Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review.

BACKGROUND: Emerging digital health technology has moved into the reproductive health market for female individuals. In the past, mobile health apps have been used to monitor the menstrual cycle using manual entry. New technological trends involve the use of wearable devices to track fertility by assessing physiological changes such as temperature, heart rate, and respiratory rate. OBJECTIVE: The primary aims of this study are to review the types of wearables that have been developed and evaluated for menstrual cycle tracking and to examine whether they may detect changes in the menstrual cycle in female individuals. Another aim is to review whether these devices are effective for tracking various stages in the menstrual cycle including ovulation and menstruation. Finally, the secondary aim is to assess whether the studies have validated their findings by reporting accuracy and sensitivity. METHODS: A review of PubMed or MEDLINE was undertaken to evaluate wearable devices for their effectiveness in predicting fertility and differentiating between the different stages of the menstrual cycle. RESULTS: Fertility cycle-tracking wearables include devices that can be worn on the wrists, on the fingers, intravaginally, and inside the ear. Wearable devices hold promise for predicting different stages of the menstrual cycle including the fertile window and may be used by female individuals as part of their reproductive health. Most devices had high accuracy for detecting fertility and were able to differentiate between the luteal phase (early and late), fertile window, and menstruation by assessing changes in heart rate, heart rate variability, temperature, and respiratory rate. CONCLUSIONS: More research is needed to evaluate consumer perspectives on reproductive technology for monitoring fertility, and ethical issues around the privacy of digital data need to be addressed. Additionally, there is also a need for more studies to validate and confirm this research, given its scarcity, especially in relation to changes in respiratory rate as a proxy for reproductive cycle staging.

Information and Communications Technologies Enabling Integrated Primary Care for Patients With Complex Care Needs: Scoping Review.

BACKGROUND: Information and communications technologies (ICTs) are recognized as critical enablers of integrated primary care to support patients with multiple chronic conditions. Although ICT-enabled integrated primary care holds promise in supporting patients with complex care needs through team-based and continued care, critical implementation factors regarding what ICTs are available and how they enable this model are yet to be mapped in the literature. OBJECTIVE: This scoping review addressed the current knowledge gap by answering the following research question: What ICTs are used in delivering integrated primary care to patients with complex care needs? METHODS: The Arksey and O'Malley method enhanced by the work by Levac et al was used to guide this scoping review. In total, 4 electronic medical databases were accessed-MEDLINE, Embase, CINAHL, and PsycINFO-collecting studies published between January 2000 and December 2021. Identified peer-reviewed articles were screened. Relevant studies were charted, collated, and analyzed using the Rainbow Model of Integrated Care and the eHealth Enhanced Chronic Care Model. RESULTS: A total of 52,216 articles were identified, of which 31 (0.06%) met the review's eligibility criteria. In the current literature, ICTs are used to serve the following functions in the integrated primary care setting: information sharing, self-management support, clinical decision-making, and remote service delivery. Integration efforts are supported by ICTs by promoting teamwork and coordinating clinical services across teams and organizations. Patient, provider, organizational, and technological implementation factors are considered important for ICT-based interventions in the integrated primary care setting. CONCLUSIONS: ICTs play a critical role in enabling clinical and professional integration in the primary care setting to meet the health system-related needs of patients with complex care needs. Future research is needed to explore how to integrate technologies at an organizational and system level to create a health system that is well prepared to optimize technologies to support patients with complex care needs.

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review.

BACKGROUND: Given the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews focus on the application of social media, and there is a lack of reviews that integrate the methods for analyzing social media information for health care. OBJECTIVE: This scoping review aims to answer the following 4 questions: (1) What types of research have been used to investigate social media for health care, (2) what methods have been used to analyze the existing health information on social media, (3) what indicators should be applied to collect and evaluate the characteristics of methods for analyzing the contents of social media for health care, and (4) what are the current problems and development directions of methods used to analyze the contents of social media for health care? METHODS: A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted. We searched PubMed, the Web of Science, EMBASE, the Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library for the period from 2010 to May 2023 for primary studies focusing on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted. RESULTS: Of 16,161 identified citations, 134 (0.8%) studies were included in this review. These included 67 (50.0%) qualitative designs, 43 (32.1%) quantitative designs, and 24 (17.9%) mixed methods designs. The applied research methods were classified based on the following aspects: (1) manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring tables) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis, topic modeling, sentiment analysis, and other natural language processing technologies), (2) categories of research contents, and (3) health care areas (health practice, health services, and health education). CONCLUSIONS: Based on an extensive literature review, we investigated the methods for analyzing the contents of social media for health care to determine the main applications, differences, trends, and existing problems. We also discussed the implications for the future. Traditional content analysis is still the mainstream method for analyzing social media content, and future research may be combined with big data research. With the progress of computers, mobile phones, smartwatches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources, such as pictures, videos, and physiological signals, with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis. Overall, this scoping review can be useful for a large audience that includes researchers entering the field.

Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review.

