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.
Crowdsourcing medical expenses is an increasingly popular method of financing health care costs . In particular, GoFundMe is the most popular crowdfunding website worldwide in terms of funds raised. As of 2021, one-third of the funds raised by GoFundMe (approximately US $650 million) are for medical campaigns [ ]. In the United States, a staggering 62% of bankruptcies are related to medical costs [ ]. The high financial burden of medical expenditures has contributed to the rise of popular crowdfunding sites such as GoFundMe [ ]. Fundraising campaigns on GoFundMe are broadly advertised via social media outlets such as Facebook or Twitter, and potential donors are encouraged to share campaigns to increase visibility. By January 2020, 22% of American adults reported contributing to a GoFundMe campaign at least once, and 3% had created their own campaigns [ ]. However, only approximately 10% of campaigns are successful in meeting their target goals [ ]. With increased competition, campaigners are tasked with creating engaging and compelling appeals [ ].
Limited research has considered the factors that influence the success of crowdfunding campaigns. Previous studies have suggested that demographic characteristics such as age and race, medical history, and proposed fund use are associated with fundraising outcomes, raising concerns about health care inequity and privacy [- ]. Crowdfunding may be partly conceptualized as a marketing endeavor that requires creation of a campaign that will be seen as deserving to attract donations, especially if a medical condition is associated with any stigma. For instance, patients with lung cancer had more successful fundraising if they mentioned that they had never smoked, and patients with hepatitis C had more successful fundraising if they specified a source of infection that was ostensibly not intravenous drug use (blood transfusion, organ donation, and occupational exposures) [ , ]. Descriptive campaigns appear to raise more money, especially when patients provide a breakdown of specific medical and nonmedical expenditures; however, this may come at the expense of patient privacy [ - ]. We sought to analyze the specific themes most commonly associated with fundraising success when mentioned in campaign narratives. Previous studies have also suggested that racial minorities and older individuals are at a fundraising disadvantage [ , ]. Thus, in evaluating GoFundMe campaigns, we wished to evaluate any possible biases against marginalized groups, namely any gender-associated or race-associated biases.
Dermatological conditions may generally be viewed by the public with a low level of urgency . However, 1 in 3 Americans may experience skin disease, and the direct costs associated with skin disease in 2013 were US $75 billion, with indirect costs (eg, loss of labor force) totaling US $11 billion [ , ]. We aim to characterize the fundraising campaigns on GoFundMe for dermatological conditions. Further, we sought to identify the qualitative themes and demographic variables associated with campaign success.
This study was deemed exempt by the institutional review board of the University of Virginia.
This study was deemed exempt by the institutional review board of the University of Virginia. We analyzed publicly available GoFundMe campaigns sorted by the platform algorithm from March 20, 2021, to May 31, 2021, until the completion of available qualifying campaigns using dermatology-specific search terms (dermatology, skin, cutaneous, dermatologist, rash, skin disease, skin infection, skin biopsy, finger and toenail infection, Mohs, scalp, alopecia, epidermal, dermal, birthmark, and skin cancer) chosen by author consensus. Exclusion criteria included campaigns outside the United States, recently activated GoFundMe campaigns (active <1 day), or if the primary reason for fundraising was not considered dermatologic. Demographic data pertaining to the beneficiary were either objectively mentioned or subjectively coded from the campaign text and images. Campaigns were classified under diagnostic categories based on the condition described and the intention for seeking treatment (eg, repair for cosmetic reasons vs functionality). Qualitative themes were coded using an inductive qualitative method until thematic saturation was reached, meaning that themes were continuously added as they appeared in the data until no novel themes emerged . Each campaign was read completely by 2 independent coders and was associated with a maximum of 3 different themes.
The cleaned data were exported to RStudio (version 4.0.2). The frequencies of themes were calculated based on the percentage of times a theme was mentioned. Mann-Whitney U tests were performed for univariate analysis. Regression analyses were performed by comparing the number of shares and updates with the amount raised, controlling for race, age, gender, and campaign goal. A total of 2 separate models were used because of concerns regarding collinearity. Multivariable linear regression was performed to investigate the amount raised against the demographic and thematic variables. The Interquartile Method of Outlier Detection was applied to the amount raised and goal of the campaign. On the basis of this outlier detection method, campaigns raising >US $17,345 were excluded from the regression analysis. A binary logistic regression was run to compare demographic variables and themes in fundraisers that raised >US $17,345 with those that raised below this amount to investigate qualities associated with extreme success in fundraising. Extreme success was defined as an amount >1.5 times the IQR (>US $17,345). The significance threshold was set at P<.05.
