Pub Date : 2025-05-01Epub Date: 2025-04-23DOI: 10.1007/s12553-025-00969-5
Andrew Thomas Reyes, Dion Candelaria, Reimund Serafica, Janett A Hildebrand, Marysol Cacciata, Axel Santa Maria, Jung-Ah Lee, Anna Strömberg, Lorraine S Evangelista
Purpose: New research shows the benefits of mobile health (mHealth) interventions for older adults. However, older adults adopt digital technology less than younger ones. This study measures the task effectiveness, perceived usability, and acceptability of a mHealth intervention (i.e., Get FIT +) consisting of a wearable activity tracker, access to the MyFitnessPal app, and personalized text messages to promote healthy behaviors in older adults.
Methods: Participants used the Get FIT + intervention for 12 weeks and engaged in monthly clinic visits with an advanced practice nurse (APRN) to monitor their progress. The monthly sessions instructed them to use the think-aloud process while doing specific tasks (e.g., using the app). Participants also completed the USABILITY Survey and provided feedback on the intervention's acceptability after the 12-week trial.
Results: Thirty older adults (mean age 66.6 ± 5.9 years, 60% female, 60% married, 50% Asian, 37% White, and 13% Hispanic) participated in this sub-analysis. Participants were able to complete the assigned tasks efficiently. The usability satisfaction assessment suggests a high level of satisfaction. The participants responded positively to Get FIT + and successfully incorporated it into their routines.
Conclusions: Our findings show that Get FIT + technologies, including smartphones, smartphone-based applications, and integrated sensors, are practical, usable, and acceptable for older adults at risk for cardiovascular disease. These scalable, low-cost technologies offer methods to monitor and promote a healthy lifestyle and enhance overall well-being.
目的：新的研究显示了移动医疗（mHealth）干预措施对老年人的益处。然而，老年人比年轻人更少使用数字技术。本研究测量了移动健康干预（即Get FIT +）的任务有效性、感知可用性和可接受性，该干预包括可穿戴活动跟踪器、MyFitnessPal应用程序的访问和个性化短信，以促进老年人的健康行为。方法：参与者使用Get FIT +干预12周，并与高级执业护士（APRN）每月进行门诊访问，以监测其进展。每月的课程指导他们在做特定任务时（例如，使用应用程序）使用有声思维过程。参与者还完成了可用性调查，并在12周的试验后对干预的可接受性提供了反馈。结果：30名老年人（平均年龄66.6±5.9岁，60%为女性，60%为已婚，50%为亚洲人，37%为白人，13%为西班牙裔）参与了这一亚组分析。参与者能够有效地完成分配的任务。可用性满意度评估表明了高水平的满意度。参与者对Get FIT +反应积极，并成功地将其纳入日常生活中。结论：我们的研究结果表明，Get FIT +技术，包括智能手机、基于智能手机的应用程序和集成传感器，对于有心血管疾病风险的老年人来说是实用、可用和可接受的。这些可扩展的低成本技术提供了监测和促进健康生活方式并提高整体福祉的方法。
{"title":"Task effectiveness, usability, and acceptability of mHealth technologies among older adults at risk for cardiovascular disease: a feasibility study.","authors":"Andrew Thomas Reyes, Dion Candelaria, Reimund Serafica, Janett A Hildebrand, Marysol Cacciata, Axel Santa Maria, Jung-Ah Lee, Anna Strömberg, Lorraine S Evangelista","doi":"10.1007/s12553-025-00969-5","DOIUrl":"10.1007/s12553-025-00969-5","url":null,"abstract":"<p><strong>Purpose: </strong>New research shows the benefits of mobile health (mHealth) interventions for older adults. However, older adults adopt digital technology less than younger ones. This study measures the task effectiveness, perceived usability, and acceptability of a mHealth intervention (i.e., <i>Get FIT</i> +) consisting of a wearable activity tracker, access to the <i>MyFitnessPal</i> app, and personalized text messages to promote healthy behaviors in older adults.</p><p><strong>Methods: </strong>Participants used the <i>Get FIT</i> + intervention for 12 weeks and engaged in monthly clinic visits with an advanced practice nurse (APRN) to monitor their progress. The monthly sessions instructed them to use the think-aloud process while doing specific tasks (e.g., using the app). Participants also completed the USABILITY Survey and provided feedback on the intervention's acceptability after the 12-week trial.</p><p><strong>Results: </strong>Thirty older adults (mean age 66.6 ± 5.9 years, 60% female, 60% married, 50% Asian, 37% White, and 13% Hispanic) participated in this sub-analysis. Participants were able to complete the assigned tasks efficiently. The usability satisfaction assessment suggests a high level of satisfaction. The participants responded positively to <i>Get FIT</i> + and successfully incorporated it into their routines.</p><p><strong>Conclusions: </strong>Our findings show that <i>Get FIT</i> + technologies, including smartphones, smartphone-based applications, and integrated sensors, are practical, usable, and acceptable for older adults at risk for cardiovascular disease. These scalable, low-cost technologies offer methods to monitor and promote a healthy lifestyle and enhance overall well-being.</p>","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"15 3","pages":"531-538"},"PeriodicalIF":2.8,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12392979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951528","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}
Pub Date : 2025-01-01Epub Date: 2025-04-25DOI: 10.1007/s12553-025-00970-y
Nebil Achour, Tomas Zapata, Yousef Saleh, Barbara Pierscionek, Natasha Azzopardi-Muscat, David Novillo-Ortiz, Cathal Morgan, Mafaten Chaouali
Purpose: This study aims to explore the application of Artificial intelligence (AI) systems in radiology departments and the role they play in the shortage of radiologists. It examines the ethical and legal considerations for uptake of AI both in relation to patient safety and for the profession of radiology.
