This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance. The system employs a transformer model to process sophisticated, multilingual user inputs and gain improved contextual understanding compared to conventional models, including long short-term memory (LSTM) models. In contrast to LSTMs, which sequence processes information and may experience challenges with long-range dependencies, transformers utilize self-attention to learn relationships among every aspect of the input in parallel. This enables them to execute more accurately in various languages and contexts, making them well-suited for applications such as translation, summarization, and conversational Comparative evaluations revealed the superiority of the transformer model (accuracy rate: 85%) compared with that of the LSTM model (accuracy rate: 65%). The experiments revealed several advantages of the transformer architecture over the LSTM model, such as more effective self-attention, the ability for models to work in parallel with each other, and contextual understanding for better multilingual compatibility. Additionally, our prediction model exhibited effectiveness for disease diagnosis, with accuracy of 85% or greater in identifying the relationship between symptoms and diseases among different demographics. The system provides translation support from English to other languages, with conversion to French (Bilingual Evaluation Understudy score: 0.7), followed by English to Hindi (0.6). The lowest Bilingual Evaluation Understudy score was found for English to Telugu (0.39). This virtual assistant can also perform symptom analysis and disease prediction, with output given in the preferred language of the user.
{"title":"Multilingual Virtual Healthcare Assistant","authors":"Geetika Munjal, Piyush Agarwal, Lakshay Goyal, Nandy Samiran","doi":"10.1002/hcs2.70031","DOIUrl":"https://doi.org/10.1002/hcs2.70031","url":null,"abstract":"<p>This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance. The system employs a transformer model to process sophisticated, multilingual user inputs and gain improved contextual understanding compared to conventional models, including long short-term memory (LSTM) models. In contrast to LSTMs, which sequence processes information and may experience challenges with long-range dependencies, transformers utilize self-attention to learn relationships among every aspect of the input in parallel. This enables them to execute more accurately in various languages and contexts, making them well-suited for applications such as translation, summarization, and conversational Comparative evaluations revealed the superiority of the transformer model (accuracy rate: 85%) compared with that of the LSTM model (accuracy rate: 65%). The experiments revealed several advantages of the transformer architecture over the LSTM model, such as more effective self-attention, the ability for models to work in parallel with each other, and contextual understanding for better multilingual compatibility. Additionally, our prediction model exhibited effectiveness for disease diagnosis, with accuracy of 85% or greater in identifying the relationship between symptoms and diseases among different demographics. The system provides translation support from English to other languages, with conversion to French (Bilingual Evaluation Understudy score: 0.7), followed by English to Hindi (0.6). The lowest Bilingual Evaluation Understudy score was found for English to Telugu (0.39). This virtual assistant can also perform symptom analysis and disease prediction, with output given in the preferred language of the user.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"281-288"},"PeriodicalIF":3.3,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888502","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}
<p>On April 26, 2025, the Second Tsinghua Medicine Journal Innovation Conference convened in Beijing. Centered on the theme “AI-driven Academic: Shaping the Next Frontier” the Conference brought together journal editors, medical researchers, and science policy experts to examine how data and artificial intelligence (AI) are reshaping scholarly publishing. Two keynote speeches set the stage: the first analyzed the opportunities for hospital-based research arising from new journal policies, data infrastructure, and enabling technologies; the second introduced the latest advances in general AI and their implications for academic publishing security and integrity.</p><p>The conference unfolded through four roundtable discussions, each addressing critical intersections of AI and medical publishing. The first session explored strategic approaches to hospital research planning and AI's catalytic role in medical innovation. The second examined how academic journals can leverage AI to enhance editorial workflows and amplify the global influence of Chinese research. The third delved into institutional strategies for building interdisciplinary research clusters, with journals serving as key dissemination platforms. The concluding discussion identified systemic bottlenecks in translational research while championing cross-sector collaboration to bridge the gap between laboratory discoveries and clinical applications. Together, these dialogues mapped the complex ecosystem of challenges and solutions reshaping medical knowledge dissemination.