Demographic Variables and Campaign Summary
A total of 2008 fundraisers were analyzed. Most campaign recipients were White (1570/2008, 78.19%). There were more women (1109/2008, 55.23%) than men (896/2008, 44.62%). The campaigns raised a total of US $15,886,807 (mean US $7911.76, SD US $18,330.94, median US $3182) and had a total goal of US $45,860,361 (mean US $23,045.41, SD US $55,814.35, median US $10,000). A few campaigns met their goals at the time of the analysis (316/2008, 15.74%;).
|Gender, n (%)|
|Age (years), n (%)|
|Relationship status, n (%)|
|In a relationship||735 (36.6)|
|Race, n (%)|
|African American||216 (10.76)|
|Insurance status, n (%)|
|Top 5 most common themes for fundraising, n (%)|
|Inadequacy of current insurance||1050 (52.29)|
|Medical condition limiting earning potential||601 (29.93)|
|Need to travel for care||448 (22.31)|
|Basic living expenses (utilities and food)||326 (16.23)|
|No insurance||213 (10.61)|
|Top 10 most common diagnoses, n (%)|
|Nonmelanoma skin cancer||232 (11.55)|
|Road rash||117 (5.83)|
|Systemic lupus erythematosus||64 (3.19)|
|Systemic scleroderma||61 (3.04)|
|Lyme disease||56 (2.79)|
|Category of diagnosis, n (%)|
|Relationship to creator of campaign, n (%)|
|Family member||877 (43.68)|
|Mention of religion, n (%)|
|Amount raised (US $)|
|Mean (SD)||7911.76 (18,330.94)|
|Goal of campaign (US $)|
|Mean (SD)||23,045.41 (55,814.35)|
|Number of updates|
|Mean (SD)||4.24 (10.14)|
|Number of donors|
|Mean (SD)||89.96 (280.09)|
|Number of shares|
|Mean (SD)||529.34 (1035.47)|
The mean number of shares on social media was nearly 6 times the mean number of donations. Men had higher median shares (279, IQR 60.75-694.25) than women (201, IQR 18-492; W=424,586; P<.001) and more median donors (45, IQR 18-112) than women (35, IQR 12-69; W=414,304; P<.001). After adjusting for age, race, gender, and goal of the campaign, every additional share was associated with an additional US $6 raised for the recipient (P<.001) and each additional campaign profile update was associated with an additional US $262 raised (P<.001;).
With respect to demographic characteristics, Black recipients earned a mean of US $1146 less than White recipients (P<.001). Those in the age group of 41 to 60 years earned a mean of US $762 less than those in the 21 to 40 age group (P=.02). Men earned a mean of US $389 more than women did (P=.02). Those who mentioned the following themes received more donation money: medical conditions limiting earning potential (US $878; P<.001), need to travel for care (US $857; P<.001), complications from treatment (US $527; P=.04), funeral expenses (US $2013; P<.001), and having a chronic condition (US $622; P=.049). Smiling in profile photographs was associated with an earning mean of US $604 more than those without smiling (P=.01). Fundraisers created by friends earned a mean of US $1126 more (P<.001), and those created by someone other than a family member, friend, or partner earned a mean of US $1655 more than if created by the beneficiary themselves (P=.02;).
Age was a significant predictor of the likelihood of extreme success (defined as positive outlier campaigns raising >US $17,345) for those in the 21 to 40 age group, who raised more funds than those in the 61 to 80 age group (odds ratio [OR] 0.94, 95% CI 0.89-0.99). Men were more likely to experience extreme success than women (OR 1.04, 95% CI 1.01-1.06). Themes that were more frequently mentioned in the group with extreme success included the expressed loss of control (OR 1.150, 95% CI 1.012-1.306), chronic medical conditions (OR 1.060, 95% CI 1.012-1.110), need for medical equipment (OR 1.124, 95% CI 1.042-1.213), and rare medical conditions (OR 1.100, 95% 1.027-1.178). Themes that were less frequently mentioned in the group with extreme success included complicated comorbid conditions (OR 0.915, 95% CI 0.876-0.955). If the recipient was smiling in the profile photograph, the campaign was associated with an increased likelihood of extreme success (OR 1.032, 95% CI 1.002-1.061). If the relationship with the campaign creator was more peripheral or ill-defined, the campaign had a higher likelihood of extreme success (OR 1.170, 95% CI 1.061-1.292). An increase in the number of updates was seen in the group with extreme success (OR 1.006, 95% CI 1.005-1.007;).
