Expressions of pandemic fatigue on digital platforms: a thematic analysis of sentiment and narratives for infodemic insights.

BACKGROUND: The infodemic accompanying the COVID-19 pandemic has led to an overwhelming amount of information, including questions, concerns and misinformation. Pandemic fatigue has been identified as a concern from early in the pandemic. With new and ongoing health emergencies in 2022, it is important to understand how pandemic fatigue is being discussed and expressed by users on digital channels. This study aims to explore and report on key narrative themes associated with expressions of pandemic fatigue by users on digital platforms. METHODS: This paper describes the collection of publicly available data over a 3-month period from multiple online sources using the Meltwater and CrowdTangle platforms to source data from Twitter, Facebook, Instagram, YouTube, TikTok, Pinterest, Product Reviews, Twitch, blogs & forums. A comprehensive search strategy was developed and tested. A total of 1,484,042 social media posts were identified during the time-period that included the defined search terms for pandemic fatigue. These data were initially sorted by highest levels of engagement and from this dataset, analysts reviewed the identified posts to isolate and remove irrelevant content and identify dominant narratives. A thematic analysis was carried out on these narratives to identify themes related to expression of pandemic fatigue. Two researchers reviewed the data and themes. RESULTS: The thematic analysis of narratives identified six main themes relating to expression of pandemic fatigue, and one theme of counter narratives against pandemic fatigue. Data volume increased concurrent with the time of the mpox emergency announcement. Emergent themes showed the different ways users expressed pandemic fatigue and how it was interlaced with issues of trust, preventative measure acceptance and uptake, misinformation, and being overwhelmed with multiple or sustained emergencies. CONCLUSIONS: This paper has identified the different ways users express pandemic fatigue on digital channels over a 3-month period. Better understanding the implications of the information environment on user's perceptions, questions, and concerns regarding pandemic and more broadly emergency fatigue is vital in identifying relevant interventions and, in the longer term, strengthening the global architecture for health emergency preparedness, prevention, readiness and resilience, as evidenced in this paper. There are clear pathways for further research, including incorporating additional languages and reviewing these themes over longer time periods.

Informing social media analysis for public health: a cross-sectional survey of professionals.

BACKGROUND: During the COVID-19 pandemic, the field of infodemic management has grown in response to urgent global need. Social listening is the first step in managing the infodemic, and many organizations and health systems have implemented processes. Social media analysis tools have traditionally been developed for commercial purposes, rather than public health, and little is known of the experiences and needs of those professionals using them for infodemic management. METHODS: We developed a cross sectional survey and distributed through global infodemic management networks between December 2022 and February 2023. Questions were structured over four sections related to work-practice and user needs and did not collect any personal details from participants. Descriptive analysis was conducted on the study results. Qualitative analysis was used to categorise and understand answers to open-text questions. RESULTS: There were 417 participants, 162/417 who completed all survey questions, and 255/417 who completed some, all responses are included in analysis. Respondents came from all global regions and a variety of workplaces. Participants had an average of 4.4 years' experience in the analysis of social media for public health. COVID-19 was the most common health issue people had conducted social media analysis for. Results reveal a range of training, technical capacity, and support needs. CONCLUSIONS: This paper is the first we are aware of to seek and describe the needs of those using social media analysis platforms for public health purposes since the start of the COVID-19 pandemic. There are key areas for future work and research, including addressing the training, capacity building and leadership needs of those working in this space, and the need to facilitate easier access to better platforms for performing social media analysis.

Mapping breastfeeding and COVID-19 related content and engagement on Facebook: Results from an online social listening study.

ISSUE ADDRESSED: The COVID-19 pandemic has seen evidence and advice evolve quickly. Since the start of the pandemic there has been confusion and concern about breastfeeding and COVID-19, and advice for this group has at times been contradictory. The volume of information on social media has exacerbated this. This study aimed to understand breastfeeding-related COVID-19 information sharing on social media during the global and Australian vaccine roll-out. METHODS: The CrowdTangle platform was used to source data from December 2020 to December 2021. Posts were categorised to intent and source and mapped to a timeline of pandemic-related events and announcements. Descriptive analysis was used to understand data distribution patterns and qualitative analysis for post-intent. RESULTS: A total of 945 posts were included. Post-interactions ranged from 0 to 6500. Vaccine-related posts were the highest in number and increased over time. Non-profit organisations shared the highest number of posts (n = 241), but interactions were highest with personal and government accounts. Peaks in posts and interactions mapped to key pandemic-related announcements and events. CONCLUSION: These results describe the breastfeeding and COVID-19 related content shared on Facebook over 13 months, and the associated interactions. Breastfeeding is an important public health issue and breastfeeding women have experienced conflicting and confusing breastfeeding-related information during the COVID-19 pandemic. Better understanding of social media usage, and the monitoring of changes in usage, as an emergency unfolds, can help target communications. This article adds to the evidence in understanding user reactions to COVID-19 related breastfeeding information on social media. SO WHAT?: Social listening is an important part of health communication and infodemic management. Understanding how users react to and engage with COVID-19 related breastfeeding information on social media can help to understand how the general public perceives and responds to health advice and other information being shared.

