Applications of crowdsourcing in health: an overview

Crowdsourcing strategies to improve access to HIV pre-exposure prophylaxis in Australia, the Philippines, Thailand and China

BACKGROUND

Many Asian countries have yet to scale up HIV pre-exposure prophylaxis (PrEP). Crowdsourcing has a group of individuals solving a specific problem before sharing solutions with the public. This approach enhances community engagement and ownership of the solutions and can be used to generate culturally relevant solutions. We used crowdsourcing to seek innovative strategies to optimise PrEP access by increasing the uptake and effective use of PrEP. This study describes the experiences of crowdsourcing open calls in Australia, the Philippines, Thailand and China.

METHODS

Four crowdsourcing open calls were conducted between 2021-2023 in Australia, the Philippines, Thailand and China. All open calls entailed: 1) problem identification; 2) committee formation with local groups; 3) community engagement for idea submission (e.g., texts, posters, pitches); 4) evaluation of submissions; 5) awarding incentives to finalists; and 6) solution dissemination via web and social media. We reported the number of total and high-quality submissions. We also identified themes across countries.

RESULTS

The Australian, Filipino, Thai and Chinese teams received 9, 22, 9 and 19 eligible submissions, respectively. A total of 3, 10, 7 and 8 submissions had a mean score of 6/10 or greater. Three common solutions emerged across all the finalist ideas: enhanced service access, optimising promotional campaigns, and person-centred promotional materials. The winning ideas from the Australian, Filipino, Thai and Chinese teams were an anonymous online PrEP service, a printed ready-to-wear garment to create awareness about PrEP, PrEP and HIV self-testing kit dispensing kiosks and a poster on PrEP effectiveness, respectively.

CONCLUSIONS

Crowdsourcing was a promising and versatile tool for developing PrEP strategies in the Asia-Pacific region. Further evaluations via clinical trials can bridge the gap between idea generation and implementation, creating the empirical evidence that is pivotal for the policy adoption of these innovations.

PrEP your step: Implementing an online crowdsourcing contest to engage young people in HIV prevention in Washington DC, USA

HIV incidence among young people (Black and Latinx women and men who have sex with men ages 16-24 years), in the United States is high. Traditional top-down approaches for pre-exposure prophylaxis (PrEP) social marketing are not effectively reaching this population. Crowdsourcing is a promising approach to engaging young people in the development of innovative solutions to raise awareness and use of PrEP among those at highest risk of HIV. This study engaged young people in the design and evaluation of an online crowdsourcing contest to promote PrEP among Washington, DC youth. The contest used standard methods recommended by the World Health Organization and feedback from our community partners. Online recruitment using social media elicited online votes and survey responses. We analyzed cross-sectional surveys using descriptive statistics, and semi-structured interviews with contest participants using thematic coding to explore barriers and facilitators to contest engagement. Approximately 82% of entries were from young people in DC. A convenience sample of 181 people voted on their favorite crowdsourced PrEP messages and shared their awareness and attitudes about PrEP. The contest website received 2,500 unique visitors and 4,600 page views. Themes from semi-structured interviews (n = 16) included the need for more community engagement in developing PrEP messaging and positive attitudes towards crowdsourcing. Survey data (n = 887) showed that the crowdsourced messages were well-liked and resonated with the community. Most preferred to see PrEP messages in social media (23%), email (17%) and videos (14%). Approximately 70% of survey participants reported that after viewing the crowdsourced message they would talk to their sexual partner or medical provider (63%) about PrEP, use PrEP (58%), and learn more about PrEP (56%). Crowdsourced messages solicit substantial online viewership. More implementation research is needed to understand the public health impact of integrating social media, crowdsourcing, and community engagement to develop PrEP promotional messages.

How to (or how not to) implement crowdsourcing for the development of health interventions: lessons learned from four African countries

Crowdsourcing strategies are useful in the development of public health interventions. Crowdsourcing engages end users in a co-creation process through challenge contests, designathons or online collaborations. Drawing on our experience of crowdsourcing in four African countries, we provide guidance on designing crowdsourcing strategies across seven steps: deciding on the type of crowdsourcing strategy, convening a steering committee, developing the content of the call for ideas, promotion, evaluation, recognizing finalists and sharing back ideas or implementing the solutions.

"A National Review of Crowdfunding for Plagiocephaly Helmets"

OBJECTIVE

Custom prescription helmets for plagiocephaly may be a significant financial burden for families, especially when not covered by insurance. This study aims to identify factors that influence the success of crowdsourcing campaigns for this therapy.

DESIGN

GoFundMe campaigns were collected by searching terms such as "plagiocephaly" and "baby helmet." Two reviewers analyzed each campaign for variables, including demographic data, story elements, and photo characteristics. Univariate logistic regression was used to determine each variable's impact on success, defined as attaining ≥75% of a campaign goal and significance of p ≤ 0.05.

RESULTS

Campaign data from 2011 to 2022 were analyzed. Initial search yielded 1464 campaigns; among these 413 met final inclusion criteria. On average, campaigns raised $2005 (range: $0-$7799) and requested $3151 (range: $160-$30,000). In total, 228 (54%) achieved success, 167 (40%) met their goal, and 35 (8%) raised no funds. A total of $828,256 was raised from the requested $1,301,317. The average reported age was six months (range: 2-17 m). Significant factors associated with success were military affiliation, providing multiple images, including a quoted cost, providing campaign updates, indicating a sense of urgency, diagnosis of torticollis, and mentioning possible complications without treatment. Raising additional funds for therapy, multiple helmets, and unrelated medical costs negatively impacted success. Racial disparities were observed between campaigns. Additionally, regional differences were noted between campaigns.

CONCLUSIONS

Crowdsourcing can be a successful endeavor for some families experiencing financial hardships from helmet therapy. This study highlights current gaps within healthcare coverage for helmet treatment and identifies various factors influencing crowdfunding campaigns.

Health Information Seeking Using Tech and Non-Tech Sources Among a Diverse Sample of Caregivers in the Deep South

Caregivers of people living with dementia (PLWD) are often tasked with making decisions about their loved one's daily care and healthcare treatment, causing stress and decision-making fatigue. Many caregivers engage in health information seeking to improve their health literacy for optimal decision-making, though there is limited knowledge about the strategies used to increase their health literacy. This study involved a survey of caregivers in Alabama, most of whom were African American and/or living in rural communities that have historically underserved. The findings shed light on caregivers' experiences in seeking out health-related information and their perceptions of various sources of information.

Crowdsourcing with the drift diffusion model of decision making

Crowdsourcing involves the use of annotated labels with unknown reliability to estimate ground truth labels in datasets. A common task in crowdsourcing involves estimating reliabilities of annotators (such as through the sensitivities and specificities of annotators in the binary label setting). In the literature, beta or dirichlet distributions are typically imposed as priors on annotator reliability. In this study, we investigated the use of a neuroscientifically validated model of decision making, known as the drift-diffusion model, as a prior on the annotator labeling process. Two experiments were conducted on synthetically generated data with non-linear (sinusoidal) decision boundaries. Variational inference was used to predict ground truth labels and annotator related parameters. Our method performed similarly to a state-of-the-art technique (SVGPCR) in prediction of crowdsourced data labels and prediction through a crowdsourced-generated Gaussian process classifier. By relying on a neuroscientifically validated model of decision making to model annotator behavior, our technique opens the avenue of predicting neuroscientific biomarkers of annotators, expanding the scope of what may be learnt about annotators in crowdsourcing tasks.