Commentary associated with each theme is seen in.
|Dependent variable: amount raised||Shares||Updates|
|β (SE)||95% CI||P value||β (SE)||95% CI||P value|
|Number of shares or updates, respectively||5.729 (.2974)b||5.15 to 6.31||<.001||262.3 (31.71)b||200.08 to 324.45||<.001|
|Goal||.1743 (.0055)b||0.16 to 0.18||<.001||.1869 (.0058)b||0.18 to 0.20||<.001|
|Age group (years; reference: 21-40 years)|
|<10||−367.5 (854.4)||−2043.16 to 1308.21||.67||−185.3 (913.8)||−1977.38 to 1606.72||.84|
|11-20||466.9 (1139)||−1757.57 to 2701.42||.68||−82.41 (122)||−2475.38 to 2310.55||.95|
|41-60||−159.1 (767.1)||−1663.58 to 1345.31||.84||−1210 (819.9)||−2818.16 to 397.85||.14|
|61-80||−1487 (1309)||−4053.90 to 1078.98||.26||−3501 (1394)c||−6235.36 to −766.78||.01|
|>81||−946.5 (5963)||−12,640 to 10,747.78||.87||−3635 (6371)||−16,129.83 to 8859.52||.57|
|Race (reference: White)|
|African American||−3561 (988.4)b||−5499.47 to −1622.75||<.001||−3550 (1057)b||−5622.48 to −1477.06||<.001|
|Asian||2547 (1808)||−998.40 to 6091.47||.16||2568 (1949)||−1253.48 to 6389.43||.19|
|Hispanic||−1310 (1125)||−3516.84 to 896.70||.24||−461.5 (1203)||−2821.50 to 1898.57||.70|
|Other||1274 (4442)||−7437.70 to 9985.73||.77||−13.21 (4747)||−9322.41 to 9295.99||.99|
|Gender (reference: female)|
|Male||927.3 (608.2)||−265.50 to 2120.19||.13||1841 (648.9)d||568.74 to 3113.79||.005|
aAdjusted R2 for shares=0.4687 and R2 for updates=0.3865.
|Dependent variable: amount raised||β (SE)||95% CI||P value|
|Goal||.210 (.016)c||0.19 to 0.23||<.001|
|Age group (years; reference: 21-40)|
|<10||393.5 (268.2)||−132.49 to 919.53||.14|
|11-20||228.9 (322.0)||−401.66 to 860.43||.48|
|41-60||−716.7 (216.2)c||−1185.74 to −337.69||<.001|
|61-80||−417.5 (360.1)||−1123.84 to 288.80||.25|
|>80||−2207 (1451)||−5053.80 to 640.06||.13|
|Race (reference: White)|
|African American||−1146 (270.0)c||−1675.96 to −616.76||<.001|
|Asian||−690.6 (507.5)||−1686.09 to 304.93||.17|
|Hispanic||−36.48 (305.7)||−636.07 to 563.11||.91|
|Other||−872.2 (1323)||−3467.55 to 1723.15||.51|
|Gender (reference: female)|
|Male||389.2 (170.3)d||55.23 to 723.16||.02|
|Loss of employment||567.6 (391.9)||−201.09 to 1336.37||.15|
|Medical condition limiting earning potential||878.0 (186.1)c||512.93 to 1243.01||<.001|
|Need to travel for care||857.3 (202.5)c||460.07 to 1254.61||<.001|
|Complications from treatment||527.3 (255.1)d||26.94 to 1027.62||.04|
|Funeral expenses||201.3 (519.1)c||995.08 to 3031.55||<.001|
|Medical condition limiting activities||513.5 (281.4)||−38.40 to 1065.35||.07|
|Chronic condition needing long-term treatment||621.5 (314.9)d||3.83 to 1239.23||.05|
|Delayed medical attention||908.4 (491.7)||−56.14 to 1872.93||.06|
|Money for childcare or family during treatment||−2316 (1318)||−4900.54 to 268.64||.08|
|Fundraiser creator (reference: self)|
|Family member||300.5 (230.6)||−151.91 to 752.90||.003|
|Friend||1126 (240.1)c||655.51 to 1597.23||<.001|
|Partner||−232.0 (407.8)||−1031.93 to 567.85||.57|
|Other||1655 (682.2)d||316.64 to 2992.95||.02|
|Patient smiling||603.6 (182.6)c||245.46 to 961.74||<.001|
|Patient single (reference: in relationship)||300.5 (230.6)e||−1017.49 to −211.27||.19|
|Number of updates||87.99 (11.0)c||66.37 to 109.61||<.001|
aAmounts raised >US $17,345 were excluded from analysis.
