Design Implications for Robots That Facilitate Groups—A Scoping Review on Improving Group Interactions through Directed Robot Action

An Introduction to Scoping Reviews.

Social Educational Robotics and Learning Analytics (LA) are prominent fields in technology-enhanced learning, but their combined potential remains underexplored, despite methodological similarities. Increasingly, signs of joint interests have emerged, with a surge in publications mentioning both social robots and learning analytics in the last five years. We therefore conducted a scoping review to explore if a new research field is emerging. We identified 29 empirical studies that combine social robots and LA, but also found that few studies explicitly state that social educational robots and LA are used in combination. Several studies used social educational robots that adapted to the learners or the learning environment based on interaction data. This signifies that they are in fact employing the feedback cycle that is at the core of LA methodology, but as most of these studies update the learner model using post-session data (e.g., learner improvement or feedback), they are long-term studies with repeated interventions that are applying LA methodology inadvertently. There are also benefits for LA research to use social educational robots, since LA increasingly uses an array of equipment to collect multimodal data, and all studies in this review employ at least two input modalities (μ = 4.4). Social robots provide the possibility to collect this data non-intrusively with the robot itself, in addition to creating a pedagogically boosted interaction compared to traditional LA interventions (e.g., learning management systems). By raising researchers’ awareness of how close the fields of social educational robotics and LA are, substantial synergy effects could therefore be gained.

Social robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector. To ensure the successful use of this technology, acceptance is paramount. Generative artificial intelligence (AI) is an emerging technology with the potential to enhance the functionality of SR and promote user acceptance by further improving human-robot interaction. We present a protocol for a scoping review of the literature on the implementation of generative AI in SR in the health care sector. The aim of this scoping review is to map out the intersection of SR and generative AI in the health care sector; to explore if generative AI is applied in SR in the health care sector; to outline which models of generative AI and SR are used for these implementations; and to explore whether user acceptance is reported as an outcome following these implementations. This scoping review supports future research by providing an overview of the state of connectedness of 2 emerging technologies and by mapping out research gaps. We follow the methodological framework developed by Arksey and O'Malley and the recommendations by the Joanna Briggs Institute. Our protocol was drafted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews). We will conduct a systematic literature search of the online databases MEDLINE, Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and IEEE Xplore, aiming to retrieve relevant data items via tabular data charting from references meeting specific inclusion criteria which are studies published from 2010 onwards, set in the health care sector, focusing on SR with physical bodies and implemented generative AI. There are no restrictions on study types. Results will be categorized, clustered, and summarized using tables, graphs, visual representations, and narratives. After conducting a preliminary search and deduplication in the second quarter of 2024, we retrieved 3176 preliminary results. This scoping review will be supplemented with the next methodological steps, including retrieving the results in a reference management tool as well as screening titles, abstracts, and full text regarding specific inclusion criteria. The completion of these steps is scheduled for the second quarter of 2025. Limitations based on the heterogeneity of the included studies and the general breadth of a scoping review compared to a systematic review are to be expected. To reduce bias, we adopted a system of dual reviews and thorough documentation of the study selection. The conducted preliminary search implies that there are a sufficient number of heterogeneous references to complete this scoping review. To our knowledge, this is the first scoping review on generative AI in health care SR. PRR1-10.2196/63017.

Dentists are typically at high risk of developing low back pain (LBP) due to their working position. Therefore, this study aimed to evaluate the role of ergonomic interventions in preventing LBP. The study procedures were carried out using a scoping review method with Boolean search based on PCC (Population, Concept, and Context) on PubMed, Wiley, and Google Scholar. Article management and selection process was then conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) as a guide. Inclusion criteria were experimental articles from 2011 to 2021, while exclusion criteria included scoping, rapid, and systematic reviews, gray literature, or papers that were not fully accessible. A total of 1775 articles were obtained and only 12 were selected with a total of 557 participants. The selected articles consisted of 2, 1, and 7 in the work environment, organizational, and individual domains, respectively, while 2 articles had more than 1 ergonomic intervention in different domains. The results showed that ergonomic interventions could prevent LBP among dentists. The clinical significance reported across all included articles showed that participants experienced positive changes in posture, decreased pain levels, and improved work quality after receiving the treatment across all domains.