A Mixed-Methods Feasibility Study of a Gamified Therapy Prescription App for Children with Neurodisability.

AIM: Determine the feasibility of a gamified therapy (occupational therapy, physiotherapy, speech pathology) prescription app developed for children with neurodisability for delivering school and home therapy programs (the Zingo app). METHOD: A mixed-methods feasibility study was conducted with children (and their parents, therapists, and teachers) with neurodisability (n = 8, female= 5) who were prescribed a 4-week individualized therapy program by their usual treating therapist using Zingo. Primary outcome measures were program adherence, engagement, app quality, and user experience, collected with quantitative and qualitative methods. RESULTS: Mean adherence to the program was 58.0% (SD 27.2). Our combined Engagement Index (EI) score was 74.4% (SD 11.7). App quality measured using Mobile Application Rating Scale- User version was 4.6/5 (SD 0.7, n = 6) for parents, 4.6/5 (SD 0.5, n = 5) for teachers, and 4.4/5 (SD 0.6, n = 6) for therapists. Thematic analysis of semi-structured interviews yielded a primary theme of "app as motivator" for therapy. CONCLUSIONS: Adherence findings were affected by COVID-19 outbreak however remain comparable with other studies in this cohort. EI findings compared favorably with other studies. The findings are supportive of the feasibility of Zingo for delivering home and school therapy programs for children with neurodisability and was found to motivate therapy program completion.

Using Machine Learning Technology (Early Artificial Intelligence-Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study.

BACKGROUND: Amid the COVID-19 pandemic, there has been a need for rapid social understanding to inform infodemic management and response. Although social media analysis platforms have traditionally been designed for commercial brands for marketing and sales purposes, they have been underused and adapted for a comprehensive understanding of social dynamics in areas such as public health. Traditional systems have challenges for public health use, and new tools and innovative methods are required. The World Health Organization Early Artificial Intelligence-Supported Response with Social Listening (EARS) platform was developed to overcome some of these challenges. OBJECTIVE: This paper describes the development of the EARS platform, including data sourcing, development, and validation of a machine learning categorization approach, as well as the results from the pilot study. METHODS: Data for EARS are collected daily from web-based conversations in publicly available sources in 9 languages. Public health and social media experts developed a taxonomy to categorize COVID-19 narratives into 5 relevant main categories and 41 subcategories. We developed a semisupervised machine learning algorithm to categorize social media posts into categories and various filters. To validate the results obtained by the machine learning-based approach, we compared it to a search-filter approach, applying Boolean queries with the same amount of information and measured the recall and precision. Hotelling T2 was used to determine the effect of the classification method on the combined variables. RESULTS: The EARS platform was developed, validated, and applied to characterize conversations regarding COVID-19 since December 2020. A total of 215,469,045 social posts were collected for processing from December 2020 to February 2022. The machine learning algorithm outperformed the Boolean search filters method for precision and recall in both English and Spanish languages (P<.001). Demographic and other filters provided useful insights on data, and the gender split of users in the platform was largely consistent with population-level data on social media use. CONCLUSIONS: The EARS platform was developed to address the changing needs of public health analysts during the COVID-19 pandemic. The application of public health taxonomy and artificial intelligence technology to a user-friendly social listening platform, accessible directly by analysts, is a significant step in better enabling understanding of global narratives. The platform was designed for scalability; iterations and new countries and languages have been added. This research has shown that a machine learning approach is more accurate than using only keywords and has the benefit of categorizing and understanding large amounts of digital social data during an infodemic. Further technical developments are needed and planned for continuous improvements, to meet the challenges in the generation of infodemic insights from social media for infodemic managers and public health professionals.

Social Media Analysis Tools for Public Health: A Cross-Sectional Survey.