</p><p>AI's transformative impact manifests across healthcare's clinical and academic dimensions. Beijing Children's Hospital, Capital Medical University demonstrated their “Futang Baichuan” pediatric AI system—A state-of-the-art model trained on 38 million research publications, 40,000+ clinical guidelines, and 80 years of institutional case data [<span>1</span>]. Beyond achieving 95% diagnostic concordance with senior specialists, its dedicated research module autonomously generates hypotheses by mining multimodal clinical data, creating a closed-loop system between bedside practice and bench research.</p><p>The publishing workflow is also being rapidly transformed by AI. Elsevier has launched its end-to-end Research Information Management System (RIMS) product, integrating literature management and data storage, boosting efficiency by 40% [<span>2</span>]. As for the scientific editing process, Dr. Yong Hu introduced a pilot study where large language models could complete most of pre-screening and basic editing tasks, albeit with a very low rate of hallucinated errors. AgentReview, a novel LLM-based simulation framework to analyze peer review dynamics, revealed a 37.1% decision variance due to reviewer biases while addressing privacy concerns and latent factors in the process [<span>3</span>].</p><p>As AI development accelerates exponentially, more people began to recognize the value of its true enabler—data. Medical d
2025年4月26日，第二届清华医学期刊创新大会在北京召开。会议以“人工智能驱动的学术：塑造下一个前沿”为主题，汇集了期刊编辑、医学研究人员和科学政策专家，探讨数据和人工智能（AI）如何重塑学术出版。两个主题演讲奠定了基础：第一个分析了新的期刊政策、数据基础设施和使能技术给医院研究带来的机会；第二部分介绍了通用人工智能的最新进展及其对学术出版安全和诚信的影响。会议通过四次圆桌讨论展开，每次讨论都涉及人工智能和医学出版的关键交叉点。第一场会议探讨了医院研究规划的战略方法和人工智能在医疗创新中的催化作用。第二项研究研究了学术期刊如何利用人工智能来加强编辑工作流程，并扩大中国研究的全球影响力。第三章探讨了建立跨学科研究集群的制度策略，期刊作为关键的传播平台。结论性讨论确定了转化研究中的系统性瓶颈，同时支持跨部门合作，以弥合实验室发现和临床应用之间的差距。这些对话共同描绘了重塑医学知识传播的挑战和解决方案的复杂生态系统。人工智能的变革性影响体现在医疗保健的临床和学术层面。首都医科大学北京儿童医院展示了他们的“福堂百川”儿科人工智能系统，这是一个最先进的模型，由3800万篇研究论文、4万多份临床指南和80年的机构病例数据训练而成。除了与资深专家达到95%的诊断一致性外，其专用研究模块通过挖掘多模式临床数据自主生成假设，在床边实践和实验室研究之间创建了一个闭环系统。人工智能也正在迅速改变出版工作流程。爱思唯尔推出了端到端研究信息管理系统（RIMS）产品，集成了文献管理和数据存储，将效率提高了40%。至于科学编辑过程，胡勇博士介绍了一项试点研究，大型语言模型可以完成大部分预筛选和基本编辑任务，尽管出现幻觉的错误率非常低。AgentReview是一个基于法学硕士的新型仿真框架，用于分析同行评议动态，在解决隐私问题和过程中的潜在因素bbb的同时，发现评议偏见导致的决策方差为37.1%。随着人工智能的发展呈指数级加速，越来越多的人开始认识到它真正的推动者——数据的价值。医学数据不再仅仅是研究的副产品，而是一项关键资产。数据论文的爆炸式增长支持了这一转变。数据论文——也称为数据描述符或数据集文章——是专注于数据集的详细描述、验证和潜在重用的学术出版物，而不是传统的假设驱动的结果。这些论文通常包括全面的元数据，数据收集和处理方法，以及便于再现的使用说明。例子包括爱思唯尔的Data in Brief期刊[4]和Nature的Scientific Data[5]。据Web of Science统计，截至2025年初，医学领域共发表了4800多篇数据论文，共被引用24.1万次，平均每篇文章被引用5.02次，而传统论文被引用2.8次。像爱思唯尔和施普林自然这样的领先出版商鼓励作者将他们的支持数据存储在公开可用的存储库中，或者在手稿或其他支持文件中报告这些数据。与此同时，国际科学、技术和医学出版商协会发布了“数据共享的12个最佳实践”，提出了评估学术影响的新标准。值得注意的是，数据重用正在成为一个关键指标，标志着从静态出版物到动态的、基于基础设施的科学的转变。本月早些时候，当美国国立卫生研究院（National Institutes of Health）突然限制中国访问其一些主要生物医学数据库时，控制生物医学数据访问的重要性变得清晰起来。这一举动凸显了中国10年前做出的决定的价值——通过中国科学院启动“科学数据库”计划。1989年至2017年期间，对NCBI数据库的使用迅速增长，中国研究人员约占所有访问量的15%。新的限制措施严重打击了中国的生物医学研究，尤其是依赖国际开放数据的项目。 然而，中国确实提前制定了卫生数据共享举措和措施来应对这些不可预见的挑战[7,8]。这也凸显了为什么中华人民共和国科学技术部早在2018年就开始通过《科学数据管理办法》将科学数据视为国家战略资源，到目前为止，中国已经建立了包括人口健康数据档案在内的20个国家科学数据中心。对于国家卫生健康委员会资助的项目，数据沉积率达到100%。在圆桌会议期间，与会者强烈支持建立一个针对特定疾病的医疗数据库国家联盟，以解决数据资源碎片化的问题。第二，与会者主张将数据论文纳入专业评价系统，包括在学术推广期间为此类出版物增加学分的可能性。第三，在提出人工智能预筛选工作流程的同时，人们一致认为该工具应该能够在本地运行（而不是在云上），并且最终的编辑决策应该始终依赖于人类专家。最后，构建自主的、可互操作的学术基础设施被确定为帮助中国发展具有全球竞争力的科学出版平台的长期战略目标。在地缘政治不确定性增加、人工智能和数据基础设施快速发展的推动下，医疗出版行业正处于十字路口。在会议上，与会者分享了机构如何通过更好的数据策略、人工智能支持的编辑系统和改进的国家平台来应对。这些共同的优先事项可能标志着医学出版发展的一个新阶段，对全球研究产生持久影响。尤武：构思（平等），写作-审编（平等）。王海波：观念（平等），资源（平等）。作者没有什么可报告的。作者没有什么可报告的。王海波教授是《卫生保健科学》编委会成员。为了尽量减少偏倚，他被排除在所有与接受这篇文章发表相关的编辑决策之外。其余的作者声明没有利益冲突。
{"title":"Redefining Medical Publishing in the Artificial Intelligence Era","authors":"You Wu, Haibo Wang","doi":"10.1002/hcs2.70026","DOIUrl":"https://doi.org/10.1002/hcs2.70026","url":null,"abstract":"<p>On April 26, 2025, the Second Tsinghua Medicine Journal Innovation Conference convened in Beijing. Centered on the theme “AI-driven Academic: Shaping the Next Frontier” the Conference brought together journal editors, medical researchers, and science policy experts to examine how data and artificial intelligence (AI) are reshaping scholarly publishing. Two keynote speeches set the stage: the first analyzed the opportunities for hospital-based research arising from new journal policies, data infrastructure, and enabling technologies; the second introduced the latest advances in general AI and their implications for academic publishing security and integrity.