Acute abdominal pain (colic) is the most common reason for emergency veterinary treatment in the horse. Consolidation of data through a systematic review is important to inform evidence-based medicine and clinical guidelines, but there are currently no published systematic reviews on colic in the horse. The aim of this study was to identify, categorize and appraise the evidence on factors associated with increased risk of developing abdominal pain (colic) due to gastrointestinal disease in the adult horse. A scoping review was performed to identify and categorize evidence on all risk factors for colic. A systematic review of management-related risk factors was then performed following PRISMA guidelines. Both searches were conducted in Medline, CAB s and Web of Science databases, and publications were assessed against inclusion and exclusion criteria. For the scoping review, study and participant characteristics of included publications and key results were extracted and tabulated. For the systematic review, cohort, case-control or cross-sectional studies investigating acute abdominal pain in horses within two weeks of management changes were assessed. Study characteristics, participant characteristics and study results of included publications for the systematic review were extracted and tabulated. Included publications were appraised using the Joanna Briggs Institute Critical Appraisal Tools for cohort, case-control and cross-sectional studies. The scoping review search identified 3,756 publications. Fifty eight studies met final inclusion criteria, and 22 categories of risk factors were identified. These were grouped into three broad areas: horse-related factors, management-related factors and environment-related factors. The largest body of evidence related to management change. The systematic review of management change identified 410 publications: 14 met inclusion criteria for analysis. These consisted of one cohort, eight case-control and five cross-sectional studies. The studies were conducted between 1990–2008, and the majority of studies were located in the USA (8/14) or UK (3/14). The risk factors related to management change that were assessed were feed, carer, exercise, pasture, water and housing. The largest bodies of evidence for increased risk of colic associated with management change were changes in feed (5/14 publications) and recent change in housing (3/14). Most studies (8/14) did not meet the JBI criterion on confounding factors. There was marked heterogeneity of study methodologies and measures. This is the first study to use a combined scoping and systematic review to analyse evidence for modifiable risk factors for a common condition in the horse. It provides a comprehensive review that will be a key resource for researchers, veterinary practitioners and horse owners. It identified modifiable risk factors associated with an increased risk of colic which should be a key target for preventative health programmes. The findings from the critical appraisal were used to develop recommendations for future research to improve the quality of evidence-based veterinary medicine.

Direct Effect of Iron Deficiency Independent of Anemia on Adverse Perinatal Outcomes- a Scoping Review

BackgroundDigital microscopy combined with artificial intelligence (AI) is increasingly being implemented in health care, predominantly in advanced laboratory settings. However, AI-supported digital microscopy could be especially advantageous in primary health care settings, since such methods could improve access to diagnostics via automation and a decreased need for experts on-site. To our knowledge, no scoping or systematic review has previously examined the use of AI-supported digital microscopy in primary health care laboratories, and a scoping review could guide future research by providing insights into the challenges of implementing these novel methods.ObjectiveThis scoping review aimed to map published peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories to generate an overview of the subject.MethodsA systematic search of the databases PubMed, Web of Science, Embase, and IEEE was conducted on October 2, 2024. The inclusion criteria in the scoping review were based on 3 concepts: using digital microscopy, AI, and comparison of the results with a standard diagnostic system, and 1 context, being performed in primary health care laboratories. Additional inclusion criteria were peer-reviewed diagnostic accuracy studies published in English, performed on humans and achieving a sample-level diagnosis. The study selection and data extraction were performed by 2 independent researchers (JVB and AS), and cases of disagreement were resolved through discussion with a third researcher (NL). The methodology is in accordance with the Joanna Briggs Institute methodology for scoping reviews.ResultsA total of 3403 papers were screened during the paper identification process, of which 22 (0.6%) were included in the scoping review. The samples analyzed were as follows: blood (n=12) for blood cell and malaria detection, urine (n=4) for urinalysis and parasite detection, cytology of atypical oral (n=1) and cervical cells (n=2), stool (n=2) for parasite detection, and sputum (n=1) for ferning patterns indicating inflammation. Both conventional (n=15) and specifically developed methods (n=7) were used in sample preparation. The AI-supported digital microscopy achieved comparable diagnostic accuracy to the reference standard for complete blood counts, malaria detection, identification of stool and genitourinary parasites, screening for oral and cervical cellular atypia, detection of pulmonary inflammation, and urinalysis. Furthermore, AI-supported digital microscopy achieved higher sensitivity than manual microscopy in 6/7 (85.7%) studies that used a reference standard that allowed for this comparison.ConclusionsAI-supported digital microscopy achieved comparable diagnostic accuracy to the reference standard for diagnosing multiple targets in primary health care laboratories and may be particularly advantageous for improving diagnostic sensitivity. With further research addressing challenges such as scalability and cost-effectiveness, AI-supported digital microscopy could improve access to diagnostics, especially in expert-scarce and resource-limited settings.

