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.

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.

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.

Plasma concentrations of SSRI/SNRI after bariatric surgery and the effects on depressive symptoms.

Background: Depression and treatment with antidepressants SSRI/SNRI are common in people with morbid obesity who are candidates for bariatric surgery. There is few and inconsistent data about the postoperative plasma concentrations of SSRI/SNRI. The aims of our study were to provide comprehensive data about the postoperative bioavailability of SSRI/SNRI, and the clinical effects on depressive symptoms. Methods: Prospective multicenter study including 63 patients with morbid obesity and therapy with fixed doses of SSRI/SNRI: participants filled the Beck Depression Inventory (BDI) questionnaire, and plasma levels of SSRI/SNRI were measured by HPLC, preoperatively (T0), and 4 weeks (T1) and 6 months (T2) postoperatively. Results: The plasma concentrations of SSRI/SNRI dropped significantly in the bariatric surgery group from T0 to T2 by 24.7% (95% confidence interval [CI], -36.8 to -16.6, p = 0.0027): from T0 to T1 by 10.5% (95% 17 CI, -22.7 to -2.3; p = 0.016), and from T1 to T2 by 12.8% (95% CI, -29.3 to 3.5, p = 0.123), respectively.There was no significant change in the BDI score during follow-up (-2.9, 95% CI, -7.4 to 1.0; p = 0.13).The clinical outcome with respect to SSRI/SNRI plasma concentrations, weight change, and change of BDI score were similar in the subgroups undergoing gastric bypass surgery and sleeve gastrectomy, respectively. In the conservative group the plasma concentrations of SSRI/SNRI remained unchanged throughout the 6 months follow-up (-14.7, 95% CI, -32.6 to 1.7; p = 0.076). Conclusion: In patients undergoing bariatric surgery plasma concentrations of SSRI/SNRI decrease significantly by about 25% mainly during the first 4 weeks postoperatively with wide individual variation, but without correlation to the severity of depression or weight loss.

Partial staple line reinforcement with synthetic buttressing material in laparoscopic sleeve gastrectomy: a propensity score-matched analysis.

PURPOSE: Staple line leakage (SLL) and staple line bleeding (SLB) are the most relevant postoperative complications of sleeve gastrectomy (SG). It is controversial whether and which method of staple line reinforcement (SLR) can best reduce these complications. The primary objective of this study was to investigate whether reinforcement of the most proximal part of the staple line with synthetic buttressing material, a strategy we termed partial SLR (p-SLR), reduces the 30-day incidence of SLL. METHODS: A retrospective search of medical records of all bariatric patients from 2010 to 2019 was performed. Patients who underwent SG with either p-SLR or non-SLR were included. Intraoperative and postoperative outcomes were analyzed before and after propensity score matching (PSM). RESULTS: Data from 431 patients were analyzed (364 in the p-SLR group and 67 in the non-SLR group). No difference in the 30-day incidence of SLL was observed between the two groups. The 30-day incidence of SLB (1.1% vs. 6.0% in the p-SLR and non-SLR groups, respectively) was significantly lower in the p-SLR group. These results were confirmed by PSM analysis. CONCLUSION: Partial staple line reinforcement with synthetic buttressing material does not reduce the 30-day incidence of SLL. Although our analysis showed a significant reduction in the 30-day incidence of SLB in the p-SLR group, this result should be interpreted with caution.

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.

Effects of short or long biliopancreatic limb length after laparoscopic Roux-en-Y gastric bypass surgery for obesity: a propensity score-matched analysis.

PURPOSE: Although recent studies reported superior weight reduction in patients undergoing Roux-en-Y gastric bypass (RYGB) with long biliopancreatic limb (BPL), no recommendation regarding limb lengths exists. This study compares weight loss and resolution of obesity-related comorbidities in patients undergoing RYGB with either long or short BPL. METHODS: A retrospective data search from medical records was performed. A total of 308 patients underwent laparoscopic RYGB with a BPL length of either 100 cm or 50 cm. Data was analyzed before and after propensity score matching. RESULTS: No statistically significant difference in weight reduction between long and short BPL RYGB in terms of percentage of excess weight loss (%EWL) (86.4 ± 24.5 vs. 83.4 ± 21.4, p = 0.285) and percentage of total weight loss (%TWL) (32.4 ± 8.4 vs. 33.0 ± 8.3, p = 0.543) was found 24 months after surgery. Propensity score-matched analysis did not show any statistically significant difference between groups in both %EWL and %TWL. No significant difference between long and short BPL RYGB in the resolution of obesity-related comorbidities was noted 24 months after surgery. CONCLUSION: Weight loss and resolution of obesity-related comorbidities were not significantly different between long and short BPL RYGB 24 months after surgery.

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.

Fast and automated biomarker detection in breath samples with machine learning.

