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.

A taxonomy of early diagnosis research to guide study design and funding prioritisation.

Researchers and research funders aiming to improve diagnosis seek to identify if, when, where, and how earlier diagnosis is possible. This has led to the propagation of research studies using a wide range of methodologies and data sources to explore diagnostic processes. Many such studies use electronic health record data and focus on cancer diagnosis. Based on this literature, we propose a taxonomy to guide the design and support the synthesis of early diagnosis research, focusing on five key questions: Do healthcare use patterns suggest earlier diagnosis could be possible? How does the diagnostic process begin? How do patients progress from presentation to diagnosis? How long does the diagnostic process take? Could anything have been done differently to reach the correct diagnosis sooner? We define families of diagnostic research study designs addressing each of these questions and appraise their unique or complementary contributions and limitations. We identify three further questions on relationships between the families and their relevance for examining patient group inequalities, supported with examples from the cancer literature. Although exemplified through cancer as a disease model, we recognise the framework is also applicable to non-neoplastic disease. The proposed framework can guide future study design and research funding prioritisation.

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.

Diagnostic windows in non-neoplastic diseases: a systematic review.

BACKGROUND: Investigating changes in prediagnostic healthcare utilisation can help identify how much earlier conditions could be diagnosed. Such 'diagnostic windows' are established for cancer but remain relatively unexplored for non-neoplastic conditions. AIM: To extract evidence on the presence and length of diagnostic windows for non-neoplastic conditions. DESIGN AND SETTING: A systematic review of studies of prediagnostic healthcare utilisation was carried out. METHOD: A search strategy was developed to identify relevant studies from PubMed and Connected Papers. Data were extracted on prediagnostic healthcare use, and evidence of diagnostic window presence and length was assessed. RESULTS: Of 4340 studies screened, 27 were included, covering 17 non-neoplastic conditions, including both chronic (for example, Parkinson's disease) and acute conditions (for example, stroke). Prediagnostic healthcare events included primary care encounters and presentations with relevant symptoms. For 10 conditions, sufficient evidence to determine diagnostic window presence and length was available, ranging from 28 days (herpes simplex encephalitis) to 9 years (ulcerative colitis). For the remaining conditions, diagnostic windows were likely to be present, but insufficient study duration was often a barrier to robustly determining their length, meaning that diagnostic window length may exceed 10 years for coeliac disease, for example. CONCLUSION: Evidence of changing healthcare use before diagnosis exists for many non-neoplastic conditions, establishing that early diagnosis is possible, in principle. In particular, some conditions may be detectable many years earlier than they are currently diagnosed. Further research is required to accurately estimate diagnostic windows and to determine how much earlier diagnosis may be possible, and how this might be achieved.

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.

An Adaptive Digital Intelligence System to Support Infodemic Management: The WHO EARS Platform.

The WHO Early AI-Supported Response with Social Listening (EARS) platform was developed to help inform infodemic response during the COVID-19 pandemic. There was continual monitoring and evaluation of the platform and feedback from end-users was sought on a continual basis. Iterations were made to the platform in response to user needs, including the introduction of new languages and countries, and additional features to better enable more fine-grained and rapid analysis and reporting. The platform demonstrates how a scalable, adaptable system can be iterated upon to continue to support those working in emergency preparedness and response.

Narrative Trends over the COVID-19 Pandemic: Digital Social Listening to Inform WHO Infodemic Management.

The COVID-19 infodemic is an overwhelming amount of information that has challenged pandemic communication and epidemic response. WHO has produced weekly infodemic insights reports to identify questions, concerns, information voids expressed and experienced by people online. Publicly available data was collected and categorized to a public health taxonomy to enable thematic analysis. Analysis showed three key periods of narrative volume peaks. Understanding how conversations change over time can help inform future infodemic preparedness and prevention planning.

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.

Relationship between ethnicity and stage at diagnosis in England: a national analysis of six cancer sites.

OBJECTIVES: Cancer stage at diagnosis is a determinant of treatment options and survival. Previous research has shown differences in barriers to presentation with cancer between ethnic groups. The completeness and quality of cancer stage and ethnicity data has improved markedly over recent years in England, allowing for comparison of stage distributions at diagnosis between ethnic groups. This study aimed to assess relationships between ethnic group and two outcomes: unknown stage cancer and late stage (stages 3 and 4) cancer, after adjustment for confounders. DESIGN AND SETTING: A retrospective secondary data analysis using data from NHS Digital's National Cancer Registration and Analysis Service and Hospital Episode Statistics records from 2012 to 2016. PARTICIPANTS: This study analysed newly diagnosed breast, colon, non-small cell lung cancer (NSCLC), ovary, prostate and uterine cancers in white British, Caribbean, African, Chinese and Asian patients aged 15-99 in England. RESULTS: Caribbean, African and Asian women with breast or ovarian cancer, Caribbean and African women with uterine or colon cancer, Caribbean women with NSCLC and Caribbean men with colon cancer had increased odds of late-stage disease at diagnosis compared with the white British cohort. In contrast, Caribbean and African men with prostate cancer had decreased odds of late-stage cancer. Where stage was known, there were variations in late-stage cancer by ethnic group. CONCLUSIONS: Low symptom awareness and barriers to presentation can cause delays, resulting in later stage diagnosis. Targeted intervention campaigns to help raise awareness of cancer signs and symptoms and the benefits of early diagnosis, along with removing barriers to appropriate referrals, could help to improve these inequalities.

Underlying cancer risk among patients with fatigue and other vague symptoms: a population-based cohort study in primary care.