Decision-making for congenital anomalies diagnosed during pregnancy: a narrative review

PURPOSE

The purpose of this narrative review was to assess the limited literature on fetal anomalies diagnosed in the second trimester of pregnancy and parental decision-making and identify sources of information deemed as facilitators and barriers to medical decisions.

METHODS

This was a literature review of source material and information about fetal anomalies diagnosed in the second trimester of pregnancy, decision-making, decision tools or aids, and sources of information for anomalies. The search string used explored related peer-reviewed publications and systematic reviews between 2007 and 2024. We also reviewed references from publications meeting inclusion criteria. The search was conducted between June 2022 and February 2024. Exclusion criteria included conference abstracts, non-peer reviewed literature, and articles not available in English language. A total of 77 publications were identified by searching multiple databases using a predefined search string. The search encompassed full text articles from 2007 to 2024 and 11 full-text publications were ultimately included in the review. A list of 45 co-occurring keywords was generated from the included texts, with each keyword having a minimum of two co-occurrences.

RESULTS

Key themes identified included (1) the role of the clinician and need for development of professional knowledge and empathy surrounding discussion of fetal anomalies with patients; (2) information gathering, with individuals reporting use of multiple strategies to obtain information; while the majority found information satisfying, they preferred more details on diagnosis, long-term outcomes of the fetus/child and management of the pregnancy or termination process; and (3) decision-making, the path and process of how individuals made decisions about the pregnancy including quality of life, future fertility, and seeking other people's experiences.

CONCLUSION

Many factors contribute to an individual's decision-making after a diagnosis of a fetal anomalies diagnosed in the second trimester of pregnancy, ranging from personal beliefs and goals to shared experiences of others and access to care. Understanding how sources of information may be deemed both as facilitators and barriers to different individuals during the decision-making process is important for healthcare providers in order to understand how to most effectively support patients. There is a dearth of information on training healthcare professionals to provide support to patients facing these decisions.

Cardiac screening in school children: Combining auscultation and electrocardiography with a crowdsourcing model

BACKGROUND/PURPOSE

School-based cardiac screening is useful for identifying children and adolescents with a high risk of sudden cardiac death. However, because of challenges associated with cost, distance, and human resources, cardiac screening is not widely implemented, especially in rural areas with limited medical resources. This study aims to establish a cloud-based system suitable for mass cardiac screening of schoolchildren in rural areas with limited medical resources.

METHODS

Students from three schools were included. They or their guardians completed a simple questionnaire, administered in paper or electronic form. Heart sounds were recorded using an electronic stethoscope. Twelve-lead electrocardiograms (ECGs) were recorded and digitalized. The signals were transmitted through Bluetooth to a tablet computer and then uploaded to a cloud server over Wi-Fi. Crowdsourced pediatric cardiologists reviewed those data from a web-based platform and provided remote consultation. In cases in which abnormal heart sounds or ECGs were noted, the students were referred to the hospital for further evaluation.

RESULTS

A total of 1004 students were enrolled in this study. Of the 138 students referred, 62 were diagnosed as having an abnormal heart condition and most had previously been undiagnosed. The interrater agreeability was high.

CONCLUSION

An innovative strategy combining a cloud-based cardiac screening system with remote consultation by crowdsourced experts was established. This system allows pediatric cardiologists to provide consultation and make reliable diagnoses. Combined with crowdsourcing, the system constitutes a viable approach for mass cardiac screening in children and adolescents living in rural areas with insufficient medical resources.

Insights on Juniperus phoenicea Essential Oil as Potential Anti-Proliferative, Anti-Tyrosinase, and Antioxidant Candidate

In this study, the anti-cancer, anti-tyrosinase, and antioxidant activities of essential oils (EOs) of berries and leaves of Juniperus phoenicea grown wild in North of Tunisia were investigated. The EO yields from leaves and berries were 1.69% and 0.45%, respectively. GC-MS analysis revealed that α-pinene is the predominant component in both EOs (44.17 and 83.56%, respectively). Leaves essential oil presented high levels of β-phellandrene (18%) and camphene (15%). The EOs displayed cytotoxic effects against MCF-7 breast cancer cell, HT-29 colon cancer, and the normal cells H9C2 cardiomyoblasts. Leaves oil strongly inhibited colon cell line proliferation (IC50 of 38 µg/mL), while berries essential oil was more potent against breast cancerous cells MCF-7 (IC50 of 60 µg/mL). Interestingly, berries essential oil exhibited high ability to inhibit melanin synthesis by inhibiting enzyme mono and diphenolase activities. Overall, the results suggested that the two oils are significant sources of healthy natural chemicals.

Feasibility assessment of crowdsourcing slogans for promoting household waste segregation in India: a cross-sectional study

Introduction

Crowdsourcing is an emerging technique to engage or access a wider set of experts and multiple stakeholders through online platforms, which might effectively be employed in waste management. Therefore, we assessed the feasibility of the crowdsourcing method to provide an alternative approach that can improve household waste segregation using an "online-slogan-contest".

Methods

The contest was promoted via targeted emails to various governmental and non-governmental organizations and through social media platforms for around 4 weeks (25 days). The entries were received through a Google form. The slogans were assessed by the experts and analyzed using content analysis methods.

Results

Total 969 entries were received from different geographic regions in India. Of that, 456 were in English and 513 in Hindi. Five themes of waste segregation emerged from the received slogans: (1) Community awareness, responsibility, and support, (2) Significance of household waste segregation, (3) Use of separate dustbins, (4) Health and well-being, and (5) Environment and sustainability.

Discussion

Crowdsourcing approaches can be used by local authorities for improving waste management approaches and are recommended as these involve a wider audience within a short time frame. Moreover, this approach is flexible and integrating crowdsourcing approaches strengthens our understanding of existing waste management activities.

Research on the doctors' win in crowdsourcing competitions: perspectives on service content and competitive environment

Medical crowdsourcing competitions can help patients get more efficient and comprehensive treatment advice than "one-to-one" service, and doctors should be encouraged to actively participate. In the crowdsourcing competitions, winning the crowdsourcing competition is the driving force for doctors to continue to participate in the service. Therefore, how to improve the winning probability needs to be revealed. From the service content and competitive environment perspectives, this study introduces doctor competence indicators to investigate the key influence factors of doctors' wins on the online platform. The results show that the emotional interaction in doctors' service content positively influences doctors' wins. However, the influence of information interaction presents heterogeneity. Conclusive information helps doctors win, while suggestive information negatively affects them. For the competitive environment, the competitive environment negatively moderates the relationship between doctors' service content and doctors' wins. The results of this study provide important contributions to the research on crowdsourcing competitions and online healthcare services and guide the participants of the competition, including patients, doctors, and platforms.

The case for citizen science in public health policy and practice: a mixed methods study of policymaker and practitioner perspectives and experiences

BACKGROUND

Citizen science (CS) is increasingly being utilised to involve the public in public health research, but little is known about whether and how CS can address the needs of policy and practice stakeholders in health promotion and chronic disease prevention.

