaking directly to the health care provider. Adjusted multivariate logistic regression analysis revealed that medication adherence was not associated with application use (Odds Ratio (OR): 0.65; 95% CI: 0.33–1.29). However, male patients had significantly higher adherence than females (OR 2.68, 95% CI 1.31 to 5.51), and employed patients had significantly lower adherence than unemployed patients (OR 0.37, 95% CI 0.17 to 0.81). Conclusions Providing patients with access to their medication list through a mobile application alone did not significantly impact medication adherence. Further research is needed to explore the potential benefits of incorporating additional features, such as medication instructions and reminders within mobile applications, to improve medication adherence.","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135791439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tuuned in: use of an online contraceptive decision aid for women increases reproductive self-efficacy and knowledge; results of an experimental clinical trial","authors":"Summer Mengelkoch, Matthew Espinosa, Stephen A. Butler, Laura Joigneau Prieto, Emma Russell, Chris Ramshaw, Shardi Nahavandi, Sarah E. Hill","doi":"10.1186/s44247-023-00034-z","DOIUrl":"https://doi.org/10.1186/s44247-023-00034-z","url":null,"abstract":"Abstract Background Digital decision aids are becoming increasingly common in many areas of healthcare. These aids are designed to involve patients in medical decision making, with the aim of improving patient outcomes while decreasing healthcare burden. Previously developed contraceptive-based decision aids have been found to be effective at increasing women’s knowledge about reproductive health and contraception. Here, we sought to evaluate the effectiveness of a novel contraceptive-based decision aid at increasing women’s self-efficacy and knowledge about their reproductive health and contraceptive options, as well as their perceptions of their learning. This study was registered as a clinic trial at ClinicalTrials.gov (Contraception Decision Aid Use and Patient Outcomes, ID# NCT05177783) on 05/01/2022. Methods The Tuune® contraceptive decision aid’s effectiveness was evaluated by conducting an experiment in which 324 women were assigned to use the Tuune® decision aid or a control decision aid. Primary outcomes included reproductive health self-efficacy, reproductive health and contraceptive knowledge, and perceptions of learning. Secondary analyses examined whether prior experience using hormonal contraceptives moderated the relationship between decision aid and each outcome measure. Results Women assigned to use the Tuune® decision aid exhibited greater reproductive health self-efficacy, greater knowledge about reproductive health and contraception, and perceived having learned more than women assigned to use the control decision aid ( p s ≤ .029). This pattern was also observed in women with previous contraceptive use experience, where women using Tuune® reported better outcomes than women using the control aid, regardless of their history of hormonal contraceptive use experience, although this interaction was not significant ( p = .089). Conclusions Use of the Tuune® contraceptive-based decision aid improved each of the predicted outcomes relative to a control decision aid. This suggests that use of the Tuune® contraceptive-based decision aid is well poised to increase women’s confidence and knowledge about contraceptive use and may also reduce burden on healthcare systems.","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135110872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Machine learning-based prediction of COVID-19 mortality using immunological and metabolic biomarkers","authors":"Thomas Wetere Tulu, Tsz Kin Wan, Ching Long Chan, Chun Hei Wu, Peter Yat Ming Woo, Cee Zhung Steven Tseng, Asmir Vodencarevic, Cristina Menni, Kei Hang Katie Chan","doi":"10.1186/s44247-023-00045-w","DOIUrl":"https://doi.org/10.1186/s44247-023-00045-w","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135878150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovering social determinants of health from case reports using natural language processing: algorithmic development and validation","authors":"Shaina Raza, Elham Dolatabadi, Nancy Ondrusek, Laura Rosella, Brian Schwartz","doi":"10.1186/s44247-023-00035-y","DOIUrl":"https://doi.org/10.1186/s44247-023-00035-y","url":null,"abstract":"Abstract Background Social determinants of health are non-medical factors that influence health outcomes (SDOH). There is a wealth of SDOH information available in electronic health records, clinical reports, and social media data, usually in free text format. Extracting key information from free text poses a significant challenge and necessitates the use of natural language processing (NLP) techniques to extract key information. Objective The objective of this research is to advance the automatic extraction of SDOH from clinical texts. Setting and data The case reports of COVID-19 patients from the published literature are curated to create a corpus. A portion of the data is annotated by experts to create ground truth labels, and semi-supervised learning method is used for corpus re-annotation. Methods An NLP framework is developed and tested to extract SDOH from the free texts. A two-way evaluation method is used to assess the quantity and quality of the methods. Results The proposed NER implementation achieves an accuracy (F1-score) of 92.98% on our test set and generalizes well on benchmark data. A careful analysis of case examples demonstrates the superiority of the proposed approach in correctly classifying the named entities. Conclusions NLP can be used to extract key information, such as SDOH factors from free texts. A more accurate understanding of SDOH is needed to further improve healthcare outcomes.","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135938654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A protocol for the development and validation of a virtual reality-based clinical test of social cognition","authors":"M. Matre, T. Johansen, A. Olsen, S. Tornås, AC Martinsen, A. Lund, F. Becker, C. Brunborg, J. Spikman, J. Ponsford, D. Neumann, S. McDonald, M. Løvstad","doi":"10.1186/s44247-023-00036-x","DOIUrl":"https://doi.org/10.1186/s44247-023-00036-x","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48323806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The qualities of patients interested in using a game-based digital mental health intervention for depression: a sequential mixed methods study","authors":"Lauri Lukka, Antti Salonen, M. Vesterinen, Veli-Matti Karhulahti, S. Palva, J. Palva","doi":"10.1186/s44247-023-00037-w","DOIUrl":"https://doi.org/10.1186/s44247-023-00037-w","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42471605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barriers and facilitators to patient-to-provider messaging using the COM-B model and theoretical domains framework: a rapid umbrella review","authors":"Megan M. MacPherson, Shabana Kapadia","doi":"10.1186/s44247-023-00033-0","DOIUrl":"https://doi.org/10.1186/s44247-023-00033-0","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44938484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digitalization of home-based records for maternal, newborn, and child health: a scoping review","authors":"M. Geldof, Nina Gerlach, A. Portela","doi":"10.1186/s44247-023-00032-1","DOIUrl":"https://doi.org/10.1186/s44247-023-00032-1","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42413801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Essential Network (TEN): engagement and mental health insights from a digital mental health assessment tool for Australian health professionals during COVID-19","authors":"M. Coleshill, D. Alagirisamy, S. Patki, M. Ronksley, M. Black, S. Yu, M. Phillips, J. Newby, N. Cockayne, J. Tennant, S. Harvey, H. Christensen, P. Baldwin","doi":"10.1186/s44247-023-00031-2","DOIUrl":"https://doi.org/10.1186/s44247-023-00031-2","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49136634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The barriers and facilitators to young people’s engagement with bidirectional digital sexual health interventions: a mixed methods systematic review","authors":"C. Bennett, Massirfufulay Kpehe Musa, Judith Carrier, D. Edwards, Elizabeth Gillen, A. Sydor, Catherine Dunn, Kaye Jones-Mahoney, Alex Nute, D. Kelly","doi":"10.1186/s44247-023-00030-3","DOIUrl":"https://doi.org/10.1186/s44247-023-00030-3","url":null,"abstract":"","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45053517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}