Areti Efthymiou, Argyroula Kalaitzaki, Michael Rovithis, Gregor Petrič
{"title":"Validation of the eHealth literacy scales: comparison between the shorter and longer versions.","authors":"Areti Efthymiou, Argyroula Kalaitzaki, Michael Rovithis, Gregor Petrič","doi":"10.1080/17538157.2025.2451427","DOIUrl":"10.1080/17538157.2025.2451427","url":null,"abstract":"<p><p>Digital service provision became necessary during and after the COVID-19 pandemic highlighting the technological disparity experienced by healthcare professionals and healthcare users. eHealth Literacy skills are mostly measured with the use of the eHeals, but recently more instruments have been developed to meet this need. The aim of the study was to validate and compare the two scales in Greek: the eHeals and the revised eHeals-Extended. In total, 401 participants replied to the eHeals, the revised eHeals-Extended, and the HLS-EU-Q16. The eHeals scales provided good psychometric properties. The validation of the eHeals confirmed the two dimensions with high internal consistency (total score α = .91, eHeals1 α = .88, eHeals2 α = .78). The revised eHeals-Extended exploratory analysis extracted five factors with satisfactory internal consistency (Cronbach's α = .62-.89): awareness and quality of resources online, understanding online information, smart on the net, accessing and validating online information and perceived efficiency. The use of the revised eHeals-Extended and eHeals validated in Greek, could be valuable tools in clinical and research settings. The eHeals could be used as an additional tool when eHealth Literacy is not the core concept measured and the revised eHeals-Extended can be used when researchers wish to measure eHealth Literacy concept more thoroughly.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"33-47"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143019750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Usability testing of a palliative care information resource - outcomes from the formative evaluation of the CarerHelp Toolkit prototype.","authors":"A Adams, L Miller-Lewis, J Tieman","doi":"10.1080/17538157.2024.2433942","DOIUrl":"10.1080/17538157.2024.2433942","url":null,"abstract":"<p><p>CarerHelp is an online resource supporting Australian family carers providing palliative care to loved ones at home. To confidently care for a dying person, family carers require access to evidence-based resources, accessible day or night when healthcare professionals or services are unavailable. Given carer diversity, usability evaluations assist online developers in shaping information experiences to family carer's needs and abilities. This study aimed to use a comprehensive usability testing protocol to evaluate the prototype, with a sample involving six family carers aged 36-74 years. A concurrent think-aloud approach generated quantitative and qualitative feedback from scenario-based tasks. Single ease questions (SEQ) and computer satisfaction usability questionnaire (CSUQ) assessed end-user attitudes. Performance, SEQ, and CSUQ were calculated, errors were analyzed, and severity rating applied. Overall, family carers identified 54 errors. All carers detected highly severe errors impacting critical function; technical ability influenced error detection, affecting navigation, utility, and content. Language modification was guided by family carers' narratives, contextualizing interface use with real-life experiences. For the multidisciplinary development team, formal reporting of findings was advantageous in informing meaningful reiterative interface changes and giving a voice to family carers. This approach was essential to assist as many carers as possible in accessing palliative care information when needed.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Applications of generative and predictive AI in nutrition and dietetics: a narrative review.","authors":"Hatice Merve Bayram, Arda Ozturkcan","doi":"10.1080/17538157.2025.2560834","DOIUrl":"10.1080/17538157.2025.2560834","url":null,"abstract":"<p><p>In the era of Industry 4.0, where automation and digitalization are central to processes and systems, artificial intelligence (AI) is becoming an essential tool that provides innovative solutions across various fields. Nutrition, as a vital component of public health, is among the areas increasingly shaped by the integration of AI technologies. This review aims to identify the strengths and limitations of these models, assess their potential as decision-support tools for healthcare professionals, and shed light on the existing gaps in the field. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar databases to identify relevant studies published between January 2019 and May 2025. A total of 44 articles were included in the review. The main findings suggest that the application of AI in nutrition is still emerging, with the majority of studies centered on dietary assessment. There is comparatively less emphasis on food estimation, disease prediction, lifestyle interventions, and understanding diet-related diseases. Further clinical studies are necessary to evaluate the effectiveness of AI-based interventions.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"133-156"},"PeriodicalIF":2.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152305","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}