METHODS

Using a mixed methods approach we conducted an online survey (n = 83) and semi-structured interviews (n = 21) with policy and practice stakeholders across Australia to explore how CS approaches are perceived and applied in chronic disease prevention, how CS aligns with existing approaches to community engagement, and how the uptake of CS can be supported within policy and practice settings.

RESULTS

Most participants had heard of CS, and while few had experience of using CS, there was widespread support for this approach, with many seeing it as complementary to other community engagement approaches. CS was seen as providing: (a) a robust framework for engagement; (b) access to rich data; (c) opportunities for more meaningful engagement; and (d) a mutually beneficial approach for stakeholders and community members. However, stakeholders identified a need to weigh benefits against potential risks and challenges including competing organisational priorities, resourcing and expertise, data quality and rigour, governance, and engagement.

CONCLUSIONS

To expand the use of CS, stakeholders identified the need for increased awareness, acceptance, and capacity for CS within public health organisations, greater access to supporting tools and technology, and evidence on processes, feasibility and impacts to enhance the visibility and legitimacy of CS approaches.

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

BACKGROUND

The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.

METHODS

In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.

RESULTS AND CONCLUSION

The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

Implementation and evaluation of crowdsourcing in global health education

BACKGROUND

Current global health course is most set as elective course taught in traditional teacher-taught model with low credit and short term. Innovate teaching models are required. Crowdsourcing characterized by high flexibility and strong application-orientation holds its potential to enhance global health education. We applied crowdsourcing to global health teaching for undergraduates, aiming to develop and evaluate a new teaching model for global health education.

METHODS

Crowdsourcing was implemented into traditional course-based teaching via introducing five COVID-19 related global health debates. Undergraduate students majoring in preventative medicine and nursing grouped in teams of 5-8, were asked to resolve these debates in reference to main content of the course and with manner they thought most effective to deliver the messages. Students' experience and teaching effect, were evaluated by questionnaires and teachers' ratings, respectively. McNemar's test was used to compare the difference in students' experience before and after the course, and regression models were used to explore the influencing factors of the teaching effect.

RESULTS

A total of 172 undergraduates were included, of which 122 (71%) were females. Students' evaluation of the new teaching model improved after the course, but were polarized. Students' self-reported teaching effect averaged 67.53 ± 16.8 and the teachers' rating score averaged 90.84 ± 4.9. Students majoring in preventive medicine, participated in student union, spent more time on revision, and had positive feedback on the new teaching model tended to perform better.

CONCLUSION

We innovatively implemented crowdsourcing into global health teaching, and found this new teaching model was positively received by undergraduate students with improved teaching effects. More studies are needed to optimize the implementation of crowdsourcing alike new methods into global health education, to enrich global health teaching models.

Lessons Learned from CDC's Global COVID-19 Early Warning and Response Surveillance System

Early warning and response surveillance (EWARS) systems were widely used during the early COVID-19 response. Evaluating the effectiveness of EWARS systems is critical to ensuring global health security. We describe the Centers for Disease Control and Prevention (CDC) global COVID-19 EWARS (CDC EWARS) system and the resources CDC used to gather, manage, and analyze publicly available data during the prepandemic period. We evaluated data quality and validity by measuring reporting completeness and compared these with data from Johns Hopkins University, the European Centre for Disease Prevention and Control, and indicator-based data from the World Health Organization. CDC EWARS was integral in guiding CDC's early COVID-19 response but was labor-intensive and became less informative as case-level data decreased and the pandemic evolved. However, CDC EWARS data were similar to those reported by other organizations, confirming the validity of each system and suggesting collaboration could improve EWARS systems during future pandemics.

Crowdsourcing Operational and Design Flaws of Diabetes Mobile Apps

Unfortunately, many of the diabetes mobile apps have operational and design flaws that are debarring users from maximizing from the self-management paradigm. We, therefore, aim to identify the markers of operational and design flaws of diabetes mobile apps to facilitate a better user-centred design. e crowdsourced negative user review comments (rating score: 1-3) of 47 diabetes mobile apps from the google play store. A total of 781 negative user comments (rating score 1-3) from the apps are coded to identify and categorize the themes relating to the operational and design flaws. The operational and design flaws account for 50.32% of the challenges faced by the unhappy diabetes mobile apps users. Among them, 44.73% have issues with app crashing, 17.3% are concerned about device compatibility that inhibits seamless operations, 9.67% are worried about the problem of data uploading. Poor design is a worry to 19.29% of the users who complain of the crowded user interface, poor data management, poor analytics, difficulty scheduling doctors' appointments, and transferring data. More patients with diabetes can be encouraged to continue using diabetes mobile apps for self-management of diabetes through improved design and a pace-wise software advancement to match the ever-growing enhancements in android operating systems and telecommunication devices. This will help to counter most of the challenges identified in this study.

On the use of the descriptive variable for enhancing the aggregation of crowdsourced labels

The use of crowdsourcing for annotating data has become a popular and cheap alternative to expert labelling. As a consequence, an aggregation task is required to combine the different labels provided and agree on a single one per example. Most aggregation techniques, including the simple and robust majority voting—to select the label with the largest number of votes—disregard the descriptive information provided by the explanatory variable. In this paper, we propose domain-aware voting, an extension of majority voting which incorporates the descriptive variable and the rest of the instances of the dataset for aggregating the label of every instance. The experimental results with simulated and real-world crowdsourced data suggest that domain-aware voting is a competitive alternative to majority voting, especially when a part of the dataset is unlabelled. We elaborate on practical criteria for the use of domain-aware voting.

Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?

BACKGROUND

Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest.

OBJECTIVE

This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster.

METHODS

This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking "How to faster end the COVID-19 pandemic?" and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes - personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users.

RESULTS

The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results.

CONCLUSIONS

Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance.

Incidence and prevalence of coma in the UK and the USA

The epidemiology of coma is unknown because case ascertainment with traditional methods is difficult. Here, we used crowdsourcing methodology to estimate the incidence and prevalence of coma in the UK and the USA. We recruited UK and US laypeople (aged ≥18 years) who were nationally representative (i.e. matched for age, gender and ethnicity according to census data) of the UK and the USA, respectively, utilizing a crowdsourcing platform. We provided a description of coma and asked survey participants if they-'right now' or 'within the last year'-had a family member in coma. These participants (UK n = 994, USA n = 977) provided data on 30 387 family members (UK n = 14 124, USA n = 16 263). We found more coma cases in the USA (n = 47) than in the UK (n = 20; P = 0.009). We identified one coma case in the UK (0.007%, 95% confidence interval 0.00-0.04%) on the day of the survey and 19 new coma cases (0.13%, 95% confidence interval 0.08-0.21%) within the preceding year, resulting in an annual incidence of 135/100 000 (95% confidence interval 81-210) and a point prevalence of 7 cases per 100 000 population (95% confidence interval 0.18-39.44) in the UK. We identified five cases in the USA (0.031%, 95% confidence interval 0.01-0.07%) on the day of the survey and 42 new cases (0.26%, 95% confidence interval 0.19-0.35%) within the preceding year, resulting in an annual incidence of 258/100 000 (95% confidence interval 186-349) and a point prevalence of 31 cases per 100 000 population (95% confidence interval 9.98-71.73) in the USA. The five most common causes were stroke, medically induced coma, COVID-19, traumatic brain injury and cardiac arrest. To summarize, for the first time, we report incidence and prevalence estimates for coma across diagnosis types and settings in the UK and the USA using crowdsourcing methods. Coma may be more prevalent in the USA than in the UK, which requires further investigation. These data are urgently needed to expand the public health perspective on coma and disorders of consciousness.

