BACKGROUND: Over the past 25 years, the development of multiuser applications has seen considerable advancements and challenges. The technological development in this field has emerged from simple chat rooms through videoconferencing tools to the creation of complex, interactive, and often multisensory virtual worlds. These multiuser technologies have gradually found their way into mental health care, where they are used in both dyadic counseling and group interventions. However, some limitations in hardware capabilities, user experience designs, and scalability may have hindered the effectiveness of these applications. OBJECTIVE: This systematic review aims at summarizing the progress made and the potential future directions in this field while evaluating various factors and perspectives relevant to remote multiuser interventions. METHODS: The systematic review was performed based on a Web of Science and PubMed database search covering articles in English, published from January 1999 to March 2024, related to multiuser mental health interventions. Several inclusion and exclusion criteria were determined before and during the records screening process, which was performed in several steps. RESULTS: We identified 49 records exploring multiuser applications in mental health care, ranging from text-based interventions to interventions set in fully immersive environments. The number of publications exploring this topic has been growing since 2015, with a large increase during the COVID-19 pandemic. Most digital interventions were delivered in the form of videoconferencing, with only a few implementing immersive environments. The studies used professional or peer-supported group interventions or a combination of both approaches. The research studies targeted diverse groups and topics, from nursing mothers to psychiatric disorders or various minority groups. Most group sessions occurred weekly, or in the case of the peer-support groups, often with a flexible schedule. CONCLUSIONS: We identified many benefits to multiuser digital interventions for mental health care. These approaches provide distributed, always available, and affordable peer support that can be used to deliver necessary help to people living outside of areas where in-person interventions are easily available. While immersive virtual environments have become a common tool in many areas of psychiatric care, such as exposure therapy, our results suggest that this technology in multiuser settings is still in its early stages. Most identified studies investigated mainstream technologies, such as videoconferencing or text-based support, substituting the immersive experience for convenience and ease of use. While many studies discuss useful features of virtual environments in group interventions, such as anonymity or stronger engagement with the group, we discuss persisting issues with these technologies, which currently prevent their full adoption.
- MeSH
- duševní poruchy terapie MeSH
- duševní zdraví MeSH
- lidé MeSH
- služby péče o duševní zdraví * MeSH
- telemedicína MeSH
- videokonferování MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- systematický přehled MeSH
BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences. OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS). METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17). RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features. CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.
- MeSH
- deprese * psychologie MeSH
- dospělí MeSH
- epilepsie * psychologie MeSH
- kvalitativní výzkum * MeSH
- lidé středního věku MeSH
- lidé MeSH
- mobilní aplikace MeSH
- nositelná elektronika MeSH
- pacientova volba psychologie statistika a číselné údaje MeSH
- roztroušená skleróza * psychologie MeSH
- senioři MeSH
- telemedicína MeSH
- vizualizace dat MeSH
- zjišťování skupinových postojů * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Despite the ever-increasing offering of SMART technologies (ie, computer-controlled devices acting intelligently and capable of monitoring, analyzing or reporting), a wide gap exists between the development of new technological innovations and their adoption in everyday care for older adults. OBJECTIVE: This study aims to explore the barriers and concerns related to the adoption of SMART technologies among different groups of stakeholders. METHODS: Data from 4 sources were used: semistructured in-person or internet-based interviews with professional caregivers (n=12), structured email interviews with experts in the area of aging (n=9), a web-based survey of older adults (>55 years) attending the Virtual University of the Third Age (n=369), and a case study on the adoption of new technology by an older adult care facility. RESULTS: Although all stakeholders noted the potential of SMART technologies to improve older adult care, multiple barriers to their adoption were identified. Caregivers perceived older adults as disinterested or incompetent in using technology, reported preferring known strategies over new technologies, and noted own fears of using technology. Experts viewed technologies as essential but expressed concerns about cost, low digital competency of older adults, and lack of support or willingness to implement technologies in older adult care. Older adults reported few concerns overall, but among the mentioned concerns were lack of ability or interest, misuse of data, and limited usefulness (in specific subgroups or situations). In addition, older adults' ratings of the usefulness of different technologies correlated with their self-rating of digital competency (r=0.258; P<.001). CONCLUSIONS: Older adults appeared to have more positive views of various technologies than professional caregivers; however, their concerns varied by the type of technology. Lack of competence and lack of support were among the common themes, suggesting that educationally oriented programs for both older adults and their caregivers should be pursued.
