High User Engagement Research Articles

The Influence of Short Video Marketing on Consumer Brand Attitudes under New Media Environment

With the development of the Internet, it has become a convenient shopping platform for consumers. In the ear of new media and big data, the short video market has gradually become the mainstream trend of society. The research theme of this paper aims to explore the influence of short video marketing on consumer brand attitude in the context of new media. Specifically, it will analyze how factors such as content creativity and brand loyalty influence consumers perceptions and attitudes toward brands through short video marketing. In this paper, the influence of short video on brand perception and consumer brand attitude is studied. The author investigates how high quality content, user engagement and brand loyalty increase consumer brand attitude. Besides, this study aims to optimize short video marketing strategies, enhance brand influence, and analyze the impact of brand loyalty on consumers purchasing power. Overall, this study contributes to theoretical research by enriching readers understanding of new media marketing strategies while providing practical insights for consumers.

Midwifery student engagement with digital interactive books: A cross sectional survey

AimTo explore the benefit and engagement of undergraduate students’ use of H5P interactive books for student learning. DesignAn evaluation study of technology enabled learning for first year undergraduate Bachelor of Midwifery students in Australia. MethodsStudents were invited to complete an online evaluation survey of their use and engagement with H5P interactive books. The survey included the long form User Engagement Scale which has four subscales of focused attention, aesthetic appeal, reward factor and perceived usability scored on a 5-point Likert scale. Content analysis was used to analyse the text comments given to five open text questions. ResultsThere were 21 students who completed the survey. There was a high overall User Engagement Scale score of 73.1 % with aesthetic appeal and reward factor being the highest scoring subscales. The content analysis showed students found the interactive books engaging and easy to navigate. Areas for improvement identified were not including a large amount of content and providing downloadable content. ConclusionsThis study demonstrates the valuable and engaging use of H5P Interactive Books for undergraduate students in higher education. Students who used H5P Interactive Books identified their ease of use, organised layout and engaging format.

Virtual Journeys, Real Engagement: Analyzing User Experience on a Virtual Travel Social Platform

A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores the potential of web and immersive technologies, specifically the Virtual Romania (VRRO) platform, in enhancing sustainable tourism by redirecting tourist traffic to lesser-known destinations and boosting user engagement through interactive experiences. Our research examines how virtual tourism platforms (VTPs), which include web-based and immersive technologies, support sustainable tourism, complement physical visits, influence user engagement, and foster community building through social features and user-generated content (UGC). An empirical analysis of the VRRO platform reveals high user engagement levels, attributed to its intuitive design and interactive features, regardless of the users’ technological familiarity. Our findings also highlight the necessity for ongoing enhancements to maintain user satisfaction. In conclusion, VRRO demonstrates how accessible and innovative technologies in tourism can modernize travel experiences and contribute to the evolution of the broader tourism ecosystem by supporting sustainable practices and fostering community engagement.

Real-World Evidence From a Digital Health Treatment Program for Female Urinary Incontinence: Observational Study of Outcomes Following User-Centered Product Design.