During the COVID-19 pandemic the field of infodemic management has grown significantly. Social listening is the first step in managing the infodemic but little is known of the experience of public health professionals using social media analysis tools for health. Our survey sought the views of infodemic managers. Participants (n=417) had an average of 4.4 years' experience in social media analysis for health. Results reveal gaps in technical capabilities of tools, data sources, and languages covered. For future planning for infodemic preparednessand preventi on it is vital to understand and deliver for analysis needs of those working in the field.

Infodemic Insights on Trust in a Health Emergency: A Narrative Deep-Dive.

Trust in authorities is important during health emergencies, and there are many factors that influence this. The infodemic has resulted in overwhelming amounts of information being shared on digital media during the COVID-19 pandemic, and this research looked at trust-related narratives during a one-year period. We identified three key findings related to trust and distrust narratives, and a country-level comparison showed less mistrust narratives in a country with a higher level of trust in government. Trust is a complex construct and the findings of this study present results that warrant further exploration.

Investigating Maternal Perspectives of Breastfeeding Support Targeted Towards Fathers in the Milk Man Mobile App Intervention.

BACKGROUND: The support of her infant's father is one of the most important factors influencing a mother's breastfeeding success, and an increasing number of interventions are targeted towards fathers. Engaging fathers as agents to influence a maternal behavior is potentially problematic, yet few studies report on maternal experiences. OBJECTIVE: This study aims to explore mothers' perspectives of their partners' use of Milk Man, a father-focused breastfeeding smartphone app, and the acceptability of this approach. MATERIALS AND METHODS: New mothers (N = 459) whose partners had access to the app completed a questionnaire at six weeks postpartum. These data were used to determine knowledge, use and perspectives of the app. A sentiment analysis was conducted on responses to an open-ended question seeking maternal perspectives of the app. RESULTS: Just over a quarter of mothers (28%) had been shown something from the app, and 37% had discussed something from Milk Man with their partner. There were 162 open-ended responses related to mothers' perspectives of the app. Relevant responses (n = 129) were coded to an overall sentiment node and then to a total of 23 child nodes (sub-nodes). Most comments were positive (94), with a smaller number either negative (25) or neutral (21). Negative comments related to the usability of the app and not its intent or content. CONCLUSION: Mothers found the father-focussed breastfeeding app to be acceptable. When designing interventions targeting one group to affect the behaviour of another, inclusion of measures to gain the perspectives of both should be seen as an imperative.

Gamification and older adults: opportunities for gamification to support health promotion initiatives for older adults in the context of COVID-19.

The COVID-19 pandemic has increased reliance on digital service delivery, including the delivery of health promotion initiatives. Health promotion interventions need to carefully consider user engagement. Gamification is a strategy used to engage and motivate people, and evidence shows overall cautious positive results in the use of gamification for older people across a range of health areas although more evidence is needed. Gamification has been used as a strategy in COVID-19 related initiatives and there is potential to build on the evidence to further develop gamification initiatives for those living in the Western Pacific region to impact positively on healthy behaviours and health outcomes.

User Experience of COVID-19 Chatbots: Scoping Review.

BACKGROUND: The COVID-19 pandemic has had global impacts and caused some health systems to experience substantial pressure. The need for accurate health information has been felt widely. Chatbots have great potential to reach people with authoritative information, and a number of chatbots have been quickly developed to disseminate information about COVID-19. However, little is known about user experiences of and perspectives on these tools. OBJECTIVE: This study aimed to describe what is known about the user experience and user uptake of COVID-19 chatbots. METHODS: A scoping review was carried out in June 2021 using keywords to cover the literature concerning chatbots, user engagement, and COVID-19. The search strategy included databases covering health, communication, marketing, and the COVID-19 pandemic specifically, including MEDLINE Ovid, Embase, CINAHL, ACM Digital Library, Emerald, and EBSCO. Studies that assessed the design, marketing, and user features of COVID-19 chatbots or those that explored user perspectives and experience were included. We excluded papers that were not related to COVID-19; did not include any reporting on user perspectives, experience, or the general use of chatbot features or marketing; or where a version was not available in English. The authors independently screened results for inclusion, using both backward and forward citation checking of the included papers. A thematic analysis was carried out with the included papers. RESULTS: A total of 517 papers were sourced from the literature, and 10 were included in the final review. Our scoping review identified a number of factors impacting adoption and engagement including content, trust, digital ability, and acceptability. The papers included discussions about chatbots developed for COVID-19 screening and general COVID-19 information, as well as studies investigating user perceptions and opinions on COVID-19 chatbots. CONCLUSIONS: The COVID-19 pandemic presented a unique and specific challenge for digital health interventions. Design and implementation were required at a rapid speed as digital health service adoption accelerated globally. Chatbots for COVID-19 have been developed quickly as the pandemic has challenged health systems. There is a need for more comprehensive and routine reporting of factors impacting adoption and engagement. This paper has shown both the potential of chatbots to reach users in an emergency and the need to better understand how users engage and what they want.