BACKGROUND Digital microscopy combined with artificial intelligence (AI) is increasingly being implemented in health care, predominantly in advanced laboratory settings. However, AI-supported digital microscopy could be especially advantageous in primary health care settings, since such methods could improve access to diagnostics via automation and a decreased need for experts on-site. To our knowledge, no scoping or systematic review has previously examined the use of AI-supported digital microscopy in primary health care laboratories, and a scoping review could guide future research by providing insights into the challenges of implementing these novel methods. OBJECTIVE This scoping review aimed to map published peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories to generate an overview of the subject. METHODS A systematic search of the databases PubMed, Web of Science, Embase, and IEEE was conducted on October 2, 2024. The inclusion criteria in the scoping review were based on three concepts: using digital microscopy, AI, and comparison of the results to a standard diagnostic system; and one context, being performed in primary health care laboratories. Additional inclusion criteria were peer reviewed diagnostic accuracy studies in English performed on humans and achieving a sample level diagnosis. The study selection and data extraction were performed by two independent researchers, and cases of disagreement were solved through discussion with a third researcher. The methodology is in accordance with the JBI methodology for scoping reviews. RESULTS A total of 3,403 articles were screened during the article identification process, of which 22 (0.6%) were included in the scoping review. The samples analyzed were as follows: blood (n=12) for blood cell and malaria detection; urine (n=4) for urinalysis and parasite detection; cytology of atypical oral (n=1) and cervical cells (n=2); stool (n=2) for parasite detection; and sputum (n=1) for ferning-patterns indicating inflammation. Both conventional (n=15) and specifically developed methods (n=7) were used in sample preparation. The AI models used were based on both single (n=11) and multiple AI-algorithms (n=11) and all studies except one used convolutional neural networks. The AI-supported digital microscopy achieved comparable diagnostic accuracy to the reference standard for complete blood counts, malaria detection, identification of stool and genitourinary parasites, screening for oral and cervical cellular atypia, detection of pulmonary inflammation, and urinalysis. The AI-supported digital microscopy had higher sensitivity than manual microscopy in six out of seven (85.7%) studies that used a reference standard that allowed for this comparison. CONCLUSIONS AI-supported digital microscopy achieved comparable diagnostic accuracy to the reference standard for diagnosing multiple targets in primary health care laboratories and may be particularly advantageous for improving diagnostic sensitivity. However, many shared challenges, ranging from sample preparation to workflow integration, need to be addressed to enable real world implementation. CLINICALTRIAL JMIR Res Protoc 2024;13:e58149 doi:10.2196/58149 INTERNATIONAL REGISTERED REPORT RR2-10.2196/58149

Social robots are widely used in educational activities. Apart from their hardware features that makes them capable of interacting with students, teachers, and educational stakeholders, the software applications are of great importance for a successful use. In the current paper, we present the design and architecture of the STIMEY robot application. The application was designed to transmit all information to and from the robot, ensuring communication between the robot agent and a) the educational platform, b) other social robots, c) the current user.