Crowdsourcing homemade facemasks: 772 U.S. health facilities' responses to personal protective equipment shortages in the first half of 2020

Purpose

We examined 772 U.S. health facilities' responses to Personal Protective Equipment (PPE) shortages in the first half of 2020, as they crowdsourced face coverings from volunteer makers to be used as respiratory protection during crisis surge capacity. The purpose was to examine facemask specification requests from health facilities and develop a framework for crowdsourcing last resort PPE.

Design/methodology/approach

Homemade facemask donation requests from health facilities in 47 states systematically recorded in a public database maintained by public health graduate students at a major U.S. university were analysed. Open coding was used to content analyse facemask types and specifications, intended uses, delivery logistics and donation management strategies.

Findings

Our analysis revealed information gaps: Science‐based information was scarce in 2020, leading to improvised specifications for facemask materials and designs. It also revealed the emergence of a crowdsourcing structure: Task specifications for volunteer facemasks makers, delivery logistics, and practical management of donations within the pandemic context. In anticipation of future pandemics and localised PPE shortages, we build on this empirical evidence to propose a framework for crowdsourcing science‐informed facemasks from volunteers. Categorised within (a) logistics and workflow management, (b) task specifications and management, and (c) practical management of contributions functional areas, the framework outlines the required tasks and specifications for crowdsourcing.

Originality

A novel empirically derived framework for crowdsourcing homemade facemasks is proposed, based on empirical analysis and crowdsourcing system design strategies. Our findings and the framework may be used for refining crisis capacity guidelines, as part of strategic planning and preparation for future pandemics that disrupt supply chains and cause shortages in protective equipment.

At least 772 health facilities in 47 U.S. states experienced Personal Protective Equipment (PPE) shortages in 2020.

During crisis surge capacity, they crowdsourced homemade masks from volunteers.

The database shows information gaps and an emerging crowdsourcing structure.

A crowdsourcing framework is essential for effective sourcing of homemade face coverings from volunteer makers during pandemics and surge capacity.

Understanding factors that promote uptake of HIV self-testing among young people in Nigeria: Framing youth narratives using the PEN-3 cultural model

It is important to understand how to frame the formats for promoting HIV self-testing to increase uptake among young people. In this study, we used a culture-centered model to understand the narratives of HIV self-testing preferences among young people in Nigeria. We conducted a crowdsourcing contest to solicit ideas surrounding HIV self-testing promotion among young people (10–24 years) in Nigeria from October to November 2018 as part of the 2018 World AIDS Day event. We received 903 submissions and employed thematic content analysis to evaluate 769 eligible youth narratives. Thematic content analysis of the statements from the youth narratives was guided by the PEN-3 cultural model to examine the positive, existential, and negative perceptions (beliefs and values), enablers (resources), and nurturers (roles of friends and family) of HIV self-testing promotion among young people in Nigeria. Several themes emerged as factors that influence the uptake of HIV self-testing among young people in Nigeria. Specifically, seven themes emerged as perceptions: HIV testing accessibility, stigma reduction, and autonomy (positive); HIV self-testing kit packaging and advertisements (existential); lack of knowledge and increased stigma (negative). Seven themes emerged as enablers: social media, school, and government promotion (positive); gamification and animation (existential); high cost and access to linkage to care services (negative); And seven themes emerged as nurturers: peer, families, and faith-based communities (positive); parents and family-centered approach (existential); and partners and family (negative). Our data suggests that increased awareness around HIV self-testing on current youth-friendly platforms, de-stigmatization of HIV and HIV self-testing, decreased prices for HIV self-testing kits, reliability of testing kits, increased linkage to care services, and promotion of self-testing among family members and the community will be beneficial for HIV self-testing scale-up measures among young people in Nigeria.

The feasibility of a crowd-based early developmental milestone tracking application

Objective

Parents’ tracking of developmental milestones can assist healthcare providers with early detection of developmental delays and appropriate referrals to early intervention. Crowdsourcing is one way to update the content and age data distribution of developmental checklists for parents and providers. This feasibility study examined which developmental milestones parents chose to track and what they added beyond traditional milestones, using the babyTRACKS crowd-based mobile app.

Method

We analyzed the developmental diaries of 3,832 children, registered in the babyTRACKS app at an average age of 9.3 months. Their parents recorded a median of 5 milestones per diary, selecting from the accumulating lists of age-appropriate milestones or authoring new milestones. The final database included 645 types of milestones; 89.15% were developmental, of which 43.6% were comparable to the Centers for Disease Control (CDC) milestones while the rest were crowd-authored. Milestones were categorized into developmental domains: Gross Motor, Fine Motor, Oral Motor, Self-Care, Cognitive, Language Comprehension, Speech, Non-Verbal Communication, Social, Emotional, and Regulation.

Results

On average, the milestone domains of Gross Motor, Fine Motor, Cognitive and Social were the most added to diaries (20%-30% of a diary). Within the Cognitive, Speech and Language Comprehension domains there were significantly more CDC comparable versus crowd-authored milestones (29% versus 21%, 22% versus 10%, 8% versus 4%). In contrast, within the Regulation and Oral Motor domains there were more crowd versus CDC milestones (17% versus 3%, 9% versus 3%). Crowd-authored Speech milestones were significantly older by 7 months than CDC milestones.

Conclusion

Tracking daily observations of child development provides a window into personally relevant milestones for the child and parent. The crowd of parents can independently track and add new milestones across main developmental domains. Regulation and Oral Motor development especially interest parents. Parents may be less aware of early progress in Language Comprehension and Speech; thus, these domains require more structured screening. Designing mobile early screening which is crowd-based engages parents as proactive partners in developmental tracking.

Identifying Barriers to Enrollment in Patient Pregnancy Registries: Building Evidence Through Crowdsourcing

Background

Enrollment in pregnancy registries is challenging despite substantial awareness-raising activities, generally resulting in low recruitment owing to limited safety data. Understanding patient and physician awareness of and attitudes toward pregnancy registries is needed to facilitate enrollment. Crowdsourcing, in which services, ideas, or content are obtained by soliciting contributions from a large group of people using web-based platforms, has shown promise for improving patient engagement and obtaining patient insights.

Objective

This study aimed to use web-based crowdsourcing platforms to evaluate Belimumab Pregnancy Registry (BPR) awareness among patients and physicians and to identify potential barriers to pregnancy registry enrollment with the BPR as a case study.