Intervention Mapping of a Gamified Therapy Prescription App for Children With Disabilities: User-Centered Design Approach.

BACKGROUND: Mobile health (mHealth) apps for children are increasing in availability and scope. Therapy (physiotherapy, speech pathology, and occupational therapy) prescription apps to improve home or school program adherence work best when developed to be highly engaging for children and when they incorporate behavior change techniques (BCTs) within their design. OBJECTIVE: The aim of this study was to describe the development of a user-centered therapy prescription app for children (aged 6-12 years) with neurodevelopmental disabilities (eg, cerebral palsy, autism spectrum disorder, and intellectual disability) incorporating intervention mapping (IM) and gamified design. METHODS: We used an iterative, user-centered app development model incorporating the first 3 steps of IM. We conducted a needs analysis with user feedback from our previous mHealth app study, a literature review, and a market audit. Change objectives were then specified in alignment with the psychological needs of autonomy, competence, and relatedness identified in self-determination theory. From these objectives, we then selected BCTs, stipulating parameters for effectiveness and how each BCT would be operationalized. A gamification design was planned and implemented focusing on maximizing engagement in children. In total, 2 rounds of consultations with parents, teachers, and therapists and 1 round of prototype app testing with children were conducted to inform app development, with a final iteration developed for further testing. RESULTS: The IM process resulted in the specification of app elements, self-determination theory-informed BCTs, that were embedded into the app design. The gamification design yielded the selection of a digital pet avatar with a fantasy anime visual theme and multiple layers of incentives earned by completing prescribed therapy activities. Consultation groups with professionals working with children with disabilities (4 therapists and 3 teachers) and parents of children with disabilities (n=3) provided insights into the motivation of children and the pragmatics of implementing app-delivered therapy programs that informed the app development. User testing with children with disabilities (n=4) highlighted their enthusiasm for the app and the need for support in the initial phase of learning the app. App quality testing (Mobile Application Rating Scale-user version) with the children yielded means (out of 5) of 4.5 (SD 0.8) for engagement, 3.3 (SD 1.6) for function, 3.3 (SD 1.7) for aesthetics, and 4.3 (SD 1.1) for subjective quality. CONCLUSIONS: mHealth apps designed for children can be greatly enhanced with a systematic yet flexible development process considering the specific contextual needs of the children with user-centered design, addressing the need for behavior change using the IM process, and maximizing engagement with gamification and strong visual design.

Measuring User Engagement with a Socially Connected, Gamified Health Promotion Mobile App.

Participant engagement is an important consideration in mHealth interventions and there are no standardised measurements available to guide researchers. This paper describes the engagement index customised for the Milk Man app, a mobile app designed to engage fathers with breastfeeding and parenting information. Participants were recruited from maternity hospitals in Perth, Western Australia. An engagement index with scores ranging from 0 to 100 was calculated. Kaplan Meier survival analysis was used to determine difference in duration of exclusive breastfeeding, and Pearson's chi square analysis was conducted to investigate the association of engagement level with demographic characteristics and exclusive breastfeeding at 6 weeks. While overall, partners of participants who installed Milk Man were less likely to have ceased exclusive breastfeeding at any time point from birth to six weeks postpartum, this result was modest and of borderline significance (log rank test p = 0.052; Breslow p = 0.046; Tarone-Ware p = 0.049). The mean engagement score was 29.7% (range 1-80%), median 27.6%. Engagement level had no impact on duration of exclusive breastfeeding and demographic factors were not associated with engagement level. This research demonstrates a range of metrics that can be used to quantify participant engagement. However, more research is needed to identify ways of measuring effective engagement.

How New and Expecting Fathers Engage With an App-Based Online Forum: Qualitative Analysis.

