Mental health challenges and digital platform opportunities in patients and families affected by pediatric neuromuscular diseases - experiences from Switzerland.

Receiving the diagnosis of a severe disease may present a traumatic event for patients and their families. To cope with the related challenges, digital interventions can be combined with traditional psychological support to help meet respective needs. We aimed to 1) discuss the most common consequences and challenges for resilience in Neuro Muscular Disease patients and family members and 2) elicit practical needs, concerns, and opportunities for digital platform use. We draw from findings of a transdisciplinary workshop and conference with participants ranging from the fields of clinical practice to patient representatives. Reported consequences of the severe diseases were related to psychosocial challenges, living in the nexus between physical development and disease progression, social exclusion, care-related challenges, structural and financial challenges, and non-inclusive urban design. Practical needs and concerns regarding digital platform use included social and professional support through these platforms, credibility and trust in online information, and concerns about privacy and informed consent. Furthermore, the need for safe, reliable, and expert-guided information on digital platforms and psychosocial and relationship-based digital interventions was expressed. There is a need to focus on a family-centered approach in digital health and social care and a further need in researching the suitability of digital platforms to promote resilience in the affected population. Our results can also inform city councils regarding investments in inclusive urban design allowing for disability affected groups to enjoy a better quality of life.

The Role of Social Media in Building Pandemic Resilience in an Urban Community: A Qualitative Case Study.

This paper explores the influence of social media in fostering resilience within an urban spatial context, specifically in Bangalore, India, during the COVID-19 lockdown, a period marked by a surge in digital communication due to movement restrictions. To control the rapid spread of the virus, over 1.38 billion people were given stay-at-home orders by the government of India during the onset of the pandemic. The restrictions in movement forced individuals to shift to online modes of connection and communication. As the field of digital epidemiology, that is, the use of digital tools and data to understand and improve health took center stage during the pandemic, the focus shifted towards the social media landscape, which is often associated with its negative aspects, such as misinformation. However, this paper delves into social media's potential to build resilience on a local scale, particularly given its increased usage during the pandemic. Through in-depth online interviews with eight urban residents, we conducted a thematic analysis to understand social media's role during the lockdown. Results indicate that social media facilitated effective information exchange and fostered a sense of community. Furthermore, it engendered an environment conducive to prosocial behavior, a known resilience amplifier. We also highlight the importance of baseline context regarding the users directly engaged in social media data generation with respect to digital epidemiology analytics tools for large-scale social media data and the need for qualitative input feeding into their design. Our study highlights the need for a balanced perspective on social media use in times of crisis, recognizing its potential to boost community resilience in an urban setting, and further enriching digital epidemiology approaches.

Sustainable Smart Cities-Social Media Platforms and Their Role in Community Neighborhood Resilience-A Systematic Review.

The COVID-19 pandemic took most communities off guard and has highlighted gaps in community preparedness and resilience in spite of the numerous technological advancements and the variety of available social media platforms that many relied on during lockdown periods. This served to emphasise the necessity for exploring the roles of social media and smart city technologies in mitigating pandemic impacts. In this systematic literature review, we examined twelve articles on social media usage and smart city technologies and their contributions to community resilience during COVID-19. The analysis focused on the use of social media platforms and smart city technologies during and after lockdown periods, examining their role in fostering community resilience. Results indicate that social media and smart city technologies were instrumental in helping communities adapt and recover from the pandemic. While past studies have examined community resilience, social media, or smart cities separately, there is limited literature collating insights on the three elements combined. We therefore argue that these technologies, employed collaboratively, enhance community resilience during crises. Nevertheless, further research is recommended, particularly on urban resilience and comparative analyses to deepen our understanding of the complex interplay between these variables.

Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action.

The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and digital epidemiology. This commentary highlights methodological and analytic approaches that can reduce research waste and improve the reproducibility and replicability of big data research in public health. The recommendations described in this commentary, including a focus on practices, publication norms, and education, are neither exhaustive nor unique to big data, but, nonetheless, implementing them can broadly improve public-health research. Clearly defined and openly shared guidelines will not only improve the quality of current research practices but also initiate change at multiple levels: the individual level, the institutional level, and the international level.

Digital Platform Uses for Help and Support Seeking of Parents With Children Affected by Disabilities: Scoping Review.