Methods: A systematised review was selected for this research study to collect maximum relevant evidence that provides a comprehensive overview of AI application in radiology specifically in terms of addressing radiologist shortages in hospitals. The search was complemented by grey literature to fill potential gaps.
Results: Findings suggest that AI can read and interpret images more effectively and faster than radiologists and that it could be more widely used to reduce the impact of the global radiologist shortage, leading to better patient outcomes and safety. However, there are potential challenges predominantly ethical and legal. Concerns over complete radiologist replacement by AI do not currently seem likely, but rather the use of AI to complement radiologists in their work.
Conclusions: AI cannot replace radiologists, instead radiology services will need the input of radiologists, AI systems and radiographers to provide a safe healthcare for all patients, therefore they are complementary. Radiologist jobs will most probably change to reduce repetitive tasks that can be conducted by AI. Radiologists and radiographers play a role in the provision of quality care in both normal day-to-day events and during times of disaster. Their role in diagnosing and prognosing diseases provides guidance during preparedness, response and recovery.
{"title":"The role of AI in mitigating the impact of radiologist shortages: a systematised review.","authors":"Nebil Achour, Tomas Zapata, Yousef Saleh, Barbara Pierscionek, Natasha Azzopardi-Muscat, David Novillo-Ortiz, Cathal Morgan, Mafaten Chaouali","doi":"10.1007/s12553-025-00970-y","DOIUrl":"10.1007/s12553-025-00970-y","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to explore the application of Artificial intelligence (AI) systems in radiology departments and the role they play in the shortage of radiologists. It examines the ethical and legal considerations for uptake of AI both in relation to patient safety and for the profession of radiology.</p><p><strong>Methods: </strong>A systematised review was selected for this research study to collect maximum relevant evidence that provides a comprehensive overview of AI application in radiology specifically in terms of addressing radiologist shortages in hospitals. The search was complemented by grey literature to fill potential gaps.</p><p><strong>Results: </strong>Findings suggest that AI can read and interpret images more effectively and faster than radiologists and that it could be more widely used to reduce the impact of the global radiologist shortage, leading to better patient outcomes and safety. However, there are potential challenges predominantly ethical and legal. Concerns over complete radiologist replacement by AI do not currently seem likely, but rather the use of AI to complement radiologists in their work.</p><p><strong>Conclusions: </strong>AI cannot replace radiologists, instead radiology services will need the input of radiologists, AI systems and radiographers to provide a safe healthcare for all patients, therefore they are complementary. Radiologist jobs will most probably change to reduce repetitive tasks that can be conducted by AI. Radiologists and radiographers play a role in the provision of quality care in both normal day-to-day events and during times of disaster. Their role in diagnosing and prognosing diseases provides guidance during preparedness, response and recovery.</p>","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"15 3","pages":"489-501"},"PeriodicalIF":3.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12085355/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144101783","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}
Pub Date : 2024-01-10DOI: 10.1007/s12553-024-00814-1
Yanting Wu, Yawen Li, Andrius Baskys, J. Chok, Janice Hoffman, Don Roosan
{"title":"Health disparity in digital health technology design","authors":"Yanting Wu, Yawen Li, Andrius Baskys, J. Chok, Janice Hoffman, Don Roosan","doi":"10.1007/s12553-024-00814-1","DOIUrl":"https://doi.org/10.1007/s12553-024-00814-1","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"53 9","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139441197","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}