Rafaela Oliveira, Susana Pedras, Carlos Veiga, Luís Moreira, Daniel Santarém, Daniel Guedes, Hugo Paredes, Ivone Silva
{"title":"Adherence, acceptability, and usability of a smartphone app to promote physical exercise in patients with peripheral arterial disease and intermittent claudication.","authors":"Rafaela Oliveira, Susana Pedras, Carlos Veiga, Luís Moreira, Daniel Santarém, Daniel Guedes, Hugo Paredes, Ivone Silva","doi":"10.1080/17538157.2025.2465527","DOIUrl":"10.1080/17538157.2025.2465527","url":null,"abstract":"<p><p>This study presents the development and assessment of a mobile application - the WalkingPAD app - aimed at promoting adherence to physical exercise among patients with Peripheral Arterial Disease (PAD). The assessment of adherence, acceptability, and usability was performed using mixed methods. Thirty-eight patients participated in the study with a mean age of 63.4 years (SD = 6.8). Thirty patients used the application for three months, responded to a semi-structured interview, and completed a task test and the System Usability Scale (SUS, ranging from 0 to 100). The application's adherence rate was 73%. When patients were asked about their reasons for using the app, the main themes that emerged were motivation, self-monitoring, and support in fulfilling a commitment. The average SUS score was 82.82 (SD = 18.4), indicating high usability. An upcoming version of the WalkingPAD app is expected to redesign both tasks - opening the app and looking up the walking history - which were rated as the most difficult tasks to accomplish. The new version of the WalkingPAD app will incorporate participants' comments and suggestions to enhance usability for this population.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"49-62"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560551","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}
Margarida Duarte, Catarina Ferreira da Silva, Sérgio Moro
{"title":"Machine learning models to predict the COVID-19 reproduction rate: combining non-pharmaceutical interventions with sociodemographic and cultural characteristics.","authors":"Margarida Duarte, Catarina Ferreira da Silva, Sérgio Moro","doi":"10.1080/17538157.2025.2491517","DOIUrl":"10.1080/17538157.2025.2491517","url":null,"abstract":"<p><p>Since the beginning of the COVID-19 pandemic, countries worldwide have implemented a set of Non-Pharmaceutical Interventions (NPIs) to prevent the dissemination of the pandemic. Few studies applied machine learning models to compare the use of NPIs, socioeconomic and demographic characteristics, and cultural dimensions in predicting the reproduction rate R<sub>t</sub>. We adopted the CRISP-DM methodology using as data sources the \"Our World in Data COVID-19,\" the \"Oxford COVID-19 Government Response Tracker\" and the Hofstede Insights data. We analyzed the impact that Hofstede's cultural dimensions, the implementation of various degrees of restriction of NPIs and the sociodemographic variables may have in the reproduction rate by applying machine learning models to understand whether cultural characteristics are useful information to improve reproduction rate predictions. We included data from 101 countries to train several machine learning models to compare the results between the models with and without Hofstede's cultural dimensions. Our results show the use of cultural dimensions helps to improve the models, and that the ones that obtained a better prediction of the R<sub>t</sub> were the ensemble models, especially the Random Forest.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"81-99"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060208","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}
Richard Fletcher, Chris May, Rebecca Liackman, Jennifer StGeorge, Casey Regan, Michael Stark
