Racial and gender disparities among highly successful medical crowdfunding campaigns

There has been growing recognition of the popularity of medical crowdfunding and research documenting how crowdfunding arises from, and contributes to, social and health inequities. While many researchers have surmised that racism could well play a role in medical crowdfunding campaign outcomes, research on these dynamics has been limited. No research to date has examined these dynamics among the most successful medical crowdfunding campaigns, focusing instead on average users' experiences or specific patient subpopulations. This paper analyzes key characteristics and demographics of the 827 most successful medical crowdfunding campaigns captured at a point in time in 2020 on the popular site GoFundMe, creating the first demographic archetype of "viral" or highly successful campaigns. We hypothesized that this sample would skew towards whiter, younger populations, more heavily represent men, and reflect critical illnesses and accidents affecting these populations, in addition to having visually appealing, well-crafted storytelling. Analysis supported these hypotheses, showing significant levels of racial and gender disparities among campaigners. While white men had the greatest representation, Black and Asian users, and black women in particular, were highly underrepresented. Like other studies, we find evidence that racial and gender disparities persist in terms of campaign outcomes as well. Alongside this quantitative analysis, a targeted discourse analysis revealed campaign narratives and comments reinforced racist and sexist tropes of selective deservingness. These findings add to growing calls for more health research into the ways that social media technologies shape health inequities for historically marginalized and disenfranchised populations. In particular, we underscore how successful crowdfunding campaigns, as a both a means of raising funds for health and a broader site of public engagement, may deepen and normalize gendered and racialized inequities. In this way, crowdfunding can be seen as a significant technological amplifier of the fundamental social causes of health disparities.

Medical Crowdfunding and Disparities in Health Care Access in the United States, 2016‒2020

Objectives. To assess whether medical crowdfunding use and outcomes are aligned with health financing needs in the United States. Methods. We collected data on 437 596 US medical GoFundMe campaigns between 2016 and 2020. In addition to summarizing trends in campaign initiation and earnings, we used state- and county-level data to assess whether crowdfunding usage and earnings were higher in areas with greater medical debt, uninsured populations, and poverty. Results. Campaigns raised more than $2 billion from 21.7 million donations between 2016 and 2020. Returns were highly unequal, and success was low, especially in 2020: only 12% of campaigns met their goals, and 16% received no donations at all. Campaigns in 2020 raised substantially less money in areas with more medical debt, higher uninsurance rates, and lower incomes. Conclusions. Despite its popularity and portrayals as an ad-hoc safety net, medical crowdfunding is misaligned with key indicators of health financing needs in the United States. It is best positioned to help in populations that need it the least. (Am J Public Health. 2022;112(3):491-498. https://doi.org/10.2105/AJPH.2021.306617).

Crowdsourced Tick Image-Informed Updates to U.S. County Records of Three Medically Important Tick Species

Burgeoning cases of tick-borne disease present a significant public health problem in the United States. Passive tick surveillance gained traction as an effective way to collect epidemiologic data, and in particular, photograph-based tick surveillance can complement in-hand tick specimen identification to amass distribution data and related encounter demographics. We compared the Federal Information Processing Standards (FIPS) code of tick photos submitted to a free public identification service (TickSpotters) from 2014 to 2019 to published nationwide county reports for three tick species of medical concern: Ixodes scapularis Say (Ixodida: Ixodidae), Ixodes pacificus Cooley and Kohls (Ixodida: Ixodidae), and Amblyomma americanum Linneaus (Ixodida: Ixodidae). We tallied the number of TickSpotters submissions for each tick species according to "Reported" or "Established" criteria per county, and found that TickSpotters submissions represented more than half of the reported counties of documented occurrence, and potentially identified hundreds of new counties with the occurrence of these species. We detected the largest number of new county reports of I. scapularis presence in Michigan, North Carolina, and Texas. Tick image submissions revealed potentially nine new counties of occurrence for I. pacificus, and we documented the largest increase in new county reports of A. americanum in Kentucky, Illinois, Indiana, and Ohio. These findings demonstrate the utility of crowdsourced photograph-based tick surveillance as a complement to other tick surveillance strategies in documenting tick distributions on a nationwide scale, its potential for identifying new foci, and its ability to highlight at-risk localities that might benefit from tick-bite prevention education.

Association Between Crowdsourced Health Care Facility Ratings and Mortality in US Counties

IMPORTANCE

Mortality across US counties varies considerably, from 252 to 1847 deaths per 100 000 people in 2018. Although patient satisfaction with health care is associated with patient- and facility-level health outcomes, the association between health care satisfaction and community-level health outcomes is not known.