|Dependent variable: amount raised >US $17,345 compared with below||β (SE)||Odds ratio (95% CI)||P value|
|Goal||.008 (.025)b||1.008 (0.961-1.058)||<.001|
|Age group (reference: 21-40 years)|
|<10||−.030 (.021)||0.970 (0.932-1.011)||.15|
|11-20||−.039 (.026)||0.962 (0.915-1.012)||.05|
|41-60||−.032 (.016)||0.968 (0.938-1.000)||.13|
|61-80||−.061 (.028)c||0.941 (0.891-0.993)||.03|
|>80||−.050 (.126)||0.951 (0.744-1.216)||.69|
|Race (reference: White)|
|African American||.008 (.021)||1.008 (0.967-1.051)||.71|
|Asian||.075 (.038)c||1.078 (1.000-1.163)||.05|
|Hispanic||.010 (.024)||1.010 (0.964-1.058)||.68|
|Other||.126 (.094)||1.135 (0.945-1.363)||.18|
|Gender (reference: female)|
|Male||.036 (.013)d||1.037 (1.010-1.064)||.006|
|Inadequate insurance or financial capacity||.022 (.013)||1.022 (0.996-1.049)||.09|
|Diagnostic difficulty||.045 (.024)||1.046 (0.999-1.095)||.06|
|Donation to charity or research||−.072 (.035)c||0.930 (0.868-0.997)||.04|
|Loss of family time||.049 (.033)||1.051 (0.985-1.120)||.13|
|Medical condition limiting activities||−.054 (.022)c||0.947 (0.908-0.989)||.01|
|Express loss of control||.140 (.065)c||1.150 (1.012-1.306)||.03|
|Chronic condition needing LTe treatment||.059 (.024)c||1.060 (1.012-1.110)||.01|
|Need for medical equipment||.117 (.039)d||1.124 (1.042-1.213)||.003|
|Rare medical condition||.095 (.035)d||1.100 (1.027-1.178)||.007|
|At-home care expenses||−.059 (.032)||0.943 (0.886-1.003)||.06|
|Complicating comorbidities||−.089 (.022)b||0.915 (0.876-0.955)||<.001|
|Lacking self-confidence because of illness||−.043 (.027)||0.958 (0.909-1.010)||.11|
|Fundraiser creator (reference: self)|
|Family member||.035 (.018)||1.035 (0.999-1.072)||.05|
|Friend||.031 (.019)||1.032 (0.994-1.071)||.1|
|Partner||.038 (.031)||1.039 (0.977-1.104)||.22|
|Other||.158 (.050)d||1.171 (1.062-1.292)||.002|
|Patient smiling||.031 (.014)c||1.032 (1.002-1.061)||.03|
|Patient Single (reference: in relationship)||−.033 (.016)c||0.968 (0.938-0.999)||.04|
|Number of updates||.006 (.001)b||1.006 (1.005-1.007)||<.001|
|Variable||Participantsa, n (%)||Quotesb|
|Inadequate insurance||1050 (22.9)|
|Limited ability to work||601 (13.1)|
|Money for basics (food, rent, and utilities)||326 (7.1)|
|No insurance||213 (4.6)|
|Complications from treatment||210 (4.6)|
|Limited activities||187 (4.1)|
|Complicating comorbiditiesc||184 (4)|
|Chronic condition with need for long-term care||157 (3.4)|
|Diagnostic difficulty||156 (3.4)|
|Wig or hair prosthetic||100 (2.2)|
|At-home care expenses||87 (1.9)|
|Loss of employment||86 (1.9)|
|Burden of previous debt||83 (1.8)|
|Loss of family time||77 (1.7)|
|Rare medical conditions||69 (1.5)|
|Medical devices||59 (1.2)|
|Funeral expenses||55 (1.2)|
|Delay in medical attention||54 (1.2)|
|Trying to connect with people with similar diseases||22 (0.5)|
|Loss of control||19 (0.4)|
|End of life costs||15 (0.3)|
|Preventative and alternative health||15 (0.3)|
|Familial conflict because of disease||7 (0.2)|
aAs campaigns endorsed multiple themes, and n reflects the total times a theme was endorsed, the total n does not equal the number of campaigns.