Urinary incontinence (UI) affects millions of women with substantial health and quality-of-life impacts. Supervised pelvic floor muscle training (PFMT) is the recommended first-line treatment. However, multiple individual and institutional barriers impede women's access to skilled care. Evidence suggests that digital health solutions are acceptable and may be effective in delivering first-line incontinence treatment, although these technologies have not yet been leveraged at scale. The primary objective is to describe the effectiveness and safety of a prescribed digital health treatment program to guide PFMT for UI treatment among real-world users. The secondary objectives are to evaluate patient engagement following an updated user platform and identify the factors predictive of success. This retrospective cohort study of women who initiated device use between January 1, 2022, and June 30, 2023, included users aged ≥18 years old with a diagnosis of stress, urgency, or mixed incontinence or a score of >33.3 points on the Urogenital Distress Inventory Short Form (UDI-6). Users are prescribed a 2.5-minute, twice-daily, training program guided by an intravaginal, motion-based device that pairs with a smartphone app. Data collected by the device or app include patient-reported demographics and outcomes, adherence to the twice-daily regimen, and pelvic floor muscle performance parameters, including angle change and hold time. Symptom improvement was assessed by the UDI-6 score change from baseline to the most recent score using paired 2-tailed t tests. Factors associated with meeting the UDI-6 minimum clinically important difference were evaluated by regression analysis. Of 1419 users, 947 met inclusion criteria and provided data for analysis. The mean baseline UDI-6 score was 46.8 (SD 19.3), and the mean UDI-6 score change was 11.3 (SD 19.9; P<.001). Improvement was reported by 74% (697/947) and was similar across age, BMI, and incontinence subtype. Mean adherence was 89% (mean 12.5, SD 2.1 of 14 possible weekly uses) over 12 weeks. Those who used the device ≥10 times per week were more likely to achieve symptom improvement. In multivariate logistic regression analysis, baseline incontinence symptom severity and maximum angle change during pelvic floor muscle contraction were significantly associated with meeting the UDI-6 minimum clinically important difference. Age, BMI, and UI subtype were not associated. This study provides real-world evidence to support the effectiveness and safety of a prescribed digital health treatment program for female UI. A digital PFMT program completed with visual guidance from a motion-based device yields significant results when executed ≥10 times per week over a period of 12 weeks. The program demonstrates high user engagement, with 92.9% (880/947) of users adhering to the prescribed training regimen. First-line incontinence treatment, when implemented using this digital program, leads to statistically and clinically substantial symptom improvements across age and BMI categories and incontinence subtypes.

Creating Digital Content for Traditional Children's Games in North Sumatra to Preserve Culture and Enhance Sports Participation

As globalization progresses, local cultures, including traditional games, are increasingly at risk of erosion. There is a pressing need to develop strategies to preserve these cultural elements, introduce them to younger generations, and enhance active participation in sports. This study focuses on creating multimedia content based on traditional games from the North Sumatra region to achieve these goals. The research utilized the Research and Development (RD) model by Borg and Gall, which includes ten systematic steps. Participants included 40 children aged 6-12 years and 40 adolescents aged 13-15 years from North Sumatra, divided into individual and small group trials. The setting comprised elementary and junior high schools in Deliserdang district and Medan city. The development process involved initial design, expert validation, iterative revisions, and field trials to test and refine the multimedia content. The developed multimedia content, featuring animated video media of traditional game activities, was validated by experts and received high feasibility ratings. Initial validation stages yielded a feasibility percentage of 73.80%, improving to 95.20% after revisions. Material validation assessments also showed significant improvement, with feasibility increasing from 75.55% to 92.22%. Field trials indicated that the content was well-received by participants, effectively preserving regional culture and promoting active participation in sports. The study demonstrates the potential of multimedia content in preserving cultural heritage and encouraging sports participation among youth. The positive feedback from expert validators and participants underscores the content's educational and cultural value. However, further research with larger and more diverse samples is recommended to confirm these findings and explore long-term impacts. The multimedia content developed through this research effectively preserves traditional games from North Sumatra and promotes active participation in sports among children and adolescents. The iterative validation and testing process ensured high feasibility and user engagement, making it a valuable tool for cultural and educational initiatives.

Instagram for audience engagement: an evaluation of CERC framework in the GCC nations for digital public health during the Covid-19 pandemic

BackgroundIn this study, we investigate the utilization of Instagram by public health ministries across the Gulf Cooperation Council (GCC) nations to disseminate health-related information during the COVID-19 pandemic. With Instagram’s visual-centric approach and high user engagement, the research aims to investigate its critical yet complex role in information dissemination amid a health crisis.MethodsTo examine how Instagram communication strategies align with the CDC’s Crisis and Emergency Risk Communication (CERC) framework, we employ the content analysis method. This approach helps to evaluate the effectiveness and challenges of employing Instagram for health communication within a region known for its significant social media usage.ResultsFindings indicate that Instagram serves as a vital platform for the rapid dissemination of health information in the GCC, leveraging its visual capabilities and wide reach. The GCC ministries of health utilized Instagram to demonstrate a consistent and strategic approach to communicate essential COVID-19 related information. Kuwait and Bahrain were the most active of all the assessed ministries with respect to the number of engagement metrics (likes and comments). Most of the posts, as per the CERC framework, were informational and related to vaccine infection and death cases. The second most salient theme in line with the CERC framework was about promoting actions, followed by Instagram posts about activities, events, and campaigns.ConclusionsThe research underscores Instagram’s potential as a powerful tool in enhancing public health resilience and responsiveness during health emergencies in the GCC. It suggests that leveraging social media, with careful consideration of its affordances, can contribute significantly to effective health communication strategies in times of crisis.

