Frontiers in digital health最新文献

{"title":"Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder.","authors":"Carolin S Klein, Karsten Hollmann, Jan Kühnhausen, Annika K Alt, Anja Pascher, Lennart Seizer, Jonas Primbs, Winfried Ilg, Annika Thierfelder, Björn Severitt, Helene Passon, Ursula Wörz, Heinrich Lautenbacher, Wolfgang A Bethge, Johanna Löchner, Martin Holderried, Walter Swoboda, Enkelejda Kasneci, Martin A Giese, Christian Ernst, Gottfried M Barth, Annette Conzelmann, Michael Menth, Caterina Gawrilow, Tobias J Renner","doi":"10.3389/fdgth.2024.1384540","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1384540","url":null,"abstract":"<p><strong>Introduction: </strong>The present study investigates the feasibility and usability of a sensor-based eHealth treatment in psychotherapy for pediatric obsessive-compulsive disorder (OCD), and explores the promises and pitfalls of this novel approach. With eHealth interventions, therapy can be delivered in a patient's home environment, leading to a more ecologically valid symptom assessment and access to experts even in rural areas. Furthermore, sensors can help indicate a patient's emotional and physical state during treatment. Finally, using sensors during exposure with response prevention (E/RP) can help individualize therapy and prevent avoidance behavior.</p><p><strong>Methods: </strong>In this study, we developed and subsequently evaluated a multimodal sensor-based eHealth intervention during 14 video sessions of cognitive-behavioral therapy (CBT) in 20 patients with OCD aged 12-18. During E/RP, we recorded eye movements and gaze direction via eye trackers, and an ECG chest strap captured heart rate (HR) to identify stress responses. Additionally, motion sensors detected approach and avoidance behavior.</p><p><strong>Results: </strong>The results indicate a promising application of sensor-supported therapy for pediatric OCD, such that the technology was well-accepted by the participants, and the therapeutic relationship was successfully established in the context of internet-based treatment. Patients, their parents, and the therapists all showed high levels of satisfaction with this form of therapy and rated the wearable approach in the home environment as helpful, with fewer OCD symptoms perceived at the end of the treatment.</p><p><strong>Discussion: </strong>The goal of this study was to gain a better understanding of the psychological and physiological processes that occur in pediatric patients during exposure-based online treatment. In addition, 10 key considerations in preparing and conducting sensor-supported CBT for children and adolescents with OCD are explored at the end of the article. This approach has the potential to overcome limitations in eHealth interventions by allowing the real-time transmission of objective data to therapists, once challenges regarding technical support and hardware and software usability are addressed.</p><p><strong>Clinical trial registration: </strong>www.ClinicalTrials.gov, identifier (NCT05291611).</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11460578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating normative data from web-based administration of the Cambridge Neuropsychological Test Automated Battery using a Bayesian framework.","authors":"Elizabeth Wragg, Caroline Skirrow, Pasquale Dente, Jack Cotter, Peter Annas, Milly Lowther, Rosa Backx, Jenny Barnett, Fiona Cree, Jasmin Kroll, Francesca Cormack","doi":"10.3389/fdgth.2024.1294222","DOIUrl":"10.3389/fdgth.2024.1294222","url":null,"abstract":"<p><strong>Introduction: </strong>Normative cognitive data can distinguish impairment from healthy cognitive function and pathological decline from normal ageing. Traditional methods for deriving normative data typically require extremely large samples of healthy participants, stratifying test variation by pre-specified age groups and key demographic features (age, sex, education). Linear regression approaches can provide normative data from more sparsely sampled datasets, but non-normal distributions of many cognitive test results may lead to violation of model assumptions, limiting generalisability.</p><p><strong>Method: </strong>The current study proposes a novel Bayesian framework for normative data generation. Participants (<i>n</i> = 728; 368 male and 360 female, age 18-75 years), completed the Cambridge Neuropsychological Test Automated Battery via the research crowdsourcing website Prolific.ac. Participants completed tests of visuospatial recognition memory (Spatial Working Memory test), visual episodic memory (Paired Associate Learning test) and sustained attention (Rapid Visual Information Processing test). Test outcomes were modelled as a function of age using Bayesian Generalised Linear Models, which were able to derive posterior distributions of the authentic data, drawing from a wide family of distributions. Markov Chain Monte Carlo algorithms generated a large synthetic dataset from posterior distributions for each outcome measure, capturing normative distributions of cognition as a function of age, sex and education.