bQuotes have been paraphrased for anonymity and brevity.
cComplicating comorbidities refer to any expense incurred because of concurrent medical problems not associated with the primary disease stated in the fundraiser.
Our study identified factors associated with successful fundraising for dermatologic conditions on GoFundMe and specifically showed that thematic and demographic factors, including race and gender, have associations. Importantly, increasing the use of web-based crowdfunding introduces a new variable in the relationship between social media and medicine. The results of our study support the hypothesis that greater web-based social capital may be associated with successful fundraising. However, mobilizing these resources almost necessarily compromises patient privacy. Modifiable factors associated with success included a larger number of updates, non–self-identity of the campaign creator, mention of a chronic condition, and smiling in campaign profile photographs. Nonmodifiable factors associated with greater success included male gender, early to middle adulthood (age 21-40 years), and White race. Improved understanding of modifiable factors may guide future campaigns, and these identified nonmodifiable factors may have policy implications for improving health care equity and financing. Further, any reliance on crowdfunding to supplement insurance coverage highlights the potential shortcomings of the health care system and introduces questions regarding the balance between the risks and benefits for patients using social media to support their health care expenses. In particular, the identified nonmodifiable differences in crowdfunding may perpetuate the existing disparities in disadvantaged populations.
Social media literacy and robust web-based networks may increase the success of campaign fundraising. For every additional campaign profile update, fundraisers earned US $262 more per post, and for every additional share on social media, fundraisers earned US $6 more per post when controlling for race, age, gender, and goal of campaign. On an average, it took 6 shares to garner a single donation. Therefore, those with larger following on the web or followers with greater access to disposable capital may be at an advantage. Notably, higher income and educational levels have been associated with a larger number of donors and donation size in fundraisers for COVID-19 . Together, these findings suggest that crowdfunded donations may be distributed inequitably, favoring the privileged [ , ]. Income and educational level were not available for analysis in our study and could provide further evidence to support this hypothesis. Access to technology, literacy, social capital, robust web-based networks, and self-marketing skills are factors that may contribute to a widening digital divide by enhancing opportunities to increase crowd appeal.
The need to mobilize these social networks and create an effective emotional appeal may undercut the right to medical privacy and patient autonomy. Campaigners noted detail information not only about their medical conditions but also personal expenses (). This information was provided voluntarily; however, pressure to increase appeal and legitimacy because of impending financial needs may undermine the right to medical privacy. The process of consent is also a concern when a campaigner is fundraising on behalf of a recipient and sharing second-hand personal information [ ]. Interestingly, our study found that when the campaign creator was not the fundraising recipient, there was an association with increased success. Relationships that were more peripheral (friends) or ill-defined (others) had the greatest success. Potential donors may view fundraising by surrogates as credible evidence of increased disease severity, strong social ties that merit more donations, or an otherwise greater need for donation. Along the same line, other studies regarding GoFundMe success in patients with hepatitis C and lung cancer have shown that successful campaigns featured motifs emphasizing self-sufficiency, use of this platform as a last resort, framing the request for help as atypical, and highlighting that the individual was not at fault for their illness [ , ]. Campaigns that provided more information about etiology of disease and a breakdown of treatment costs were likely to receive higher donations [ ]. GoFundMe encourages the release of this information through their “Top Tips” page, which includes recommendations for frequent updates, inclusion of ≥5 images, and divulsion of details regarding the recipient’s personal life and medical treatment [ ]. Other studies have similarly noted the trend of including extensive personal information, with some advocating for GoFundMe to change their recommendations; institute a consent process for fundraising on behalf of others; and obtain a release for personal information or restrict information posted without consent [ , ].