</p><p>The conference unfolded through four roundtable discussions, each addressing critical intersections of AI and medical publishing. The first session explored strategic approaches to hospital research planning and AI's catalytic role in medical innovation. The second examined how academic journals can leverage AI to enhance editorial workflows and amplify the global influence of Chinese research. The third delved into institutional strategies for building interdisciplinary research clusters, with journals serving as key dissemination platforms. The concluding discussion identified systemic bottlenecks in translational research while championing cross-sector collaboration to bridge the gap between laboratory discoveries and clinical applications. Together, these dialogues mapped the complex ecosystem of challenges and solutions reshaping medical knowledge dissemination.</p><p>AI's transformative impact manifests across healthcare's clinical and academic dimensions. Beijing Children's Hospital, Capital Medical University demonstrated their “Futang Baichuan” pediatric AI system—A state-of-the-art model trained on 38 million research publications, 40,000+ clinical guidelines, and 80 years of institutional case data [<span>1</span>]. Beyond achieving 95% diagnostic concordance with senior specialists, its dedicated research module autonomously generates hypotheses by mining multimodal clinical data, creating a closed-loop system between bedside practice and bench research.</p><p>The publishing workflow is also being rapidly transformed by AI. Elsevier has launched its end-to-end Research Information Management System (RIMS) product, integrating literature management and data storage, boosting efficiency by 40% [<span>2</span>]. As for the scientific editing process, Dr. Yong Hu introduced a pilot study where large language models could complete most of pre-screening and basic editing tasks, albeit with a very low rate of hallucinated errors. AgentReview, a novel LLM-based simulation framework to analyze peer review dynamics, revealed a 37.1% decision variance due to reviewer biases while addressing privacy concerns and latent factors in the process [<span>3</span>].</p><p>As AI development accelerates exponentially, more people began to recognize the value of its true enabler—data. Medical d","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"314-315"},"PeriodicalIF":3.3,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888519","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}
Fen Deng, Liru Pan, Lei Tao, Xiaoyu Qiu, Bing Li, Jing Hao, Huihui Li, Zhenzhen Zhang, Weiwei Ding, Yingying Wang, Bo Ning
<div> <section> <h3> Background</h3> <p>To comprehensively analyze the clinical characteristics of patients who underwent gastric endoscopic submucosal dissection (ESD) and explore the incidence and influencing factors of postoperative pain.</p> </section> <section> <h3> Methods</h3> <p>The clinical data of patients who underwent gastric ESD at our center from 2009 to 2024 were retrospectively analyzed. Pain severity was assessed using a visual analogue scale, with a score ≥ 4 defined as postoperative pain. Based on the presence or absence of postoperative pain, patients were divided into a pain group and a control group. Independent factors influencing postoperative pain were identified using multivariate logistic regression analysis. To control for confounding bias, patients in the case and control groups were matched by sex and lesion size, and the matched participants were further analyzed using a conditional logistic regression model.</p> </section> <section> <h3> Results</h3> <p>In total, 993 patients were analyzed. The incidence of postoperative pain was 9.1% (95% confidence interval [CI], 7.3–11.1). In the univariate analysis, sex, operation duration, anesthesia method, intraoperative electrocoagulation, nasogastric tube placement, and postoperative vomiting were significantly associated with postoperative pain. Multivariate analysis identified eight independent factors: male sex (odds ratio [OR], 0.61; 95% CI, 0.37–0.97; <i>p</i> = 0.04), operation duration (OR, 1.29; 95% CI, 1.03–1.63; <i>p</i> = 0.02), protuberant lesions (OR, 0.43; 95% CI, 0.26–0.71; <i>p</i> < 0.01), antral lesions (OR, 1.84; 95% CI, 1.10–3.05; <i>p</i> = 0.01), intubation general anesthesia (OR, 0.40; 95% CI, 0.22–0.72; <i>p</i> = 0.002), intraoperative electrocoagulation (OR, 0.32; 95% CI, 0.19–0.55; <i>p</i> < 0.01), nasogastric tube placement (OR, 2.005; 95% CI, 1.12–3.57; <i>p</i> = 0.01), and postoperative vomiting (OR, 3.24; 95% CI, 1.40–7.47; <i>p</i> = 0.005). Conditional logistic regression analysis further identified diabetes mellitus (OR, 2.50; 95% CI, 1.03–6.06; <i>p</i> = 0.04).</p> </section> <section> <h3> Conclusion</h3> <p>Female sex, diabetes mellitus, concave-type lesions, lesions in the gastric antrum, non-intubation general anesthesia, absence of intraoperative electrocoagulation, prolonged operation duration, nasogastric tube placement, and postoperative vomiting were independent factors associated with moderate to severe pain after gastric ESD. For patients at increased risk of postoperative pain, appropriate prophylactic and therapeutic m
