Designing personalised mHealth solutions: An overview.

INTRODUCTION: Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation. MATERIALS AND METHODS: We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques. RESULTS: Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed. DISCUSSION: Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it. CONCLUSIONS: Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.

Social Media as an Effective Provider of Quality-Assured and Accurate Information to Increase Vaccine Rates: Systematic Review.

BACKGROUND: Vaccination programs are instrumental in prolonging and improving people's lives by preventing diseases such as measles, diphtheria, tetanus, pertussis, and influenza from escalating into fatal epidemics. Despite the significant impact of these programs, a substantial number of individuals, including 20 million infants annually, lack sufficient access to vaccines. Therefore, it is imperative to raise awareness about vaccination programs. OBJECTIVE: This study aims to investigate the potential utilization of social media, assessing its scalability and robustness in delivering accurate and reliable information to individuals who are contemplating vaccination decisions for themselves or on behalf of their children. METHODS: The protocol for this review is registered in PROSPERO (identifier CRD42022304229) and is being carried out in compliance with the Cochrane Handbook for Systematic Reviews of Interventions. Comprehensive searches have been conducted in databases including MEDLINE, Embase, PsycINFO, CINAHL (Cumulative Index to Nursing and Allied Health), CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar. Only randomized controlled trials (RCTs) were deemed eligible for inclusion in this study. The target population encompasses the general public, including adults, children, and adolescents. The defined interventions comprise platforms facilitating 2-way communication for sharing information. These interventions were compared against traditional interventions and teaching methods, referred to as the control group. The outcomes assessed in the included studies encompassed days unvaccinated, vaccine acceptance, and the uptake of vaccines compared with baseline. The studies underwent a risk-of-bias assessment utilizing the Cochrane Risk-of-Bias tool for RCTs, and the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment. RESULTS: This review included 10 studies, detailed in 12 articles published between 2012 and 2022, conducted in the United States, China, Jordan, Australia, and Israel. The studies involved platforms such as Facebook, Twitter, WhatsApp, and non-general-purpose social media. The outcomes examined in these studies focused on the uptake of vaccines compared with baseline, vaccine acceptance, and the number of days individuals remained unvaccinated. The overall sample size for this review was 26,286, with individual studies ranging from 58 to 21,592 participants. The effect direction plot derived from articles of good and fair quality indicated a nonsignificant outcome (P=.12). CONCLUSIONS: The findings suggest that, in a real-world scenario, an equal number of positive and negative results may be expected due to the interventions' impact on the acceptance and uptake of vaccines. Nevertheless, there is a rationale for accumulating experience to optimize the use of social media with the aim of enhancing vaccination rates. Social media can serve as a tool with the potential to disseminate information and boost vaccination rates within a population. However, relying solely on social media is not sufficient, given the complex structures at play in vaccine acceptance. Effectiveness hinges on various factors working in tandem. It is crucial that authorized personnel closely monitor and moderate discussions on social media to ensure responsible and accurate information dissemination.

Misinformation About COVID-19 Vaccines on Social Media: Rapid Review.

BACKGROUND: The development of COVID-19 vaccines has been crucial in fighting the pandemic. However, misinformation about the COVID-19 pandemic and vaccines is spread on social media platforms at a rate that has made the World Health Organization coin the phrase infodemic. False claims about adverse vaccine side effects, such as vaccines being the cause of autism, were already considered a threat to global health before the outbreak of COVID-19. OBJECTIVE: We aimed to synthesize the existing research on misinformation about COVID-19 vaccines spread on social media platforms and its effects. The secondary aim was to gain insight and gather knowledge about whether misinformation about autism and COVID-19 vaccines is being spread on social media platforms. METHODS: We performed a literature search on September 9, 2021, and searched PubMed, PsycINFO, ERIC, EMBASE, Cochrane Library, and the Cochrane COVID-19 Study Register. We included publications in peer-reviewed journals that fulfilled the following criteria: original empirical studies, studies that assessed social media and misinformation, and studies about COVID-19 vaccines. Thematic analysis was used to identify the patterns (themes) of misinformation. Narrative qualitative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 Statement and the Synthesis Without Meta-analysis reporting guideline. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tool. Ratings of the certainty of evidence were based on recommendations from the Grading of Recommendations Assessment, Development and Evaluation Working Group. RESULTS: The search yielded 757 records, with 45 articles selected for this review. We identified 3 main themes of misinformation: medical misinformation, vaccine development, and conspiracies. Twitter was the most studied social media platform, followed by Facebook, YouTube, and Instagram. A vast majority of studies were from industrialized Western countries. We identified 19 studies in which the effect of social media misinformation on vaccine hesitancy was measured or discussed. These studies implied that the misinformation spread on social media had a negative effect on vaccine hesitancy and uptake. Only 1 study contained misinformation about autism as a side effect of COVID-19 vaccines. CONCLUSIONS: To prevent these misconceptions from taking hold, health authorities should openly address and discuss these false claims with both cultural and religious awareness in mind. Our review showed that there is a need to examine the effect of social media misinformation on vaccine hesitancy with a more robust experimental design. Furthermore, this review also demonstrated that more studies are needed from the Global South and on social media platforms other than the major platforms such as Twitter and Facebook. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42021277524; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021277524. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.31219/osf.io/tyevj.

