Veille sur les nouvelles technologies de l'information et de la communication

Educ Inf Technol (Dordr). 2022 Nov 4:1-32. doi: 10.1007/s10639-022-11414-9. Online ahead of print.

ABSTRACT

Digital gaming has broad appeal globally, with a reported 2.7 billion gamers worldwide. There is significant interest in using games to enhance learning, with 'serious games' being included in classrooms to engage adolescents' learning across a range of domains. A systematic scoping review of serious games used for health promotion with adolescents was conducted to identify serious games, review the methods used to evaluate these games, and outline evidence available to support the efficacy of these games in improving knowledge, beliefs/attitudes and behaviours in the target groups. Player engagement/enjoyment was reported if assessed. A total of 21 studies were found to have met the inclusion criteria domains: 'healthy lifestyle' 'sexual health' and 'substance use'. A heterogenous approach across studies to game design and development, duration of game play, use of a control group and measurement of outcome(s) was observed. Game efficacy was difficult to assess due to broad generalisations and lack of consistent evaluation methods. Several studies demonstrate serious games can be engaging and pedagogically effective as a learning device and behaviour-change agent. Several studies, however, had less rigorous evaluation and lacked longer-term follow up. The ability for developers to demonstrate positive short- and long-term impacts of serious games with high-quality evidence is essential to the ongoing acceptance and use of these serious games as part of the school curriculum.

PMID:36373044 | PMC:PMC9638273 | DOI:10.1007/s10639-022-11414-9

JMIR Pediatr Parent. 2022 Oct 6;5(4):e37718. doi: 10.2196/37718.

ABSTRACT

BACKGROUND: Recent increases in smartphone ownership among underserved populations have inspired researchers in medicine, computing, and health informatics to design and evaluate mobile health (mHealth) interventions, specifically for those supporting child development and growth. Although these interventions demonstrate possible effectiveness at larger scales, few of these interventions are evaluated to address racial disparities and health equity, which are known factors that affect relevance, uptake, and adherence in target populations.

OBJECTIVE: In this study, we aimed to identify and document the current design and evaluation practices of mHealth technologies that promote early childhood health, with a specific focus on opportunities for those processes to address health disparities and health equity.

METHODS: We completed a systematic literature review of studies that design and evaluate mHealth interventions for early childhood health promotion. We then analyzed these studies to identify opportunities to address racial disparities in early- and late-stage processes and to understand the potential efficacy of these interventions.

RESULTS: Across the literature from medical, computing, and health informatics fields, we identified 15 articles that presented a design or evaluation of a parent-facing health intervention. We found that using mobile-based systems to deliver health interventions was generally well accepted by parents of children aged <5 years. We also found that, when measured, parenting knowledge of early childhood health topics and confidence to engage in health-promoting behaviors improved. Design and evaluation methods held internal consistency within disciplines (eg, experimental study designs were the most prevalent in medical literature, while computing researchers used user-centered design methods in computing fields). However, there is little consistency in design or evaluation methods across fields.

CONCLUSIONS: To support more interventions with a comprehensive design and evaluation process, we recommend attention to design at the intervention (eg, reporting content sources) and system level; interdisciplinary collaboration in early childhood health intervention development can lead to large-scale deployment and success among populations.

TRIAL REGISTRATION: PROSPERO CRD42022359797; https://tinyurl.com/586nx9a2.

PMID:36201391 | DOI:10.2196/37718

JMIR Res Protoc. 2022 Oct 11;11(10):e40265. doi: 10.2196/40265.

ABSTRACT

BACKGROUND: Interactive conversational agents, also known as "chatbots," are computer programs that use natural language processing to engage in conversations with humans to provide or collect information. Although the literature on the development and use of chatbots for health interventions is growing, important knowledge gaps remain, such as identifying design aspects relevant to health care and functions to offer transparency in decision-making automation.

OBJECTIVE: This paper presents the protocol for a scoping review that aims to identify and categorize the interactive conversational agents currently used in health care.

METHODS: A mixed methods systematic scoping review will be conducted according to the Arksey and O'Malley framework and the guidance of Peters et al for systematic scoping reviews. A specific search strategy will be formulated for 5 of the most relevant databases to identify studies published in the last 20 years. Two reviewers will independently apply the inclusion criteria using the full texts and extract data. We will use structured narrative summaries of main themes to present a portrait of the current scope of available interactive conversational agents targeting health promotion, prevention, and care. We will also summarize the differences and similarities between these conversational agents.

RESULTS: The search strategy and screening steps were completed in March 2022. Data extraction and analysis started in May 2022, and the results are expected to be published in October 2022.

CONCLUSIONS: This fundamental knowledge will be useful for the development of interactive conversational agents adapted to specific groups in vulnerable situations in health care and community settings.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40265.