背景综合分析胃内镜下粘膜下剥离术（ESD）患者的临床特点，探讨术后疼痛的发生率及影响因素。方法回顾性分析2009 ~ 2024年我院行胃ESD手术患者的临床资料。使用视觉模拟量表评估疼痛严重程度，评分≥4分定义为术后疼痛。根据有无术后疼痛，将患者分为疼痛组和对照组。采用多因素logistic回归分析确定影响术后疼痛的独立因素。为了控制混杂偏倚，病例组和对照组的患者按性别和病变大小进行匹配，并使用条件逻辑回归模型对匹配的参与者进行进一步分析。结果共分析993例患者。术后疼痛发生率为9.1%（95%可信区间[CI]， 7.3-11.1）。在单因素分析中，性别、手术时间、麻醉方式、术中电凝、鼻胃管放置和术后呕吐与术后疼痛显著相关。多因素分析确定了8个独立因素：男性（优势比[OR]， 0.61, 95% CI, 0.37-0.97, p = 0.04），手术时间（OR, 1.29, 95% CI, 1.03-1.63, p = 0.02），突出病变（OR, 0.43, 95% CI, 0.26-0.71, p = 0.01），胃窦病变（OR, 1.84, 95% CI, 1.10-3.05, p = 0.01），插管全麻（OR, 0.40, 95% CI, 0.22-0.72, p = 0.002），术中电凝（OR, 0.32, 95% CI, 0.19-0.55, p < 0.01），鼻胃管放置（OR, 2.005, p = 0.04）；95% ci, 1.12-3.57；p = 0.01)和术后呕吐（OR, 3.24; 95% CI, 1.40-7.47; p = 0.005）。条件logistic回归分析进一步确定了糖尿病（OR, 2.50; 95% CI, 1.03-6.06; p = 0.04）。结论女性、糖尿病、凹型病变、胃窦病变、非插管全麻、术中未电凝、手术时间延长、鼻胃管放置、术后呕吐是胃ESD术后中重度疼痛的独立影响因素。对于术后疼痛风险增高的患者，围手术期采取适当的预防和治疗措施可有效缓解胃ESD术后疼痛。
{"title":"Clinical Characteristics and Influencing Factors of Postoperative Pain in Patients Undergoing Gastric Endoscopic Submucosal Dissection","authors":"Fen Deng, Liru Pan, Lei Tao, Xiaoyu Qiu, Bing Li, Jing Hao, Huihui Li, Zhenzhen Zhang, Weiwei Ding, Yingying Wang, Bo Ning","doi":"10.1002/hcs2.70024","DOIUrl":"https://doi.org/10.1002/hcs2.70024","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To comprehensively analyze the clinical characteristics of patients who underwent gastric endoscopic submucosal dissection (ESD) and explore the incidence and influencing factors of postoperative pain.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The clinical data of patients who underwent gastric ESD at our center from 2009 to 2024 were retrospectively analyzed. Pain severity was assessed using a visual analogue scale, with a score ≥ 4 defined as postoperative pain. Based on the presence or absence of postoperative pain, patients were divided into a pain group and a control group. Independent factors influencing postoperative pain were identified using multivariate logistic regression analysis. To control for confounding bias, patients in the case and control groups were matched by sex and lesion size, and the matched participants were further analyzed using a conditional logistic regression model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In total, 993 patients were analyzed. The incidence of postoperative pain was 9.1% (95% confidence interval [CI], 7.3–11.1). In the univariate analysis, sex, operation duration, anesthesia method, intraoperative electrocoagulation, nasogastric tube placement, and postoperative vomiting were significantly associated with postoperative pain. Multivariate analysis identified eight independent factors: male sex (odds ratio [OR], 0.61; 95% CI, 0.37–0.97; <i>p</i> = 0.04), operation duration (OR, 1.29; 95% CI, 1.03–1.63; <i>p</i> = 0.02), protuberant lesions (OR, 0.43; 95% CI, 0.26–0.71; <i>p</i> < 0.01), antral lesions (OR, 1.84; 95% CI, 1.10–3.05; <i>p</i> = 0.01), intubation general anesthesia (OR, 0.40; 95% CI, 0.22–0.72; <i>p</i> = 0.002), intraoperative electrocoagulation (OR, 0.32; 95% CI, 0.19–0.55; <i>p</i> < 0.01), nasogastric tube placement (OR, 2.005; 95% CI, 1.12–3.57; <i>p</i> = 0.01), and postoperative vomiting (OR, 3.24; 95% CI, 1.40–7.47; <i>p</i> = 0.005). Conditional logistic regression analysis further identified diabetes mellitus (OR, 2.50; 95% CI, 1.03–6.06; <i>p</i> = 0.04).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Female sex, diabetes mellitus, concave-type lesions, lesions in the gastric antrum, non-intubation general anesthesia, absence of intraoperative electrocoagulation, prolonged operation duration, nasogastric tube placement, and postoperative vomiting were independent factors associated with moderate to severe pain after gastric ESD. For patients at increased risk of postoperative pain, appropriate prophylactic and therapeutic m","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"289-298"},"PeriodicalIF":3.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888447","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}
Young-Myoung Lim, Ah-Ram Kim, Seung-Ju Lim, Ji-Hyuk Park
Background
In this study, we aimed to validate and test the reliability of the Yonsei lifestyle profile (YLP) in assessing multifaceted health lifestyle levels in a study population from the United States.
Methods
The YLP-English version and health-promoting lifestyle profile II were administered to 100 individuals living in the United States. Concurrent validity was analyzed using Pearson's correlation coefficient, and discriminant validity was examined by comparing sex and age differences through t-tests and multiple variance analysis. Internal consistency was assessed using Cronbach's α for each sub-factor.
Results
The YLP-English Version demonstrated concurrent validity with the Health-Promoting Lifestyle Profile II, showing consistent correlations for the total score (0.3, p < 0.01) and frequency sub-factors (0.25–0.69, p < 0.01). Among the satisfaction sub-factors, only nutrition showed a weak negative correlation (−0.19, p < 0.01); all others were nonsignificant. Discriminant validity revealed no significant sex differences, but physical activity frequency varied across age groups. Internal consistency was high (Cronbach's α = 0.80–0.86).