</p><p><strong>Results: </strong>Comparison with stratified and linear regression methods showed converging results, with the Bayesian approach producing similar age, sex and education trends in the data, and similar categorisation of individual performance levels.</p><p><strong>Conclusion: </strong>This study documents a novel, reproducible and robust method for describing normative cognitive performance with ageing using a large dataset.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11451437/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The user-centered design and development of a childhood and adolescent obesity Electronic Health Record tool, a mixed-methods study.","authors":"K Taylor Bosworth, Parijat Ghosh, Lauren Flowers, Rachel Proffitt, Richelle J Koopman, Aneesh K Tosh, Gwen Wilson, Amy S Braddock","doi":"10.3389/fdgth.2024.1396085","DOIUrl":"10.3389/fdgth.2024.1396085","url":null,"abstract":"<p><strong>Background: </strong>Childhood and adolescent obesity are persistent public health issues in the United States. Childhood obesity Electronic Health Record (EHR) tools strengthen provider-patient relationships and improve outcomes, but there are currently limited EHR tools that are linked to adolescent mHealth apps. This study is part of a larger study entitled, CommitFit, which features both an adolescent-targeted mobile health application (mHealth app) and an ambulatory EHR tool. The CommitFit mHealth app was designed to be paired with the CommitFit EHR tool for integration into clinical spaces for shared decision-making with patients and clinicians.</p><p><strong>Objectives: </strong>The objective of this sub-study was to identify the functional and design needs and preferences of healthcare clinicians and professionals for the development of the CommitFit EHR tool, specifically as it relates to childhood and adolescent obesity management.</p><p><strong>Methods: </strong>We utilized a user-centered design process with a mixed-method approach. Focus groups were used to assess current in-clinic practices, deficits, and general beliefs and preferences regarding the management of childhood and adolescent obesity. A pre- and post-focus group survey helped assess the perception of the design and functionality of the CommitFit EHR tool and other obesity clinic needs. Iterative design development of the CommitFit EHR tool occurred throughout the process.</p><p><strong>Results: </strong>A total of 12 healthcare providers participated throughout the three focus group sessions. Two themes emerged regarding EHR design: (1) Functional Needs, including Enhancing Clinical Practices and Workflow, and (2) Visualization, including Colors and Graphs. Responses from the surveys (<i>n</i> = 52) further reflect the need for <i>Functionality</i> and <i>User-Interface Design</i> by clinicians. Clinicians want the CommitFit EHR tool to enhance in-clinic adolescent lifestyle counseling, be easy to use, and presentable to adolescent patients and their caregivers. Additionally, we found that clinicians preferred colors and graphs that improved readability and usability. During each step of feedback from focus group sessions and the survey, the design of the CommitFit EHR tool was updated and co-developed by clinicians in an iterative user-centered design process.</p><p><strong>Conclusion: </strong>More research is needed to explore clinician actual user analytics for the CommitFit EHR tool to evaluate real-time workflow, design, and function needs. The effectiveness of the CommitFit mHealth and EHR tool as a weight management intervention needs to be evaluated in the future.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11476727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting health information system in guiding decisions for improving performance: an intervention study at the Research Institute of Ophthalmology, Giza, Egypt.","authors":"Yara H Abdelgawad, Madiha Said Abd El Razik, Doa'a A Saleh, Manal H Abuelela, Marwa Rashad Salem","doi":"10.3389/fdgth.2024.1288776","DOIUrl":"10.3389/fdgth.2024.1288776","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to design and test a platform of key performance indicators (KPIs) and indices emphasizing achievements and improvement and helping decision-making.</p><p><strong>Methods: </strong>An operations research study was designed to analyze data from the Hospital Management Information System (HMIS) from July 2017 to June 2018 at the Research Institute of Ophthalmology (RIO), Giza, Egypt. The HMIS data were submitted to reform covering parameters in service delivery and corresponding indicators and indices. Data were grouped into four themes: human resources and outpatient, inpatient, and surgical operations. A total of 14 performance indicators were deployed to four specific indices and total performance indices and applied to six teams of ophthalmologists at RIO. The decision matrices were deliberated to demonstrate achievements and provide recommendations for subsequent improvements.