Bibliographic record
Abstract
While this piece is being written (December 2005), the blood supply barometer used by America's Blood Centers to indicate the health of the nation's blood supply is “green”—most centers have a 3-day or better inventory. But if history is any guide, by January many urban areas will find their blood stocks depleted. Radio and television will broadcast urgent appeals for donors, and elective surgeries will be canceled. This pattern has repeated itself over the past 15 years, although the duration and the depth of the shortages is worsening over time, and blood appeals are no longer limited to a few holiday periods. Indeed, the fragility of our blood supply is illustrated by what happened in 2003 when the Red Cross discovery of white particulate matter in RBCs in Atlanta temporarily suspended its blood shipments to Atlanta-area hospitals.1 The result was a widespread blood shortage causing emergency surgeries to rely on imported blood and elective surgeries to be canceled. Few people die in this country for lack of blood. But in the United States, that number should be zero. And given the sobering issues discussed daily on the evening news—how can we be sure that deaths due to unavailability of blood will not increase dramatically in the future? For example, if an influenza pandemic reaches our shores, hundreds of thousands of potential blood donors could either be ill or be too frightened to donate in public places, or if 1 g of aerosolized anthrax released in an urban area could infect 500,000 people, it is easy to imagine that prospective blood donors would stay away during the ensuing panic, similar to crowd behavior during the 1950s’ polio outbreaks.2 Would the “green” light of a 3-day supply be adequate to meet such a contingency? Could blood be moved quickly enough from a green to a “red” zone to prevent life-threatening blood shortages in areas of our country? These scenarios, however, severe they seem, are not far-fetched. A surge in blood donations (mimicking post-September 11, 2001) would be of no use for patients with emergent needs in hard hit areas. While the Department of Health and Human Services Advisory Committee on Blood Safety and Availability recommends that a 5- to 7-day supply is the desirable goal for the nation's blood centers, many centers cannot sustain even a 3-day supply.3 Recruiting donors through raffle tickets, tee shirts, and cholesterol tests is not a sustainable answer. A number of ideas have been advanced to drive an increase in sustained donations, including 1) modifying the health history questionnaire and adjusting the hemoglobin acceptance criteria to broaden the eligible donor pool, 2) providing iron supplementation to donors (particularly women), 3) permitting 16-year-olds to donate, 4) preventing donor reactions, and 5) recruiting patients with hereditary hemochromatosis.4,5 While these ideas have merit, and may provide short-term successes, they do not address the deeper question as to why current donors do not donate more frequently and, more importantly, why do so many fail to return or never donate at all. It is disturbing that in a recent study of long-term commitment of first-time donors, Schreiber and coworkers6 found that of donors who gave blood only 4 percent became regular donors within 12 months of their first donation. No wonder urgent appeals for blood are so frequent! Clearly, urgent appeals are not long-term solutions. With fewer than 5 percent of the eligible population donating, we must acknowledge that the lynchpin to transfusion medicine—the blood donor—is poorly understood. That term, blood donor, may itself be a misnomer. It implies that all individuals who are willing to give 60 minutes or more of their time to be stuck by a needle are motivated by the same reasons, irrespective of background or personal circumstances. Intuitively, we know this is wrong. Gillespie7 acknowledged this in her recent editorial in this journal. There has been little effort in the past to assess the donor or prospective donor in a rigorous, scientific way, taking into account such issues as demographics and socioeconomics. Fortunately, this knowledge gap is beginning to be addressed by behavioral scientists and others. Hupfer and colleagues8 used multivariate analysis to evaluate beliefs and motivations among Canadian undergraduate students, representing donors and nondonors. While altruism was the dominant reason for donating, logistical issues (time, inconvenience, and fear of disease) were most significant for donation avoidance. Significant differences were found between men and women in their stated motivations. The study by Schreiber and associates9 in this issue of TRANSFUSION is the perfect bookend to the Canadian study. This study was an analysis of a large group of US first-time and lapsed donors (repeat donors who had not donated in 2 to 3 years) who completed a self-administered questionnaire. Six blood centers from the west, midwest, and east participated. The response rate was 24.3 percent. Forty-one percent were first-timers, with approximately 60 percent from minority groups. The lack of a convenient location was the most important factor for both first-time (32-42%) and repeat donors (26-43%). The “convenience factor” was much more important to donors who were age 25 or younger. With the acknowledged need for the “next generation” of donors, such a finding is significant. Lack of staff skill and poor treatment were a distant second in overall importance, but minority donors were twice as likely as white donors to cite these factors. As today's minorities become tomorrow's majority, it is vital that behavioral deterrents be addressed to make the donation experience satisfying for all. This study is very important because it is methodologically sound and provides the blood collecting community with a road map for prioritization of its energy and resources. Because the data indicate that donors feel strongly about convenience, what does convenience look like for the nation's blood centers? Success will look different, depending on the community. This must be a time for new, creative ideas, and the sharing of best practices based on physiological and behavioral data. All-night blood drives for college-aged night owls or viewing of pop culture movies or television complete with coffee bars and ATMs are not out of the question. Automated collection technology may play a vital role, too, in the mobile setting, as well as fixed sites; to collect blood components from the technology-savvy younger generation; group O RBCs; AB or A plasma; platelets; or all of the above. The nation is 300,000,000 strong and growing and with it the demand for blood. With a graying population and a delicate blood supply chain, the time is now for bold steps to expand the donor pool. The basis for action should be strong behavioral and related science.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".