OBJECTIVE

To examine the association between online ratings of health care facilities and mortality across US counties and to identify language specific to 1-star (lowest rating) and 5-star (highest rating) reviews in counties with high vs low mortality.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective population-based cross-sectional study examined reviews and ratings of 95 120 essential health care facilities across 1301 US counties. Counties that had at least 1 essential health care facility with reviews available on Yelp, an online review platform, were included. Essential health care was defined according to the 10 essential health benefits covered by Affordable Care Act insurance plans.

MAIN OUTCOMES AND MEASURES

The mean rating of essential health care facilities was calculated by county from January 1, 2015, to December 31, 2019. Ratings were on a scale of 1 to 5 stars, with 1 being the worst rating and 5 the best. County-level composite measures of health behaviors, clinical care, social and economic factors, and physical environment were obtained from the University of Wisconsin School of Medicine and Public Health County Health Rankings database. The 2018 age-adjusted mortality by county was obtained from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiological Research database. Multiple linear regression analysis was used to estimate the association between mean facility rating and mortality, adjusting for county health ranking variables. Words with frequencies of use that were significantly different across 1-star and 5-star reviews in counties with high vs low mortality were identified.

RESULTS

The 95 120 facilities meeting inclusion criteria were distributed across 1301 of 3142 US counties (41.4%). At the county level, a 1-point increase in mean rating was associated with a mean (SE) age-adjusted decrease of 18.05 (3.68) deaths per 100 000 people (P < .001). Words specific to 1-star reviews in high-mortality counties included told, rude, and wait, and words specific to 5-star reviews in low-mortality counties included Dr, pain, and professional.

CONCLUSIONS AND RELEVANCE

This study found that, at the county level, higher online ratings of essential health care facilities were associated with lower mortality. Equivalent online ratings did not necessarily reflect equivalent experiences of care across counties with different mortality levels, as evidenced by variations in the frequency of use of key words in reviews. These findings suggest that online ratings and reviews may provide insight into unequal experiences of essential health care.

The people vs science: can passively crowdsourced internet data shed light on host-parasite interactions?

Every internet search query made out of curiosity by anyone who observed something in nature, as well as every photo uploaded to the internet, constitutes a data point of potential use to scientists. Researchers have now begun to exploit the vast online data accumulated through passive crowdsourcing for studies in ecology and epidemiology. Here, we demonstrate the usefulness of iParasitology, i.e. the use of internet data for tests of parasitological hypotheses, using hairworms (phylum Nematomorpha) as examples. These large worms are easily noticeable by people in general, and thus likely to generate interest on the internet. First, we show that internet search queries (collated with Google Trends) and photos uploaded to the internet (specifically, to the iNaturalist platform) point to parts of North America with many sightings of hairworms by the public, but few to no records in the scientific literature. Second, we demonstrate that internet searches predict seasonal peaks in hairworm abundance that accurately match scientific data. Finally, photos uploaded to the internet by non-scientists can provide reliable data on the host taxa that hairworms most frequently parasitize, and also identify hosts that appear to have been neglected by scientific studies. Our findings suggest that for any parasite group likely to be noticeable by non-scientists, information accumulating through internet search activity, photo uploads, social media or any other format available online, represents a valuable source of data that can complement traditional scientific data sources in parasitology.

The disproportion of crowd wisdom: The impact of status seeking on Yelp reviews

This study shows that while status seeking motivates people to participate in crowdsourcing platforms, it also negatively impacts the bedrock of crowdsourcing-wisdom of crowds. Using Yelp restaurant reviews in 6 cities, we found that motivations of status seeking lead people to review a greater variety of restaurants, and achieving status further encourages this variety seeking as well as the targeting of more expensive restaurants for review. The impact of this individual-level tendency is confirmed by our aggregate-level analysis which shows that restaurants with higher price levels, higher uniqueness levels, and a larger percentage of elite reviews tend to obtain enough reviews to generate wisdom of crowds sooner than other restaurants. This leads to a different kind of distortion to crowd wisdom: an over-representation of status-conferring products and an under-representation of products that are not status-worthy. The findings suggest the importance of studying sources of distortion that are endemic to crowdsourcing itself.

Crowdsourcing to measure financial toxicity in gynecologic oncology

OBJECTIVE

To utilize a novel crowdsourcing method to measure financial toxicity and its effects among a national cohort of gynecologic cancer patients.