BACKGROUND: Presenting to primary care with fatigue is associated with slightly increased cancer risk, although it is unknown how this varies in the presence of other 'vague' symptoms. AIM: To quantify cancer risk in patients with fatigue who present with other 'vague' symptoms in the absence of 'alarm' symptoms for cancer. DESIGN AND SETTING: Cohort study of patients presenting in UK primary care with new-onset fatigue during 2007-2015, using Clinical Practice Research Datalink data linked to national cancer registration data. METHOD: Patients presenting with fatigue without co-occurring alarm symptoms or anaemia were identified, who were further characterised as having co-occurrence of 19 other 'vague' potential cancer symptoms. Sex- and age-specific 9-month cancer risk for each fatigue-vague symptom cohort were calculated. RESULTS: Of 285 382 patients presenting with new-onset fatigue, 84% (n = 239 846) did not have co-occurring alarm symptoms or anaemia. Of these, 38% (n = 90 828) presented with ≥1 of 19 vague symptoms for cancer. Cancer risk exceeded 3% in older males with fatigue combined with any of the vague symptoms studied. The age at which risk exceeded 3% was 59 years for fatigue-weight loss, 65 years for fatigue-abdominal pain, 67 years for fatigue-constipation, and 67 years for fatigue-other upper gastrointestinal symptoms. For females, risk exceeded 3% only in older patients with fatigue-weight loss (from 65 years), fatigue-abdominal pain (from 79 years), or fatigue-abdominal bloating (from 80 years). CONCLUSION: In the absence of alarm symptoms or anaemia, fatigue combined with specific vague presenting symptoms, alongside patient age and sex, can guide clinical decisions about referral for suspected cancer.

Pandemics, infodemics and health promotion.

The COVID-19 pandemic and the accompanying infodemic are significant public health issues. The COVID-19 infodemic has been prolific from early in the pandemic response, and has continued to escalate during vaccine rollout. COVID-19 is the first pandemic in the social media era, expediting the need for effective measures to manage the high volume of information and misinformation. To address the infodemic, the World Health Organization (WHO) and others have commenced a comprehensive program of work, building capacity, raising awareness and developing new tools and methods. As part of the WHO capacity building effort, they have developed a comprehensive infodemic manager training program. The authors of this paper are Australian alumni from the first two training courses, all authors have health promotion backgrounds. Health Promotion Practitioners are uniquely positioned to build on existing skills, knowledge and reach to develop preventative strategies to help mitigate infodemics. This paper offers our combined perspectives on why the infodemic is a significant health promotion concern and the role we believe Health Promotion Practitioners can play in managing and mitigating the infodemic.

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.

Mental Health Morbidities and Time to Cancer Diagnosis Among Adults With Colon Cancer in England.

Importance: Mental health morbidity (MHM) in patients presenting with possible cancer symptoms may be associated with prediagnostic care and time to cancer diagnosis. Objective: To compare the length of intervals to cancer diagnosis by preexisting MHM status in patients who presented with symptoms of as-yet-undiagnosed colon cancer and evaluate their risk of emergency cancer diagnosis. Design, Setting, and Participants: This cohort study was conducted using linked primary care data obtained from the population-based Clinical Practice Research Datalink, which includes primary care practices in England, linked to cancer registry and hospital data. Included participants were 3766 patients diagnosed with colon cancer between 2011 and 2015 presenting with cancer-relevant symptoms up to 24 months before their diagnosis. Data analysis was performed in January 2021 to April 2022. Exposures: Mental health conditions recorded in primary care before cancer diagnosis, including anxiety, depression, schizophrenia, bipolar disorder, alcohol addiction, anorexia, and bulimia. Main Outcomes and Measures: Fast-track (also termed 2-week wait) specialist referral for investigations, time to colonoscopy and cancer diagnosis, and risk of emergency cancer diagnosis. Results: Among 3766 patients with colon cancer (median [IQR] age, 75 [65-82] years; 1911 [50.7%] women ), 623 patients [16.5%] had preexisting MHM recorded in primary care the year before cancer diagnosis, including 562 patients (14.9%) with preexisting anxiety or depression (accounting for 90.2% of patients with preexisting MHM) and 61 patients (1.6%) with other MHM; 3143 patients (83.5%) did not have MHM. Patients with MHM had records of red-flag symptoms or signs (ie, rectal bleeding, change in bowel habit, or anemia) in the 24 months before cancer diagnosis in a smaller proportion compared with patients without MHM (308 patients [49.4%] vs 1807 patients [57.5%]; P < .001). Even when red-flag symptoms were recorded, patients with MHM had lower odds of fast-track specialist referral (adjusted odds ratio [OR] = 0.72; 95% CI, 0.55-0.94; P = .01). Among 2115 patients with red-flag symptoms or signs, 308 patients with MHM experienced a more than 2-fold longer median (IQR) time to cancer diagnosis (326 [75-552] days vs 133 [47-422] days) and higher odds of emergency diagnosis (90 patients [29.2%] vs 327 patients [18.1%]; adjusted OR = 1.63; 95% CI, 1.23-2.24; P < .001) compared with 1807 patients without MHM. Conclusions and Relevance: This study found that patients with MHM experienced large and prognostically consequential disparities in diagnostic care before a colon cancer diagnosis. These findings suggest that appropriate pathways and follow-up strategies after symptomatic presentation are needed for earlier cancer diagnoses and improved health outcomes in this large patient group.

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.

Another case of cryptococcal meningitis in a person without HIV who injects drugs: A possible risk factor in need of further investigation.

Cryptococcal meningitis is a fungal central nervous infection typically occurring in patients with severe immunocompromise. We present a case of cryptococcal meningitis occurring in a patient with active injection drug use (IDU) but no immunocompromising condition. This is the seventh case in the recent literature of cryptococcal central nervous involvement in an otherwise healthy young person with IDU, suggesting a possible association in need of further exploration.