BACKGROUND: Complementary and alternative (CAM) cancer treatment is often expensive and not covered by insurance. As a result, many people turn to crowdfunding to access this treatment.
OBJECTIVE: The aim of this study is to identify the rationales of patients with cancer seeking CAM treatment abroad by looking specifically at crowdfunding campaigns to support CAM cancer treatment in Tijuana, Mexico.
METHODS: We scraped the GoFundMe.com and GiveSendGo.com crowdfunding platforms for campaigns referencing CAM cancer clinics in Tijuana, initiated between January 1, 2022, and February 28, 2023. The authors created a coding framework to identify rationales for seeking CAM treatment in Tijuana. To supplement campaign metadata, we coded the beneficiary\'s cancer stage, type, age, specific treatment sought, whether the beneficiary died, gender, and race.
RESULTS: Patients sought CAM cancer treatment in Tijuana because the (1) treatment offers the greatest efficacy (29.9%); (2) treatment offered domestically was not curative (23.2%); (3) the clinic treats the whole person, and addresses the spiritual dimension of the person (20.1%); (4) treatments are nontoxic, natural, or less invasive (18.2%); and (5) clinic offers the newest technology (8.5%). Campaigns raised US $5,275,268.37 and most campaign beneficiaries were women (69.7%) or White individuals (71.1%).
CONCLUSIONS: These campaigns spread problematic misinformation about the likely efficacy of CAM treatments, funnel money and endorsements to CAM clinics in Tijuana, and leave many campaigners short of the money needed to pay for CAM treatments while costing beneficiaries and their loved one\'s time, privacy, and dignity. This study affirms that Tijuana, Mexico, is a very popular destination for CAM cancer treatment.

暂无摘要。

Patients may use crowdfunding to solicit donations, typically from multiple small donors using internet-based means, to offset the financial toxicity of cancer care.
To describe crowdfunding campaigns by gynecologic cancer patients and to compare campaign characteristics and needs expressed between patients with cervical, uterine, and ovarian cancer.
We queried the public crowdfunding forum GoFundMe.com for \"cervical cancer,\" \"uterine cancer,\" and \"ovarian cancer.\" The first 200 consecutive posts for each cancer type fundraising within the United States were analyzed. Data on campaign goals and needs expressed were manually extracted. Descriptive statistics and bivariate analyses were performed.
Among the 600 fundraising pages, the median campaign goal was $10,000 [IQR $5000-$23,000]. Campaigns raised a median of 28.6% of their goal with only 8.7% of campaigns reaching their goal after a median of 54 days online. On average, ovarian cancer campaigns had higher monetary goals, more donors, and larger donation amounts than cervical cancer campaigns and raised more money than both cervical and uterine cancer campaigns. Campaigns were fundraising to support medical costs (80-85%) followed by lost wages (36-56%) or living expenses (27-41%). Cervical cancer campaigns reported need for non-medical costs more frequently than uterine or ovarian cancer campaigns. States without Medicaid expansions (31% of the national population) were over-represented among cervical cancer and uterine cancer, but not ovarian cancer campaigns.
Crowdfunding pages reveal patients fundraising for out-of-pocket costs in the thousands of dollars and a wide range of unmet financial needs based on cancer type.