METHODS

Crowdsourcing methods were used to administer an online survey to women in the United States with gynecologic cancers. We used the Comprehensive Score for Financial Toxicity (COST) tool to measure financial toxicity and the EQ-5D-3L to measure quality of life (QOL). Based on prior work, we defined high financial toxicity as a COST score ≤ 23. We assessed correlation of COST scores with QOL. We used log-binomial regression to examine associations between high financial toxicity and cost-coping strategies.

RESULTS

Among the final study sample of 334 respondents, 87% were white, median age at diagnosis was 55 (interquartile range 47-63), 52% had stage III or IV disease and 90% had private insurance or Medicare. Median COST score was 24 (interquartile range 15-32) and 49% of respondents reported high financial toxicity. Greater financial toxicity was correlated with worse QOL (p < 0.001). Participants reporting high financial toxicity were more likely to use cost-coping strategies, including spending less on basic goods (RR: 3.3; 95% CI: 2.1-5.1), borrowing money or applying for financial assistance (RR: 4.0; 95% CI: 2.4-6.9), and delaying or avoiding care (RR: 5.6; 95% CI: 2.6-12.1).

CONCLUSIONS

Crowdsourcing is an effective tool to measure financial toxicity. Nearly half of respondents reported high financial toxicity, which was significantly associated with worse QOL, utilization of cost-coping strategies and delays or avoidance of care.

Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study

Background

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

Methods

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

Findings

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35-60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

Interpretation

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

Funding

Fogarty International Center, US National Institutes of Health.

Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study

BACKGROUND

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

METHODS

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

FINDINGS

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35-60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

INTERPRETATION

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

FUNDING

Fogarty International Center, US National Institutes of Health.

Estimating the global distribution of field size using crowdsourcing

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.

Medical Crowdfunding for Patients Undergoing Orthopedic Surgery

Crowdfunding for medical expenses is growing in popularity. Through several websites, patients create public campaign profiles to which donors can contribute. Research on medical crowdfunding is limited, and there have been no studies of crowdfunding in orthopedics. Active medical crowdfunding campaigns for orthopedic trauma, total joint arthroplasty, and spine surgery were queried from a crowdfunding website. The characteristics and outcomes of crowdfunding campaigns were abstracted and analyzed. For this study, 444 campaigns were analyzed, raising a total of $1,443,528. Among the campaigns that received a donation, mean amount raised was $4414 (SE, $611). Multivariate analysis showed that campaigns with unspecified location (odds ratio, 0.26; P=.0008 vs West) and those for total joint arthroplasty (odds ratio, 0.35; P=.0003 vs trauma) had significantly lower odds of receipt of any donation. Description length was associated with higher odds of donation receipt (odds ratio, 1.13 per +100 characters; P<.0001). Among campaigns that received any donation, those with Southern location (-65.5%, P<.0001), international location (-68.5%, P=.0028), and unspecified location (-63.5%, P=.0039) raised lower amounts compared with campaigns in the West. Goal amount was associated with higher amount raised (+3.2% per +$1000, P<.0001). Resources obtained through crowdfunding may be disproportionately available to patients with specific diagnoses, those from specific regions, those who are able to craft a lengthy descriptive narrative, and those with access to robust digital social networks. Clinicians are likely to see a greater proportion of patients turning to crowdfunding as it grows in popularity. Patients may ask physicians for information about crowdfunding or request testimonials to support campaigns. Surgeons should consider their response to such requests individually. These findings shed light on the dynamics of medical crowdfunding and support robust personal and professional deliberation. [Orthopedics. 2018; 41(1):e58-e63.].

Utility of social media and crowd-sourced data for pharmacovigilance: a scoping review protocol

INTRODUCTION

Adverse events associated with medications are under-reported in postmarketing surveillance systems. A systematic review of published data from 37 studies worldwide (including Canada) found the median under-reporting rate of adverse events to be 94% in spontaneous reporting systems. This scoping review aims to assess the utility of social media and crowd-sourced data to detect and monitor adverse events related to health products including pharmaceuticals, medical devices, biologics and natural health products.

METHODS AND ANALYSIS

Our review conduct will follow the Joanna Briggs Institute scoping review methods manual. Literature searches were conducted in MEDLINE, EMBASE and the Cochrane Library from inception to 13 May 2016. Additional sources included searches of study registries, conference abstracts, dissertations, as well as websites of international regulatory authorities (eg, Food and Drug Administration (FDA), the WHO, European Medicines Agency). Search results will be supplemented by scanning the references of relevant reviews. We will include all publication types including published articles, editorials, websites and book sections that describe use of social media and crowd-sourced data for surveillance of adverse events associated with health products. Two reviewers will perform study selection and data abstraction independently, and discrepancies will be resolved through discussion. Data analysis will involve quantitative (eg, frequencies) and qualitative (eg, content analysis) methods.