</p><p><strong>Results: </strong>Throughout 1 year, six teams of ophthalmologists (<i>n</i> = 222) at RIO provided the following services: outpatient (<i>n</i> = 116,043), inpatient (<i>n</i> = 8,081), and surgical operations (<i>n</i> = 9,174). Teams 2, 1, and 6 were the top teams in the total performance index. Team 4 had plunges in the outpatient index, and Team 5 faced limitations in the inpatient index.</p><p><strong>Conclusion: </strong>The study provided a model for upgrading the performance of the management information system (MIS) in health organizations. The KPIs and indices were used not only for documenting successful models of efficient service delivery but also as examples of limitations for further support and interventions.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11444961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaling up! Staff e-learning for a national take-home naloxone program.","authors":"Øystein Bruun Ericson, Desiree Eide, Håvar Brendryen, Philipp Lobmaier, Thomas Clausen","doi":"10.3389/fdgth.2024.1404646","DOIUrl":"10.3389/fdgth.2024.1404646","url":null,"abstract":"<p><strong>Background: </strong>A staff e-learning course was developed to prepare for scaling up a national take-home naloxone (THN) program in Norway. The aims of the study were to (a) describe participant characteristics for those that completed a THN e-learning course, (b) compare opioid overdose knowledge scores before and after e-learning course completion, and (c) to explore subsequent THN distribution by those trained.</p><p><strong>Methods: </strong>This was a quasi-experimental pre-test, post-test longitudinal cohort study of individuals completing a THN e-learning course from April 2021 to May 2022. Frequency analyses were performed for participant characteristics and subsequent naloxone distributions at 1-week and 1-month follow-up. The opioid overdose knowledge scale (OOKS) was used to measure pre-test-post-test knowledge among participants. Wilcoxon signed-rank test was performed for comparison between pre-test and post-test. Effect size was calculated using Cohen criteria.</p><p><strong>Results: </strong>In total, 371 individuals were included in this study. Most were either nurses or social workers (<i>n</i> = 277, 75%). Participant knowledge increased by medium or large effect for all items measured. At 1-month follow-up, 15% reported naloxone distribution. During the study period, 94 naloxone kits were distributed. Major reasons for not distributing were \"clients not interested\", \"workplace not distributing\" and \"workplace in process of distributing\".</p><p><strong>Conclusions: </strong>Our findings suggest that an e-learning course is equally effective in terms of knowledge transfer as an in-person classroom setting, and may provide engagement in terms of naloxone distribution. However, our findings also emphasize the importance of clear implementation routines, including support from central coordinators to optimize the implementation process.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11448357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study.","authors":"Mitiku Kassaw, Getasew Amare, Kegnie Shitu, Binyam Tilahun, Bayou Tilahun Assaye","doi":"10.3389/fdgth.2024.1437134","DOIUrl":"10.3389/fdgth.2024.1437134","url":null,"abstract":"<p><strong>Introduction: </strong>Currently, mortality by non-communicable diseases is increasing alarmingly. They account for approximately 35 million deaths each year, of which 14% are due to cardiovascular disease and 9.2% occur in Africa. Patients do not have access to healthcare services outside the healthcare setting, resulting in missed follow-ups and appointments and adverse outcomes. This study aimed to assess the willingness to use remote monitoring among cardiovascular patients in a resource-limited setting in Ethiopia.</p><p><strong>Method: </strong>An institution-based cross-sectional study was conducted from April to June 2021 among cardiovascular patients at referral hospitals in Ethiopia. A structured interview questionnaire was used to collect the data. A systematic random sampling technique was used to select 397 study participants. Binary and multivariable logistic regression analyses were employed and a 95% confidence level with a <i>p</i>-value <0.05 was used to determine the level of association between variables.</p><p><strong>Result: </strong>In total, 81.61% of the study participants were willing to use remote patient monitoring [95% confidence interval (CI) = 77.4%-85.1%]. Age [adjusted odds ratio (AOR) = 0.94; 95% CI: 0.90-0.98], having a mobile phone (AOR = 5.70; 95% CI: 1.86-17.22), and perceived usefulness (AOR = 1.50; 95% CI: 1.18-1.82) were significantly associated with willingness to use remote patient monitoring among cardiovascular patients.</p><p><strong>Conclusion: </strong>Cardiovascular patients had a high willingness to use remote patient monitoring. Age, perceived usefulness of remote patient monitoring, and having a mobile phone were significantly associated with a willingness to use remote patient monitoring.