COVID-19-related misinformation on social media: a systematic review.

OBJECTIVE: To review misinformation related to coronavirus disease 2019 (COVID-19) on social media during the first phase of the pandemic and to discuss ways of countering misinformation. METHODS: We searched PubMed®, Scopus, Embase®, PsycInfo and Google Scholar databases on 5 May 2020 and 1 June 2020 for publications related to COVID-19 and social media which dealt with misinformation and which were primary empirical studies. We followed the preferred reporting items for systematic reviews and meta-analyses and the guidelines for using a measurement tool to assess systematic reviews. Evidence quality and the risk of bias of included studies were classified using the grading of recommendations assessment, development and evaluation approach. The review is registered in the international prospective register of systematic reviews (PROSPERO; CRD42020182154). FINDINGS: We identified 22 studies for inclusion in the qualitative synthesis. The proportion of COVID-19 misinformation on social media ranged from 0.2% (413/212 846) to 28.8% (194/673) of posts. Of the 22 studies, 11 did not categorize the type of COVID-19-related misinformation, nine described specific misinformation myths and two reported sarcasm or humour related to COVID-19. Only four studies addressed the possible consequences of COVID-19-related misinformation: all reported that it led to fear or panic. CONCLUSION: Social media play an increasingly important role in spreading both accurate information and misinformation. The findings of this review may help health-care organizations prepare their responses to subsequent phases in the COVID-19 infodemic and to future infodemics in general.

Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression.

OBJECTIVE: To determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed and seven additional databases, from 2007 to 2020. STUDY SELECTION: Randomised controlled trials in adults (18-65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted. DATA EXTRACTION AND SYNTHESIS: We conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses. MAIN OUTCOME MEASURES: Physical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents. RESULTS: Thirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I2=69%, T 2=0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression. CONCLUSION: Interventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.

Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review.

BACKGROUND: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients' skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions. OBJECTIVE: This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations. METHODS: We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies' quality, methods of evaluation, and evaluation criteria. RESULTS: Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence. CONCLUSIONS: There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management.

Factors Engaging Users of Diabetes Social Media Channels on Facebook, Twitter, and Instagram: Observational Study.

BACKGROUND: Diabetes patient associations and diabetes-specific patient groups around the world are present on social media. Although active participation and engagement in these diabetes social media groups has been mostly linked to positive effects, very little is known about the content that is shared on these channels or the post features that engage their users the most. OBJECTIVE: The objective of this study was to analyze (1) the content and features of posts shared over a 3-year period on 3 diabetes social media channels (Facebook, Twitter, and Instagram) of a diabetes association, and (2) users' engagement with these posts (likes, comments, and shares). METHODS: All social media posts published from the Norwegian Diabetes Association between January 1, 2017, and December 31, 2019, were extracted. Two independent reviewers classified the posts into 7 categories based on their content. The interrater reliability was calculated using Cohen kappa. Regression analyses were carried out to analyze the effects of content topic, social media channel, and post features on users' engagement (likes, comments, and shares). RESULTS: A total of 1449 messages were posted. Posts of interviews and personal stories received 111% more likes, 106% more comments, and 112% more shares than miscellaneous posts (all P<.001). Messages posted about awareness days and other celebrations were 41% more likely to receive likes than miscellaneous posts (P<.001). Conversely, posts on research and innovation received 31% less likes (P<.001), 35% less comments (P=.02), and 25% less shares (P=.03) than miscellaneous posts. Health education posts received 38% less comments (P=.003) but were shared 39% more than miscellaneous posts (P=.007). With regard to social media channel, Facebook and Instagram posts were both 35 times more likely than Twitter posts to receive likes, and 60 times and almost 10 times more likely to receive comments, respectively (P<.001). Compared to text-only posts, those with videos had 3 times greater chance of receiving likes, almost 4 times greater chance of receiving comments, and 2.5 times greater chance of being shared (all P<.001). Including both videos and emoji in posts increased the chances of receiving likes by almost 7 times (P<.001). Adding an emoji to posts increased their chances of receiving likes and being shared by 71% and 144%, respectively (P<.001). CONCLUSIONS: Diabetes social media users seem to be least engaged in posts with content topics that a priori could be linked to greater empowerment: research and innovation on diabetes, and health education. Diabetes social media groups, public health authorities, and other stakeholders interested in sharing research and innovation content and promoting health education on social media should consider including videos and emoji in their posts, and publish on popular and visual-based social media channels, such as Facebook and Instagram, to increase user engagement. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12913-018-3178-7.