- MeSH
- elektronická pošta MeSH
- lidé MeSH
- senioři MeSH
- stárnutí MeSH
- strach MeSH
- technologie * MeSH
- zlepšení kvality * MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- MeSH
- posudkové řízení MeSH
- psaní * MeSH
- umělá inteligence * MeSH
- Publikační typ
- časopisecké články MeSH
- komentáře MeSH
BACKGROUND: Artificial intelligence (AI) has advanced substantially in recent years, transforming many industries and improving the way people live and work. In scientific research, AI can enhance the quality and efficiency of data analysis and publication. However, AI has also opened up the possibility of generating high-quality fraudulent papers that are difficult to detect, raising important questions about the integrity of scientific research and the trustworthiness of published papers. OBJECTIVE: The aim of this study was to investigate the capabilities of current AI language models in generating high-quality fraudulent medical articles. We hypothesized that modern AI models can create highly convincing fraudulent papers that can easily deceive readers and even experienced researchers. METHODS: This proof-of-concept study used ChatGPT (Chat Generative Pre-trained Transformer) powered by the GPT-3 (Generative Pre-trained Transformer 3) language model to generate a fraudulent scientific article related to neurosurgery. GPT-3 is a large language model developed by OpenAI that uses deep learning algorithms to generate human-like text in response to prompts given by users. The model was trained on a massive corpus of text from the internet and is capable of generating high-quality text in a variety of languages and on various topics. The authors posed questions and prompts to the model and refined them iteratively as the model generated the responses. The goal was to create a completely fabricated article including the abstract, introduction, material and methods, discussion, references, charts, etc. Once the article was generated, it was reviewed for accuracy and coherence by experts in the fields of neurosurgery, psychiatry, and statistics and compared to existing similar articles. RESULTS: The study found that the AI language model can create a highly convincing fraudulent article that resembled a genuine scientific paper in terms of word usage, sentence structure, and overall composition. The AI-generated article included standard sections such as introduction, material and methods, results, and discussion, as well a data sheet. It consisted of 1992 words and 17 citations, and the whole process of article creation took approximately 1 hour without any special training of the human user. However, there were some concerns and specific mistakes identified in the generated article, specifically in the references. CONCLUSIONS: The study demonstrates the potential of current AI language models to generate completely fabricated scientific articles. Although the papers look sophisticated and seemingly flawless, expert readers may identify semantic inaccuracies and errors upon closer inspection. We highlight the need for increased vigilance and better detection methods to combat the potential misuse of AI in scientific research. At the same time, it is important to recognize the potential benefits of using AI language models in genuine scientific writing and research, such as manuscript preparation and language editing.
- MeSH
- algoritmy * MeSH
- analýza dat MeSH
- jazyk (prostředek komunikace) MeSH
- lidé MeSH
- sémantika MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Scholars from the health and medical sciences have recently proposed the term social informatics (SI) as a new scientific subfield of health informatics (HI). However, SI is not a new academic concept; in fact, it has been continuously used in the social sciences and informatics since the 1970s. Although the dominant understanding of SI was established in the 1990s in the United States, a rich international perspective on SI has existed since the 1970s in other regions of the world. When that perspective is considered, the fields of understanding can be structured into 7 SI schools of thought. Against that conceptual background, this paper contributes to the discussion on the relationship between SI and HI, outlining possible perspectives of SI that are associated with health, medical, and clinical aspects. This paper argues against the multiplication and inconsistent appearance of the term SI when newly used in health and medical sciences. A more explicit name for the area that uses health and social data to advance individual and population health might be helpful to overcome this issue; giving an identity to this new field would help it to be understood more precisely and bring greater separation. This labeling could be fruitful for further segmentation of HI, which is rapidly expanding.
- MeSH
- internacionalita MeSH
- lékařská informatika * MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Spojené státy americké MeSH
BACKGROUND: Users with experience of eating disorders use the internet as a source of information, whether for prorecovery activities (such as web-based treatment, looking for information, support, and sharing) or activities that promote eating disorder behavior as a desirable lifestyle choice (such as pro-eating disorder communities and reading and creating pro-eating disorder posts). Their assessment of web-based eating disorder-related information is crucial for understanding the context of the illness and for health professionals and their web-based interventions. OBJECTIVE: This study aimed to understand the criteria young women with the experience of eating disorders use in evaluating eating disorder-related web-based information and what eating disorder-related characteristics of these women are involved in their evaluation. METHODS: We analyzed 30 semistructured individual interviews with Czech women aged 16 to 28 years with past or present eating disorder experience using a qualitative approach. Thematic analysis was adopted as an analytical tool. RESULTS: The specifics of eating disorder phases (the disorder stage and the treatment process) emerged as important aspects in the process of information assessment. Other specific characteristics of respondents (eg, motivation, abilities, and resources) addressed how the respondents arrived at certain web-based information and how they evaluated it. In addition, the respondents described some content cues as features of information (eg, novelty and social information pooling). Another finding is that other users' attitudes, experiences, activities, and personal features are involved in the information evaluation of these users and the information presented by them. Finally, the respondents evaluated the websites' visual look and graphic components. CONCLUSIONS: This study shows that web-based information evaluation reported by women with experience of eating disorders is a complex process. The assessment is influenced by current personal characteristics related to the illness (mainly the motivation for maintaining or curing the eating disorder) using cues associated with information content, other users, and website look. The study findings have important implications for health professionals, who should ask their clients questions about web-based communities and their needs to understand what information and sources they choose.