Methods

We conducted 2 surveys using separate web-based crowdsourcing platforms: Amazon Mechanical Turk (a 14-question patient survey) and Sermo RealTime (a 11-question rheumatologist survey). Eligible patients were women, aged 18-55 years; diagnosed with systemic lupus erythematosus (SLE); and pregnant, recently pregnant (within 2 years), or planning pregnancy. Eligible rheumatologists had prescribed belimumab and treated pregnant women. Responses were descriptively analyzed.

Results

Of 151 patient respondents over a 3-month period (n=88, 58.3% aged 26-35 years; n=149, 98.7% with mild or moderate SLE; and n=148, 98% from the United States), 51% (77/151) were currently or recently pregnant. Overall, 169 rheumatologists completed the survey within 48 hours, and 59.2% (100/169) were based in the United States. Belimumab exposure was reported by 41.7% (63/151) patients, whereas 51.7% (75/145) rheumatologists had prescribed belimumab to <5 patients, 25.5% (37/145) had prescribed to 5-10 patients, and 22.8% (33/145) had prescribed to >10 patients who were pregnant or trying to conceive. Of the patients exposed to belimumab, 51% (32/63) were BPR-aware, and 45.5% (77/169) of the rheumatologists were BPR-aware. Overall, 60% (38/63) of patients reported belimumab discontinuation because of pregnancy or planned pregnancy. Among the 77 BPR-aware rheumatologists, 70 (91%) referred patients to the registry. Concerns among rheumatologists who did not prescribe belimumab during pregnancy included unknown pregnancy safety profile (119/169, 70.4%), and 61.5% (104/169) reported their patients’ concerns about the unknown pregnancy safety profile. Belimumab exposure during or recently after pregnancy or while trying to conceive was reported in patients with mild (6/64, 9%), moderate (22/85, 26%), or severe (1/2, 50%) SLE. Rheumatologists more commonly recommended belimumab for moderate (84/169, 49.7%) and severe (123/169, 72.8%) SLE than for mild SLE (36/169, 21.3%) for patients trying to conceive recently or currently pregnant. Overall, 81.6% (138/169) of the rheumatologists suggested a belimumab washout period before pregnancy of 0-30 days (44/138, 31.9%), 30-60 days (64/138, 46.4%), or >60 days (30/138, 21.7%).

Conclusions

In this case, crowdsourcing efficiently obtained patient and rheumatologist input, with some patients with SLE continuing to use belimumab during or while planning a pregnancy. There was moderate awareness of the BPR among patients and physicians.

[Social media-Chances and risks for rheumatology]

Die Nutzung von sozialen Medien (Social Media) und sozialen Netzwerken (Social Networks) hat in den letzten Jahren stark zugenommen. Sie gewinnen als Informationskanäle sowohl im privaten als auch beruflichen Kontext immer mehr an Bedeutung. Auch in der Medizin werden Social Media bereits vielfältig eingesetzt. So sind Fachgesellschaften und Interessenverbände immer stärker in den sozialen Netzwerken vertreten. Durch die breite Nutzung und große Reichweite der Netzwerke ergeben sich neue Möglichkeiten auch für das Fach der Rheumatologie. Dieser Übersichtsartikel gibt einen Überblick über die Charakteristika einiger großer Social-Media-Plattformen und untersucht bisherige Publikationen aus diesem Themengebiet im Rahmen einer systematischen Analyse. Weiterhin werden Vorteile, aber auch potenzielle Risiken, die bei der Nutzung entstehen können, beschrieben.

A treatment recommender clinical decision support system for personalized medicine: method development and proof-of-concept for drug resistant tuberculosis

Background

Personalized medicine tailors care based on the patient’s or pathogen’s genotypic and phenotypic characteristics. An automated Clinical Decision Support System (CDSS) could help translate the genotypic and phenotypic characteristics into optimal treatment and thus facilitate implementation of individualized treatment by less experienced physicians.

Methods

We developed a hybrid knowledge- and data-driven treatment recommender CDSS. Stakeholders and experts first define the knowledge base by identifying and quantifying drug and regimen features for the prototype model input. In an iterative manner, feedback from experts is harvested to generate model training datasets, machine learning methods are applied to identify complex relations and patterns in the data, and model performance is assessed by estimating the precision at one, mean reciprocal rank and mean average precision. Once the model performance no longer iteratively increases, a validation dataset is used to assess model overfitting.

Results

We applied the novel methodology to develop a treatment recommender CDSS for individualized treatment of drug resistant tuberculosis as a proof of concept. Using input from stakeholders and three rounds of expert feedback on a dataset of 355 patients with 129 unique drug resistance profiles, the model had a 95% precision at 1 indicating that the highest ranked treatment regimen was considered appropriate by the experts in 95% of cases. Use of a validation data set however suggested substantial model overfitting, with a reduction in precision at 1 to 78%.

Conclusion

Our novel and flexible hybrid knowledge- and data-driven treatment recommender CDSS is a first step towards the automation of individualized treatment for personalized medicine. Further research should assess its value in fields other than drug resistant tuberculosis, develop solid statistical approaches to assess model performance, and evaluate their accuracy in real-life clinical settings.

Using crowdsourced medicine to manage uncertainty on Reddit: The case of COVID-19 long-haulers

OBJECTIVE

Causes of and treatments for long-COVID syndrome remain unknown. Drawing on uncertainty management theory (UMT), this study elucidates the communicative nature of crowdsourced medicine as a means by which COVID "long-haulers" respond to their poorly understood illness.

METHODS

31,892 posts on the long-haulers subreddit (r/covidlonghaulers) were analyzed, starting with its creation date, July 24th, 2020, until January 7, 2021. The Meaning Extraction Method was used to identify clusters of words that mathematically group together across the text observations.

RESULTS

Analyses yielded 16 distinct factors of words, which we thematized based on their composition, the data, and UMT. The 16 themes encompassed symptoms (e.g., pain, respiratory, sensory), diagnostic concerns (testing, diagnosis), broad health concerns (immunity, physical activity, diet), chronicity, support, identity, and anxiety.

CONCLUSION

Findings provide a succinct, yet robust set of themes reflecting the information-seeking (i.e., "This is happening to me") and support-seeking functions of long-haulers' talk (i.e., "Is this happening to you?"). Findings have implications for collective uncertainty management, online crowdsourcing, and patient advocacy.

PRACTICE IMPLICATIONS

We recommend that health care providers employ sensitivity when addressing the anxiety that long-haulers are experiencing while also validating that their physical symptoms are real. Online communities help long-haulers manage their uncertainty.

Branded Foods Databases as a Tool to Support Nutrition Research and Monitoring of the Food Supply: Insights From the Slovenian Composition and Labeling Information System

Branded foods databases are becoming very valuable not only in nutrition research but also for clinical practice, policymakers, businesses, and general population. In contrast to generic foods, branded foods are marked by rapid changes in the food supply because of reformulations, the introduction of new foods, and the removal of existing ones from the market. Also, different branded foods are available in different countries. This not only complicates the compilation of branded foods datasets but also causes such datasets to become out of date quickly. In this review, we present different approaches to the compilation of branded foods datasets, describe the history and progress of building and updating such datasets in Slovenia, and present data to support nutrition research and monitoring of the food supply. Manufacturers are key sources of information for the compilation of branded foods databases, most commonly through food labels. In Slovenia, the branded food dataset is compiled using standard food monitoring studies conducted at all major retailers. Cross-sectional studies are conducted every few years, in which the food labels of all available branded foods are photographed. Studies are conducted using the Composition and Labeling Information System (CLAS) infrastructure, composed of a smartphone application for data collection and online data extraction and management tool. We reviewed various uses of branded foods datasets. Datasets can be used to assess the nutritional composition of food in the food supply (i.e., salt, sugar content), the use of specific ingredients, for example, food additives, for nutrient profiling, and assessment of marketing techniques on food labels. Such datasets are also valuable for other studies, for example, assessing nutrient intakes in dietary surveys. Additional approaches are also being tested to keep datasets updated between food monitoring studies. A promising approach is the exploitation of crowdsourcing through the mobile application VešKajJeš, which was launched in Slovenia to support consumers in making healthier dietary choices.