Breaking presence in Immersive Virtual Reality toward behavioral and emotional engagement

Background and objectiveMany recent studies in virtual reality (VR) have managed the sense of Presence to assess the suitability of their designs, mainly when focused on learning goals that require high user engagement, such as in serious games for psychomotor training. However, the place and plausibility illusions needed to promote Presence are achieved by combining different VR-based design cues, and their individual contribution to preserving the Presence's engagement/involvement component is still unclear. This article explored the single effect of breaking the sense of Presence per VR factor, i.e., removing VR cues related to Social Presence (human interactions), Self-Presence (embodiment), and Physical Presence (Scenario realism). MethodsThirty-three participants were asked to play an immersive VR simulation of an arcade game three times by experiencing a stepped Break of Illusion in one of the VR factors, i.e., while two factors were kept high, the remaining one was reduced to a low and null (hypothetical) level. The game difficulty was fixed after assessing each person's skills. ResultsResults showed that psychophysiology indicators (heart rate and skin conductance) were not affected by the level of illusion, whereas exercise intensity was significantly higher with low body and social presence-based conditions. Moreover, skin conductance was lower in the Social-presence group, which suggests that perspiration is only affected by breaks in realism (scenario and body representations). Based on the obtained evidence, we proposed some guidelines for adapting the design of immersive virtual environments through Breaks in Presence, mainly by changing the realism of the scenario and body representation depending on the skin conductance or the interaction with virtual humans depending on exercise intensity.

Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to identify key features in anti-vaping Instagram image posts associated with high social media user engagement by artificial intelligence. We collected 8972 anti-vaping Instagram image posts and hand-coded 2200 Instagram images to identify nine image features such as warning signs and person-shown vaping. We utilized a deep-learning model, the OpenAI: contrastive language-image pre-training with ViT-B/32 as the backbone and a 5-fold cross-validation model evaluation, to extract similar features from the Instagram image and further trained logistic regression models for multilabel classification. Latent Dirichlet Allocation model and Valence Aware Dictionary and sEntiment Reasoner were used to extract the topics and sentiment from the captions. Negative binomial regression models were applied to identify features associated with the likes and comments count of posts. Several features identified in anti-vaping Instagram image posts were significantly associated with high social media user engagement (likes or comments), such as educational warnings and warning signs. Instagram posts with captions about health risks associated with vaping received significantly more likes or comments than those about help quitting smoking or vaping. Compared to the model based on 2200 hand-coded Instagram image posts, more significant features have been identified from 8972 AI-labeled Instagram image posts. Features identified from anti-vaping Instagram image posts will provide a potentially effective way to communicate with the public about the health effects of e-cigarette use. Considering the increasing popularity of social media and the current vaping epidemic, especially among youth and young adults, it becomes necessary to understand e-cigarette-related content on social media. Although pro-vaping messages dominate social media, anti-vaping messages are limited and often have low user engagement. Using advanced deep-learning and statistical models, we identified several features in anti-vaping Instagram image posts significantly associated with high user engagement. Our findings provide a potential approach to effectively communicate with the public about the health risks of vaping to protect public health.

User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study.