This scoping review aims to systematically identify and map the roles of primary healthcare professionals in rural and remote areas during natural, man-made and pandemic disasters. Disasters can be caused by natural events, man-made incidents or infective agents resulting in a pandemic. Healthcare practitioners working in primary care settings have important roles during disaster prevention, preparedness, response and recovery. When rural and remote settings are affected by disasters, there are unique challenges for healthcare professionals. This review will aim to contribute to disaster management knowledge within rural and remote primary health care, and assist in the development of practice-based disaster preparedness and future policy discussion. This review will consider studies that include primary healthcare professionals, defined as having first-level contact with patients in the community, in rural or remote areas only. The role of the healthcare professional will also be discussed within the paper. Research from Australia, Canada, the USA, New Zealand and the UK will be included. Databases to be searched include CINAHL (EBSCOhost), PubMed, Scopus and Embase (Elsevier), as well as gray literature within Trove, MedNar and OpenGrey. The search will be limited to articles written in English and published from 1978 to the present. Titles and abstracts will be screened by two independent reviewers, and full-text studies will be retrieved and assessed against the inclusion criteria. Results will be recorded in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram. Data will be extracted and presented as a tabular summary with supporting narratives and figures.

This scoping review aims to map the evidence on circus activities described and/or evaluated as a health intervention for children, youths, and adolescents. Increased understanding of how these interventions work, and gaps identified, will allow researchers and practitioners to advance the science behind these approaches. Circus activities are proposed in the literature as a health intervention, due to their variety, non-competitive nature, and potential to develop fundamental physical and social skills. For the purposes of this review, circus activities as a health intervention are defined as aerial, acrobatic, equilibristic, and manipulation skills taught to participants to maintain, improve, or modify health, functioning, or health conditions. English-language evidence will be considered where circus activities as a health intervention are described and/or evaluated for participants up to 24 years of age, or who are defined as children, youths, or adolescents. Literature will be excluded where the focus of the intervention is clowning, magic, or drama games, or where circus activities are not the therapeutic part of the activity. MEDLINE (Ovid), CINAHL Complete (EBSCO), Scopus (Elsevier), PsycINFO (Ovid), ProQuest Dissertations and Theses Global, and Google Scholar will be searched for peer-reviewed and gray literature. No restriction on dates, type, methodology, or setting will be imposed, but limits will include "human" and "English language." Screening and data extraction will be performed by two independent reviewers. Reference lists of included sources will be screened. Results will be presented in diagrammatic or tabular format, alongside a narrative description, under headings aligning with the research sub-questions.

There is currently no systematic review of the growing body of literature on using social robots in early developmental research. Designing appropriate methods for early childhood research is crucial for broadening our understanding of young children's social and cognitive development. This scoping review systematically examines the existing literature on using social robots to study social and cognitive development in infants and toddlers aged between 2 and 35 months. Moreover, it aims to identify the research focus, findings, and reported gaps and challenges when using robots in research. We included empirical studies published between 1990 and May 29, 2023. We searched for literature in PsychINFO, ERIC, Web of Science, and PsyArXiv. Twenty-nine studies met the inclusion criteria and were mapped using the scoping review method. Our findings reveal that most studies were quantitative, with experimental designs conducted in a laboratory setting where children were exposed to physically present or virtual robots in a one-to-one situation. We found that robots were used to investigate four main concepts: animacy concept, action understanding, imitation, and early conversational skills. Many studies focused on whether young children regard robots as agents or social partners. The studies demonstrated that young children could learn from and understand social robots in some situations but not always. For instance, children's understanding of social robots was often facilitated by robots that behaved interactively and contingently. This scoping review highlights the need to design social robots that can engage in interactive and contingent social behaviors for early developmental research.