Conclusion
In this study, we validated the YLP-English version as a reliable instrument for assessing health-related lifestyle behaviors. The YLP uniquely captures both lifestyle frequency and satisfaction, offering a comprehensive perspective on health behaviors. Although this tool is currently most applicable in population-level studies, future research should establish clinical thresholds to enhance its utility in individualized health assessments and interventions.
{"title":"Validation and Reliability Testing of the Yonsei Lifestyle Profile for Assessing Multifaceted Health Lifestyles","authors":"Young-Myoung Lim, Ah-Ram Kim, Seung-Ju Lim, Ji-Hyuk Park","doi":"10.1002/hcs2.70023","DOIUrl":"https://doi.org/10.1002/hcs2.70023","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In this study, we aimed to validate and test the reliability of the Yonsei lifestyle profile (YLP) in assessing multifaceted health lifestyle levels in a study population from the United States.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The YLP-English version and health-promoting lifestyle profile II were administered to 100 individuals living in the United States. Concurrent validity was analyzed using Pearson's correlation coefficient, and discriminant validity was examined by comparing sex and age differences through <i>t</i>-tests and multiple variance analysis. Internal consistency was assessed using Cronbach's α for each sub-factor.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The YLP-English Version demonstrated concurrent validity with the Health-Promoting Lifestyle Profile II, showing consistent correlations for the total score (0.3, <i>p</i> < 0.01) and frequency sub-factors (0.25–0.69, <i>p</i> < 0.01). Among the satisfaction sub-factors, only nutrition showed a weak negative correlation (−0.19, <i>p</i> < 0.01); all others were nonsignificant. Discriminant validity revealed no significant sex differences, but physical activity frequency varied across age groups. Internal consistency was high (Cronbach's <i>α</i> = 0.80–0.86).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>In this study, we validated the YLP-English version as a reliable instrument for assessing health-related lifestyle behaviors. The YLP uniquely captures both lifestyle frequency and satisfaction, offering a comprehensive perspective on health behaviors. Although this tool is currently most applicable in population-level studies, future research should establish clinical thresholds to enhance its utility in individualized health assessments and interventions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"243-249"},"PeriodicalIF":3.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888493","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}
Wolmark Xiques-Molina, Ivan David Lozada-Martinez, Ornella Fiorillo-Moreno, Alexis Narvaez-Rojas
<p>Breast cancer is the leading cause of cancer-related mortality in women globally, with its incidence continuing to rise, particularly in low- and middle-income countries, presenting a significant public health challenge worldwide [<span>1</span>]. According to data from the Institute for Health Metrics and Evaluation (IHME) and the World Health Organization (WHO), the gap in access to healthcare services between high- and low-income countries contributes to delayed detection, increased incidence of advanced-stage disease, and, consequently, higher mortality rates (up to 50% higher compared to high-income countries) [<span>1, 2</span>]. This translates into inequalities in access to screening and early diagnosis methods, which exacerbate the burden of this disease in low-resource settings where infrastructure, funding, and access to trained professionals are limited [<span>3</span>]. These limitations hinder the implementation of resource-dependent strategies required to achieve evidence-based outcomes, such as clinical breast exams (which necessitate trained personnel) or screening mammography (which requires appropriate infrastructure and trained specialists with adequate operator concordance) [<span>4</span>].</p><p>The use of artificial intelligence (AI) and emerging health technologies, particularly in the field of breast cancer screening, has shown to significantly enhance diagnostic accuracy and reduce operational costs in delivering comprehensive breast health services [<span>5</span>]. For instance, AI enables the development of low-cost imaging analysis systems, such as for mammograms and ultrasounds, that can be implemented in resource-limited settings [<span>5</span>]. Recent evidence suggests that these technologies can match or even exceed the diagnostic accuracy of radiologists in detecting suspicious lesions, a critical advancement in regions facing a shortage of these professionals [<span>6</span>].</p><p>A common limitation in low- and middle-income countries is the presence of cultural and social barriers, often related to the preferences, values, and needs of women [<span>7</span>]. In ancestral, conservative, and vulnerable communities, there is a notable level of mistrust and resistance toward certain interventions, primarily when these do not account for factors that benefit their communities [<span>7</span>]. Integrating women's values and preferences is essential for the success of any public health program. Previous research has indicated that women in these communities prefer noninvasive methods that reduce pain and minimize the risk of unnecessary radiation exposure [<span>7</span>]. AI-based technologies can personalize the screening experience, making it less invasive and more aligned with patient needs, thereby enhancing acceptability and adherence [<span>5</span>]. This approach can help overcome barriers such as language, physical exposure, direct palpation, among others, which strengthens trust and demonstrates
{"title":"Noninvasive Breast Cancer Screening Strategies Supported by AI-Based Technologies in Resource-Limited Settings: Is It the Best Opportunity to Strengthen Women's Preferences, Values and Acceptability?","authors":"Wolmark Xiques-Molina, Ivan David Lozada-Martinez, Ornella Fiorillo-Moreno, Alexis Narvaez-Rojas","doi":"10.1002/hcs2.70025","DOIUrl":"https://doi.org/10.1002/hcs2.70025","url":null,"abstract":"<p>Breast cancer is the leading cause of cancer-related mortality in women globally, with its incidence continuing to rise, particularly in low- and middle-income countries, presenting a significant public health challenge worldwide [<span>1</span>]. According to data from the Institute for Health Metrics and Evaluation (IHME) and the World Health Organization (WHO), the gap in access to healthcare services between high- and low-income countries contributes to delayed detection, increased incidence of advanced-stage disease, and, consequently, higher mortality rates (up to 50% higher compared to high-income countries) [<span>1, 2</span>]. This translates into inequalities in access to screening and early diagnosis methods, which exacerbate the burden of this disease in low-resource settings where infrastructure, funding, and access to trained professionals are limited [<span>3</span>]. These limitations hinder the implementation of resource-dependent strategies required to achieve evidence-based outcomes, such as clinical breast exams (which necessitate trained personnel) or screening mammography (which requires appropriate infrastructure and trained specialists with adequate operator concordance) [<span>4</span>].