PMID:36222804 | DOI:10.2196/40265

Int J Med Inform. 2022 Aug 17;166:104855. doi: 10.1016/j.ijmedinf.2022.104855. Online ahead of print.

ABSTRACT

BACKGROUND: Artificial intelligence is fueling a new revolution in medicine and in the healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there are several aspects that limit the measure of its impact in people's health. It is necessary to assess the current status on the application of AI towards the improvement of people's health in the domains defined by WHO's Thirteenth General Programme of Work (GPW13) and the European Programme of Work (EPW), to inform about trends, gaps, opportunities, and challenges.

OBJECTIVE: To perform a systematic overview of systematic reviews on the application of artificial intelligence in the people's health domains as defined in the GPW13 and provide a comprehensive and updated map on the application specialties of artificial intelligence in terms of methodologies, algorithms, data sources, outcomes, predictors, performance, and methodological quality.

METHODS: A systematic search in MEDLINE, EMBASE, Cochrane and IEEEXplore was conducted between January 2015 and June 2021 to collect systematic reviews using a combination of keywords related to the domains of universal health coverage, health emergencies protection, and better health and wellbeing as defined by the WHO's PGW13 and EPW. Eligibility criteria was based on methodological quality and the inclusion of practical implementation of artificial intelligence. Records were classified and labeled using ICD-11 categories into the domains of the GPW13. Descriptors related to the area of implementation, type of modeling, data entities, outcomes and implementation on care delivery were extracted using a structured form and methodological aspects of the included reviews studies was assessed using the AMSTAR checklist.

RESULTS: The search strategy resulted in the screening of 815 systematic reviews from which 203 were assessed for eligibility and 129 were included in the review. The most predominant domain for artificial intelligence applications was Universal Health Coverage (N = 98) followed by Health Emergencies (N = 16) and Better Health and Wellbeing (N = 15). Neoplasms area on Universal Health Coverage was the disease area featuring most of the applications (21.7 %, N = 28). The reviews featured analytics primarily over both public and private data sources (67.44 %, N = 87). The most used type of data was medical imaging (31.8 %, N = 41) and predictors based on regions of interest and clinical data. The most prominent subdomain of Artificial Intelligence was Machine Learning (43.4 %, N = 56), in which Support Vector Machine method was predominant (20.9 %, N = 27). Regarding the purpose, the application of Artificial Intelligence I is focused on the prediction of the diseases (36.4 %, N = 47). With respect to the validation, more than a half of the reviews (54.3 %, N = 70) did not report a validation procedure and, whenever available, the main performance indicator was the accuracy (28.7 %, N = 37). According to the methodological quality assessment, a third of the reviews (34.9 %, N = 45) implemented methods for analysis the risk of bias and the overall AMSTAR score below was 5 (4.01 ± 1.93) on all the included systematic reviews.

CONCLUSION: Artificial intelligence is being used for disease modelling, diagnose, classification and prediction in the three domains of GPW13. However, the evidence is often limited to laboratory and the level of adoption is largely unbalanced between ICD-11 categoriesand diseases. Data availability is a determinant factor on the developmental stage of artificial intelligence applications. Most of the reviewed studies show a poor methodological quality and are at high risk of bias, which limits the reproducibility of the results and the reliability of translating these applications to real clinical scenarios. The analyzed papers show results only in laboratory and testing scenarios and not in clinical trials nor case studies, limiting the supporting evidence to transfer artificial intelligence to actual care delivery.

PMID:35998421 | DOI:10.1016/j.ijmedinf.2022.104855

JMIR Mhealth Uhealth. 2022 Aug 19;10(8):e39520. doi: 10.2196/39520.

ABSTRACT

BACKGROUND: In the United States, almost 90% of women are at risk of at least one chronic condition. However, the awareness, management, and monitoring of these conditions are low and present a substantial public health problem. Digital health tools can be leveraged to reduce the alarmingly high rates of chronic condition-related mortality and morbidity in women.

OBJECTIVE: This study aimed to investigate the 4-year trend of digital health use for health promotion among women with chronic conditions in the United States.

METHODS: Data for this study were obtained from the 2017 to 2020 iterations of the Health Information Trends Survey 5. Separate weighted logistic regression models were conducted to test the unadjusted and adjusted association of the study variables and each digital health use. The 95% CI, adjusted odds ratio (aOR), and P value (.05) were reported. Analysis was conducted using Stata 17 software.