NextGen Public Health Surveillance and the Internet of Things (IoT)

Recent advances in technology have led to the rise of new-age data sources (e.g., Internet of Things (IoT), wearables, social media, and mobile health). IoT is becoming ubiquitous, and data generation is accelerating globally. Other health research domains have used IoT as a data source, but its potential has not been thoroughly explored and utilized systematically in public health surveillance. This article summarizes the existing literature on the use of IoT as a data source for surveillance. It presents the shortcomings of current data sources and how NextGen data sources, including the large-scale applications of IoT, can meet the needs of surveillance. The opportunities and challenges of using these modern data sources in public health surveillance are also explored. These IoT data ecosystems are being generated with minimal effort by the device users and benefit from high granularity, objectivity, and validity. Advances in computing are now bringing IoT-based surveillance into the realm of possibility. The potential advantages of IoT data include high-frequency, high volume, zero effort data collection methods, with a potential to have syndromic surveillance. In contrast, the critical challenges to mainstream this data source within surveillance systems are the huge volume and variety of data, fusing data from multiple devices to produce a unified result, and the lack of multidisciplinary professionals to understand the domain and analyze the domain data accordingly.

Joint international consensus statement on crowdsourcing challenge contests in health and medicine: results of a modified Delphi process

OBJECTIVES

To develop a consensus statement to provide advice on designing, implementing and evaluating crowdsourcing challenge contests in public health and medical contexts.

DESIGN

Modified Delphi using three rounds of survey questionnaires and one consensus workshop.

SETTING

Uganda for face-to-face consensus activities, global for online survey questionnaires.

PARTICIPANTS

A multidisciplinary expert panel was convened at a consensus-development conference in Uganda and included 21 researchers with experience leading challenge contests, five public health sector workers, and nine Ugandan end users. An online survey was sent to 140 corresponding authors of previously published articles that had used crowdsourcing methods.

RESULTS

A subgroup of expert panel members developed the initial statement and survey. We received responses from 120 (85.7%) survey participants, which were presented at an in-person workshop of all 21 panel members. Panelists discussed each of the sections, revised the statement, and participated in a second round of the survey questionnaire. Based on this second survey round, we held detailed discussions of each subsection with workshop participants and further revised the consensus statement. We then conducted the third round of the questionnaire among the 21 expert panelists and used the results to finalize the statement. This iterative process resulted in 23 final statement items, all with greater than 80% consensus. Statement items are organised into the seven stages of a challenge contest, including the following: considering the appropriateness, organising a community steering committee, promoting the contest, assessing contributions, recognising contributors, sharing ideas and evaluating the contest (COPARSE).

CONCLUSIONS

There is high agreement among crowdsourcing experts and stakeholders on the design and implementation of crowdsourcing challenge contests. The COPARSE consensus statement can be used to organise crowdsourcing challenge contests, improve the rigour and reproducibility of crowdsourcing research and enable large-scale collaboration.

Entrepreneurial treatment activism for undone science: mannitol and Parkinson's disease

This paper describes CliniCrowd, a patient-designed, entrepreneurial, crowd-sourced citizen-science approach to evaluating mannitol-essentially, an orphan drug-as a Parkinson's disease treatment. As such, CliniCrowd addresses 'undone science', and our paper contributes to the sociological literature thereon. Based on 38 qualitative interviews, fieldwork, and content analyses (2017-2020), we trace CliniCrowd's background and rationale. We: discuss undone science and its wider contexts; present earlier iterations of citizen-science and treatment activism; examine CliniCrowd's application of crowd-sourced citizen-science to address undone science around 'orphan drug' treatment for Parkinson's disease; explore how CliniCrowd has evolved, and re-framed its work, since its founding; ponder its future; and consider whether their approach can guide future citizen-science treatment research. Our paper contributes to the existing literature in four ways. First, we focus on medical treatment issues, an under-studied area of undone science. Second, we highlight orphan drugs as both major source of, and fruitful area for research on, undone science. Third, we describe CliniCrowd's pragmatic, entrepreneurial-rather than the more common activist-citizen-science approach to addressing undone treatment science. Finally, from our data on CliniCrowd we distil a preliminary model for future treatment activism around undone science.

Video-Based Coaching: Current Status and Role in Surgical Practice (Part 1) From the Society for Surgery of the Alimentary Tract, Health Care Quality and Outcomes Committee

Patient safety and outcomes are directly related to surgical performance. Surgical training emphasizes the importance of the surgeon in determining these outcomes. After training is complete, there is a lack of structured programs for surgeons to audit their skills and continue their individual development. There is a significant linear relationship between surgeon technical skill and surgical outcomes; however, measuring technical performance is difficult. Video-based coaching matches an individual surgeon in practice with a surgical colleague who has been trained in the core principles of coaching for individualizing instruction. It can provide objective assessment for teaching higher-level concepts, such as technical skills, cognitive skills, and decision-making. There are many benefits to video-based coaching. While the concept is gaining acceptance as a method of surgical education, it is still novel in clinical practice. As more surgeons look towards video-based coaching for quality improvement, a consistent definition of the program, goals, and metrics for assessment will be critical. This paper is a review on the status of the video-based coaching as it applies to practicing surgeons.

Social Media in Radiology: Overview and Usefulness of Online Professional #SoMe Profiles

Social media is a ubiquitous part of society and used by many healthcare professionals, including radiologists. This article prepared by the 2019-2020 Radiology Research Alliance Social Media Task Force presents different uses and benefits of an online professional social media profile. Physician and healthcare-specific issues along with popular platforms such as LinkedIn, Facebook, Twitter, Instagram, and YouTube are used to explore topics including education, branding, research, mentorship, promotion, and leadership.