In recent years, there has been growing concern about prejudice in crowdfunding; however, empirical research remains limited, particularly in the context of medical crowdfunding. This study addresses the pressing issue of racial disparities in medical crowdfunding, with a specific focus on cancer crowdfunding on the GoFundMe platform.
This study aims to investigate racial disparities in cancer crowdfunding using average donation amount, number of donations, and success of the fundraising campaign as outcomes.
Drawing from a substantial data set of 104,809 campaigns in the United States, we used DeepFace facial recognition technology to determine racial identities and used regression models to examine racial factors in crowdfunding performance. We also examined the moderating effect of the proportion of White residents on crowdfunding bias and used 2-tailed t tests to measure the influence of racial anonymity on crowdfunding success. Owing to the large sample size, we set the cutoff for significance at P<.001.
In the regression and supplementary analyses, the racial identity of the fundraiser significantly predicted average donations (P<.001), indicating that implicit bias may play a role in donor behavior. Gender (P=.04) and campaign description length (P=.62) did not significantly predict the average donation amounts. The race of the fundraiser was not significantly associated with the number of donations (P=.42). The success rate of cancer crowdfunding campaigns, although generally low (11.77%), showed a significant association with the race of the fundraiser (P<.001). After controlling for the covariates of the fundraiser gender, fundraiser age, local White proportion, length of campaign description, and fundraising goal, the average donation amount to White individuals was 17.68% higher than for Black individuals. Moreover, campaigns that did not disclose racial information demonstrated a marginally higher average donation amount (3.92%) than those identified as persons of color. Furthermore, the racial composition of the fundraiser\'s county of residence was found to exert influence (P<.001); counties with a higher proportion of White residents exhibited reduced racial disparities in crowdfunding outcomes.
This study contributes to a deeper understanding of racial disparities in cancer crowdfunding. It highlights the impact of racial identity, geographic context, and the potential for implicit bias in donor behavior. As web-based platforms evolve, addressing racial inequality and promoting fairness in health care financing remain critical goals. Insights from this research suggest strategies such as maintaining racial anonymity and ensuring that campaigns provide strong evidence of deservingness. Moreover, broader societal changes are necessary to eliminate the financial distress that drives individuals to seek crowdfunding support.

BACKGROUND: Due to rising health care costs, patients have sought alternative ways of addressing medical expenses. In particular, transplant patients have complex and expensive medical needs-including skin cancer surveillance-that may not be fully covered by insurance. One such method of financing medical costs is by crowdsourcing through web-based platforms, most notably GoFundMe.
OBJECTIVE: Previous work identified factors associated with GoFundMe campaigns\' fundraising success for dermatologic diseases. We sought to characterize these factors in transplant recipients\' campaigns for funds raised for covering skin cancer-related costs. These factors include demographics, campaign traits, and subjective themes.
METHODS: From January to April 2022, we analyzed GoFundMe campaigns using the following search terms chosen on the basis of author consensus: \"transplant skin cancer,\" \"transplant basal cell,\" \"transplant squamous,\" \"transplant melanoma,\" and \"dermatologist transplant.\" Demographic data were coded from campaign text or subjectively coded based on author consensus. Campaigns were read completely by 2 independent coders and associated with up to 3 different themes. Linear regression was performed to examine the qualities associated with success, which was defined as funds raised when controlling for campaign goals. Logistic regression was used to examine qualities associated with extremely successful campaigns, defined as those raising funds over 1.5 times the IQR.
RESULTS: Across 82 campaigns, we identified several factors that were associated with fundraiser success. Patients who experienced complications during infectious disease treatment, those who received a pancreas transplant, or those who died from their disease raised significantly more money. Patients older than 61 years raised significantly less money. Extremely successful campaigns (>US $20,177) were associated with campaigners who emphasized a disability from their disease, those who were reluctant to ask for help, or those who died due to their disease.
CONCLUSIONS: Demographic and thematic factors are associated with transplant patients\' skin cancer-related fundraising success, favoring those who are younger, in more extreme situations, and appear reluctant to ask for help; these findings are consistent with those of previous studies. Additionally, transplant patients have complex and expensive dermatologic needs that may not be fully covered by insurance, as reflected in their GoFundMe campaigns. The most commonly mentioned reasons for fundraising included living expenses or loss of income, inadequate or no insurance, and end-of-life costs. Our findings may inform transplant patients how to maximize the success of their campaigns and highlight gaps in health care coverage for skin cancer-related costs. Limitations include the possibility for misclassification due to the data abstraction process and limiting data collection to fundraisers available on GoFundMe while excluding those on other websites. Further research should investigate the ethical implications of crowdfunding, financial needs of this patient population, and potential ways to improve access to routine skin cancer surveillance among patients receiving transplants.