BACKGROUND: Pancreatic cancer is the 12th most common cancer worldwide, with an overall survival rate of 4.9%. Early diagnosis of pancreatic cancer is essential for timely treatment and survival. Artificial intelligence (AI) provides advanced models and algorithms for better diagnosis of pancreatic cancer. OBJECTIVE: This study aims to explore AI models used for the prediction and early diagnosis of pancreatic cancers as reported in the literature. METHODS: A scoping review was conducted and reported in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. PubMed, Google Scholar, Science Direct, BioRXiv, and MedRxiv were explored to identify relevant articles. Study selection and data extraction were independently conducted by 2 reviewers. Data extracted from the included studies were synthesized narratively. RESULTS: Of the 1185 publications, 30 studies were included in the scoping review. The included articles reported the use of AI for 6 different purposes. Of these included articles, AI techniques were mostly used for the diagnosis of pancreatic cancer (14/30, 47%). Radiological images (14/30, 47%) were the most frequently used data in the included articles. Most of the included articles used data sets with a size of <1000 samples (11/30, 37%). Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). Six validation approaches were used in the included studies, of which the most frequently used approaches were k-fold cross-validation (10/30, 33%) and external validation (10/30, 33%). A higher level of accuracy (99%) was found in studies that used support vector machine, decision trees, and k-means clustering algorithms. CONCLUSIONS: This review presents an overview of studies based on AI models and algorithms used to predict and diagnose pancreatic cancer patients. AI is expected to play a vital role in advancing pancreatic cancer prediction and diagnosis. Further research is required to provide data that support clinical decisions in health care.

Defining the Digital Measurement of Scratching During Sleep or Nocturnal Scratching: Review of the Literature.

BACKGROUND: Digital sensing solutions represent a convenient, objective, relatively inexpensive method that could be leveraged for assessing symptoms of various health conditions. Recent progress in the capabilities of digital sensing products has targeted the measurement of scratching during sleep, traditionally referred to as nocturnal scratching, in patients with atopic dermatitis or other skin conditions. Many solutions measuring nocturnal scratch have been developed; however, a lack of efforts toward standardization of the measure's definition and contextualization of scratching during sleep hampers the ability to compare different technologies for this purpose. OBJECTIVE: We aimed to address this gap and bring forth unified measurement definitions for nocturnal scratch. METHODS: We performed a narrative literature review of definitions of scratching in patients with skin inflammation and a targeted literature review of sleep in the context of the period during which such scratching occurred. Both searches were limited to English language studies in humans. The extracted data were synthesized into themes based on study characteristics: scratch as a behavior, other characterization of the scratching movement, and measurement parameters for both scratch and sleep. We then developed ontologies for the digital measurement of sleep scratching. RESULTS: In all, 29 studies defined inflammation-related scratching between 1996 and 2021. When cross-referenced with the results of search terms describing the sleep period, only 2 of these scratch-related papers also described sleep-related variables. From these search results, we developed an evidence-based and patient-centric definition of nocturnal scratch: an action of rhythmic and repetitive skin contact movement performed during a delimited time period of intended and actual sleep that is not restricted to any specific time of the day or night. Based on the measurement properties identified in the searches, we developed ontologies of relevant concepts that can be used as a starting point to develop standardized outcome measures of scratching during sleep in patients with inflammatory skin conditions. CONCLUSIONS: This work is intended to serve as a foundation for the future development of unified and well-described digital health technologies measuring nocturnal scratching and should enable better communication and sharing of results between various stakeholders taking part in research in atopic dermatitis and other inflammatory skin conditions.

Performance-Based Measurement of eHealth Literacy: Systematic Scoping Review.

BACKGROUND: eHealth literacy describes the ability to locate, comprehend, evaluate, and apply web-based health information to a health problem. In studies of eHealth literacy, researchers have primarily assessed participants' perceived eHealth literacy using a short self-report instrument, for which ample research has shown little to no association with actual performed eHealth-related skills. Performance-based measures of eHealth literacy may be more effective at assessing actual eHealth skills, yet such measures seem to be scarcer in the literature. OBJECTIVE: The primary purpose of this study was to identify tools that currently exist to measure eHealth literacy based on objective performance. A secondary purpose of this study was to characterize the prevalence of performance-based measurement of eHealth literacy in the literature compared with subjective measurement. METHODS: We conducted a systematic scoping review of the literature, aligning with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist, in 3 stages: conducting the search, screening articles, and extracting data into a summary table. The summary table includes terminology for eHealth literacy, description of participants, instrument design, health topics used, and a brief note on the evidence of validity for each performance-based measurement tool. A total of 1444 unique articles retrieved from 6 relevant databases (MEDLINE; PsycINFO; CINAHL; Library and Information Science Abstracts [LISA]; Library, Information Science & Technology Abstracts [LISTA]; and Education Resources Information Center [ERIC]) were considered for inclusion, of which 313 (21.68%) included a measure of eHealth literacy. RESULTS: Among the 313 articles that included a measure of eHealth literacy, we identified 33 (10.5%) that reported on 29 unique performance-based eHealth literacy measurement tools. The types of tools ranged from having participants answer health-related questions using the internet, having participants engage in simulated internet tasks, and having participants evaluate website quality to quizzing participants on their knowledge of health and the web-based health information-seeking process. In addition, among the 313 articles, we identified 280 (89.5%) that measured eHealth literacy using only a self-rating tool. CONCLUSIONS: This study is the first research synthesis looking specifically at performance-based measures of eHealth literacy and may direct researchers toward existing performance-based measurement tools to be applied in future projects. We discuss some of the key benefits and drawbacks of different approaches to performance-based measurement of eHealth literacy. Researchers with an interest in gauging participants' actual eHealth literacy (as opposed to perceived eHealth literacy) should make efforts to incorporate tools such as those identified in this systematic scoping review.