Medical fundraising campaigns may affect the relationship between physicians and patients on social media. For instance, campaigns may mention physician names and private medical details to increase campaign legitimacy. Jia et al  found that if the physician’s name was mentioned in melanoma campaigns, the amount raised was doubled. Other studies have noted concerns over the use of GoFundMe without physician supervision as it may promote unfounded medical treatments [ - ]. Currently, it is not common practice for patients to consult physicians about information shared via social media. If physicians see their obligation to their patients as maximizing patient benefits and minimizing harm, this implies that physicians may choose to expand their roles as patient consultants in web-based and social media venues. However, it is worth noting that this raises further questions regarding physician privacy and traditional professional boundaries.
Disclosure of a chronic medical condition was another modifiable variable associated with increased success in both regressions. Previous reports have recognized that individuals with chronic conditions often have unmet needs within the American health care system . Furthermore, chronic rather than acute conditions are hypothesized to more strongly invoke the sick role and increase donor sympathy [ ]. Some believe that this phenomenon occurs because of reinforcement of the concept that the resolution of chronic disease is unexpected and thus may be costlier [ ]. Consistent with other studies on GoFundMe donations, the success of campaigns citing this theme may be related to creating an image of deservingness and emphasizing the lack of culpability in their disease processes or financial situations [ , ]. This knowledge could potentially be applied to educate patients seeking to maximize their returns from GoFundMe fundraising. Similar to many profit-based endeavors, improving social media skills and expertise could assist patients in increasing fundraising success through comprehension of which qualities to emphasize and which to avoid.
Along these lines, smiling in campaign profile photographs was also associated with increased success, suggesting the benefits of strategized visual campaign curation. Other studies have theorized that this effect may be because of observers mimicking the emotions depicted in images, thus motivating donations to maintain these sentiments [, ]. Smiling may also influence the perceived attractiveness of a recipient. Previous research suggests that the perceived attractiveness of female recipients may lead to larger donations [ ]. These observations, in conjunction with the fact that this study found men to be more likely to achieve campaign success, may have ethical implications regarding distributive justice and evoke concerns about unconscious biases in crowdfunding. Canadian researchers have suggested that, paradoxically, although campaigns are typically created in response to known gaps in the social system, the resulting campaign outcomes reinforce rather than rectify established socioeconomic disparities [ , ]. If health care financing shifts from an institutionalized to an individual system, resources may be distributed not based on need but rather based on social worthiness or appeal.
In both regressions, the goals of campaigns were related to increases in the amounts raised. There are limitations to interpreting this relationship, given several confounding factors. Those with higher goals are less likely to meet their fundraising ceilings. In theory, having a high unmet goal could potentially encourage additional donations until an inflection point is reached, and these exceptionally high goals may seem futile and unobtainable for donors. In addition, higher goals may reflect disease states of greater severity and need. Conditions that are more severe may inherently have a greater crowd appeal and contribute to the higher amount raised.
Regarding nonmodifiable variables, our study suggests that demographic differences, including race, age, and gender, affect fundraising. Black, female, and older patients were all less successful in their fundraising campaigns. Kenworthy et al  also found that, although women were less likely to be as successful as men in fundraising, women created most fundraisers. In this study, men also had more shares and donations than women. Notably, trends in fundraising success within the limited landscape of GoFundMe may not mimic trends in earning potential and health care burden seen in society at large. Previous studies have found that compared with their White counterparts, people of color are more likely to be both underinsured and experience adverse health outcomes [ ]. In addition, according to the Pew Research Center, the salary of American women in 2020 was 84% of the salary earned by men [ ]. Older individuals have more limited income opportunities and are also more likely to experience medical conditions, particularly skin cancers [ ]. These differences may be exacerbated by the increased burden that traditionally marginalized groups (ie, older patients, racial minorities, and individuals of lower socioeconomic status) have accessing web-based resources, thereby leading to smaller web-based social networks and influence. In interpreting these findings, it is imperative to question the role that donor bias may play in fundraising success. Unconscious bias regarding darker skin tones has been associated with lower fundraising amounts, even when controlling for donor education, race, gender, political ideology, and past giving behavior [ ]. Although gender and age biases against women and older individuals in nonmedical fundraising have been documented, controlled experiments to evaluate unconscious biases in health care crowdfunding are needed [ ]. Given that these specific populations, on average, earned less money fundraising, these observed trends suggest that patients with the greatest need for financial assistance may be particularly disadvantaged.