BACKGROUND: Crowdfunding for medical costs is becoming increasingly popular. Few previous studies have described the fundraising characteristics and qualities associated with success.
OBJECTIVE: This study aimed to characterize and investigate the qualities associated with successful dermatological fundraisers.
METHODS: This cross-sectional study of dermatological GoFundMe campaigns collected data, including demographic variables, thematic variables using an inductive qualitative method, and quantitative information. Linear regression examined the qualities associated with success, which are defined based on funds raised when controlling for campaign goals. Logistic regression was used to examine qualities associated with extremely successful campaigns, defined as those raising >1.5 times the IQR. Statistical significance was set at P<.05.
RESULTS: A total of 2008 publicly available campaigns at the time of data collection were evaluated. Nonmodifiable factors associated with greater success included male gender, age 20-40 years, and White race. Modifiable factors associated with success included more updates posted to the campaign page, non-self-identity of the campaign creator, mention of a chronic condition, and smiling in campaign profile photographs.
CONCLUSIONS: Understanding the modifiable factors of medical crowdfunding may inform future campaigns, and nonmodifiable factors may have policy implications for improving health care equity and financing. Crowdfunding for medical disease treatment may have potential implications for medical privacy and exacerbation of existing health care disparities. This study was limited to publicly available GoFundMe campaigns. Potential limitations for this study include intercoder variability, misclassification bias because of the data abstraction process, and prioritization of campaigns based on the proprietary GoFundMe algorithm.

Recent studies have analyzed the factors that contribute to variations in the success of crowdfunding campaigns for a specific cancer type; however, little is known about the influential factors among crowdfunding campaigns for multiple cancers.
The purpose of this study was to examine the relationship between project features and the success of cancer crowdfunding campaigns and to determine whether text features affect campaign success for various cancers.
Using cancer-related crowdfunding projects on the GoFundMe website, we transformed textual descriptions from the campaigns into structured data using natural language processing techniques. Next, we used penalized logistic regression and correlation analyses to examine the influence of project and text features on fundraising project outcomes. Finally, we examined the influence of campaign description sentiment on crowdfunding success using Linguistic Inquiry and Word Count software.
Campaigns were significantly more likely to be successful if they featured a lower target amount (Goal amount, β=-1.949, z score=-82.767, P<.001) for fundraising, a higher number of previous donations, agency (vs individual) organizers, project pages containing updates, and project pages containing comments from readers. The results revealed an inverted U-shaped relationship between the length of the text and the amount of funds raised. In addition, more spelling mistakes negatively affected the funds raised (Number of spelling errors, β=-1.068, z score=-38.79, P<.001).
Difficult-to-treat cancers and high-mortality cancers tend to trigger empathy from potential donors, which increases the funds raised. Gender differences were observed in the effects of emotional words in the text on the amount of funds raised. For cancers that typically occur in women, links between emotional words used and the amount of funds raised were weaker than for cancers typically occurring among men.

Crowdfunding is increasingly used to offset the financial burdens of illness and health care. In the era of the COVID-19 pandemic and associated infodemic, the role of crowdfunding to support controversial COVID-19 stances is unknown.
We sought to examine COVID-19-related crowdfunding focusing on the funding of alternative treatments not endorsed by major medical entities, including campaigns with an explicit antivaccine, antimask, or antihealth care stances.
We performed a cross-sectional analysis of GoFundMe campaigns for individuals requesting donations for COVID-19 relief. Campaigns were identified by key word and manual review to categorize campaigns into \"Traditional treatments,\" \"Alternative treatments,\" \"Business-related,\" \"Mandate,\" \"First Response,\" and \"General.\" For each campaign, we extracted basic narrative, engagement, and financial variables. Among those that were manually reviewed, the additional variables of \"mandate type,\" \"mandate stance,\" and presence of COVID-19 misinformation within the campaign narrative were also included. COVID-19 misinformation was defined as \"false or misleading statements,\" where cited evidence could be provided to refute the claim. Descriptive statistics were used to characterize the study cohort.
A total of 30,368 campaigns met the criteria for final analysis. After manual review, we identified 53 campaigns (0.17%) seeking funding for alternative medical treatment for COVID-19, including popularized treatments such as ivermectin (n=14, 26%), hydroxychloroquine (n=6, 11%), and vitamin D (n=4, 7.5%). Moreover, 23 (43%) of the 53 campaigns seeking support for alternative treatments contained COVID-19 misinformation. There were 80 campaigns that opposed mandating masks or vaccination, 48 (60%) of which contained COVID-19 misinformation. Alternative treatment campaigns had a lower median amount raised (US $1135) compared to traditional (US $2828) treatments (P<.001) and a lower median percentile of target achieved (11.9% vs 31.1%; P=.003). Campaigns for alternative treatments raised substantially lower amounts (US $115,000 vs US $52,715,000, respectively) and lower proportions of fundraising goals (2.1% vs 12.5%) for alternative versus conventional campaigns. The median goal for campaigns was significantly higher (US $25,000 vs US $10,000) for campaigns opposing mask or vaccine mandates relative to those in support of upholding mandates (P=.04). Campaigns seeking funding to lift mandates on health care workers reached US $622 (0.15%) out of a US $410,000 goal.
A small minority of web-based crowdfunding campaigns for COVID-19 were directed at unproven COVID-19 treatments and support for campaigns aimed against masking or vaccine mandates. Approximately half (71/133, 53%) of these campaigns contained verifiably false or misleading information and had limited fundraising success.
RR2-10.1001/jamainternmed.2019.3330.