Social Media Use in Interventions for Diabetes: Rapid Evidence-Based Review.

BACKGROUND: Health authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients' outcomes. OBJECTIVE: The objective of our study was to review and describe the current existing evidence on the use of social media in interventions targeting people affected with diabetes. METHODS: A search was conducted across 4 databases (PubMed, Scopus, EMBASE, and Cochrane Library).The quality of the evidence of the included primary studies was graded according to the Grading of Recommendations Assessment, Development and Evaluation criteria, and the risk of bias of systematic reviews was assessed by drawing on AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. The outcomes reported by these studies were extracted and analyzed. RESULTS: We included 20 moderate- and high-quality studies in the review: 17 primary studies and 3 systematic reviews. Of the 16 publications evaluating the effect on glycated hemoglobin (HbA1c) of the interventions using social media, 13 reported significant reductions in HbA1c values. The 5 studies that measured satisfaction with the interventions using social media found positive effects. We found mixed evidence regarding the effect of interventions using social media on health-related quality of life (2 publications found positive effects and 3 found no differences) and on diabetes knowledge or empowerment (2 studies reported improvements and 2 reported no significant changes). CONCLUSIONS: There is very little good-quality evidence on the use of social media in interventions aimed at helping people with diabetes. However, the use of these channels is mostly linked to benefits on patients' outcomes. Public health institutions, clinicians, and other stakeholders who aim at improving the knowledge of diabetic patients could consider the use of social media in their interventions.

Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers.

Symptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n=53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n=15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms.

Is There a Weekly Pattern for Health Searches on Wikipedia and Is the Pattern Unique to Health Topics?

BACKGROUND: Online health information-seeking behaviors have been reported to be more common at the beginning of the workweek. This behavior pattern has been interpreted as a kind of "healthy new start" or "fresh start" due to regrets or attempts to compensate for unhealthy behavior or poor choices made during the weekend. However, the observations regarding the most common health information-seeking day were based only on the analyses of users' behaviors with websites on health or on online health-related searches. We wanted to confirm if this pattern could be found in searches of Wikipedia on health-related topics and also if this search pattern was unique to health-related topics or if it could represent a more general pattern of online information searching--which could be of relevance even beyond the health sector. OBJECTIVE: The aim was to examine the degree to which the search pattern described previously was specific to health-related information seeking or whether similar patterns could be found in other types of information-seeking behavior. METHODS: We extracted the number of searches performed on Wikipedia in the Norwegian language for 911 days for the most common sexually transmitted diseases (chlamydia, gonorrhea, herpes, human immunodeficiency virus [HIV], and acquired immune deficiency syndrome [AIDS]), other health-related topics (influenza, diabetes, and menopause), and 2 nonhealth-related topics (footballer Lionel Messi and pop singer Justin Bieber). The search dates were classified according to the day of the week and ANOVA tests were used to compare the average number of hits per day of the week. RESULTS: The ANOVA tests showed that the sexually transmitted disease queries had their highest peaks on Tuesdays (P<.001) and the fewest searches on Saturdays. The other health topics also showed a weekly pattern, with the highest peaks early in the week and lower numbers on Saturdays (P<.001). Footballer Lionel Messi had the highest mean number of hits on Tuesdays and Wednesdays, whereas pop singer Justin Bieber had the most hits on Tuesdays. Both these tracked search queries also showed significantly lower numbers on Saturdays (P<.001). CONCLUSIONS: Our study supports prior studies finding an increase in health information searching at the beginning of the workweek. However, we also found a similar pattern for 2 randomly chosen nonhealth-related terms, which may suggest that the search pattern is not unique to health-related searches. The results are potentially relevant beyond the field of health and our preliminary findings need to be further explored in future studies involving a broader range of nonhealth-related searches.