DISSEMINATION

The summary of results will be sent to Health Canada, who commissioned the review, and other relevant policymakers involved with the Drug Safety and Effectiveness Network. We will compile and circulate a 1-page policy brief and host a 1-day stakeholder meeting to discuss the implications, key messages and finalise the knowledge translation strategy. Findings from this review will ultimately inform the design and development of a data analytics platform for social media and crowd-sourced data for pharmacovigilance in Canada and internationally.

REGISTRATION DETAILS

Our protocol was registered prospectively with the Open Science Framework (https://osf.io/kv9hu/).

Crowdsourcing the Measurement of Interstate Conflict

Much of the data used to measure conflict is extracted from news reports. This is typically accomplished using either expert coders to quantify the relevant information or machine coders to automatically extract data from documents. Although expert coding is costly, it produces quality data. Machine coding is fast and inexpensive, but the data are noisy. To diminish the severity of this tradeoff, we introduce a method for analyzing news documents that uses crowdsourcing, supplemented with computational approaches. The new method is tested on documents about Militarized Interstate Disputes, and its accuracy ranges between about 68 and 76 percent. This is shown to be a considerable improvement over automated coding, and to cost less and be much faster than expert coding.

HowNutsAreTheDutch (HoeGekIsNL): A crowdsourcing study of mental symptoms and strengths

HowNutsAreTheDutch (Dutch: HoeGekIsNL) is a national crowdsourcing study designed to investigate multiple continuous mental health dimensions in a sample from the general population (n = 12,503). Its main objective is to create an empirically based representation of mental strengths and vulnerabilities, accounting for (i) dimensionality and heterogeneity, (ii) interactivity between symptoms and strengths, and (iii) intra-individual variability. To do so, HowNutsAreTheDutch (HND) makes use of an internet platform that allows participants to (a) compare themselves to other participants via cross-sectional questionnaires and (b) to monitor themselves three times a day for 30 days with an intensive longitudinal diary study via their smartphone. These data enable for personalized feedback to participants, a study of profiles of mental strengths and weaknesses, and zooming into the fine-grained level of dynamic relationships between variables over time. Measuring both psychiatric symptomatology and mental strengths and resources enables for an investigation of their interactions, which may underlie the wide variety of observed mental states in the population. The present paper describes the applied methods and technology, and presents the sample characteristics. Copyright © 2015 John Wiley & Sons, Ltd.

New tools for emergency managers: an assessment of obstacles to use and implementation

This paper focuses on the role of the formal response community's use of social media and crowdsourcing for emergency managers (EMs) in disaster planning, response and recovery in the United States. In-depth qualitative interviews with EMs on the Eastern seaboard at the local, state and federal level demonstrate that emergency management tools are in a state of transition--from formal, internally regulated tools for crisis response to an incorporation of new social media and crowdsourcing tools. The first set of findings provides insight into why many EMs are not using social media, and describes their concerns that result in fear, uncertainty and doubt. Second, this research demonstrates how internal functioning and staffing issues within these agencies present challenges. This research seeks to examine the dynamics of this transition and offer lessons for how to improve its outcomes--critical to millions of people across the United States.

Crowdsourcing and mining crowd data

The following sections are included: Introduction, Session articles, Acknowledgements and References.

Reputation-based collaborative network biology

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

Crowdsourcing RNA structural alignments with an online computer game

The annotation and classification of ncRNAs is essential to decipher molecular mechanisms of gene regulation in normal and disease states. A database such as Rfam maintains alignments, consensus secondary structures, and corresponding annotations for RNA families. Its primary purpose is the automated, accurate annotation of non-coding RNAs in genomic sequences. However, the alignment of RNAs is computationally challenging, and the data stored in this database are often subject to improvements. Here, we design and evaluate Ribo, a human-computing game that aims to improve the accuracy of RNA alignments already stored in Rfam. We demonstrate the potential of our techniques and discuss the feasibility of large scale collaborative annotation and classification of RNA families.

Using patient-reported experiences for pharmacovigilance?

Recent international guidelines encourage more prominent placement of patient-generated information about medications on the pharmacovigilance information landscape. Online platforms where patients share medication experiences with one another and with healthcare professionals are one possible avenue to accomplishing this goal. Public reports of medication-related events posted on the web, however, are under-utilized in the pharmacovigilance community. Moreover, little is known about who writes such reviews, what information is shared and how this information can be used by authorities. This paper reports the first results of a study of user and comment characteristics on a European-based platform.