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the world. Common comorbidities are central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome. Cardiovascular disease is the most common cause of death among people with NAFLD, and lifestyle changes can improve health outcomes. This study aims to explore the acceptability of a digital health program in terms of engagement, retention, and user satisfaction in addition to exploring changes in clinical outcomes, such as weight, cardiometabolic risk factors, and health-related quality of life. We conducted a prospective, open-label, single-arm, 12-week study including 38 individuals with either a BMI >30, metabolic syndrome, or type 2 diabetes mellitus and NAFLD screened by FibroScan. An NAFLD-specific digital health program focused on disease education, lowering carbohydrates in the diet, food logging, increasing activity level, reducing stress, and healthy lifestyle coaching was offered to participants. The coach provided weekly feedback on food logs and other in-app activities and opportunities for participants to ask questions. The coaching was active throughout the 12-week intervention period. The primary outcome was feasibility and acceptability of the 12-week program, assessed through patient engagement, retention, and satisfaction with the program. Secondary outcomes included changes in weight, liver fat, body composition, and other cardiometabolic clinical parameters at baseline and 12 weeks. In total, 38 individuals were included in the study (median age 59.5, IQR 46.3-68.8 years; n=23, 61% female). Overall, 34 (89%) participants completed the program and 29 (76%) were active during the 12-week program period. The median satisfaction score was 6.3 (IQR 5.8-6.7) of 7. Mean weight loss was 3.5 (SD 3.7) kg (P<.001) or 3.2% (SD 3.4%), with a 2.2 (SD 2.7) kg reduction in fat mass (P<.001). Relative liver fat reduction was 19.4% (SD 23.9%). Systolic blood pressure was reduced by 6.0 (SD 13.5) mmHg (P=.009). The median reduction was 0.14 (IQR 0-0.47) mmol/L for triglyceride levels (P=.003), 3.2 (IQR 0.0-5.4) µU/ml for serum insulin (s-insulin) levels (P=.003), and 0.5 (IQR -0.7 to 3.8) mmol/mol for hemoglobin A1c (HbA1c) levels (P=.03). Participants who were highly engaged (ie, who used the app at least 5 days per week) had greater weight loss and liver fat reduction. The 12-week-long digital health program was feasible for individuals with NAFLD, receiving high user engagement, retention, and satisfaction. Improved liver-specific and cardiometabolic health was observed, and more engaged participants showed greater improvements. This digital health program could provide a new tool to improve health outcomes in people with NAFLD. Clinicaltrials.gov NCT05426382; https://clinicaltrials.gov/study/NCT05426382.

Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development Process and Randomized Controlled Trial.

Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot. We aim to report results of the user-centered design development process and randomized controlled trial for a novel and comprehensive quit smoking conversational chatbot called QuitBot. The 4 years of formative research for developing QuitBot followed an 11-step process: (1) specifying a conceptual model; (2) conducting content analysis of existing interventions (63 hours of intervention transcripts); (3) assessing user needs; (4) developing the chat's persona ("personality"); (5) prototyping content and persona; (6) developing full functionality; (7) programming the QuitBot; (8) conducting a diary study; (9) conducting a pilot randomized controlled trial (RCT); (10) reviewing results of the RCT; and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot RCT results. The process of adding a QnA function itself involved a three-step process: (1) generating QnA pairs, (2) fine-tuning large language models (LLMs) on QnA pairs, and (3) evaluating the LLM outputs. We developed a quit smoking program spanning 42 days of 2- to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing Food and Drug Administration-approved cessation medications, coping with triggers, and recovering from lapses and relapses. In a pilot RCT with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT text messaging program, particularly among those who viewed all 42 days of program content: 30-day, complete-case, point prevalence abstinence rates at 3-month follow-up were 63% (39/62) for QuitBot versus 38.5% (45/117) for SmokefreeTXT (odds ratio 2.58, 95% CI 1.34-4.99; P=.005). However, Facebook Messenger intermittently blocked participants' access to QuitBot, so we transitioned from Facebook Messenger to a stand-alone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions led to us develop a core conversational feature, enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT-3.5 (OpenAI) responds to questions that are not within our library of QnA pairs. The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions. ClinicalTrials.gov NCT03585231; https://clinicaltrials.gov/study/NCT03585231.