The Effectiveness of Digital Apps Providing Personalized Exercise Videos: Systematic Review With Meta-Analysis.

BACKGROUND: Among available digital apps, those providing personalized video exercises may be helpful for individuals undergoing functional rehabilitation. OBJECTIVE: We aimed to assess the effectiveness of apps providing personalized video exercises to support rehabilitation for people with short- and long-term disabling conditions, on functional capacity, confidence in exercise performance, health care consumption, health-related quality of life, adherence, and adverse events. METHODS: In this systematic review, we searched MEDLINE, CENTRAL, and Embase databases up to March 2022. All randomized controlled trials evaluating the effect of apps providing personalized video exercises to support rehabilitation for any condition requiring physical rehabilitation were included. Selection, extraction, and risk of bias assessment were performed by 2 independent reviewers. The primary outcome was functional capacity at the end of the intervention. The secondary outcomes included confidence in exercise performance, care consumption, health-related quality of life, adherence, and adverse events. A meta-analysis was performed where possible; the magnitude of the effect was assessed with the standardized mean difference (SMD). RESULTS: From 1641 identified references, 10 papers (n=1050 participants, 93% adults) were included: 7 papers (n=906 participants) concerned musculoskeletal disorders and 3 (n=144 participants) concerned neurological disorders. Two (n=332 participants) were employee based. The apps were mostly commercial (7/10); the videos were mostly elaborated on by a physiotherapist (8/10). The duration of app use was 3-48 weeks. All included studies had a high overall risk of bias. Low-quality evidence suggested that the use of apps providing personalized video exercises led to a significant small to moderate improvement in physical function (SMD 0.35, 95% CI 0.19-0.51; Phet=.86; I2=0%) and confidence in exercise performance (SMD 0.67; 95% CI 0.37-0.96; Phet=.22; I2=33%). Because of the very low quality of the evidence, the effects on quality of life and exercise adherence were uncertain. Apps did not influence the rate of adverse events. CONCLUSIONS: Apps providing personalized video exercises to support exercise performance significantly improved physical function and confidence in exercise performance. However, the level of evidence was low; more robust studies are needed to confirm these results. TRIAL REGISTRATION: PROSPERO CRD42022323670; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323670.

Health-Related Data Sources Accessible to Health Researchers From the US Government: Mapping Review.

BACKGROUND: Big data from large, government-sponsored surveys and data sets offers researchers opportunities to conduct population-based studies of important health issues in the United States, as well as develop preliminary data to support proposed future work. Yet, navigating these national data sources is challenging. Despite the widespread availability of national data, there is little guidance for researchers on how to access and evaluate the use of these resources. OBJECTIVE: Our aim was to identify and summarize a comprehensive list of federally sponsored, health- and health care-related data sources that are accessible in the public domain in order to facilitate their use by researchers. METHODS: We conducted a systematic mapping review of government sources of health-related data on US populations and with active or recent (previous 10 years) data collection. The key measures were government sponsor, overview and purpose of data, population of interest, sampling design, sample size, data collection methodology, type and description of data, and cost to obtain data. Convergent synthesis was used to aggregate findings. RESULTS: Among 106 unique data sources, 57 met the inclusion criteria. Data sources were classified as survey or assessment data (n=30, 53%), trends data (n=27, 47%), summative processed data (n=27, 47%), primary registry data (n=17, 30%), and evaluative data (n=11, 19%). Most (n=39, 68%) served more than 1 purpose. The population of interest included individuals/patients (n=40, 70%), providers (n=15, 26%), and health care sites and systems (n=14, 25%). The sources collected data on demographic (n=44, 77%) and clinical information (n=35, 61%), health behaviors (n=24, 42%), provider or practice characteristics (n=22, 39%), health care costs (n=17, 30%), and laboratory tests (n=8, 14%). Most (n=43, 75%) offered free data sets. CONCLUSIONS: A broad scope of national health data is accessible to researchers. These data provide insights into important health issues and the nation's health care system while eliminating the burden of primary data collection. Data standardization and uniformity were uncommon across government entities, highlighting a need to improve data consistency. Secondary analyses of national data are a feasible, cost-efficient means to address national health concerns.

The Effects of Internet-Based Cognitive Behavioral Therapy for Suicidal Ideation or Behaviors on Depression, Anxiety, and Hopelessness in Individuals With Suicidal Ideation: Systematic Review and Meta-Analysis of Individual Participant Data.