RESULTS: In total, 8573 women were included in this study. The weighted prevalence of the use of a smartphone or tablet for various activities were as follows: track health goals, 50.3% (95% CI 48.4%-52.2%; 3279/7122); make a health decision, 43.6% (95% CI 41.9%-45.3%; 2998/7101); and discuss with a provider, 40% (95% CI 38.2%-41.8%; 2834/7099). In the preceding 12 months, 33% (95% CI 30.9%-35.2%; 1395/4826) of women used an electronic wearable device, 18.7% (95% CI 17.3%-20.2%; 1532/7653) shared health information, and 35.2% (95% CI 33.2%-37.3%; 2262/6349) sent or received an SMS text message with a health professional. Between 2017 and 2020, the weighted prevalence of having 0, 1, and multiple chronic conditions were 37.4% (2718/8564), 33.4% (2776/8564), and 29.3% (3070/8564), respectively. However, slightly above half (52.2%, 95% CI 0.50%-0.53%; 4756/8564) of US women reported having at least one chronic disease. Women with multiple chronic conditions had higher odds of using their tablet or smartphone to achieve a health-related goal (aOR 1.43, 95% CI 1.16-1.77; P=.001) and discuss with their provider (aOR 1.55 95% CI 1.20-2.00; P=.001) than those without any chronic conditions. Correspondingly, in the past 12 months, the odds of using an electronic wearable device (aOR 1.40, 95% CI 1.00-1.96; P=.04), sharing health information (aOR 1.91, 95% CI 1.46-2.51; P<.001), and communicating via SMS text messaging with a provider (aOR 1.31, 95% CI 1.02-1.68; P=.03) were significantly higher among women with chronic conditions than those without a chronic condition.

CONCLUSIONS: This study suggests that women with chronic conditions accept and integrate digital health tools to manage their care. However, certain subpopulations experience a digital disconnect that may exacerbate existing health inequities. Implications for research and opportunities to leverage and integrate digital health tools to prevent, monitor, manage, and treat chronic conditions in women are discussed.

PMID:35984680 | DOI:10.2196/39520

JMIR Res Protoc. 2022 Jul 21;11(7):e37729. doi: 10.2196/37729.

ABSTRACT

BACKGROUND: Digital technologies could contribute to health promotion and disease prevention. It is unclear if and how such digital technologies address the health needs of older people in nonclinical settings (ie, daily life).

OBJECTIVE: This study aims to identify digital technologies for health promotion and disease prevention that target the needs of older people in nonclinical settings by performing a scoping review of the published literature. The scoping review is guided by the framework of Arksey and O'Malley.

METHODS: Our scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The information sources are bibliographic databases (MEDLINE, PsycINFO, CINAHL, and SCOPUS) and bibliographies of any included systematic reviews. Manual searches for additional studies will be performed in Google Scholar and most relevant journals. The electronic search strategy was developed in collaboration with a librarian who performed the search for studies on digital technologies for health promotion and disease prevention targeting the needs of older people. Study selection and data coding will be performed independently by 2 authors. Consensus will be reached by discussion. Eligibility is based on the PCC (Population, Concept, and Context) criteria as follows: (1) older people (population); (2) any digital (health) technology, such as websites, smartphone apps, or wearables (concept); and (3) health promotion and disease prevention in nonclinical (daily life, home, or community) settings (context). Primary studies with any design or reviews with a systematic methodology published in peer-reviewed academic journals will be included. Data items will address study designs, PCC criteria, benefits or barriers related to digital technology use by older people, and evidence gaps. Data will be synthesized using descriptive statistics or narratively described by identifying common themes. Quality appraisal will be performed for any included systematic reviews, using a validated instrument for this study type (A Measurement Tool to Assess Systematic Reviews, version 2 [AMSTAR2]).

RESULTS: Following preliminary literature searches to test and calibrate the search syntax, the electronic literature search was performed in March 2022 and manual searches were completed in June 2022. Study selection based on titles and abstracts was completed in July 2022, and the full-text screen was initiated in July 2022.

CONCLUSIONS: Our scoping review will identify the types of digital technologies, health targets in the context of health promotion and disease prevention, and health benefits or barriers associated with the use of such technologies for older people in nonclinical settings. This knowledge could guide further research on how digital technologies can support healthy aging.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37729.

PMID:35862187 | DOI:10.2196/37729

Ce guide • Il vise notamment à favoriser le développement d’une politique d’inclusion numérique à destination de personnes âgées qui s’articule avec les solutions de médiation numérique existantes ou en construction sur les territoires, dont les conférences des financeurs doivent être la pierre angulaire. • Ce guide présente dans un premier temps un panorama des principales politiques d’inclusion numérique portées par les membres des conférences, en particulier des départements et des caisses de retraite. • Des pratiques d’intérêt pour l’articulation locale des politiques d’inclusion numérique y sont ensuite détaillées, que ce soit, d’une part, entre les membres financeurs des conférences et avec la politique territoriale d’inclusion numérique – les Hubs notamment – et, d’autre part, pour détecter les personnes âgées ayant besoin d’un accompagnement vers l’autonomie numérique et les orienter, à la suite des ateliers, vers les partenaires relais existants, grâce au maillage local mis en place.
EN SAVOIR PLUS / https://www.cnsa.fr/documentation/guide_autonomie_numerique_cnav_cnsa.pdf

E-learning : mieux détecter les consommations nocives d’alcool

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