Current status and future development of digital therapeutics

Background: Digital therapeutics, evidence-based software applications, offer preventive measures for various diseases and enhance healthcare accessibility and change. This article explores the current status and future trajectory of these devices.Current Concepts: Digital therapeutics prioritize a patient-centered approach. Historically, healthcare relied heavily on prescribed treatments during hospital visits. However, these devices provide objective data on patient symptoms through real-time digital monitoring. They also foster advancements in biotechnology and information technology, leading to improved patient care through technologies like artificial intelligence and virtual reality apps. Rigorous clinical trials are crucial for these devices, and integrating digital technology is proving increasingly efficient, particularly for decentralized clinical trials. Despite initial promise, challenges abound. While an international leader in this sector gained U.S. Food and Drug Administration approval, it recently filed for bankruptcy. Similarly, companies employing gaming techniques for attention deficit hyperactivity disorder treatment experienced lackluster performance. In Korea, the domestic digital therapeutics ecosystem stagnates with limited new approvals. High dropout rates and low user engagement remain major hurdles. Addressing these issues requires a design focused on user experience and motivation.Discussion and Conclusion: Digital therapeutic devices, coupled with digital monitoring, are poised to revolutionize healthcare into a patient-centered ecosystem. Establishing this ecosystem demands collaboration among patients, medical professionals, developers, and regulatory agencies. Continuous regulatory innovation, such as shortening the medical device evaluation process from 390 days to 80 days, is vital for progress.

Addressing Gaps in Access to LGBTQIA + Health Education Resources: A Novel E-Learning Platform.

To reduce health inequities for lesbian, gay, bisexual, transgender, queer, intersex, asexual, and all sexually and gender diverse (LGBTQIA+) people, healthcare professionals need increased access to education and training resources on LGBTQIA + health. Web-based, asynchronous, electronic learning (e-learning) resources are critical for expanding the availability of LGBTQIA + health programs. This article presents the design and utilization outcomes of a novel e-learning platform for engaging healthcare professionals in LGBTQIA + health online continuing education. As of December 2022, the e-learning platform consisted of 293 resources within 17 topic domains. Modalities included: learning modules, recorded webinars, publications, videos, and toolkits. We conducted a descriptive analysis of the e-learning platform's website traffic and user engagement data. Google Universal Analytics and event tracking were used to measure website traffic, user locations, and publication downloads. Learning module and webinar completions were exported from the learning management system and run as frequencies. Between January 1, 2020, and December 31, 2022, over 650,000 people from all U.S. states, 182 countries, and 31 territories visited the website. Platform users downloaded publications 66,225 times, and completed 29,351 learning modules and 24,654 webinars. The broad reach and high user engagement of the e-learning platform indicate acceptability of web-based, asynchronous online continuing education in LGBTQIA + health, and suggest that this platform is filling a need in health professional education. Remote, online learning opportunities may be especially important in jurisdictions with bans on medical care for transgender and gender diverse youth. Future growth of the platform, paired with in-person and other online learning opportunities, has the potential to reduce gaps in LGBTQIA + health training, and mitigate LGBTQIA + health inequities.

Smart phone application for early detection of adverse clinical outcomes in solid malignancy.