BACKGROUND: Suicide is a global public health problem. Digital interventions are considered a low-threshold treatment option for people with suicidal ideation or behaviors. Internet-based cognitive behavioral therapy (iCBT) targeting suicidal ideation has demonstrated effectiveness in reducing suicidal ideation. However, suicidal ideation often is related to additional mental health problems, which should be addressed for optimal care. Yet, the effects of iCBT on related symptoms, such as depression, anxiety, and hopelessness, remain unclear. OBJECTIVE: We aimed to analyze whether digital interventions targeting suicidal ideation had an effect on related mental health symptoms (depression, anxiety, and hopelessness). METHODS: We systematically searched CENTRAL, PsycInfo, Embase, and PubMed for randomized controlled trials that investigated guided or unguided iCBT for suicidal ideation or behaviors. Participants reporting baseline suicidal ideation were eligible. Individual participant data (IPD) were collected from eligible trials. We conducted a 1-stage IPD meta-analysis on the effects on depression, anxiety, and hopelessness-analyzed as 2 indices: symptom severity and treatment response. RESULTS: We included IPD from 8 out of 9 eligible trials comprising 1980 participants with suicidal ideation. iCBT was associated with significant reductions in depression severity (b=-0.17; 95% CI -0.25 to -0.09; P<.001) and higher treatment response (ie, 50% reduction of depressive symptoms; b=0.36; 95% CI 0.12-0.60; P=.008) after treatment. We did not find significant effects on anxiety and hopelessness. CONCLUSIONS: iCBT for people with suicidal ideation revealed significant effects on depression outcomes but only minor or no effects on anxiety and hopelessness. Therefore, individuals with comorbid symptoms of anxiety or hopelessness may require additional treatment components to optimize care. Studies that monitor symptoms with higher temporal resolution and consider a broader spectrum of factors influencing suicidal ideation are needed to understand the complex interaction of suicidality and related mental health symptoms.

Using Twitter-Based Data for Sexual Violence Research: Scoping Review.

BACKGROUND: Scholars have used data from in-person interviews, administrative systems, and surveys for sexual violence research. Using Twitter as a data source for examining the nature of sexual violence is a relatively new and underexplored area of study. OBJECTIVE: We aimed to perform a scoping review of the current literature on using Twitter data for researching sexual violence, elaborate on the validity of the methods, and discuss the implications and limitations of existing studies. METHODS: We performed a literature search in the following 6 databases: APA PsycInfo (Ovid), Scopus, PubMed, International Bibliography of Social Sciences (ProQuest), Criminal Justice Abstracts (EBSCO), and Communications Abstracts (EBSCO), in April 2022. The initial search identified 3759 articles that were imported into Covidence. Seven independent reviewers screened these articles following 2 steps: (1) title and abstract screening, and (2) full-text screening. The inclusion criteria were as follows: (1) empirical research, (2) focus on sexual violence, (3) analysis of Twitter data (ie, tweets or Twitter metadata), and (4) text in English. Finally, we selected 121 articles that met the inclusion criteria and coded these articles. RESULTS: We coded and presented the 121 articles using Twitter-based data for sexual violence research. About 70% (89/121, 73.6%) of the articles were published in peer-reviewed journals after 2018. The reviewed articles collectively analyzed about 79.6 million tweets. The primary approaches to using Twitter as a data source were content text analysis (112/121, 92.5%) and sentiment analysis (31/121, 25.6%). Hashtags (103/121, 85.1%) were the most prominent metadata feature, followed by tweet time and date, retweets, replies, URLs, and geotags. More than a third of the articles (51/121, 42.1%) used the application programming interface to collect Twitter data. Data analyses included qualitative thematic analysis, machine learning (eg, sentiment analysis, supervised machine learning, unsupervised machine learning, and social network analysis), and quantitative analysis. Only 10.7% (13/121) of the studies discussed ethical considerations. CONCLUSIONS: We described the current state of using Twitter data for sexual violence research, developed a new taxonomy describing Twitter as a data source, and evaluated the methodologies. Research recommendations include the following: development of methods for data collection and analysis, in-depth discussions about ethical norms, exploration of specific aspects of sexual violence on Twitter, examination of tweets in multiple languages, and decontextualization of Twitter data. This review demonstrates the potential of using Twitter data in sexual violence research.

Evaluation of the Effectiveness of Telehealth Chronic Disease Management System: Systematic Review and Meta-analysis.