How can crowdsourcing help tackle the COVID‐19 pandemic? An explorative overview of innovative collaborative practices

The COVID‐19 pandemic has caused unprecedented public health and economic crises. As a response to face the current emergency, science and innovation communities are realizing a fundamental contribution to tackle the crisis. During the past few months, we have witnessed an impressive number of initiatives to encourage networking opportunities, to foster interactions between the different stakeholders involved (health care, industry, governments, academics, ordinary people), and to develop innovative solutions and collaborative infrastructures in support of the health sector. Adopting an open and collaborative approach and joining forces is essential in the fight against the COVID‐19 crisis. Also, the involvement of crowds as innovation partners can be of great support. Therefore, our work aims to review and classify those initiatives, based on the crowdsourcing model, that have been put into place to face the emergency generated by the novel coronavirus pandemic. We illustrate the 16 crowdsourcing initiatives devoted to the SARS‐CoV‐2 outbreak that we identified, detailing their development and implementation. Then, we propose a classification of them, along two dimensions: type of crowdsourcing configuration and kind of tasks, being able to find a relationship between these two aspects. Evidence from the analyzed projects suggests that across disparate domains, crowdsourcing can be an effective strategy in the response to the COVID‐19 pandemic. To conclude, we suggest some important implications for innovation best practices and lessons that can be learned for the future: crowdsourcing, harnessing the power of crowds and online communities, can help tackle the COVID‐19 pandemic, by providing original, actionable, quick, and low‐cost solutions to the challenges of the current health and economic crisis.

Recruiting older adult participants through crowdsourcing platforms: Mechanical Turk versus Prolific Academic

BACKGROUND

Recruiting older adults (OA) into research is challenging.

OBJECTIVE

To assess the feasibility of using two crowdsourcing platforms, Amazon's Mechanical Turk (MTurk) and Prolific Academic (ProA), as efficient and low-cost venues for recruiting survey participants aged 65 and older.

METHODS

We developed an online survey to investigate and compare the demographics, technology use, and motivations for research participation of OA on MTurk and ProA. Qualitative responses, response time, word count, and recruitment costs were analyzed.

RESULTS

We recruited 97 OA survey participants on both MTurk and ProA. Participants were similar in terms ofdemographics, technology usage, and motivations for participation (topic interest and payment).

CONCLUSION

Both crowdsourcing platforms are useful for rapid and low-cost recruitment of OA. The OA recruitment process was more efficient with ProA. Crowdsourcing platforms are potential sources of OA research participants; however, the pool is limited to generally healthy, technologically active, and well-educated older adults.

Crowdsourcing snake identification with online communities of professional herpetologists and avocational snake enthusiasts

Species identification can be challenging for biologists, healthcare practitioners and members of the general public. Snakes are no exception, and the potential medical consequences of venomous snake misidentification can be significant. Here, we collected data on identification of 100 snake species by building a week-long online citizen science challenge which attracted more than 1000 participants from around the world. We show that a large community including both professional herpetologists and skilled avocational snake enthusiasts with the potential to quickly (less than 2 min) and accurately (69-90%; see text) identify snakes is active online around the clock, but that only a small fraction of community members are proficient at identifying snakes to the species level, even when provided with the snake's geographical origin. Nevertheless, participants showed great enthusiasm and engagement, and our study provides evidence that innovative citizen science/crowdsourcing approaches can play significant roles in training and building capacity. Although identification by an expert familiar with the local snake fauna will always be the gold standard, we suggest that healthcare workers, clinicians, epidemiologists and other parties interested in snakebite could become more connected to these communities, and that professional herpetologists and skilled avocational snake enthusiasts could organize ways to help connect medical professionals to crowdsourcing platforms. Involving skilled avocational snake enthusiasts in decision making could build the capacity of healthcare workers to identify snakes more quickly, specifically and accurately, and ultimately improve snakebite treatment data and outcomes.

Crowdsourcing and open innovation in drug discovery: recent contributions and future directions

The past decade has seen significant growth in the use of 'crowdsourcing' and open innovation approaches to engage 'citizen scientists' to perform novel scientific research. Here, we quantify and summarize the current state of adoption of open innovation by major pharmaceutical companies. We also highlight recent crowdsourcing and open innovation research contributions to the field of drug discovery, and interesting future directions.

Digital crowdsourced intervention to promote HIV testing among MSM in China: study protocol for a cluster randomized controlled trial

BACKGROUND

Men who have sex with men (MSM) are an important HIV key population in China. However, HIV testing rates among MSM remain suboptimal. Digital crowdsourced media interventions may be a useful tool to reach this marginalized population. We define digital crowdsourced media as using social media, mobile phone applications, Internet, or other digital approaches to disseminate messages developed from crowdsourcing contests. The proposed cluster randomized controlled trial (RCT) study aims to assess the effectiveness of a digital crowdsourced intervention to increase HIV testing uptake and decrease risky sexual behaviors among Chinese MSM.

METHODS

A two-arm, cluster-randomized controlled trial will be implemented in eleven cities (ten clusters) in Shandong Province, China. Targeted study participants will be 250 MSM per arm and 50 participants per cluster. MSM who are 18 years old or above, live in the study city, have not been tested for HIV in the past 3 months, are not living with HIV or have never been tested for HIV, and are willing to provide informed consent will be enrolled. Participants will be recruited through banner advertisements on Blued, the largest gay dating app in China, and in-person at community-based organizations (CBOs). The intervention includes a series of crowdsourced intervention materials (24 images and four short videos about HIV testing and safe sexual behaviors) and HIV self-test services provided by the study team. The intervention was developed through a series of participatory crowdsourcing contests before this study. The self-test kits will be sent to the participants in the intervention group at the 2nd and 3rd follow-ups. Participants will be followed up quarterly during the 12-month period. The primary outcome will be self-reported HIV testing uptake at 12 months. Secondary outcomes will include changes in condomless sex, self-test efficacy, social network engagement, HIV testing social norms, and testing stigma.

DISCUSSION

Innovative approaches to HIV testing among marginalized population are urgently needed. Through this cluster randomized controlled trial, we will evaluate the effectiveness of a digital crowdsourced intervention, improving HIV testing uptake among MSM and providing a resource in related public health fields.

TRIAL REGISTRATION

ChiCTR1900024350 . Registered on 6 July 2019.

Crowdsourcing to identify social innovation initiatives in health in low- and middle-income countries

BACKGROUND

Crowdsourcing is a distributed problem-solving and production mechanism that leverages the collective intelligence of non-expert individuals and networked communities for specific goals. Social innovation (SI) initiatives aim to address health challenges in a sustainable manner, with a potential to strengthen health systems. They are developed by actors from different backgrounds and disciplines. This paper describes the application of crowdsourcing as a research method to explore SI initiatives in health.

METHODS

The study explored crowdsourcing as a method to identify SI initiatives implemented in Africa, Asia and Latin America. While crowdsourcing has been used in high-income country settings, there is limited knowledge on its use, benefits and challenges in low- and middle-income country (LMIC) settings. From 2014 to 2018, six crowdsourcing contests were conducted at global, regional and national levels.

RESULTS

A total of 305 eligible projects were identified; of these 38 SI initiatives in health were identified. We describe the process used to perform a crowdsourcing contest for SI, the outcome of the contests, and the challenges and opportunities when using this mechanism in LMICs.

CONCLUSIONS

We demonstrate that crowdsourcing is a participatory method, that is able to identify bottom-up or grassroots SI initiatives developed by non-traditional actors.

Benefits of crowdsourcing for libraries: A case study from Africa

Many libraries in the Global South do not collect comprehensive data about themselves, which creates challenges in terms of local and international visibility. Crowdsourcing is an effective tool that engages the public to collect missing data, and it has proven to be particularly valuable in countries where governments collect little public data. Whereas crowdsourcing is often used within fields that have high levels of development funding, such as health, the authors believe that this approach would have many benefits for the library field as well. They present qualitative and quantitative evidence from 23 African countries involved in a crowdsourcing project to map libraries. The authors find benefits in terms of increased connections between stakeholders, capacity-building, and increased local visibility. These findings demonstrate the potential of crowdsourced approaches for tasks such as mapping to benefit libraries and similarly positioned institutions in the Global South in multifaceted ways.