562 Background: The widespread application of mobile technology in healthcare, particularly in the realm of telemedicine and Patient-Reported Outcomes (PRO), is revolutionizing care. We have developed a mobile application that leverages artificial intelligence (AI) and The Internet of Medical Things (IoMT) using machine learning (ML) assisted dashboard to enable real-time documentation and communication between patients and healthcare providers. The aim of our research is to explore the potential of this innovative combination in boosting patient quality of life (QoL) and enabling prompt, effective patient management. Methods: We conducted a pilot randomized controlled trial. The trial focused on comparing the quality of life at baseline, 1 month, and 3 months of cancer patients receiving standard conventional follow-up care versus those using our intervention. Patients receive a smartwatch and download our application, while a monitoring care team was established. Our application incorporates guidelines from MacMillan Cancer providing ML-guided symptom assessment. If adverse drug reactions or treatment effects occurred, the application provided prompt self-care suggestions. The secondary outcomes evaluated included cumulative emergency visits, cancer care knowledge assessment results, and the feasibility. Results: Between December 1, 2022, and June 1, 2023, a total of 30 patients were recruited for the trial. The average age of the patients was 51 years, with a majority being women (76.6%). The cohort comprised five types of solid malignancies, with breast cancer accounting for 56.6%. Most patients were in stage 4, and the aim of treatment for them was palliative (60%). The mean FACT-G scores were similar between the two groups at all time points. However, the control group showed a significant decrease in Functional Well-Being at 3 months compared to baseline (P = .025). Additionally, while the Intervention group had zero emergency visits, the Control group experienced a total of five visits (P = .016). The literacy test scores showed no significant difference. On average, individuals spent 60 minutes per day using the application, indicating high user engagement and overall feasibility. Conclusions: Mobile application, powered by AI and IoMT, has the potential to significantly impact patient care and further research is warranted to explore its broader implementation in healthcare settings. Clinical trial information: TCTR20230331002 .[Table: see text]

Results of the Italian RESILIEN-T Pilot Study: A Mobile Health Tool to Support Older People with Mild Cognitive Impairment.

(1) Background: The RESILIEN-T system addresses the need for innovative solutions to support self-management in older people with Mild Cognitive Impairment (MCI). Despite the increasing prevalence of dementia and MCI, there is a lack of tailored solutions for these individuals. The RESILIEN-T system aims to empower and engage people with cognitive decline by providing a modular platform for self-management and coaching services. (2) Methods: Italian data collected for the RESILIEN-T project involved 62 older participants randomly assigned to the intervention or control group. Data were collected through questionnaires and user interactions with the system over a three-month period. (3) Results: Quantitative outcomes showed no significant differences between the intervention and control groups, except for an improvement in perceived memory capability in the intervention group. The usability assessment indicated a high level of acceptance of the RESILIEN-T system. (4) Discussions: Although no significant improvements were observed in most quantitative measures, the high user engagement and acceptance suggest the potential effectiveness of the RESILIEN-T system. Future improvements could involve integrating smart objects and interactive virtual agents. Overall, RESILIEN-T represents a promising step toward empowering individuals with cognitive impairment in their self-management and decision-making processes.

Experiences of Xhosa women providing Kangaroo mother care in a tertiary hospital in the Western Cape, South Africa

Kangaroo mother care has been recognized as a credible intervention to improve preterm birth outcomes by the World Health Organization. Kangaroo mother care requires high user engagement and consists of continuous skin-to-skin contact between the mother and infant and exclusive breastfeeding. We conducted a qualitative study of Xhosa women ( n = 10) practicing Kangaroo mother care in a tertiary hospital in the Western Cape, South Africa. All interviews were conducted in isiXhosa, audio-recorded, and transcribed. The transcribed data were analysed using thematic analysis. Four themes emerged: (1) Kangaroo mother care, a beneficial but foreign concept; (2) distress in the Kangaroo mother care ward; (3) the missing umbilical cord: cultural experiences of mothers in the Kangaroo mother care ward; and (4) the Kangaroo mother care village: interpersonal relations in the ward. Our study showed that cultural practices still pose a challenge to fully accepting Kangaroo mother care. We suggest more studies on cultural sensitivity to encourage acceptance of interventions that affect culturally diverse groups.

Keep it #Unreal: Exploring Instagram Users’ Engagement With Virtual Influencers in Tourism Contexts

As an emerging category of non-human influencers, virtual influencers (VIs) have received increasing attention on social media. While VIs generate high user engagement, the underlying factors that drive social media engagement are poorly understood. Informed by communication theory, this study aims to explore Instagram users’ perceptions of VIs and the key source and content factors that prompt user engagement in tourism contexts. An initial netnographic observation of Instagram posts was followed by five online focus group interviews using a photo elicitation technique. The results indicated that Instagram users had mixed feelings towards VIs; however, most were receptive to VI marketing provided that ethical concerns had been addressed. Key source and content factors that stimulate user engagement with VIs are integrated into a proposed framework. The findings will assist tourism practitioners and content creators to design VI marketing campaigns that incorporate and leverage important influencer and post-related features.