BACKGROUND: Long-term daily health monitoring and management play a more significant role in telehealth management systems nowadays, which require evaluation indicators to present patients' general health conditions and become applicable to multiple chronic diseases. OBJECTIVE: This study aims to evaluate the effectiveness of subjective indicators of telehealth chronic disease management system (TCDMS). METHODS: We selected Web of Science, ScienceDirect, Scopus, Cochrane library, IEEE, and Chinese National Knowledge Infrastructure and Wanfang, a Chinese medical database, and searched papers published from January 1, 2015, to July 1, 2022, regarding randomized controlled trials on the effectiveness of the telehealth system on patients with chronic diseases. The narrative review summarized the questionnaire indicators presented in the selected studies. In the meta-analysis, Mean Difference (MD) and Standardized Mean Difference (SMD) with a 95% CI were pooled depending on whether the measurements were the same. Subgroup analysis was conducted if the heterogeneity was significant, and the number of studies was sufficient. RESULTS: Twenty RCTs with 4153 patients were included in the qualitative review. Seventeen different questionnaire-based outcomes were found, within which quality of life, psychological well-being (including depression, anxiety, and fatigue), self-management, self-efficacy, and medical adherence were most frequently used. Ten RCTs with 2095 patients remained in meta-analysis. Compared to usual care, telehealth system can significantly improve the quality of life (SMD 0.44; 95% CI 0.16-0.73; P=.002), whereas no significant effects were found on depression (SMD -0.25; 95% CI -0.72 to 0.23; P=.30), anxiety (SMD -0.10; 95% CI -0.27 to 0.07; P=.71), fatigue (SMD -0.36; 95% CI -1.06 to 0.34; P<.001), and self-care (SMD 0.77; 95% CI -0.28-1.81; P<.001). In the subdomains of quality of life, telehealth statistically significantly improved physical functioning (SMD 0.15; 95% CI 0.02 to 0.29; P=.03), mental functioning (SMD 0.37; 95% CI 0.13-0.60; P=.002), and social functioning (SMD 0.64; 95% CI 0.00-1.29; P=.05), while there was no difference on cognitive functioning (MD 8.31; 95% CI -7.33 to 23.95; P=.30) and role functioning (MD 5.30; 95% CI -7.80 to 18.39; P=.43). CONCLUSIONS: TCDMS positively affected patients' physical, mental, and social quality of life across multiple chronic diseases. However, no significant difference was found in depression, anxiety, fatigue, and self-care. Subjective questionnaires had the potential ability to evaluate the effectiveness of long-term telehealth monitoring and management. However, further well-designed experiments are warranted to validate TCDMS's effects on subjective outcomes, especially when tested among different chronically ill groups.

Toward Inclusive Approaches in the Design, Development, and Implementation of eHealth in the Intellectual Disability Sector: Scoping Review.

BACKGROUND: The use of eHealth is more challenging for people with intellectual disabilities (IDs) than for the general population because the technologies often do not fit the complex needs and living circumstances of people with IDs. A translational gap exists between the developed technology and users' needs and capabilities. User involvement approaches have been developed to overcome this mismatch during the design, development, and implementation processes of the technology. The effectiveness and use of eHealth have received much scholarly attention, but little is known about user involvement approaches. OBJECTIVE: In this scoping review, we aimed to identify the inclusive approaches currently used for the design, development, and implementation of eHealth for people with IDs. We reviewed how and in what phases people with IDs and other stakeholders were included in these processes. We used 9 domains identified from the Centre for eHealth Research and Disease management road map and the Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability framework to gain insight into these processes. METHODS: We identified both scientific and gray literature through systematic searches in PubMed, Embase, PsycINFO, CINAHL, Cochrane, Web of Science, Google Scholar, and (websites of) relevant intermediate (health care) organizations. We included studies published since 1995 that showed the design, development, or implementation processes of eHealth for people with IDs. Data were analyzed along 9 domains: participatory development, iterative process, value specification, value proposition, technological development and design, organization, external context, implementation, and evaluation. RESULTS: The search strategy resulted in 10,639 studies, of which 17 (0.16%) met the inclusion criteria. Various approaches were used to guide user involvement (eg, human or user-centered design and participatory development), most of which applied an iterative process mainly during technological development. The involvement of stakeholders other than end users was described in less detail. The literature focused on the application of eHealth at an individual level and did not consider the organizational context. Inclusive approaches in the design and development phases were well described; however, the implementation phase remained underexposed. CONCLUSIONS: The participatory development, iterative process, and technological development and design domains showed inclusive approaches applied at the start of and during the development, whereas only a few approaches involved end users and iterative processes at the end of the process and during implementation. The literature focused primarily on the individual use of the technology, and the external, organizational, and financial contextual preconditions received less attention. However, members of this target group rely on their (social) environment for care and support. More attention is needed for these underrepresented domains, and key stakeholders should be included further on in the process to reduce the translational gap that exists between the developed technologies and user needs, capabilities, and context.

WeChat as a platform for blending problem/case-based learning and paper review methods in undergraduate paediatric orthopaedics internships: a feasibility and effectiveness study.

BACKGROUND: Paediatric orthopaedics is a significant and difficult for undergraduate students to master. During the COVID-19 pandemic, we used the WeChat platform to combine the advantages offered by problem-based learning (PBL), case-based learning (CBL) and paper review teaching methods to establish a new blended online teaching model and demonstrated its feasibility and effectiveness. OBJECTIVE: This study aims to demonstrate the feasibility and effectiveness of a new blended pedagogical method that uses the WeChat platform and combines PBL, CBL and paper review. METHODS: We enrolled 22 students participating in the Department of Paediatric Orthopaedics. They participated in the WeChat blended pedagogy mode. Their departmental rotation examination scores were compared with those of 23 students who participated in the traditional teaching method. Moreover, an anonymous questionnaire was used to evaluate students' perceptions and experiences. RESULTS: The total average scores of students who participated in the WeChat blended pedagogy mode and the traditional teaching method were 47.27 and 44.52, respectively. There were no statistically significant differences between the online teaching mode and the traditional teaching method in terms of possessing professional accomplishment, gaining knowledge and promoting interpersonal skills (P = 0.07, P = 0.12 and P = 0.65, respectively). In terms of independent clinical thinking, self-improving capability and improving clinical skills, the scores associated with the WeChat blended pedagogy mode were 8.00, 8.00 and 6.00, whereas those associated with the traditional teaching method were 6.70, 6.87 and 7.48. The overall satisfaction with the WeChat blended pedagogy mode reached 100%. A total of 64%, 86%, 68%, 64% and 59% of students chose very large or large in response to the items concerning professional accomplishment, knowledge absorption, independent clinical thinking skills, English reading and literature exploring capacity, as well as interpersonal skills, respectively. Fifteen participants claimed that the WeChat blended pedagogy mode was less helpful to them with regard to promoting the improvement of their clinical skills. Nine students claimed that the WeChat blended pedagogy mode was time-consuming. CONCLUSIONS: Our study verified the feasibility and effectiveness of the WeChat blended pedagogy mode for undergraduate paediatric orthopaedics internships. TRIAL REGISTRATION: Retrospectively registered.