Randomized trial of a novel game-based appointment system for a university hospital venereology unit: study protocol.

BACKGROUND: Chlamydia is the most common reportable sexually transmitted disease (STD) in Norway, and its incidence in the two northernmost counties has been disclosed to be nearly the double of the Norwegian average. The latest publicly available rates showed that 85.6% of the new cases were diagnosed in people under 29 years old. The information and communication technologies are among the most powerful influences in the lives of young people. The Internet can potentially represent a way to educate on sexual health and encourage young people, and especially youth, to be tested for STDs. If hospital websites include an easy and anonymous system for scheduling appointments with the clinic, it is possible that this could lead to an increase in the number of people tested for STDs. METHODS: The purpose of the study is to assess the impact of a game-based appointment system on the frequency of consultations at a venereology unit and on the use of an educational web app. An A/B testing methodology is used. Users from the city of Tromsø, in North Norway, will be randomized to one of the two versions of the game-style web app on sexual health at www.sjekkdeg.no. Group A will have access to educational content only, while group B will have, in addition, access to a game-based appointment system with automatic prioritization. After one year of the trial, it will be analyzed if the game-based appointment system increases the number of consultations at the venereology unit and if health professionals deem the system useful. DISCUSSION: This study will explore if facilitating the access to health services for youth through the use of a game-based appointment system integrated in a game-style web app on sexual health education can have an impact on appointment rates. TRIAL REGISTRATION: The trial is registered at clinicaltrials.org under the identifier ClinicalTrials.gov NCT:02128620.

The Online Big Blue Test for Promoting Exercise: Health, Self-Efficacy, and Social Support.

BACKGROUND: Recent articles have documented the influence of self-efficacy and social support on exercising. Simultaneously, insulin use is also related to the perception of self-efficacy and social support in patients with diabetes. We combine these two ideas through the Big Blue Test experience in a social networking site and propose to analyze whether a change in blood sugar levels after completion of the Big Blue Test and insulin use are related to the perception of self-efficacy and social support in patients with diabetes. MATERIALS AND METHODS: To undergo the Big Blue Test, 3,926 participants voluntarily joined the Diabetes Hands Foundation. Responses were analyzed using descriptive analysis. RESULTS: The participants who reduced their blood glucose after exercise the least were those with lower self-efficacy and also with lower perceived social support. There seems to have been no relationship between changes in blood sugar level and the explicit intention of doing exercise in the future. Insulin-dependent participants demonstrated a lower perception of self-efficacy and social support than non-insulin-dependent participants. CONCLUSIONS: Change in blood glucose level or being insulin-dependent or not do not explain completely a health behavior such as exercise. Hence, self-efficacy and social support have an impact on behavioral change such as exercise to become a habit in people with diabetes, and this experience through a social networking site is an important tool for this behavioral change. For exercise to become a habit in people with diabetes, it is necessary to consider not only the crucial physiological variables, but also those psychological variables that clearly have an impact on behavioral change.

Tweet content related to sexually transmitted diseases: no joking matter.

BACKGROUND: Online social media, such as the microblogging site Twitter, have become a space for speedy exchange of information regarding sexually transmitted diseases (STDs), presenting a potential risk environment for how STDs are portrayed. Examining the types of "tweeters" (users who post messages on Twitter) and the nature of "tweet" messages is important for identifying how information related to STDs is posted in online social media. OBJECTIVE: The intent of the study was to describe the types of message emitters on Twitter in relation to two different STDs-chlamydia and human immunodeficiency virus (HIV)-as well as the nature of content tweeted, including how seriously the topic was treated. METHODS: We used the Twitter search engine to look for tweets posted worldwide from August 1-7, 2013, and from September 1-7, 2013, containing the words "chlamydia" or "HIV", and the hashtags "#chlamydia" or "#HIV". Tweeters were classified by two independent reviewers according to the type of avatar of the user (human, logo, or fantasy), the identification of the emitter (identifiable, semi-identifiable, or non-identifiable), and the source (private company, general media, scientific media, non-governmental, individual account, academic institution, government department, or undefined). Tweet messages were also independently classified according to their nature (serious or jokes/funny), and whether their main message was factual or of a personal nature/experience. RESULTS: A total of 694 tweets were posted by 426 different users during the first 7 days of August and September, containing the hashtags and/or simple words "chlamydia" and/or "HIV". Jokes or funny tweets were more frequently posted by individual users (89%, 66/74), with a human avatar (81%, 60/74), from a non-identifiable user (72%, 53/74), and they were most frequently related to chlamydia (76%, 56/74). Serious tweets were most frequently posted by the general media (20.6%, 128/620), using a logo avatar (66.9%, 415/620), and with identifiable accounts (85.2%, 528/620). No government departments, non-governmental organizations, scientific media, or academic institutions posted a joke on STDs. A total of 104 of these analyzed tweets were re-tweeted messages, belonging to 68 unique tweets. The content was serious (99%, 67/68), factual (90%, 52/58), and about HIV (85%, 58/68). CONCLUSIONS: Social media such as Twitter may be an important source of information regarding STDs provided that the topic is presented appropriately. Reassuringly, the study showed that almost 9/10 of tweets on STDs (chlamydia and HIV) were of serious content, and many of the tweets that were re-tweeted were facts. The jokes that were tweeted were mainly about chlamydia, and posted by non-identifiable emitters. We believe social media should be used to an even larger extent to disseminate correct information about STDs.

Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review.

BACKGROUND: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes. OBJECTIVE: This study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA. METHODS: We conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases-PubMed, Embase, and IEEE Xplore-and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). RESULTS: A total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence. CONCLUSIONS: Current research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI's impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

Social media shaping autism perception and identity.

LAY ABSTRACT: This study suggested that social media can provide important information about autism to autistic people. We interviewed 12 autistic adults (aged 18-49 years) and talked to them about the use of social media to find both general information and content specifically about autism, autism identity and online autistic communities. There is little research exploring how autistic people find information about autism on social media and how that makes them feel. Therefore, it is important to ask autistic people about their experiences with using social media to obtain content about autism. The 12 participants explained that when they searched for information about autism on the official health pages, they often felt that the information they found was insufficient and could not answer their questions. In addition, they searched on social media platforms for information about autism despite that they perceived social media as an unreliable source. On the social media platforms, many found content that was positive in relation to their autistic identities. The participants also found comfort in some of the forums and social media groups and received helpful advice. Nevertheless, some of the discussions were aggressive and the participants felt alienated, which did not provide a sense of community online. The findings from the study may advice on what is missing in the official pages about autism, and highlight the need to involve the autistic community in writing the content on such platforms.

Digital Interventions and Their Unexpected Outcomes - Time for Digitalovigilance?

The application of digital interventions in healthcare beyond research has been translated in the development of software as a medical device. Along with corresponding regulations for medical devices, there is a need for assessing adverse events to conduct post-market surveillance and to appropriately label digital health interventions to ensure proper use and patient safety. To date unexpected consequences of digital health interventions are neglected or ignored, or at least remain undescribed in literature. This paper is intended to raise awareness across the research community about these upcoming challenges. We recommend that - together with developing a new research field of digitalovigilance - a systematic assessment and monitoring of adverse events and unexpected interactions be included in clinical trials, along with the reporting of such events and the conduct of meta-analyses on critical aspects.

Exploring the Evolution of Social Media in Mental Health Interventions: A Mapping Review.

BACKGROUND: With the rise of social media, social media use for delivering mental health interventions has become increasingly popular. However, there is no comprehensive overview available on how this field developed over time. OBJECTIVES: The objective of this paper is to provide an overview over time of the use of social media for delivering mental health interventions. Specifically, we examine which mental health conditions and target groups have been targeted, and which social media channels or tools have been used since this topic first appeared in research. METHODS: To provide an overview of the use of social media for mental health interventions, we conducted a search for studies in four databases (PubMed; ACM Digital Library; PsycInfo; and CINAHL) and two trial registries (Clinicaltrials.gov; and Cochranelibrary.com). A sample of representative keywords related to mental health and social media was used for that search. Automatic text analysis methods (e.g., BERTopic analysis, word clouds) were applied to identify topics, and to extract target groups and types of social media. RESULTS: A total of 458 studies were included in this review (n=228 articles, and n=230 registries). Anxiety and depression were the most frequently mentioned conditions in titles of both articles and registries. BERTopic analysis identified depression and anxiety as the main topics, as well as several addictions (including gambling, alcohol, and smoking). Mental health and women's research were highlighted as the main targeted topics of these studies. The most frequently targeted groups were "adults" (39.5%) and "parents" (33.4%). Facebook, WhatsApp, messenger platforms in general, Instagram, and forums were the most frequently mentioned tools in these interventions. CONCLUSIONS: We learned that research interest in social media-based interventions in mental health is increasing, particularly in the last two years. A variety of tools have been studied, and trends towards forums and Facebook show that tools allowing for more content are preferred for mental health interventions. Future research should assess which social media tools are best suited in terms of clinical outcomes. Additionally, we conclude that natural language processing tools can help in studying trends in research on a particular topic.