{"title":"Facilitating family centred care: the co-design development of text messages for fathers with an infant in NICU.","authors":"Richard Fletcher, Chris May, Rebecca Liackman, Jennifer StGeorge, Casey Regan, Michael Stark","doi":"10.1080/17538157.2025.2542123","DOIUrl":"10.1080/17538157.2025.2542123","url":null,"abstract":"<p><p>While active engagement of both parents in neonatal intensive care is considered best practice, fathers are less involved than mothers. This study describes the co-development of text messages targeting fathers whose infants were admitted to NICU, supporting Family Centred Care aims. Parents whose infants were admitted to NICU completed a survey of fathers' needs (Stage 1). Qualitative descriptive analysis (Stage 2) created topics for text messages (Stage 3). These were reviewed for importance and understanding by fathers and for clinical relevance by clinicians (Stage 4). Messages were revised and screened again (Stages 5-6) to produce a final set (Stage 7). Mothers (<i>n</i> = 36) and fathers (<i>n</i> = 15) responded to the survey, with analysis producing 12 themes and 21 subthemes. The 57 draft messages generated from themes were highly rated by 64 fathers and 41 clinicians (median rating 4.85/5). Twenty-three messages were accepted unchanged whilst 32 required editing and two were discarded, resulting in 55 messages. Final evaluation by 13 fathers and 11 clinicians led to 49 messages. Messages for fathers whose infants are admitted to NICU, developed and evaluated collaboratively with lived-experience parents and clinicians, can address identified needs and may better engage fathers whilst meeting Family Centered Care goals.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"101-113"},"PeriodicalIF":2.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144877788","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}
Ugurcan Sayili, Ayse Sultan Kaya, Sumeyye Nur Aydin
{"title":"Adaptation of Extended eHealth Literacy Scale (eHEALS-E) in Turkish: validity and reliability analysis.","authors":"Ugurcan Sayili, Ayse Sultan Kaya, Sumeyye Nur Aydin","doi":"10.1080/17538157.2025.2564102","DOIUrl":"10.1080/17538157.2025.2564102","url":null,"abstract":"<p><p>The aim of the study is to adapt the \"Extended eHealth Literacy Scale\" (eHEALS-E) into Turkish, a critical component of health promotion activities, and to evaluate the scale's validity and reliability. This methodological study was conducted as an online survey between December 2-9, 2024, with 395 participants. The study included three main components: demographic information, the eHEALS-E, and the European Health Literacy Survey Questionnaire (HLS-EU-Q47). Psychometric properties were assessed through exploratory factor analysis (EFA) for construct validity, correlation analysis with HLS-EU-Q47 for convergent validity and known-groups comparisons. Reliability was evaluated using Cronbach's alpha for internal consistency, and test-retest reliability was assessed with a subset of participants after seven weeks. After removing problematic items, the Turkish version of eHEALS-E demonstrated strong psychometric properties. The final 20-item scale exhibited high internal consistency (Cronbach's alpha = 0.896 and McDonald's ω = 0.900) and strong test-retest reliability (<i>r</i> = 0.794, <i>p</i> < .001). EFA revealed a four-factor structure explaining 58.9% of the total variance. The scale showed good convergent validity, with a significant correlation with HLS-EU-Q47 (<i>r</i> = 0.514, <i>p</i> < .001). This tool can serve as a valuable resource for healthcare professionals and researchers in assessing eHealth literacy levels and designing targeted interventions for Turkish-speaking populations.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"157-174"},"PeriodicalIF":2.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145310439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clustering public hospitals based on crisp and fuzzy clustering techniques and probabilistic fuzzy efficiency estimates.","authors":"Songul Cinaroglu","doi":"10.1080/17538157.2025.2550968","DOIUrl":"10.1080/17538157.2025.2550968","url":null,"abstract":"<p><strong>Objective: </strong>Practical applications of data envelopment analysis (DEA) present several procedures including homogeneity of units and are assumed to be undertaking and producing similar activities. Previous papers creating comparable groups have been limited to generating isotonic groups by using various clustering techniques since there is considerable room exists.</p><p><strong>Methods: </strong>In this paper, homogenous hospital groups are created by using crisp and fuzzy grouping techniques. K-means, fuzzy c-means, and self-organizing map clustering techniques were applied by changing the hyperparameters of these techniques. Then, a fuzzy possibility DEA approach is applied to explore which hospitals are efficient, and grounded on primal and dual models.