Web-Based Forums for People Experiencing Substance Use or Gambling Disorders: Scoping Review.

BACKGROUND: For people experiencing substance use or gambling disorders, web-based peer-supported forums are a space where they can share their experiences, gather around a collective goal, and find mutual support. Web-based peer support can help to overcome barriers to attending face-to-face meetings by enabling people experiencing addiction to seek support beyond their physical location and with the benefit of anonymity if desired. Understanding who participates in web-based peer-supported forums (and how), and the principles underpinning forums, can also assist those interested in designing or implementing similar platforms. OBJECTIVE: This study aims to review the literature on how people experiencing substance use or gambling disorders, and their family, friends, and supporters, use and participate in web-based peer-supported forums. Specifically, we asked the following research questions: (1) What are the characteristics of people who use web-based peer-supported substance use or gambling-focused forums? (2) How do people participate in web-based peer-supported forums? (3) What are the key principles reportedly underpinning the web-based peer-supported forums? (4) What are the reported outcomes of web-based peer-supported forums? METHODS: Inclusion criteria for our scoping review were peer-reviewed primary studies reporting on web-based addiction forums for adults and available in English. A primary search of 10 databases occurred in June 2021, with 2 subsequent citation searches of included studies in September 2022 and February 2024. RESULTS: Of the 14 included studies, the majority of web-based peer-supported forums reported were aimed specifically for, or largely used by, people experiencing alcohol problems. Results from the 9 studies that did report demographic data suggest forum users were typically women, aged between 40 years and early 50 years. Participation in web-based peer-supported forums was reported quantitatively and qualitatively. The forums reportedly were underpinned by a range of key principles, mostly mutual help approaches and recovery identity formation. Only 3 included studies reported on outcomes for forum users. CONCLUSIONS: Web-based peer-supported forums are used by people experiencing addiction in a number of ways, to share information and experiences, and give and receive support. Seeking web-based support offers an alternative approach to traditional face-to-face support options, and may reduce some barriers to engaging in peer support.

Theoretical Perspectives Underpinning Research on the Physician-Patient Relationship in a Digital Health Practice: Scoping Review.

BACKGROUND: The advent of digital health technologies has transformed the landscape of health care, influencing the dynamics of the physician-patient relationship. Although these technologies offer potential benefits, they also introduce challenges and complexities that require ethical consideration. OBJECTIVE: This scoping review aims to investigate the effects of digital health technologies, such as digital messaging, telemedicine, and electronic health records, on the physician-patient relationship. To understand the complex consequences of these tools within health care, it contrasts the findings of studies that use various theoretical frameworks and concepts with studies grounded in relational ethics. METHODS: Using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review. Data were retrieved through keyword searches on MEDLINE/PubMed, Embase, IEEE Xplore, and Cochrane. We screened 427 original peer-reviewed research papers published in English-language journals between 2010 and 2021. A total of 73 papers were assessed for eligibility, and 10 of these were included in the review. The data were summarized through a narrative synthesis of the findings. RESULTS: Digital health technologies enhance communication, improve health care delivery efficiency, and empower patients, leading to shifts in power dynamics in the physician-patient relationship. They also potentially reinforce inequities in health care access due to variations in technology literacy among patients and lead to decreases in patient satisfaction due to the impersonal nature of digital interactions. Studies applying a relational ethics framework have revealed the nuanced impacts of digital health technologies on the physician-patient relationship, highlighting shifts toward more collaborative and reciprocal care. These studies have also explored transitions from traditional hierarchical relationships to mutual engagement, capturing the complexities of power dynamics and vulnerabilities. Other theoretical frameworks, such as patient-centered care, and concepts, such as patient empowerment, were also valuable for understanding these interactions in the context of digital health. CONCLUSIONS: The shift from hierarchical to collaborative models in the physician-patient relationship not only underscores the empowering potential of digital tools but also presents new challenges and reinforces existing ones. Along with applications for various theoretical frameworks and concepts, this review highlights the unique comprehensiveness of a relational ethics perspective, which could provide a more nuanced understanding of trust, empathy, and power dynamics in the context of digital health. The adoption of relational ethics in empirical research may offer richer insights into the real-life complexities of the physician-patient relationship, as mediated by digital technologies.

Digital Gamification Tools to Enhance Vaccine Uptake: Scoping Review.