Although increased reliance on crowdfunding for medical expenses could be criticized as a natural consequence of an imperfect health care system failing to meet the needs of a large segment of the population, crowdfunding may currently serve a purpose as a social safety net for those facing financial hardship. However, to ensure parity and that any social safety net provides coverage for those who need it the most, future work should continue to explore the amount of invested labor and derived benefits for all demographic groups.
This study was conducted using data from GoFundMe. Future studies are needed to examine whether these findings can be generalized to other crowdfunding platforms. There is a possibility of misclassification bias as the authenticity of each campaign could not be verified. In addition, age could only be evaluated as a categorical variable as many patients referenced their decade of life but not specific ages. There is also the possibility of misclassification because of the data abstraction process; however, each post was reviewed by 2, reviewers and entries were discussed as a team to minimize the potential introduction of bias. Furthermore, GoFundMe does not release the proprietary algorithm that guides search tools; as only the first 960 campaigns per search term are displayed, it is possible that some campaigns could not be assessed depending on how GoFundMe’s search algorithm prioritizes different content. Finally, it is worth noting that our study coincided with the COVID-19 pandemic. Although mentions of COVID-19 were not significantly associated with campaign success, future studies should seek to explore the crowdfunding frequency and success of campaigns coinciding with the pandemic.
The results of this cross-sectional study suggest that dermatologic crowdfunding success is associated with modifiable and nonmodifiable variables such as race, gender, and age. Improved understanding of modifiable factors may guide future campaigns, and identified nonmodifiable factors may have policy implications for improving health care equity and financing. GoFundMe may have the potential to exacerbate and introduce health care inequalities skewed along the lines of these factors and web-based social capital. However, identifying the factors associated with successful fundraising and social media education may assist patients in self-advocacy. Future research should further investigate the impact of GoFundMe campaigns in the medical field.
The authors would like to acknowledge Dr Marieke Jones, PhD, for her advice on data template and statistical hypothesis design.
Conflicts of Interest
- Angraal S, Zachariah AG, Raaisa R, Khera R, Rao P, Krumholz HM, et al. Evaluation of internet-based crowdsourced fundraising to cover health care costs in the United States. JAMA Netw Open 2021;4(1):e2033157 [FREE Full text] [CrossRef] [Medline]
- GoFundMe: #1 fundraising platform for crowdfunding. URL: https://www.gofundme.com/ [accessed 2021-06-22]
- Himmelstein DU, Thorne D, Warren E, Woolhandler S. Medical bankruptcy in the United States, 2007: results of a national study. Am J Med 2009;122(8):741-746. [CrossRef] [Medline]
- Kenworthy N, Dong Z, Montgomery A, Fuller E, Berliner L. A cross-sectional study of social inequities in medical crowdfunding campaigns in the United States. PLoS One 2020;15(3):e0229760 [FREE Full text] [CrossRef] [Medline]
- Joseph Mattingly 2nd T, Li K, Ng A, Ton-Nu TL, Owens J. Exploring patient-reported costs related to hepatitis C on the medical crowdfunding page GoFundMe®. Pharmacoecon Open 2021;5(2):245-250 [FREE Full text] [CrossRef] [Medline]
- Igra M, Kenworthy N, Luchsinger C, Jung JK. Crowdfunding as a response to COVID-19: increasing inequities at a time of crisis. Soc Sci Med 2021;282:114105 [FREE Full text] [CrossRef] [Medline]
- Nguyen R, Hanna NH, Vater L. Crowdfunding for lung cancer costs. J Clin Oncol 2019;37(15_suppl):e18340. [CrossRef]
- Lukk M, Schneiderhan E, Soares J. Worthy? Crowdfunding the Canadian health care and education sectors. Can Rev Sociol 2018;55(3):404-424. [CrossRef] [Medline]
- Brezinski EA, Harskamp CT, Ledo L, Armstrong AW. Public perception of dermatologists and comparison with other medical specialties: results from a national survey. J Am Acad Dermatol 2014;71(5):875-881. [CrossRef] [Medline]
- Skin conditions at a glance. National Center for Complementary and Integrative Health. URL: https://www.nccih.nih.gov/health/skin-conditions-at-a-glance [accessed 2021-06-22]
- Lim HW, Collins SA, Resneck Jr JS, Bolognia JL, Hodge JA, Rohrer TA, et al. The burden of skin disease in the United States. J Am Acad Dermatol 2017;76(5):958-72.e2. [CrossRef] [Medline]
- Boyatzis RE. Transforming qualitative information: thematic analysis and code development. Thousand Oaks, CA: Sage Publications; 1998.