</p><p>The use of artificial intelligence (AI) and emerging health technologies, particularly in the field of breast cancer screening, has shown to significantly enhance diagnostic accuracy and reduce operational costs in delivering comprehensive breast health services [<span>5</span>]. For instance, AI enables the development of low-cost imaging analysis systems, such as for mammograms and ultrasounds, that can be implemented in resource-limited settings [<span>5</span>]. Recent evidence suggests that these technologies can match or even exceed the diagnostic accuracy of radiologists in detecting suspicious lesions, a critical advancement in regions facing a shortage of these professionals [<span>6</span>].</p><p>A common limitation in low- and middle-income countries is the presence of cultural and social barriers, often related to the preferences, values, and needs of women [<span>7</span>]. In ancestral, conservative, and vulnerable communities, there is a notable level of mistrust and resistance toward certain interventions, primarily when these do not account for factors that benefit their communities [<span>7</span>]. Integrating women's values and preferences is essential for the success of any public health program. Previous research has indicated that women in these communities prefer noninvasive methods that reduce pain and minimize the risk of unnecessary radiation exposure [<span>7</span>]. AI-based technologies can personalize the screening experience, making it less invasive and more aligned with patient needs, thereby enhancing acceptability and adherence [<span>5</span>]. This approach can help overcome barriers such as language, physical exposure, direct palpation, among others, which strengthens trust and demonstrates","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"310-313"},"PeriodicalIF":3.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888494","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}
The risk of internal fixation failure remains relatively high in stable femoral neck fracture (FNF) (Garden I or II). Preoperative sagittal displacement of the femoral head has been proposed as a potential influencing factor. This study aimed to evaluate the impact of sagittal displacement on the outcomes of cannulated screw internal fixation (CSIF) in patients with stable FNF (Garden I or II) by reconstructing the axial sagittal oblique plane of the fracture using preoperative computed tomography (CT) imaging.
Methods
This study included 167 patients with FNF who underwent CSIF. The sagittal tilt angle of the femoral head (STAFH) was evaluated using three-dimensional CT (3D-CT). The distribution of preoperative STAFH was analyzed, and its independent association with treatment failure was assessed. Treatment failure was defined as the need for revision surgery within 2 years postoperatively due to avascular necrosis, nonunion, or internal fixation failure.
Results
Among the 167 patients, 9 (5.4%) exhibited anterior tilt (AT) of the femoral head, 158 (94.60%) presented with posterior tilt (PT). A total of 50 patients (29.9%) demonstrated excessive sagittal displacement (AT ≥ 10° or PT ≥ 20°). In the failure group, 80.0% of patients had excessive sagittal displacement compared to 28.1% in the healed group. Excessive sagittal displacement was significantly associated with an increased risk of surgical failure (odds ratio: 11.953, 95% CI: 3.656–39.083, p < 0.05).
Conclusions
In patients with Garden I or II FNF, greater preoperative sagittal displacement of the femoral head was correlated with a higher likelihood of CSIF failure. AT ≥ 10° or PT ≥ 20° were identified as independent predictors of CSIF failure in FNF patients. Nevertheless, these findings still require confirmation through prospective, multi-center clinical trials with large sample sizes.
{"title":"The Failure Rate of Internal Fixation Increases With Sagittal Displacement of the Femoral Head: A Retrospective Study","authors":"Lei Shi, Chen Chen, Junsong Wang, Yuanhao Wu, Jia Li, Houchen Lyu, Quanyi Guo, Peifu Tang","doi":"10.1002/hcs2.70022","DOIUrl":"https://doi.org/10.1002/hcs2.70022","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The risk of internal fixation failure remains relatively high in stable femoral neck fracture (FNF) (Garden I or II). Preoperative sagittal displacement of the femoral head has been proposed as a potential influencing factor. This study aimed to evaluate the impact of sagittal displacement on the outcomes of cannulated screw internal fixation (CSIF) in patients with stable FNF (Garden I or II) by reconstructing the axial sagittal oblique plane of the fracture using preoperative computed tomography (CT) imaging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study included 167 patients with FNF who underwent CSIF. The sagittal tilt angle of the femoral head (STAFH) was evaluated using three-dimensional CT (3D-CT). The distribution of preoperative STAFH was analyzed, and its independent association with treatment failure was assessed. Treatment failure was defined as the need for revision surgery within 2 years postoperatively due to avascular necrosis, nonunion, or internal fixation failure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among the 167 patients, 9 (5.4%) exhibited anterior tilt (AT) of the femoral head, 158 (94.60%) presented with posterior tilt (PT). A total of 50 patients (29.9%) demonstrated excessive sagittal displacement (AT ≥ 10° or PT ≥ 20°). In the failure group, 80.0% of patients had excessive sagittal displacement compared to 28.1% in the healed group. Excessive sagittal displacement was significantly associated with an increased risk of surgical failure (odds ratio: 11.953, 95% CI: 3.656–39.083, <i>p</i> < 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In patients with Garden I or II FNF, greater preoperative sagittal displacement of the femoral head was correlated with a higher likelihood of CSIF failure. AT ≥ 10° or PT ≥ 20° were identified as independent predictors of CSIF failure in FNF patients. Nevertheless, these findings still require confirmation through prospective, multi-center clinical trials with large sample sizes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 4","pages":"250-258"},"PeriodicalIF":3.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888520","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}
Haolin Shen, Yuegui Wang, Jianmei Liao, Xianbo Zuo, Bo Zhang, Xiao Yang
Background
To evaluate sex-related differences in the risk factors associated with nonhealing or recurrence of hyperthyroidism (NHRH) in patients with Graves' disease (GD) treated with radioactive iodine.