Engagement, Retention, and Acceptability in a Digital Health Program for Atopic Dermatitis: Prospective Interventional Study.

Patients with atopic dermatitis can experience chronic eczema with pruritus, skin pain, sleep problems, anxiety, and other problems that reduce their quality of life (QoL). Current treatments aim to improve these symptoms and reduce inflammation, but poor treatment adherence and disease understanding are key concerns in the long-term management of atopic dermatitis. Digital therapeutics can help with these and support patients toward a healthier lifestyle to improve their overall QoL. The aim of the study is to test the feasibility of a digital health program tailored for atopic dermatitis through program engagement, retention, and acceptability. Adults with atopic dermatitis were recruited in Iceland for a 6-week digital health program delivered through a smartphone app. Key components of the digital program were disease and trigger education; medication reminders; patient-reported outcomes (PROs) on energy levels, stress levels, and quality of sleep (referred to as QoL PROs); atopic dermatitis symptom PROs; guided meditation; and healthy lifestyle coaching. The primary outcome was program feasibility, as assessed by in-app retention and engagement. User satisfaction was assessed by the mHealth (ie, mobile health) App Usability Questionnaire (MAUQ). A total of 21 patients were recruited (17 female, mean age 31 years), 20 (95%) completed the program. On average, users were active in the app 6.5 days per week and completed 8.2 missions per day. The education content, medication reminders, and PROs had high user engagement and retention; all users who were exposed to the QoL PROs (n=17) interacted with these, and 20/21 (95%) users were continuously engaged with the education missions, medication missions, and symptom PROs. Continued engagement with the step counter and mind missions among exposed users was lower (17/21 and 13/20 participants, respectively). Medication reminder and education task completion remained high over time (at least 18/20, 90%), but weekly interactions declined. All assigned users completed atopic dermatitis symptom PROs on weeks 1-5 and only one did not do so on week 6; the reported number and total severity of atopic dermatitis symptoms reduced during the program. Regarding the QoL PROs, 16/17 (94%) and 14/17 (82%) users interacted with these at least 3 times in the first and last week of the program, respectively, and all reported improvements over time. User satisfaction was high with a total score of 6.2/7. We found high overall engagement and retention in a targeted digital health program among patients with atopic dermatitis, as well as high compliance with missions relating to medication reminders, patient education, and PROs. Symptom number and severity were reduced, and QoL PROs improved over time. We conclude that a digital health program is feasible and may provide added benefits for patients with atopic dermatitis, including the tracking and improvement of atopic dermatitis symptoms.

Characterizing Heated Tobacco Products Marketing on Instagram: Observational Study.

Heated tobacco products (HTPs), including I Quit Ordinary Smoking (IQOS), are new tobacco products that use an electronic device to heat compressed tobacco leaves to generate an aerosol for consumers to inhale. Marketing of HTPs is prevalent on Instagram, a popular social media platform. This study aims to characterize posts related to HTPs on Instagram and their associations with user engagement. Through the Instagram application programming interface, 979 Instagram posts were collected using keywords related to HTPs, such as "IQOS" and "heat-not-burn." Among them, 596 posts were related to IQOS and other HTP marketing. The codebook was developed from a randomly selected 200 posts on the post content by hand coding, which was applied to the remaining 396 Instagram posts. Summary statistics were calculated, and statistical hypothesis testing was conducted to understand the popularity of Instagram posts on HTPs. Negative binomial regression models were applied to identify Instagram post characteristics associated with user engagement (eg, count). Among Instagram posts related to HTP marketing (N=596), "product display" was dominant (n=550, 92.28%), followed by "brand promotion" (n=41, 6.88%), and "others" (n=5, 0.84%). Among posts within "product display," "device only" was the most popular (n=338, 61.45%), followed by "heatstick only" (n=80, 14.55%), "accessory" (n=66, 12%), "device and heatstick" (n=56, 10.18%), and "capsule" (n=10, 1.82%). A univariate negative binomial regression model with pairwise comparisons across "product display" types showed that the number of likes for posts with HTP heatsticks was significantly lower compared to posts with HTP devices, accessories, and device-heatstick sets. Multivariate negative binomial regression models showed that HTP-related Instagram posts with a model or lifestyle elements (;=.60, 95% CI 0.36-0.84) or without obvious product advertising information (=.69, 95% CI 0.49-0.89) received more likes. It is shown that posts with product displays were dominant among HTP-related posts on Instagram. Posts with model or lifestyle elements are associated with high user engagement, which might be one of the web-based marketing strategies of HTPs.