BACKGROUND: Gamification has been used successfully to promote various desired health behaviors. Previous studies have used gamification to achieve desired health behaviors or facilitate their learning about health. OBJECTIVE: In this scoping review, we aimed to describe digital gamified tools that have been implemented or evaluated across various populations to encourage vaccination, as well as any reported effects of identified tools. METHODS: We searched Medline, Embase, CINAHL, the Web of Science Core Collection, the Cochrane Database of Systematic Reviews, the Cochrane Central Register of Controlled Trials, Academic Search Premier, PsycInfo, Global Health, and ERIC for peer-reviewed papers describing digital gamified tools with or without evaluations. We also conducted web searches with Google to identify digital gamified tools lacking associated publications. We consulted 12 experts in the field of gamification and health behavior to identify any papers or tools we might have missed. We extracted data about the target population of the tools, the interventions themselves (eg, type of digital gamified tool platform, type of disease/vaccine, type and design of study), and any effects of evaluated tools, and we synthesized data narratively. RESULTS: Of 1402 records, we included 28 (2%) peer-reviewed papers and 10 digital gamified tools lacking associated publications. The experts added 1 digital gamified tool that met the inclusion criteria. Our final data set therefore included 28 peer-reviewed papers and 11 digital gamified tools. Of the 28 peer-reviewed papers, 7 (25%) explained the development of the tool, 16 (57%) described evaluation, and 2 (7%) reported both development and evaluation of the tool. The 28 peer-reviewed papers reported on 25 different tools. Of these 25 digital gamified tools, 11 (44%) were web-based tools, 8 (32%) mobile (native mobile or mobile-enabled web) apps, and 6 (24%) virtual reality tools. Overall, tools that were evaluated showed increases in knowledge and intentions to receive vaccines, mixed effects on attitudes, and positive effects on beliefs. We did not observe discernible advantages of one type of digital gamified tool (web based, mobile, virtual reality) over the others. However, a few studies were randomized controlled trials, and publication bias may have led to such positive effects having a higher likelihood of appearing in the peer-reviewed literature. CONCLUSIONS: Digital gamified tools appear to have potential for improving vaccine uptake by fostering positive beliefs and increasing vaccine-related knowledge and intentions. Encouraging comparative studies of different features or different types of digital gamified tools could advance the field by identifying features or types of tools that yield more positive effects across populations and contexts. Further work in this area should seek to inform the implementation of gamification for vaccine acceptance and promote effective health communication, thus yielding meaningful health and social impacts.

Artificial Intelligence Applications for Assessment, Monitoring, and Management of Parkinson Disease Symptoms: Protocol for a Systematic Review.

BACKGROUND: Parkinson disease (PD) is the second most prevalent neurodegenerative disease, with around 10 million people with PD worldwide. Current assessments of PD symptoms are conducted by questionnaires and clinician assessments and have many limitations, including unreliable reporting of symptoms, little autonomy for patients over their disease management, and standard clinical review intervals regardless of disease status or clinical need. To address these limitations, digital technologies including wearable sensors, smartphone apps, and artificial intelligence (AI) methods have been implemented for this population. Many reviews have explored the use of AI in the diagnosis of PD and management of specific symptoms; however, there is limited research on the application of AI to the monitoring and management of the range of PD symptoms. A comprehensive review of the application of AI methods is necessary to address the gap of high-quality reviews and highlight the developments of the use of AI within PD care. OBJECTIVE: The purpose of this protocol is to guide a systematic review to identify and summarize the current applications of AI applied to the assessment, monitoring, and management of PD symptoms. METHODS: This review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. The following 5 databases will be systematically searched: PubMed, IEEE Xplore, Institute for Scientific Information's Web of Science, Scopus, and the Cochrane Library. Title and abstract screening, full-text review, and data extraction will be conducted by 2 independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or extraction will be discussed. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 tool for randomized trials and the Mixed Methods Appraisal Tool for nonrandomized trials. RESULTS: As of April 2023, this systematic review has not yet been started. It is expected to begin in May 2023, with the aim to complete by September 2023. CONCLUSIONS: The systematic review subsequently conducted as a product of this protocol will provide an overview of the AI methods being used for the assessment, monitoring, and management of PD symptoms. This will identify areas for further research in which AI methods can be applied to the assessment or management of PD symptoms and could support the future implementation of AI-based tools for the effective management of PD. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46581.

The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review.

BACKGROUND: Adverse drug events (ADEs) are a considerable public health burden resulting in disability, hospitalization, and death. Even those ADEs deemed nonserious can severely impact a patient's quality of life and adherence to intervention. Monitoring medication safety, however, is challenging. Social media may be a useful adjunct for obtaining real-world data on ADEs. While many studies have been undertaken to detect adverse events on social media, a consensus has not yet been reached as to the value of social media in pharmacovigilance or its role in pharmacovigilance in relation to more traditional data sources. OBJECTIVE: The aim of the study is to evaluate and characterize the use of social media in ADE detection and pharmacovigilance as compared to other data sources. METHODS: A scoping review will be undertaken. We will search 11 bibliographical databases as well as Google Scholar, hand-searching, and forward and backward citation searching. Records will be screened in Covidence by 2 independent reviewers at both title and abstract stage as well as full text. Studies will be included if they used any type of social media (such as Twitter or patient forums) to detect any type of adverse event associated with any type of medication and then compared the results from social media to any other data source (such as spontaneous reporting systems or clinical literature). Data will be extracted using a data extraction sheet piloted by the authors. Important data on the types of methods used (such as machine learning), any limitations of the methods used, types of adverse events and drugs searched for and included, availability of data and code, details of the comparison data source, and the results and conclusions will be extracted. RESULTS: We will present descriptive summary statistics as well as identify any patterns in the types and timing of ADEs detected, including but not limited to the similarities and differences in what is reported, gaps in the evidence, and the methods used to extract ADEs from social media data. We will also summarize how the data from social media compares to conventional data sources. The literature will be organized by the data source for comparison. Where possible, we will analyze the impact of the types of adverse events, the social media platform used, and the methods used. CONCLUSIONS: This scoping review will provide a valuable summary of a large body of research and important information for pharmacovigilance as well as suggest future directions of further research in this area. Through the comparisons with other data sources, we will be able to conclude the added value of social media in monitoring adverse events of medications, in terms of type of adverse events and timing. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47068.