</p><p><strong>Results: </strong>The results identify that there are five hospitals in the best hospital group and a teaching university hospital, which is located in the southeast part of the country, is efficient according to Lertworasirikul et al.'s (2003) fuzzy DEA model and a reference hospital for others. This study also highlighted several insights interrelated with strategic grouping and fuzzy efficiency estimation. Primal efficiency results are increasing while changing the α parameter from 0 to 1.</p><p><strong>Conclusion: </strong>This study also focused on various insights about particular pitfalls of DEA such as the creation of homogenous groups and fuzzy efficiency estimation.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"114-132"},"PeriodicalIF":2.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082969","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}
N Sriraam, H S Sanjay, B R Purnima, Krv Subramanian, Vyacheslav Krut'ko, Oleg Mitrokhin, Yury Zhernov
{"title":"A critical review of geriatric care in India with regard to the needs, challenges and opportunities: a wearable care approach.","authors":"N Sriraam, H S Sanjay, B R Purnima, Krv Subramanian, Vyacheslav Krut'ko, Oleg Mitrokhin, Yury Zhernov","doi":"10.1080/17538157.2025.2488747","DOIUrl":"10.1080/17538157.2025.2488747","url":null,"abstract":"<p><p>Home is more than just a word; it represents a profound emotion for every individual. Hospitalization often deprives the geriatric population of this comforting environment due to their deteriorating health. However, with technology-oriented automated and monitored assistance systems, older adults can receive adequate care and support at home, allowing them to lead independent lives. This approach requires robust systems to assess relevant information, process data in real time, and provide dynamic solutions when necessary. Ambient Assistive Living (AAL) systems are crucial to improving the quality of life for older adults, despite the challenges they pose. India, with its diverse cultural and demographic landscape, presents unique challenges and opportunities in geriatric care. While older adults aspire to live in their own homes, they often face barriers such as limited access to affordable and user-friendly technology. However, the Indian older adult population also presents opportunities for innovation and tailored solutions that consider cultural nuances and family dynamics. This article provides an overview of available geriatric assistance technologies, highlighting their advantages and disadvantages. It critically analyzes geriatric care in the Indian context, focusing on the specific challenges and opportunities presented by the country's cultural and demographic diversity. By exploring potential integrated solutions, this article aims to enhance healthcare delivery and improve the quality of life for older adults in India.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"63-80"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143997131","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}
Celine Cammarata, Elaine Wethington, Adam K Anderson, Eve De Rosa
{"title":"Older adults' views on training tools to prevent cognitive decline.","authors":"Celine Cammarata, Elaine Wethington, Adam K Anderson, Eve De Rosa","doi":"10.1080/17538157.2024.2417659","DOIUrl":"10.1080/17538157.2024.2417659","url":null,"abstract":"<p><p>Computerized training platforms could be an accessible means for older adults to maintain cognitive health, and several such tools are already commercially available. However, it remains unclear whether older adults use these tools if training is not externally prescribed. We explored older adults' self-initiated experiences with cognitive training. We conducted semi-structured interviews with 13 community-dwelling adults aged 58-85 years, comprising university retirees (<i>N</i> = 8) and public housing residents (<i>N</i> = 5). Interviews were analyzed by thematic analysis. No participants voluntarily used cognitive training, and those who had done so previously reported negative experiences. Several factors shaped older adults' engagement with cognitive training, especially a preference for stimulating activities that are organic and inherently enjoyable. We reveal a mismatch between older adults' priorities and the interventions currently available and uncover issues of access and interest among low-income and minority individuals. We suggest ways to better align future interventions with older adults' priorities.</p>","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"246-258"},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515863","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}