- MeSH
- internet MeSH
- lidé MeSH
- motivace MeSH
- poruchy příjmu potravy * terapie MeSH
- zdravotnický personál MeSH
- životní styl MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
In the Czech Republic, the strategic data-based and organizational support for individual regions and for providers of acute care at the nationwide level is coordinated by the Ministry of Health. At the beginning of the COVID-19 pandemic, the country needed to very quickly implement a system for the monitoring, reporting, and overall management of hospital capacities. The aim of this viewpoint is to describe the purpose and basic functions of a web-based application named "Control Centre for Intensive Care," which was developed and made available to meet the needs of systematic online technical support for the management of intensive inpatient care across the Czech Republic during the first wave of the pandemic in spring 2020. Two tools of key importance are described in the context of national methodology: one module for regular online updates and overall monitoring of currently free capacities of intensive care in real time, and a second module for online entering and overall record-keeping of requirements on medications for COVID-19 patients. A total of 134 intensive care providers and 927 users from hospitals across all 14 regions of the Czech Republic were registered in the central Control Centre for Intensive Care database as of March 31, 2021. This web-based application enabled continuous monitoring and decision-making during the mass surge of critical care from autumn 2020 to spring 2021. The Control Center for Intensive Care has become an indispensable part of a set of online tools that are employed on a regular basis for crisis management at the time of the COVID-19 pandemic.
- MeSH
- COVID-19 * MeSH
- lidé MeSH
- pandemie * prevence a kontrola MeSH
- péče o pacienty v kritickém stavu MeSH
- SARS-CoV-2 MeSH
- strategické plánování MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Artificial intelligence-driven voice technology deployed on mobile phones and smart speakers has the potential to improve patient management and organizational workflow. Voice chatbots have been already implemented in health care-leveraging innovative telehealth solutions during the COVID-19 pandemic. They allow for automatic acute care triaging and chronic disease management, including remote monitoring, preventive care, patient intake, and referral assistance. This paper focuses on the current clinical needs and applications of artificial intelligence-driven voice chatbots to drive operational effectiveness and improve patient experience and outcomes.
- MeSH
- chronická nemoc terapie MeSH
- COVID-19 * MeSH
- hlas * MeSH
- komunikace * MeSH
- konziliární vyšetření a konzultace MeSH
- lidé MeSH
- mobilní telefon MeSH
- pandemie MeSH
- péče o pacienty v kritickém stavu metody MeSH
- poskytování zdravotní péče metody MeSH
- software pro rozpoznávání řeči * MeSH
- telemedicína metody MeSH
- třídění pacientů MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: The clinical application of voice technology provides novel opportunities in the field of telehealth. However, patients' readiness for this solution has not been investigated among patients with cardiovascular diseases (CVD). OBJECTIVE: This paper aims to evaluate patients' anticipated experiences regarding telemedicine, including voice conversational agents combined with provider-driven support delivered by phone. METHODS: A cross-sectional study enrolled patients with chronic CVD who were surveyed using a validated investigator-designed questionnaire combining 19 questions (eg, demographic data, medical history, preferences for using telehealth services). Prior to the survey, respondents were educated on the telemedicine services presented in the questionnaire while being assisted by a medical doctor. Responses were then collected and analyzed, and multivariate logistic regression was used to identify predictors of willingness to use voice technology. RESULTS: In total, 249 patients (mean age 65.3, SD 13.8 years; 158 [63.5%] men) completed the questionnaire, which showed good repeatability in the validation procedure. Of the 249 total participants, 209 (83.9%) reported high readiness to receive services allowing for remote contact with a cardiologist (176/249, 70.7%) and telemonitoring of vital signs (168/249, 67.5%). The voice conversational agents combined with provider-driven support delivered by phone were shown to be highly anticipated by patients with CVD. The readiness to use telehealth was statistically higher in people with previous difficulties accessing health care (OR 2.920, 95% CI 1.377-6.192) and was most frequent in city residents and individuals reporting a higher education level. The age and sex of the respondents did not impact the intention to use voice technology (P=.20 and P=.50, respectively). CONCLUSIONS: Patients with cardiovascular diseases, including both younger and older individuals, declared high readiness for voice technology.
- MeSH
- kardiovaskulární nemoci terapie MeSH
- kvalita hlasu fyziologie MeSH
- lidé MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- senioři MeSH
- technologie MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