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11448358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ProVIA-Kids - outcomes of an uncontrolled study on smartphone-based behaviour analysis for challenging behaviour in children with intellectual and developmental disabilities or autism spectrum disorder.","authors":"Rinat Meerson, Hanna Buchholz, Klaus Kammerer, Manuel Göster, Johannes Schobel, Christoph Ratz, Rüdiger Pryss, Regina Taurines, Marcel Romanos, Matthias Gamer, Julia Geissler","doi":"10.3389/fdgth.2024.1462682","DOIUrl":"10.3389/fdgth.2024.1462682","url":null,"abstract":"<p><strong>Introduction: </strong>Challenging behaviour (CB) is a common issue among children with autism spectrum disorder or intellectual and developmental disability. Mental health applications are low-threshold cost-effective tools to address the lack of resources for caregivers. This pre-post study evaluated the feasibility and preliminary effectiveness of the smartphone app <i>ProVIA-Kids</i> using algorithm-based behaviour analysis to identify causes of CB and provide individualized practical guidance to manage and prevent CB.</p><p><strong>Methods: </strong>A total of 18 caregivers (<i>M</i> = 38.9 ± 5.0) of children with a diagnosis of autism spectrum disorder (44%), intellectual and developmental disabilities (33%) or both (22%) aged 4-11 years (<i>M</i> = 7.6 ± 1.8) were included. Assessments were performed before and after an 8-week intervention period. The primary outcome was the change in parental stress. Caregiver stress experience due to CB was also rated daily via ecological momentary assessments within the app. Secondary outcomes included the intensity of the child's CB, dysfunctional parenting, feelings of parental competency as well as caregivers' mood (rated daily in the app) and feedback on the app collected via the Mobile Application Rating Scale.</p><p><strong>Results: </strong>We observed increases in parental stress in terms of conscious feelings of incompetence. However, we also saw improvements in parental stress experience due to CB and overreactive parenting, and descriptive improvements in CB intensity and caregiver mood.</p><p><strong>Discussion: </strong><i>ProVIA-Kids</i> pioneers behaviour analysis in a digital and automated format, with participants reporting high acceptance. Pilot results highlight the potential of the <i>ProVIA-Kids</i> app to positively influence child behaviour and caregiver mental health over a longer intervention period.</p><p><strong>Registration: </strong>The study was registered at https://www.drks.de (ID = DRKS00029039) on May 31, 2022.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of the community of purpose in maternal mHealth interventions in Sub-Saharan Africa context.","authors":"Karen Sowon, Priscilla Maliwichi, Wallace Chigona, Address Malata","doi":"10.3389/fdgth.2024.1343965","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1343965","url":null,"abstract":"<p><strong>Background: </strong>mHealth has increasingly been touted as having the potential to help Sub-Saharan Africa achieve their health-related sustainable development goals by reducing maternal mortality rates. Such interventions are implemented as one-way or two-way systems where maternal clients receive pregnancy related information via SMS. While such technologies often view the users (the maternal health client) as having agency to adopt, we know from pregnancy literature that the pregnancy experience in Africa and other developing countries is often more collective. In addition to the maternal health client, other members of the community have high stakes in the pregnancy, and this often affects maternal healthcare-seeking behavior.</p><p><strong>Objective: </strong>The aim of this paper, therefore, is to understand the pathways through which these other members of the community affect mHealth use.</p><p><strong>Methods: </strong>The study used a qualitative approach and a case study research design. We analyzed two mHealth cases from Kenya and Malawi. In the Kenyan case, maternal health clients had mobile phones to receive pregnancy-related messages, while in the Malawi case, maternal health clients did not have mobile phones. Data were collected through interviews and focus group discussions. The study used an inductive thematic analysis to analyze the data.</p><p><strong>Results: </strong>The findings show that maternal stakeholders form a community of purpose (CoP) that plays a crucial role in the implementation, uptake, and use of mHealth. The CoP influences maternal health clients through a diverse range of mechanisms ranging from sensitization, bridging the digital literacy gap and legitimization of the intervention. The nature of influence is largely dependent on the contextual socio-cultural nuances.</p><p><strong>Conclusion: </strong>Our results provide useful insights to mHealth implementers to know how best to leverage the CoP for better mHealth uptake and usage. For example, engaging healthcare providers could champion adoption and use, while engaging other family-related stakeholders will ensure better usage and compliance, encourage behavior change, and reduce mHealth attrition.