BACKGROUND: Breastfeeding is important for infants, and fathers are influential in supporting their partner in their decision to breastfeed and how long they breastfeed for. Fathers can feel excluded from traditional antenatal education and support opportunities but highly value social support from peers. Online health forums can be a useful source of social support, yet little is known about how fathers would use a conversation forum embedded in a breastfeeding-focused app. Milk Man is a mobile app that aimed to increase paternal support for breastfeeding using a range of strategies, including a conversation forum. OBJECTIVE: The aim of this study was to examine how fathers used a breastfeeding-focused conversation forum contained within a mobile app throughout the perinatal period. METHODS: A qualitative analysis of comments posted by users in the online forum contained within the Milk Man app was conducted. The app contained a library of information for fathers, as well as a conversation forum. Thematic analysis was used to organize and understand the data. The NVivo 11 software package was used to code comments into common nodes, which were then organized into key themes. RESULTS: In all, 208 contributors (35.5% [208/586] of those who had access to the app) posted at least once within the forum. In total, 1497 comments were included for analysis. These comments were coded to 3799 individual nodes and then summarized to 54 tree nodes from which four themes emerged to describe how fathers used the app. Themes included seek and offer support, social connection, informational support provision, and sharing experiences. Posting in the forum was concentrated in the antenatal period and up to approximately 6 weeks postpartum. CONCLUSIONS: These data show that fathers are prepared to use a breastfeeding-focused online forum in a variety of ways to facilitate social support. Fathers can be difficult to reach in the perinatal period, yet engaging them and increasing social support is important. This research demonstrates the acceptability of an innovative way of engaging new and expecting fathers.

Designing evaluation plans for health promotion mHealth interventions: a case study of the Milk Man mobile app.

Evaluating complex health promotion interventions that use mobile apps requires comprehensive and adaptive evaluation plans. As mobile usage becomes increasingly sophisticated and personalised, broad evaluation plans are important in determining the impact and efficacy of a mobile health (mHealth) app. Evaluation should consider user feedback and outcome measures, as well as examine elements such as the robustness of the technology, the intervention principles and engagement strategies, and the interaction of the user with the technology. This paper introduces four mHealth evaluation models and tools and describes the evaluation plan that has been developed for Milk Man, a breastfeeding app targeting new and expectant fathers. Milk Man is a socially connected, gamified app that is being tested in a large Randomised Control Trial (RCT). While there is a need for mobile apps to be evaluated in adequately powered RCTs, trialling mobile apps over a long period of time presents challenges. Incorporating robust evaluation design will help ensure that technological performance, app intervention principles, as well as health and behavioural outcomes are measured. The detail and scope of the Milk Man app evaluation plan will ensure the findings add to the evidence base and have broad relevance to health promotion practitioners. So what? Evidence about the efficacy of mHealth interventions is an emerging area and appropriate evaluation skills are needed. This paper illustrates an evaluation planning approach for mHealth interventions that could be adapted for use by health promotion practitioners and researchers.

Theory-Based Design and Development of a Socially Connected, Gamified Mobile App for Men About Breastfeeding (Milk Man).

BACKGROUND: Despite evidence of the benefits of breastfeeding, <15% of Australian babies are exclusively breastfed to the recommended 6 months. The support of the father is one of the most important factors in breastfeeding success, and targeting breastfeeding interventions to the father has been a successful strategy in previous research. Mobile technology offers unique opportunities to engage and reach populations to enhance health literacy and healthy behavior. OBJECTIVE: The objective of our study was to use previous research, formative evaluation, and behavior change theory to develop the first evidence-based breastfeeding app targeted at men. We designed the app to provide men with social support and information aiming to increase the support men can offer their breastfeeding partners. METHODS: We used social cognitive theory to design and develop the Milk Man app through stages of formative research, testing, and iteration. We held focus groups with new and expectant fathers (n=18), as well as health professionals (n=16), and used qualitative data to inform the design and development of the app. We tested a prototype with fathers (n=4) via a think-aloud study and the completion of the Mobile Application Rating Scale (MARS). RESULTS: Fathers and health professionals provided input through the focus groups that informed the app development. The think-aloud walkthroughs identified 6 areas of functionality and usability to be addressed, including the addition of a tutorial, increased size of text and icons, and greater personalization. Testers rated the app highly, and the average MARS score for the app was 4.3 out of 5. CONCLUSIONS: To our knowledge, Milk Man is the first breastfeeding app targeted specifically at men. The development of Milk Man followed a best practice approach, including the involvement of a multidisciplinary team and grounding in behavior change theory. It tested well with end users during development. Milk Man is currently being trialed as part of the Parent Infant Feeding Initiative (ACTRN12614000605695).