Methods
In total, 285 patients were enrolled. Data on radioactive iodine (RAI) dosage, ultrasound indexes of the thyroid, and other clinical factors were collected. Patients were divided into NHRH and non-NHRH (hypothyroidism or euthyroidism) groups based on treatment outcomes. Univariate and multivariate weighted logistic regression analyses were used to identify factors associated with NHRH. Sex-specific analyses of these risk factors were also conducted.
Results
There were no significant differences between the two groups in terms of sex, thyroid shear wave elastography velocity values, or pretreatment serum free thyroxine (FT4) levels. Thyroid volume and age were independently associated with NHRH, with the odds of NHRH gradually decreasing as age increased. In subgroup analyses, both age and thyroid volume were independent risk factors for NHRH in female patients (p < 0.05), while in male patients, only FT4 was independently associated with NHRH (p < 0.05).
Conclusions
In patients of different sexes, the influence of thyroid volume, age, and FT4 on treatment outcomes exhibits distinct patterns.
{"title":"Sex-Related Differences in Risk Factors Associated With Nonhealing or Recurrence of Hyperthyroidism in Patients With Graves' Disease Treated With Radioactive Iodine","authors":"Haolin Shen, Yuegui Wang, Jianmei Liao, Xianbo Zuo, Bo Zhang, Xiao Yang","doi":"10.1002/hcs2.70021","DOIUrl":"https://doi.org/10.1002/hcs2.70021","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To evaluate sex-related differences in the risk factors associated with nonhealing or recurrence of hyperthyroidism (NHRH) in patients with Graves' disease (GD) treated with radioactive iodine.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In total, 285 patients were enrolled. Data on radioactive iodine (RAI) dosage, ultrasound indexes of the thyroid, and other clinical factors were collected. Patients were divided into NHRH and non-NHRH (hypothyroidism or euthyroidism) groups based on treatment outcomes. Univariate and multivariate weighted logistic regression analyses were used to identify factors associated with NHRH. Sex-specific analyses of these risk factors were also conducted.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>There were no significant differences between the two groups in terms of sex, thyroid shear wave elastography velocity values, or pretreatment serum free thyroxine (FT4) levels. Thyroid volume and age were independently associated with NHRH, with the odds of NHRH gradually decreasing as age increased. In subgroup analyses, both age and thyroid volume were independent risk factors for NHRH in female patients (<i>p</i> < 0.05), while in male patients, only FT4 was independently associated with NHRH (<i>p</i> < 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In patients of different sexes, the influence of thyroid volume, age, and FT4 on treatment outcomes exhibits distinct patterns.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 3","pages":"188-194"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367498","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}
Having a primary care usual source of care (USC) is associated with better population health outcomes. However, the percent of adults in the United States (US) with a usual primary care provider is declining. We sought to identify factors associated with establishing a USC at an urgent care clinic or emergency department as opposed to primary care.
Methods
We analyzed data from 57,152 participants in the All of Us study who reported having a USC. We used the Andersen Behavioral Model of Health Services Use framework and multivariable logistic regression to examine associations among predisposing, enabling, and need factors, according to the source of usual care.
Results
An urgent care clinic, minute clinic, or emergency department was the source of usual care for 6.3% of our sample. The odds of seeking care at this type of facility increased with younger age, lower educational attainment, and better health status. Black and Hispanic individuals, as well as those who reported experiencing discrimination in medical settings or that their provider was of a different race and ethnicity, were also less likely to have a primary care USC. Financial concerns, being anxious about seeing a provider, and the inability to take time off from work also increased the likelihood of having a non-primary care USC.
Conclusions
Improving the rates of having a primary care USC among younger and healthy adults may be achievable through policies that can improve access to convenient, affordable primary care. Efforts to improve diversity among primary care providers and reduce discrimination experienced by patients may also improve the USC rates for racial and ethnic minority groups.
{"title":"Examining Reasons for Using Non-Primary Care Providers as Usual Source of Health Care: Insights From the All of Us Study","authors":"Abbey Gregg, Hui Wang, Brankeciara Ard, Marcelo Takejame Galafassi, Maryam Bidgoli","doi":"10.1002/hcs2.70020","DOIUrl":"https://doi.org/10.1002/hcs2.70020","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Having a primary care usual source of care (USC) is associated with better population health outcomes. However, the percent of adults in the United States (US) with a usual primary care provider is declining. We sought to identify factors associated with establishing a USC at an urgent care clinic or emergency department as opposed to primary care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed data from 57,152 participants in the <i>All of Us</i> study who reported having a USC. We used the Andersen Behavioral Model of Health Services Use framework and multivariable logistic regression to examine associations among predisposing, enabling, and need factors, according to the source of usual care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>An urgent care clinic, minute clinic, or emergency department was the source of usual care for 6.3% of our sample. The odds of seeking care at this type of facility increased with younger age, lower educational attainment, and better health status. Black and Hispanic individuals, as well as those who reported experiencing discrimination in medical settings or that their provider was of a different race and ethnicity, were also less likely to have a primary care USC. Financial concerns, being anxious about seeing a provider, and the inability to take time off from work also increased the likelihood of having a non-primary care USC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Improving the rates of having a primary care USC among younger and healthy adults may be achievable through policies that can improve access to convenient, affordable primary care. Efforts to improve diversity among primary care providers and reduce discrimination experienced by patients may also improve the USC rates for racial and ethnic minority groups.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 3","pages":"195-205"},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367492","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}
Nidha Shapoo, Naveed Shapoo, Abdul Rehman, Noella Boma
Digital health is transforming healthcare by integrating advanced technologies to make healthcare more accessible, efficient, and personalized. From electronic health records, telemedicine, wearable devices, and artificial intelligence to the recent smart hospitals, digital health is improving patient care and outcomes while reducing healthcare costs. However, the integration of digital health faces several challenges, including data privacy, cybersecurity risks, and inequitable access to technology. This article provides an overview of the current state of digital health, key challenges in implementation, and potential solutions to maximize the benefits of digital health and ensure efficient, equitable, and patient-centered healthcare in the future.