Research data management in health and biomedical citizen science: practices and prospects

Background

Public engagement in health and biomedical research is being influenced by the paradigm of citizen science. However, conventional health and biomedical research relies on sophisticated research data management tools and methods. Considering these, what contribution can citizen science make in this field of research? How can it follow research protocols and produce reliable results?

Objective

The aim of this article is to analyze research data management practices in existing biomedical citizen science studies, so as to provide insights for members of the public and of the research community considering this approach to research.

Methods

A scoping review was conducted on this topic to determine data management characteristics of health and bio medical citizen science research. From this review and related web searching, we chose five online platforms and a specific research project associated with each, to understand their research data management approaches and enablers.

Results

Health and biomedical citizen science platforms and projects are diverse in terms of types of work with data and data management activities that in themselves may have scientific merit. However, consistent approaches in the use of research data management models or practices seem lacking, or at least are not prevalent in the review.

Conclusions

There is potential for important data collection and analysis activities to be opaque or irreproducible in health and biomedical citizen science initiatives without the implementation of a research data management model that is transparent and accessible to team members and to external audiences. This situation might be improved with participatory development of standards that can be applied to diverse projects and platforms, across the research data life cycle.

Emerging Wireless Sensor Networks and Internet of Things Technologies-Foundations of Smart Healthcare

Future smart healthcare systems - often referred to as Internet of Medical Things (IoMT) - will combine a plethora of wireless devices and applications that use wireless communication technologies to enable the exchange of healthcare data. Smart healthcare requires sufficient bandwidth, reliable and secure communication links, energy-efficient operations, and Quality of Service (QoS) support. The integration of Internet of Things (IoT) solutions into healthcare systems can significantly increase intelligence, flexibility, and interoperability. This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications. A particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems. Major challenges in privacy and security are also discussed. A particular attention is devoted to crowdsourcing/crowdsensing, envisaged as tools for the rapid collection of massive quantities of medical data. Finally, open research challenges and future perspectives of IoMT are presented.

The 4 youth by youth HIV self-testing crowdsourcing contest: A qualitative evaluation

INTRODUCTION

Crowdsourcing, a participatory approach to solicit ideas from a large group of diverse individuals, provides an opportunity to nurture youth participation in HIV self-testing service design. The objective of this study was to describe the responses to a crowdsourcing contest aimed at soliciting ideas on how to promote HIV self-testing (HIVST) among young people in Nigeria.

METHODS

The "4 Youth by Youth" HIV Self-Testing Crowdsourcing contest was an online and off-line contest that asked Nigerian youth (10-24 years old) for ideas in response to the following: How might we promote HIVST among young people in Nigeria? All data were collected and analyzed between October 2018, and June 2019. Ideas and perceptions generated from the crowdsourcing contest were qualitatively analyzed using thematic content analysis. Specifically, four reviewers analyzed whether the ideas generated were desirable (appealing to young people), feasible (easy to implement) and impactful (will significantly influence HIVST uptake among young people).

RESULTS

A total of 903 entries were received in response to the contest prompt. Participants submitted entries in various forms: online form (39.7%), offline Dropbox (44.6%), email (6.1%) and WhatsApp (9.7%). Of the total entries, 85% (n = 769/903) entries were eligible and were scored as having either high, moderate or low level of feasibility, impact and desirability, on a 3-point Likert scale. A significant portion of the entries were given a score of 3 for feasibility (4.9%), desirability (7.1%), impact (3.0%) or a total overall score of 7 or more (8.2%). The three main themes that emerged from the entries include:1) Peer-to-peer distribution and leveraging on existing infrastructures 2) Youth-Oriented Branding of the HIVST Kit 3) Mobile platforms and social media technology.

CONCLUSION

The "4 Youth by Youth" Self-Testing contest engaged a broad audience of young people to generate ideas and perspectives on how to promote HIVST. This process informed the development of youth innovated implementation strategies to increase uptake of HIVST among adolescents and youth at risk for HIV.

Engineering Approaches for Addressing Opioid Use Disorder in the Community

Many communities in the United States are struggling to deal with the negative consequences of illicit opioid use. Effectively addressing this epidemic requires the coordination and support of community stakeholders in a change process with common goals and objectives, continuous engagement with individuals with opioid use disorder (OUD) through their treatment and recovery journeys, application of systems engineering principles to drive process change and sustain it, and use of a formal evaluation process to support a learning community that continuously adapts. This review presents strategies to improve OUD treatment and recovery with a focus on engineering approaches grounded in systems thinking.

Federal calorie labelling compliance at US chain restaurants

OBJECTIVE

The 2010 Affordable Care Act included a provision requiring chain food establishments to post calories on menus. In 2017, prior to the final implementation of the law, 59 of 90 top-selling chains had fully implemented labelling. This study extends the documentation of compliance to the 200 top-selling chains after the nationwide requirement went into effect in May 2018.

METHODS

To determine if restaurants were compliant with the federal menu labelling law, objective information was collected from all 197 of the 200 highest grossing restaurant chains in the United States. The study team obtained information via site visits and internet searches for a convenience sample of restaurants within each of these chains.

RESULTS

94% had implemented menu calorie labelling after the May 2018 deadline. Of the 11 chains not complying, six were full-service restaurants.

CONCLUSION

Most chain restaurants have complied with the federal calorie labelling law, suggesting that compliance is attainable for all chains. Given this finding, the Food and Drug Administration should initiate enforcement of labelling for noncompliant chains.

Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis

AIM

To compare the effectiveness of two well described machine learning modalities, ocular coherence tomography (OCT) and fundal photography, in terms of diagnostic accuracy in the screening and diagnosis of glaucoma.

METHODS

A systematic search of Embase and PubMed databases was undertaken up to 1^st of February 2019. Articles were identified alongside their reference lists and relevant studies were aggregated. A Meta-analysis of diagnostic accuracy in terms of area under the receiver operating curve (AUROC) was performed. For the studies which did not report an AUROC, reported sensitivity and specificity values were combined to create a summary ROC curve which was included in the Meta-analysis.

RESULTS

A total of 23 studies were deemed suitable for inclusion in the Meta-analysis. This included 10 papers from the OCT cohort and 13 from the fundal photos cohort. Random effects Meta-analysis gave a pooled AUROC of 0.957 (95%CI=0.917 to 0.997) for fundal photos and 0.923 (95%CI=0.889 to 0.957) for the OCT cohort. The slightly higher accuracy of fundal photos methods is likely attributable to the much larger database of images used to train the models (59 788 vs 1743).

CONCLUSION

No demonstrable difference is shown between the diagnostic accuracy of the two modalities. The ease of access and lower cost associated with fundal photo acquisition make that the more appealing option in terms of screening on a global scale, however further studies need to be undertaken, owing largely to the poor study quality associated with the fundal photography cohort.