Evaluation of a Computer-Assisted Language Learning System Based on Adaptive Learning Designed for Self-training in Scientific French Language

This article presents the development and evaluation of a computer-assisted language learning system designed for self-training in scientific French language. The main problem addressed by this research is the linguistic obstacles faced by students during their academic years, which inspired the implementation of an adaptive learning system personalized to their needs. The methodology applied involved a need analysis approach to better adapt the French language learning offer to students’ demand, followed by the development of an adaptive learning model based on Item Response Theory (IRT). The system was evaluated by the System Usability Scale (SUS) model which shows high usability and user satisfaction and engagement. The findings were very encouraging, demonstrating that the presented adaptive learning model improves the adaptability of students’ needs and preferences. Overall, the aim of this research is to prove that the proposed learning system will improve the learners’ performance and understanding of scientific French language.

Optimizing the Acceptability, Adherence, and Inclusiveness of the COVID Radar Surveillance App: Qualitative Study Using Focus Groups, Thematic Content Analysis, and Usability Testing.

BackgroundThe COVID Radar app was developed as a population-based surveillance instrument to identify at-risk populations and regions in response to the COVID-19 pandemic. The app boasts of >8.5 million completed questionnaires, with >280,000 unique users. Although the COVID Radar app is a valid tool for population-level surveillance, high user engagement is critical to the success of the COVID Radar app in maintaining validity.ObjectiveThis study aimed to identify optimization targets of the COVID Radar app to improve its acceptability, adherence, and inclusiveness.MethodsThe main component of the COVID Radar app is a self-report questionnaire that assesses COVID-19 symptoms and social distancing behaviors. A total of 3 qualitative substudies were conducted. First, 3 semistructured focus group interviews with end users (N=14) of the app were conducted to gather information on user experiences. The output was transcribed and thematically coded using the framework method. Second, a similar qualitative thematic analysis was conducted on 1080 end-user emails. Third, usability testing was conducted in one-on-one sessions with 4 individuals with low literacy levels.ResultsAll 3 substudies identified optimization targets in terms of design and content. The results of substudy 1 showed that the participants generally evaluated the app positively. They reported the app to be user-friendly and were satisfied with its design and functionalities. Participants’ main motivation to use the app was to contribute to science. Participants suggested adding motivational tools to stimulate user engagement. A larger national publicity campaign for the app was considered potentially helpful for increasing the user population. In-app updates informing users about the project and its outputs motivated users to continue using the app. Feedback on the self-report questionnaire, stemming from substudies 1 and 2, mostly concerned the content and phrasing of the questions. Furthermore, the section of the app allowing users to compare their symptoms and behaviors to those of their peers was found to be suboptimal because of difficulties in interpreting the figures presented in the app. Finally, the output of substudy 3 resulted in recommendations primarily related to simplification of the text to render it more accessible and comprehensible for individuals with low literacy levels.ConclusionsThe convenience of app use, enabling personal adjustments of the app experience, and considering motivational factors for continued app use (ie, altruism and collectivism) were found to be crucial to procuring and maintaining a population of active users of the COVID Radar app. Further, there seems to be a need to increase the accessibility of public health tools for individuals with low literacy levels. These results can be used to improve the this and future public health apps and improve the representativeness of their user populations and user engagement, ultimately increasing the validity of the tools.