{"title":"Smart Healthcare: The Role of Digital Health in Modern Medicine","authors":"Nidha Shapoo, Naveed Shapoo, Abdul Rehman, Noella Boma","doi":"10.1002/hcs2.70019","DOIUrl":"https://doi.org/10.1002/hcs2.70019","url":null,"abstract":"<p>Digital health is transforming healthcare by integrating advanced technologies to make healthcare more accessible, efficient, and personalized. From electronic health records, telemedicine, wearable devices, and artificial intelligence to the recent smart hospitals, digital health is improving patient care and outcomes while reducing healthcare costs. However, the integration of digital health faces several challenges, including data privacy, cybersecurity risks, and inequitable access to technology. This article provides an overview of the current state of digital health, key challenges in implementation, and potential solutions to maximize the benefits of digital health and ensure efficient, equitable, and patient-centered healthcare in the future.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 3","pages":"179-187"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367260","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}
Muhammad Khalid Anser, Agha Amad Nabi, Ishfaq Ahmad, Muhammad Moinuddin Qazi Abro, Khalid Zaman
An individual's mental health influences their capacity to think effectively, feel emotionally stable, and perform daily activities. As mental health concerns become more prevalent worldwide, new awareness and diagnostic and treatment tactics are needed. Digital tools and technology are helping solve these problems by providing scalable, tailored solutions for large populations. This detailed review examines mental health-promoting internet tools. Smartphone applications, web-based therapy systems, wearable tech, artificial intelligence-powered resources, and virtual reality (VR) technologies were evaluated for efficacy and side effects. PubMed, PsycINFO, Scopus, IEEE Xplore, and Google Scholar were carefully searched. Search terms included “digital mental health tools,” “online therapy,” and “AI in mental health.” Randomized controlled trials, cohort studies, cross-sectional studies, systematic reviews, and meta-analyses of digital technology and mental health were included from among the literature published after 2010. Cognitive behavioral therapy methods, mood monitoring, and mindfulness exercises are among the numerous features of smartphone applications that have been demonstrated to mitigate symptoms of anxiety, depression, and tension. Online therapy platforms let marginalized individuals obtain therapy remotely. Wearable technology may detect heart rate, blood pressure, and sleep length, which may reveal mental health difficulties. Chatbots employ machine learning algorithms and natural language processing to deliver customized support and show promise for quick intervention. Exposure therapy for anxiety and trauma is increasingly using virtual reality environments. Although digital mental health therapies face challenges in relation to data privacy, limited long-term efficacy, and technological inequality, digital technologies are modernizing mental healthcare. By offering inexpensive and effective alternatives to traditional therapies, digital technologies may help healthcare systems meet the growing demand for mental health services and overall well-being.
{"title":"Advancing Mental Health Care: A Comprehensive Review of Digital Tools and Technologies for Enhancing Diagnosis, Treatment, and Wellness","authors":"Muhammad Khalid Anser, Agha Amad Nabi, Ishfaq Ahmad, Muhammad Moinuddin Qazi Abro, Khalid Zaman","doi":"10.1002/hcs2.70018","DOIUrl":"https://doi.org/10.1002/hcs2.70018","url":null,"abstract":"<p>An individual's mental health influences their capacity to think effectively, feel emotionally stable, and perform daily activities. As mental health concerns become more prevalent worldwide, new awareness and diagnostic and treatment tactics are needed. Digital tools and technology are helping solve these problems by providing scalable, tailored solutions for large populations. This detailed review examines mental health-promoting internet tools. Smartphone applications, web-based therapy systems, wearable tech, artificial intelligence-powered resources, and virtual reality (VR) technologies were evaluated for efficacy and side effects. PubMed, PsycINFO, Scopus, IEEE Xplore, and Google Scholar were carefully searched. Search terms included “digital mental health tools,” “online therapy,” and “AI in mental health.” Randomized controlled trials, cohort studies, cross-sectional studies, systematic reviews, and meta-analyses of digital technology and mental health were included from among the literature published after 2010. Cognitive behavioral therapy methods, mood monitoring, and mindfulness exercises are among the numerous features of smartphone applications that have been demonstrated to mitigate symptoms of anxiety, depression, and tension. Online therapy platforms let marginalized individuals obtain therapy remotely. Wearable technology may detect heart rate, blood pressure, and sleep length, which may reveal mental health difficulties. Chatbots employ machine learning algorithms and natural language processing to deliver customized support and show promise for quick intervention. Exposure therapy for anxiety and trauma is increasingly using virtual reality environments. Although digital mental health therapies face challenges in relation to data privacy, limited long-term efficacy, and technological inequality, digital technologies are modernizing mental healthcare. By offering inexpensive and effective alternatives to traditional therapies, digital technologies may help healthcare systems meet the growing demand for mental health services and overall well-being.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 3","pages":"163-178"},"PeriodicalIF":0.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367259","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}
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