- van Duynhoven A, Lee A, Michel R, Snyder J, Crooks V, Chow-White P, et al. Spatially exploring the intersection of socioeconomic status and Canadian cancer-related medical crowdfunding campaigns. BMJ Open 2019;9(6):e026365 [FREE Full text] [CrossRef] [Medline]
- Snyder J, Crooks VA. Is there room for privacy in medical crowdfunding? J Med Ethics 2020;47(12):e40. [CrossRef] [Medline]
- Jia JL, Mills D, Sarin KY. Crowdfunding for the treatment of cutaneous malignancies: trends, correlates, and money raised. J Am Acad Dermatol 2020;83(6):AB107. [CrossRef]
- Snyder J, Turner L, Crooks VA. Crowdfunding for unproven stem cell-based interventions. JAMA 2018;319(18):1935-1936 [FREE Full text] [CrossRef] [Medline]
- Zenone M, Snyder J, Caulfield T. Crowdfunding cannabidiol (CBD) for cancer: hype and misinformation on GoFundMe. Am J Public Health 2020;110(S3):S294-S299. [CrossRef] [Medline]
- Song S, Cohen AJ, Lui H, Mmonu NA, Brody H, Patino G, et al. Use of GoFundMe® to crowdfund complementary and alternative medicine treatments for cancer. J Cancer Res Clin Oncol 2020;146(7):1857-1865. [CrossRef] [Medline]
- Anderson GF. Physician, public, and policymaker perspectives on chronic conditions. Arch Intern Med 2003;163(4):437-442. [CrossRef] [Medline]
- Varul MZ. Talcott parsons, the sick role and chronic illness. Body Soc 2010;16(2):72-94. [CrossRef]
- Hatfield E, Cacioppo JT, Rapson RL. Emotional contagion. Curr Dir Psychol Sci 1993;2(3):96-100. [CrossRef]
- Cao X, Jia L. The effects of the facial expression of beneficiaries in charity appeals and psychological involvement on donation intentions: evidence from an online experiment. Nonprofit Manag Leadersh 2017;27(4):457-473. [CrossRef]
- Raihani NJ, Smith S. Competitive helping in online giving. Curr Biol 2015;25(9):1183-1186 [FREE Full text] [CrossRef] [Medline]
- Kirby JB, Kaneda T. 'Double jeopardy' measure suggests blacks and hispanics face more severe disparities than previously indicated. Health Aff (Millwood) 2013;32(10):1766-1772. [CrossRef] [Medline]
- Pew Research Center. URL: https://www.pewresearch.org/ [accessed 2021-06-28]
- Russo AE, Ferraù F, Antonelli G, Priolo D, McCubrey JA, Libra M. Malignant melanoma in elderly patients: biological, surgical and medical issues. Expert Rev Anticancer Ther 2015;15(1):101-108. [CrossRef] [Medline]
- Bhati A. Does implicit color bias reduce giving? Learnings from fundraising survey using implicit association test (IAT). Voluntas 2021;32(2):340-350 [FREE Full text] [CrossRef]
|OR: odds ratio|
Edited by R Dellavalle; submitted 06.10.21; peer-reviewed by S Bowers, L Jin; comments to author 14.01.22; revised version received 31.01.22; accepted 24.02.22; published 22.04.22Copyright
©Erica Mark, Mira Sridharan, Brian Florenzo, Olivia L Schenck, Mary-Margaret B Noland, John S Barbieri, Jules B Lipoff. Originally published in JMIR Dermatology (http://derma.jmir.org), 22.04.2022.
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