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11424603/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence of internet addiction and associated factors among university students in Ethiopia: systematic review and meta-analysis.","authors":"Yibeltal Assefa Atalay","doi":"10.3389/fdgth.2024.1373735","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1373735","url":null,"abstract":"<p><strong>Introduction: </strong>Internet addiction refers to the excessive and uncontrolled utilization of the Internet, which disrupts one's daily activities. The current state of knowledge regarding internet addiction in Ethiopia is limited. Consequently, the objective of this study is to ascertain the combined prevalence of Internet addiction and its correlated factors among university students in Ethiopia.</p><p><strong>Methods: </strong>To identify potential research findings, an extensive literature search was conducted using electronic databases such as PubMed/MEDLINE, Web of Science, and Google Scholar. The presence of heterogeneity between studies was assessed using Cochrane Q test statistics and I2 test statistics, while the effects of small studies were examined using Eggers statistical tests at a 5% significance level. Additionally, a sensitivity analysis was carried out. A random effects model was used to estimate the pooled prevalence and associated factors of Internet addiction among students. The primary focus of this research was to determine the prevalence of Internet addiction, while the secondary aim was to identify the factors associated with Internet addiction.</p><p><strong>Results: </strong>To determine the overall prevalence of Internet addiction among university students in Ethiopia, a comprehensive analysis of 11 studies was conducted. The results of this study show that the pooled prevalence of Internet addiction was 43.42% (95% CI: 28.54, 58.31). The results also suggest that certain factors such as online gaming, depression, and current khat chewing are significantly associated with internet addiction among university students.</p><p><strong>Conclusions: </strong>In Ethiopia, about one-third of university students suffer from internet addiction. The prevalence of Internet addiction among Ethiopian students is associated with online gaming, depression, and concurrent khat consumption. Therefore, we strongly recommend that health planners and policymakers prioritize monitoring and addressing Internet use and addiction in the Ethiopian context.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11422350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A stacked machine learning-based classification model for endometriosis and adenomyosis: a retrospective cohort study utilizing peripheral blood and coagulation markers.","authors":"Weiying Wang, Weiwei Zeng, Sen Yang","doi":"10.3389/fdgth.2024.1463419","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1463419","url":null,"abstract":"<p><strong>Introduction: </strong>Endometriosis (EMs) and adenomyosis (AD) are common gynecological diseases that impact women's health, and they share symptoms such as dysmenorrhea, chronic pain, and infertility, which adversely affect women's quality of life. Current diagnostic approaches for EMs and AD involve invasive surgical procedures, and thus, methods of noninvasive differentiation between EMs and AD are needed. This retrospective cohort study introduces a novel, noninvasive classification methodology employing a stacked ensemble machine learning (ML) model that utilizes peripheral blood and coagulation markers to distinguish between EMs and AD.</p><p><strong>Methods: </strong>The study included a total of 558 patients (329 with EMs and 229 with AD), in whom key hematological and coagulation markers were analyzed to identify distinctive profiles. Feature selection was conducted through ML (logistic regression, support vector machine, and K-nearest neighbors) to determine significant hematological markers.</p><p><strong>Results: </strong>Red cell distribution width, mean corpuscular hemoglobin concentration, activated partial thromboplastin time, international normalized ratio, and antithrombin III were proved to be the key distinguishing indexes for disease differentiation. Among all the ML classification models developed, the stacked ensemble model demonstrated superior performance (area under the curve = 0.803, 95% credibility interval = 0.701-0.904). Our findings demonstrate the effectiveness of the stacked ensemble ML model for classifying EMs and AD.</p><p><strong>Discussion: </strong>Integrating biomarkers into this multi-algorithm framework offers a novel approach to noninvasive diagnosis. These results advocate for the application of stacked ensemble ML utilizing cost-effective and readily available peripheral blood and coagulation indicators for the early, rapid, and noninvasive differential diagnosis of EMs and AD, offering a potentially transformative approach for clinical decision-making and personalized treatment strategies.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11428011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}