Volatile organic compounds (VOCs) in human breath can reveal a large spectrum of health conditions and can be used for fast, accurate and non-invasive diagnostics. Gas chromatography-mass spectrometry (GC-MS) is used to measure VOCs, but its application is limited by expert-driven data analysis that is time-consuming, subjective and may introduce errors. We propose a machine learning-based system to perform GC-MS data analysis that exploits deep learning pattern recognition ability to learn and automatically detect VOCs directly from raw data, thus bypassing expert-led processing. We evaluate this new approach on clinical samples and with four types of convolutional neural networks (CNNs): VGG16, VGG-like, densely connected and residual CNNs. The proposed machine learning methods showed to outperform the expert-led analysis by detecting a significantly higher number of VOCs in just a fraction of time while maintaining high specificity. These results suggest that the proposed novel approach can help the large-scale deployment of breath-based diagnosis by reducing time and cost, and increasing accuracy and consistency.

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.

Routine histopathologic examination of the resected specimen after laparoscopic sleeve gastrectomy - what can be expected?

BACKGROUND: Laparoscopic Sleeve Gastrectomy (LSG) is nowadays an established bariatric procedure. Although preoperative gastroscopy is recommended to rule out severe pathologies, there is little evidence about the role of routine histopathologic examination of resected specimens. We sought to identify the prevalence of histopathological relevant findings in patients undergoing LSG and to evaluate their impact in clinical practice. METHODS: A retrospective analysis on a prospectively collected dataset on patients undergoing LSG between August 2009 and May 2018 in two bariatric centers was performed. Demographic and clinical data and histopathological results were analyzed. RESULTS: Sixhundred-thrirteen patients were identified, mean age was 43.1 years (14-75), average body mass index was 44.8 kg/m2 (34.4-73.9). Histopathology revealed abnormal findings in 47.97% of the patients, most common pathology was chronic non-active or minimally to moderate active gastritis (n = 202;32.95%). Among others, Helicobacter-associated gastritis (n = 33;5.38%), intestinal metaplasia (n = 13;2.12%), micronodular enterochromaffine-like cell hyperplasia (n = 2; 0.33%) and gastrointestinal stromal tumors (n = 6; 0.98%) were present. No malignancies were found. Histopathological results required a change in the postoperative management in 48 patients (7.83%). The costs of histopathological assessment ranged between 0.77% and 2.55% of per-case payment. CONCLUSION: A wide range of histopathological findings occur in specimens after LSG, requiring a relevant number of patients additional therapies or surveillance. Therefore, routine histopathological examination after LSG is recommendable.

A unified ecological framework for studying effects of digital places on well-being.

Social media has greatly expanded opportunities to study place and well-being through the availability of human expressions tagged with physical location. Such research often uses social media content to study how specific places in the offline world influence well-being without acknowledging that digital platforms (e.g., Twitter, Facebook, Youtube, Yelp) are designed in unique ways that structure certain types of interactions in online and offline worlds, which can influence place-making and well-being. To expand our understanding of the mechanisms that influence social media expressions about well-being, we describe an ecological framework of person-place interactions that asks, "at what broad levels of interaction with digital platforms and physical environments do effects on well-being manifest?" The person is at the centre of the ecological framework to recognize how people define and organize both digital and physical communities and interactions. The relevance of interactions in physical environments depends on the built and natural characteristics encountered across modes of activity (e.g., domestic, work, study). Here, social interactions are stratified into the meso-social (e.g., local social norms) and micro-social (e.g., personal conversations) levels. The relevance of interactions in digital platforms is contingent on specific hardware and software elements. Social interactions at the meso-social level include platform norms and passive use of social media, such as observing the expressions of others, whereas interactions at the micro-level include more active uses, like direct messaging. Digital platforms are accessed in a physical location, and physical locations are partly experienced through online interactions; therefore, interactions between these environments are also acknowledged. We conclude by discussing the strengths and limitations of applying the framework to studies of place and well-being.

Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media.

Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. Our sample consisted of 1,018,140 geo-located tweets that were analyzed with an advanced sentiment analysis called "Extracting the Meaning Of Terse Information in a Visualization of Emotion" (EMOTIVE). We calculated discomfort rates for 2137 NYC census tracts, applied spatial regimes regression to find associations of discomfort, and used Moran's I for spatial cluster detection across NYC boroughs over time. We found increased discomfort, that is, bundled negative emotions after the storm as compared to during the storm. Furthermore, pre- and peri-disaster discomfort was positively associated with post-disaster discomfort; however, this association was different across boroughs, with significant associations only in Manhattan, the Bronx, and Queens. In addition, rates were most prominently spatially clustered in Staten Island lasting pre- to post-disaster. This is the first study that determined significant associations of negative emotional responses found in social media posts over space and time in the context of a natural disaster, which may guide us in identifying those areas and populations mostly in need for care.