Trust and Information Habits Drive Public Enthusiasm for Blood Tests That Screen Many Cancers at Once

A single blood draw that can search for traces of many different cancers at once sounds like science fiction, but multi-cancer early detection (MCED) tests are rapidly moving from laboratory promise to clinical reality. These liquid biopsy platforms hunt for cancer-associated signals such as circulating tumor DNA in a routine blood sample, offering the possibility of screening for several tumor types simultaneously, including some that currently have no standard screening test at all. Public interest in the technology appears high, yet the psychological and structural forces that shape how ordinary people value such tests have remained largely unexplored. A new national study published in Cancer Causes & Control now provides the most systematic picture to date of what drives Americans’ perceptions of MCED testing, and the answer centers on a familiar but powerful variable: trust.

The research, led by Duxiao Hao, Chuan-Jian Zhong, and Safa Elkefi of Binghamton University, State University of New York, drew on Cycle 7 of the Health Information National Trends Survey (HINTS), a nationally representative survey of the United States noninstitutionalized adult population conducted by the National Cancer Institute. After excluding respondents missing data on the main outcome, the analytic sample comprised 6,728 participants, or 92.4 percent of the original 7,278 respondents. Missing values for predictor variables were handled using k-nearest-neighbor imputation with k equal to 3, a technique that fills gaps by borrowing information from respondents with similar answer patterns. All descriptive estimates incorporated the survey’s full-sample person-level weights to produce population-relevant figures.

What the team found was striking: 74.9 percent of respondents perceived MCED testing as very valuable. Yet that enthusiasm was not evenly spread. Perceived value rose with age, with middle-aged adults aged 40 to 59 disproportionately represented in the high-value group compared with younger adults aged 18 to 39, who reported low perceived value more frequently. College graduates were more likely than those with less education to rate the technology highly, higher household income was associated with greater perceived value, and married individuals reported high perceived value more often than unmarried ones. Racial and ethnic patterns also emerged, with Black and Hispanic participants underrepresented in the high-value group relative to their share of the overall sample, a signal the authors interpret as a warning about future inequities in uptake.

To organize the many possible influences on perception, the researchers turned to the PRECEDE–PROCEED framework, a long-established model in health behavior planning that sorts determinants into three categories. Predisposing factors are the cognitive and psychological characteristics, such as beliefs, knowledge, attitudes, and trust, that motivate or hinder action before it occurs. Enabling factors are the structural and resource-based conditions, including access to care, technology, and information, that determine whether motivation can be acted upon. Reinforcing factors are the social and interpersonal influences, such as provider communication and family history, that sustain attitudes and convert them into behavioral intentions. The team mapped candidate HINTS variables onto these domains based on theory rather than data-driven selection, then tested their associations using survey-weighted multivariable logistic regression complemented by supervised machine learning models, including logistic regression and random forest classifiers trained on a 70/30 train-test split with k-fold cross-validation.

The regression results revealed a clear hierarchy of influence, and at the top sat trust. Each point increase in trust in physicians was associated with 1.89 times the odds of perceiving MCED testing as highly valuable (95 percent confidence interval 1.52 to 2.33), the strongest association of any predictor. Trust in science followed closely with an odds ratio of 1.80 (1.56 to 2.07), and trust in the healthcare system came next at 1.64 (1.43 to 1.88). Trust in government also contributed, with an odds ratio of 1.50. In other words, people’s willingness to value an entirely new screening technology rests less on the technology itself and more on whether they believe in the institutions that create, regulate, and deliver it.

Information behavior formed the second major theme. Respondents who actively sought cancer information showed 1.59 times the odds of high perceived value, and those who used online health information sources showed 1.63 times the odds. Simply owning a smartphone raised the odds by a factor of 1.54, underscoring how deeply digital access is entangled with awareness of emerging medical technologies. Cancer-related beliefs mattered as well: fatalistic beliefs about cancer, often assumed to be a barrier to screening, were associated with 1.52 times the odds of high perceived value, a finding consistent with prior research suggesting that heightened worry about cancer can, in some contexts, strengthen motivation for early detection. Knowledge that hepatitis B is a cancer risk factor (odds ratio 1.48), cancer risk numeracy (1.33), and a family history of cancer (1.45) all added further predictive weight, as did knowledge of hepatitis C (1.36) and perceptions that there are too many cancer screening recommendations (1.34).