Mobile Apps Aimed at Preventing and Handling Unintentional Injuries in Children Aged <7 Years: Systematic Review.

BACKGROUND: Despite various global health crises, the prevention and handling of unintentional childhood injuries remains an important public health objective. Although several systematic reviews have examined the effectiveness of different child injury prevention measures, these reviews did not address the evaluation of mobile communication intervention tools. Whether and how mobile apps were evaluated provides information on the extent to which communication theories, models, and evidence-based knowledge were considered. Previous studies have shown that the effectiveness of mobile apps increases when theories and evidence are considered during their development. OBJECTIVE: This systematic review aimed to identify research on mobile apps dealing with the prevention and handling of unintentional injuries in children and examine the theoretical and methodological approaches thereof. In addition, this review analyzed the different needs of various target groups of the mobile apps described in the articles. METHODS: In total, 8 electronic databases, ranging from interdisciplinary to medical and technical as well as social sciences databases, were searched for original research articles or brief reports in peer-reviewed journals or conference proceedings. Moreover, this review encompassed a systematic scan of articles published in the BMJ journal Injury Prevention. These steps were followed by a snowball search based on the literature references in the articles identified through the initial screening. The articles had to be written in English or German, published between 2008 and 2021, and evaluate mobile apps dealing with the prevention and handling of unintentional child injuries. The identified 5 studies were analyzed by 5 independent researchers using an inductive approach. Furthermore, the quality of the studies was assessed using the Mixed Methods Appraisal Tool. RESULTS: A total of 5 articles were included and assessed with regard to overall quality of theoretical and methodological foundations, assessed variables, the focal app's architecture, and the needs of the study participants. The overall study quality was moderate, although part of this classification was due to a lack of details reported in the studies. Each study examined 1 mobile app aimed at parents and other caregivers. Each study assessed at least 1 usability- or user experience-related variable, whereas the needs of the included study participants were detailed in only 20% (1/5) of the cases. However, none of the studies referred to theories such as the Technology Acceptance Model during the development of the apps. CONCLUSIONS: The future development and evaluation of apps dealing with the prevention and handling of child injuries should combine insights into existing models on user experience and usability with established theories on mobile information behavior. This theory-based approach will increase the validity of such evaluation studies.

Methods for the Clinical Validation of Digital Endpoints: Protocol for a Scoping Review Abstract.

BACKGROUND: Clinical trials often use digital technologies to collect data continuously outside the clinic and use the derived digital endpoints as trial endpoints. Digital endpoints are also being developed to support diagnosis, monitoring, or therapeutic interventions in clinical care. However, clinical validation stands as a significant challenge, as there are no specific guidelines orienting the validation of digital endpoints. OBJECTIVE: This paper presents the protocol for a scoping review that aims to map the existing methods for the clinical validation of digital endpoints. METHODS: The scoping review will comprise searches from the electronic literature databases MEDLINE (PubMed), Scopus (including conference proceedings), Embase, IEEE (Institute of Electrical and Electronics Engineers) Xplore, ACM (Association for Computing Machinery) Digital Library, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science Core Collection (including conference proceedings), and Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports. We will also include various sources of gray literature with search terms related to digital endpoints. The methodology will adhere to the Joanna Briggs Institute Scoping Review and the Guidance for Conducting Systematic Scoping Reviews. RESULTS: A search for reviews on the existing evidence related to this topic was conducted and has shown that no such review was previously undertaken. This review will provide a systematic assessment of the literature on methods for the clinical validation of digital endpoints and highlight any potential need for harmonization or reporting of methods. The results will include the methods for the clinical validation of digital endpoints according to device, digital endpoint, and clinical application goal of digital endpoints. The study started in January 2023 and is expected to end by December 2023, with results to be published in a peer-reviewed journal. CONCLUSIONS: A scoping review of methodologies that validate digital endpoints is necessary. This review will be unique in its breadth since it will comprise digital endpoints collected from several devices and not focus on a specific disease area. The results of our work should help guide researchers in choosing validation methods, identify potential gaps in the literature, or inform the development of novel methods to optimize the clinical validation of digital endpoints. Resolving these gaps is the key to presenting evidence in a consistent way to regulators and other parties and obtaining regulatory acceptance of digital endpoints for patient benefit. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47119.