BACKGROUND: Receiving a diagnosis that leads to severe disability in childhood can cause a traumatic experience with long-lasting emotional stress for patients and family members. In recent decades, emerging digital technologies have transformed how patients or caregivers of persons with disabilities manage their health conditions. As a result, information (eg, on treatment and resources) has become widely available to patients and their families. Parents and other caregivers can use digital platforms such as websites or social media to derive social support, usually from other patients and caregivers who share their lived experiences, challenges, and successes on these platforms. However, gaps remain in our understanding of platforms that are most frequently used or preferred among parents and caregivers of children with disabilities. In particular, it is not clear what factors primarily drive or discourage engagement with these digital tools and what the main ethical considerations are in relation to these tools. OBJECTIVE: We aimed to (1) identify prominent digital platforms used by parents or caregivers of children with disabilities; (2) explore the theoretical contexts and reasons for digital platform use, as well as the experiences made with using these platforms reported in the included studies; and (3) identify any privacy and ethical concerns emerging in the available literature in relation to the use of these platforms. METHODS: We conducted a scoping review of 5 academic databases of English-language articles published within the last 10 years for diseases with childhood onset disability and self-help or parent/caregiver-led digital platforms. RESULTS: We identified 17 papers in which digital platforms used by parents of affected children predominantly included social media elements but also search engines, health-related apps, and medical websites. Information retrieval and social support were the main reasons for their utilization. Nearly all studies were exploratory and applied either quantitative, qualitative, or mixed methods. The main ethical concerns for digital platform users included hampered access due to language barriers, privacy issues, and perceived suboptimal advice (eg, due to missing empathy of medical professionals). Older and non-college-educated individuals and ethnic minorities appeared less likely to access information online. CONCLUSIONS: This review showed that limited scientifically sound knowledge exists on digital platform use and needs in the context of disabling conditions in children, as the evidence consists mostly of exploratory studies. We could highlight that affected families seek information and support from digital platforms, as health care systems seem to be insufficient for satisfying knowledge and support needs through traditional channels.

Opportunities and challenges of using social media big data to assess mental health consequences of the COVID-19 crisis and future major events.

The present commentary discusses how social media big data could be used in mental health research to assess the impact of major global crises such as the COVID-19 pandemic. We first provide a brief overview of the COVID-19 situation and the challenges associated with the assessment of its global impact on mental health using conventional methods. We then propose social media big data as a possible unconventional data source, provide illustrative examples of previous studies, and discuss the advantages and challenges associated with their use for mental health research. We conclude that social media big data represent a valuable resource for mental health research, however, several methodological limitations and ethical concerns need to be addressed to ensure safe use.

Detecting Suicide Ideation in the Era of Social Media: The Population Neuroscience Perspective.

Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic location, environmental stress). Other important research contributions on SI come from studies in neuroscience. To date, very few research studies have been conducted that combine different disciplines (epidemiology, health geography, neurosciences, psychology, and social media big data science), to build innovative research directions on this topic. This article aims to offer a new interdisciplinary perspective, that is, a Population Neuroscience perspective on SI in order to highlight new ways in which multiple scientific fields interact to successfully investigate emotions and stress in social media to detect SI in the population. We argue that a Population Neuroscience perspective may help to better understand the mechanisms underpinning SI and to promote more effective strategies to prevent suicide timely and at scale.

Ethical issues of collecting, storing, and analyzing geo-referenced tweets for mental health research.

Spatial approaches to epidemiological research with big social media data provide tremendous opportunities to study the relationship between the socio-ecological context where these data are generated and health indicators of interest. Such research poses a number of ethical challenges, particularly in relation to issues such as privacy, informed consent, data security, and storage. While these issues have received considerable attention by researchers in relation to research for physical health purposes in the past 10 years, there have been few efforts to consider the ethical challenges of conducting mental health research, particularly with geo-referenced social media data. The aim of this article is to identify strengths and limitations of current recommendations to address the specific ethical issues of geo-referenced tweets for mental health research. We contribute to the ongoing debate on the ethical implications of big data research and also provide recommendations to researchers and stakeholders alike on how to tackle them, with a specific focus on the use of geo-referenced data for mental health research purposes. With increasing awareness of data privacy and confidentiality issues (even for non-spatial social media data) it becomes crucial to establish professional standards of conduct so that compliance with ethical standards of conducting research with health-related social media data can be prioritized and easily assessed.

Space-Time Dependence of Emotions on Twitter after a Natural Disaster.

Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations between socioeconomic status and infrastructural damage with negative emotional expressions across NYC census tracts over time. A total of 984,311 geo-referenced tweets with negative basic emotions (anger, disgust, fear, sadness, shame) were collected and assigned to the census tracts within NYC boroughs between 8 October and 18 November 2012. Global and local univariate and bivariate Moran's I statistics were used to analyze the data. We found local spatial clusters of all negative emotions over all disaster periods. Socioeconomic status and infrastructural damage were predominantly correlated with disgust, fear, and shame post-disaster. We identified spatial clusters of emotional reactions during and in the aftermath of a large-scale disaster that could help provide guidance about where immediate and long-term relief measures are needed the most, if transferred to similar events and on comparable data worldwide.