There is currently no systematic review of the growing body of literature on using social robots in early developmental research. Designing appropriate methods for early childhood research is crucial for broadening our understanding of young children’s social and cognitive development. This scoping review systematically examines the existing literature on using social robots to study social and cognitive development in infants and toddlers aged between 2 and 35 months. Moreover, it aims to identify the research focus, findings, and reported gaps and challenges when using robots in research. We included empirical studies published between 1990 and May 29, 2023. We searched for literature in PsychINFO, ERIC, Web of Science, and PsyArXiv. Twenty-nine studies met the inclusion criteria and were mapped using the scoping review method. Our findings reveal that most studies were quantitative, with experimental designs conducted in a laboratory setting where children were exposed to physically present or virtual robots in a one-to-one situation. We found that robots were used to investigate four main concepts: animacy concept, action understanding, imitation, and early conversational skills. Many studies focused on whether young children regard robots as agents or social partners. The studies demonstrated that young children could learn from and understand social robots in some situations but not always. For instance, children’s understanding of social robots was often facilitated by robots that behaved interactively and contingently. This scoping review highlights the need to design social robots that can engage in interactive and contingent social behaviors for early developmental research.

PurposeThis review scopes evidence on the use of social robots for older adults with depressive symptoms, in the scenario of smart cities, analyzing the age-related depression specificities, investigated contexts and intervention protocols' features.Design/methodology/approachStudies retrieved from two major databases were selected against inclusion and exclusion criteria. Studies were included if used social robots, included older adults over 60, and reported depressive symptoms measurements, with any type of research design. Papers not published in English, published as an abstract or study protocol, or not peer-reviewed were excluded.Findings28 relevant studies were included, in which PARO was the most used robot. Most studies included very older adults with neurocognitive disorders living in long-term care facilities. The intervention protocols were heterogeneous regarding the duration, session duration and frequency. Only 35.6% of the studies had a control group. Finally, only 32.1% of the studies showed a significant improvement in depression symptoms.Originality/valueDespite the potential for using social robots in mental health interventions, in the scenario of smart cities, this review showed that their usefulness and effects in improving depressive symptoms in older adults have low internal and external validity. Future studies should consider factors as planning the intervention based on well-established supported therapies, characteristics and needs of the subjects, and the context in which the subjects are inserted.

The German health and care system is transforming due to advancing digitalization. New technological applications in nursing, such as social and assistance robotics, artificial intelligence and legal framework conditions are increasingly focused in numerous research projects. However, the approaches to digitalization in nursing are very different. When integrating technologies such as robotics and artificial intelligence into nursing, it is particularly important to ensure that ethical and human aspects are taken into account. A structured classification of the development of digitalization in nursing care is currently hardly possible. In order to be able to adequately deal with this digital transformation, the acquisition of digital competences in nursing education programs is pivotal. These include the confident, critical and creative use of information and communication technologies in a private and professional context. This paper focuses on the question which specific training offers already exist at national and international level for nursing professions to acquire digital competences. A scoping review according to the PRISMA scheme was conducted in the PubMed and CINAHL databases. The search period for the scoping review extended from 2017 to 2024. The selection of the studies took place by inclusion and exclusion criteria and the content-related orientation of the publications. After reviewing the titles and abstracts, eight studies were included. Of these, four were published in German-speaking countries and another four in international English-language journals. The topic of digitization of the nursing professions and the question of how nurses can acquire digital competences is gaining international attention. Nevertheless, the research on explicit continuing education programs for nursing professions is still undifferentiated. No specific continuing education offer for the development of digital competences of nursing professionals was identified. Many authors remained at the meta-level when developing methodological concepts for the acquisition of digital competences. The systematic integration of digitalization into higher education and continuing vocational training is mentioned in the publications. The development of theory- and research-based educational frameworks, which can be used as a basis for curricula in nursing studies and continuing education, is highly recommendable.