What Do Autistic People Discuss on Twitter? An Approach Using BERTopic Modelling.

Social media provide easy ways to autistic individuals to communicate and to make their voices heard. The objective of this paper is to identify the main themes that are being discussed by autistic people on Twitter. We collected a sample of tweets containing the hashtag #ActuallyAutistic during the period 10/02/2022 and 14/09/2022. To identify the most discussed topics, BERTopic modelling was applied. We manually grouped the detected topics into 6 major themes using inductive content analysis: 1) General aspects of autism and experiences of autistic individuals; 2) Autism awareness, pride and funding; 3) Interventions, mostly related to Applied Behavior Analysis; 4) Reactions and expressions; 5) Everyday life as an autistic (lifelong condition, work, housing…); and 6) Symbols and characteristics. The majority of tweets were presenting general aspects and experiences as autistic individuals; raising awareness; and about their dissatisfaction with some interventions. The identification of autistic individuals' main discussion themes could help to develop meaningful public health agendas and research involving and addressed to autistic individuals.

Social media interventions for autistic individuals: Systematic review.

Background: Research on the use of digital technologies for delivering behavioral interventions has shown mixed evidence on their efficacy for improving both autistic symptoms and co-occurring psychiatric disorders. Little knowledge exists on the specific use or efficacy of using social media in interventions aimed at autistic individuals. Objective: To review and describe the current existing evidence-based research on the use of social media in interventions aimed at autistic individuals. Methods: A search was conducted across 8 databases (PubMed; EMBASE; Cochrane Library; PsycInfo; ERIC; Education Source; Web of Science; and IEEE Xplore). We included primary studies and reviews that dealt with autism spectrum disorder (ASD); described interventions that use social media; and reported results from the intervention. The quality of the evidence of the included primary studies was graded according to the GRADE criteria, and the risk of bias in systematic reviews was assessed by drawing on the AMSTAR guidelines. Results were synthesized and sorted by quality of evidence. Results: A total of nine articles were included in this review: eight primary studies (five non-randomized interventions and three randomized interventions) and one systematic review. The total number of participants with an ASD-diagnosis in the included studies was 164 (aged 5 to 22 years old). Studies weighted as being of moderate quality of evidence have reported significant positive effects in the groups that received the social media interventions: increased social engagement and participation in life situations; increased physical activity level; increased improvement on occupational performance, specified goals, and behavioral problems; and decreased plaque scores coupled with parent reports of intervention success. None of the studies have reported any negative effects linked to social media interventions. Conclusion: There is very little evidence of good quality on the use of social media in interventions aimed at autistic individuals. While there is a need for more high-quality studies, all the included studies, with one exception found positive results of the interventions. These findings are encouraging, suggesting that social media-based interventions may in fact be useful for supporting behavioral changes in autistic individuals. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=337185, identifier CRD42022337185.

Personalized Digital Solutions for Mental Health.

INTRODUCTION: Mental health is one of the major global concerns in the field of healthcare. The emergence of digital solutions is proving to be a great aid for individuals suffering from mental health disorders. These solutions are particularly useful and effective when they are personalized. The objective of this paper is to understand the personalization factors and the methods that have been used to collect information to personalize the digital mental health solutions. METHODS: This paper builds on a previous review that analyzed the personalization of digital solutions in mHealth, and expands on the extracted information for the specific case of mental health. RESULTS: Ten mental health digital solutions have been analyzed. The paper focuses on targeted conditions, personalization factors and the methods used for collecting personalization factors. DISCUSSION: The analyzed mental health digital solutions cover a wide range of health conditions. It is remarkable that most articles do not explicitly mention the factors used to personalize the solution. Among the solutions that mention them, there is a great diversity of factors utilized, such as age, gender, user preferences, and subjective behavior. The authors point out the methods for obtaining data to personalize the solutions, including in-app questionnaires, self-reports, and usage data of the solutions. CONCLUSIONS: The analysis of current mental health digital solutions emphasizes the need to create guidelines for designing personalized digital solutions for mental health.