Web-based crowdfunding has become a popular method to raise money for medical expenses, and there is growing research interest in this topic. However, crowdfunding data are largely composed of unstructured text, thereby posing many challenges for researchers hoping to answer questions about specific medical conditions. Previous studies have used methods that either failed to address major challenges or were poorly scalable to large sample sizes. To enable further research on this emerging funding mechanism in health care, better methods are needed.
We sought to validate an algorithm for identifying 11 disease categories in web-based medical crowdfunding campaigns. We hypothesized that a disease identification algorithm combining a named entity recognition (NER) model and word search approach could identify disease categories with high precision and accuracy. Such an algorithm would facilitate further research using these data.
Web scraping was used to collect data on medical crowdfunding campaigns from GoFundMe (GoFundMe Inc). Using pretrained NER and entity resolution models from Spark NLP for Healthcare in combination with targeted keyword searches, we constructed an algorithm to identify conditions in the campaign descriptions, translate conditions to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes, and predict the presence or absence of 11 disease categories in the campaigns. The classification performance of the algorithm was evaluated against 400 manually labeled campaigns.
We collected data on 89,645 crowdfunding campaigns through web scraping. The interrater reliability for detecting the presence of broad disease categories in the campaign descriptions was high (Cohen κ: range 0.69-0.96). The NER and entity resolution models identified 6594 unique (276,020 total) ICD-10-CM codes among all of the crowdfunding campaigns in our sample. Through our word search, we identified 3261 additional campaigns for which a medical condition was not otherwise detected with the NER model. When averaged across all disease categories and weighted by the number of campaigns that mentioned each disease category, the algorithm demonstrated an overall precision of 0.83 (range 0.48-0.97), a recall of 0.77 (range 0.42-0.98), an F1 score of 0.78 (range 0.56-0.96), and an accuracy of 95% (range 90%-98%).
A disease identification algorithm combining pretrained natural language processing models and ICD-10-CM code-based disease categorization was able to detect 11 disease categories in medical crowdfunding campaigns with high precision and accuracy.

Cancer patients incur high care costs; however, there is a paucity of literature characterizing unmet financial obligations for patients with urologic cancers. Kidney cancer patients are particularly burdened by costs associated with novel systemic treatments. This study aimed to ascertain the characteristics of GoFundMe® crowdfunding campaigns for patients with kidney cancer, in order to better understand the financial needs of this population.
We performed a cross-sectional, quantitative, and qualitative analysis of all kidney cancer GoFundMe® campaigns since 2010. Fundraising metrics such as goal funds and amount raised, were extracted. Eight independent investigators collected patient, disease and campaign-level variables from campaign stories (κ = 0.72). In addition, we performed a content analysis of campaign narratives spotlighting the primary appeal of the patient\'s life story.
A total of 486 GoFundMe® kidney cancer campaigns were reviewed. The median goal funds were 10,000USD [IQR = 5000, 20,000] and the median amount raised was 1450USD [IQR = 578, 4050]. Most campaigns were for adult males (53%) and 62% of adults had children. A minority were for pediatric patients (17%). Thirty-seven percent of adult patients were primary wage earners and 43% reported losing their job or substantially reducing hours due to illness. Twenty-nine percent reported no insurance or insufficient coverage. Campaigns most frequently sought funds for medical bills (60%), nonmedical bills (27%), and medical travel (23%). Qualitative campaign narratives mostly emphasized patients\' hardship (46.3%) or high moral character (35.2%). Only 8% of campaigns achieved their target funds.
Despite fundraising efforts, patients with kidney cancer face persistent financial barriers, incurring both medical and nonmedical cost burdens. This may be compounded by limited or no insurance. Cancer care providers should be aware of financial constraints placed on kidney cancer patients, and consider how these may impact treatment regimens.