Pub Date : 2024-01-09DOI: 10.1007/s12553-023-00797-5
Lubna Altarawneh, Hao Wang, Yu Jin
{"title":"COVID-19 vaccine prediction based on an interpretable CNN-LSTM model with three-stage feature engineering","authors":"Lubna Altarawneh, Hao Wang, Yu Jin","doi":"10.1007/s12553-023-00797-5","DOIUrl":"https://doi.org/10.1007/s12553-023-00797-5","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"6 7","pages":"1-21"},"PeriodicalIF":2.5,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139443806","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}
Pub Date : 2024-01-09DOI: 10.1007/s12553-023-00811-w
Caroline Valentini, F. Martins, A. A. D. de Sá, E. Naves
{"title":"Training protocol for driving power wheelchairs using virtual environment: preliminary results from a pilot study","authors":"Caroline Valentini, F. Martins, A. A. D. de Sá, E. Naves","doi":"10.1007/s12553-023-00811-w","DOIUrl":"https://doi.org/10.1007/s12553-023-00811-w","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"41 22","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139442359","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}
Pub Date : 2024-01-05DOI: 10.1007/s12553-023-00807-6
Ninni Singh, Vinit Kumar Gunjan, F. Shaik, Sudipta Roy
{"title":"Detection of Cardio Vascular abnormalities using gradient descent optimization and CNN","authors":"Ninni Singh, Vinit Kumar Gunjan, F. Shaik, Sudipta Roy","doi":"10.1007/s12553-023-00807-6","DOIUrl":"https://doi.org/10.1007/s12553-023-00807-6","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"51 47","pages":"1-14"},"PeriodicalIF":2.5,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139382144","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}
Pub Date : 2023-12-29DOI: 10.1007/s12553-023-00805-8
Haohui Lu, S. Uddin
{"title":"Unsupervised machine learning for disease prediction: a comparative performance analysis using multiple datasets","authors":"Haohui Lu, S. Uddin","doi":"10.1007/s12553-023-00805-8","DOIUrl":"https://doi.org/10.1007/s12553-023-00805-8","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":" 15","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139142816","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}
Pub Date : 2023-12-28DOI: 10.1007/s12553-023-00808-5
F. Hasford, Nadia Khelassi-Toutaoui, Ehab Attalla, Theophilus Sackey, Mohammed Talbi, Alsadeg Ahmed, Abir Darsalih, Ahmad Refaat Thabet, Peter Knoll, Virginia Tsapaki
{"title":"Preliminary results of performance testing in diagnostic radiology facilities: Implementation of harmonized IAEA protocol for Africa","authors":"F. Hasford, Nadia Khelassi-Toutaoui, Ehab Attalla, Theophilus Sackey, Mohammed Talbi, Alsadeg Ahmed, Abir Darsalih, Ahmad Refaat Thabet, Peter Knoll, Virginia Tsapaki","doi":"10.1007/s12553-023-00808-5","DOIUrl":"https://doi.org/10.1007/s12553-023-00808-5","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"35 12","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149908","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}
Pub Date : 2023-12-26DOI: 10.1007/s12553-023-00809-4
Onome Christopher Edo, David Ang, Praveen Billakota, Johnny C. Ho
{"title":"A zero trust architecture for health information systems","authors":"Onome Christopher Edo, David Ang, Praveen Billakota, Johnny C. Ho","doi":"10.1007/s12553-023-00809-4","DOIUrl":"https://doi.org/10.1007/s12553-023-00809-4","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"52 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157124","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}
Pub Date : 2023-12-12DOI: 10.1007/s12553-023-00806-7
U. Pagallo, S. O’Sullivan, Nathalie Nevejans, Andreas Holzinger, Michael Friebe, Fleur Jeanquartier, Claire Jean-Quartier, Arkadiusz Miernik
{"title":"The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations","authors":"U. Pagallo, S. O’Sullivan, Nathalie Nevejans, Andreas Holzinger, Michael Friebe, Fleur Jeanquartier, Claire Jean-Quartier, Arkadiusz Miernik","doi":"10.1007/s12553-023-00806-7","DOIUrl":"https://doi.org/10.1007/s12553-023-00806-7","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"21 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138977131","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号