The machine learning analyses served as an independent check on these conclusions. Random forest and logistic regression classifiers, trained only on the theory-based PRECEDE determinants, produced predictor importance rankings that were generally consistent with the regression results, with trust-related variables and health information engagement emerging as the strongest contributors to model performance. Spearman correlation screening had already flagged the same signals, with trust in science (rho = 0.101) and cancer information seeking (rho = 0.100) topping the list, followed by cancer fatalistic beliefs (0.091) and trust in the healthcare system (0.086). The convergence of inferential and predictive methods on the same set of determinants lends considerable robustness to the study’s central claim: perceived value of MCED testing is built from an interaction of psychological trust, information engagement, and structural access rather than from any single demographic trait.

The demographic patterns add an important equity dimension to these findings. Because trust in medicine is known to be lower among communities that have experienced historical mistreatment and contemporary marginalization, and because the study found that experiences of discrimination in medical care were themselves associated with perceived value, the authors caution that MCED implementation could widen existing gaps in cancer outcomes if deployed without deliberate attention to equitable communication. Prior research has repeatedly shown that low uptake of proven screening tests, such as colorectal cancer screening, remains a persistent challenge even when multiple effective options exist, and that these shortfalls are greatest among racial and ethnic minorities, lower socioeconomic groups, and rural populations. A technology that requires high trust and high digital connectivity could, if introduced carelessly, reproduce those same disparities at a larger scale.

The study’s implications for policy are correspondingly concrete. The authors argue that future implementation strategies should prioritize strengthening public confidence in science and healthcare providers, improving access to reliable health information, and ensuring that communication about MCED testing addresses its genuine uncertainties, including concerns about false positives, overdiagnosis, the cost of follow-up diagnostics, and the still-emerging evidence on mortality reduction. Provider-patient conversation is highlighted as a critical reinforcing mechanism, since previous work shows that patient-provider communication strongly predicts screening uptake and that women who highly valued mammography attended regular screening at rates roughly 40 percent higher than those with low perceived value. Meta-analytic evidence likewise links higher perceived value to a two- to three-fold greater likelihood of screening uptake for breast, cervical, and colorectal cancers, suggesting that the perceptions measured here may foreshadow real-world adoption.

The authors are candid about the study’s limits. The cross-sectional, self-reported design precludes causal inference and invites recall and social desirability bias. Binary conversion of the four-level outcome sacrificed some resolution, KNN imputation carries assumptions about the similarity of respondents, and HINTS does not capture implementation-specific factors such as anticipated out-of-pocket costs or the financial burden of downstream diagnostics. Responses about a technology still in early deployment may also reflect hypothetical rather than settled intentions. Even so, the researchers describe the work as the first systematic, theory-driven investigation into the behavioral mechanisms of acceptance for this new generation of cancer screening tools, and they argue that its framework can guide carefully constructed interventions as MCED tests move toward broader clinical availability. If the findings hold, the fate of multi-cancer early detection may depend less on the sensitivity of a blood test than on the trustworthiness of the institutions behind it and the reliability of the information ecosystem surrounding it.

Subject of Research: Predictors of perceived value of multi-cancer early detection testing among U.S. adults using the PRECEDE–PROCEED framework

Article Title: Predictors of perceived value of multi-cancer early detection testing: a national PRECEDE–PROCEED framework study

Article References: Hao, D., Zhong, C.-J., & Elkefi, S. (2026). Predictors of perceived value of multi-cancer early detection testing: a national PRECEDE–PROCEED framework study. Cancer Causes & Control, 37(10), Article 164. https://doi.org/10.1007/s10552-026-02242-0

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02242-0

Keywords: multi-cancer early detection, MCED testing, liquid biopsy, cancer screening, public trust, health information seeking, PRECEDE–PROCEED framework, HINTS survey, health equity, circulating tumor DNA, machine learning, cancer prevention