The Accountability Gap Behind Health Misinformation: Why Age and Education Change Who Gets the Blame

The battle against health misinformation has exposed a fundamental disagreement over who should protect the public from misleading medical claims circulating online. Social media companies control the platforms, governments oversee public health policy, medical professionals provide clinical expertise, and ordinary users determine what they share. Yet Americans do not agree on which of these actors should carry the greatest responsibility, with new research revealing significant differences linked to education and age.

Published in the journal Societies, the study, "Who Should Bear the Responsibility for Combating Health Misinformation on Social Media? An Analysis of Sociodemographic Factors Using HINTS 6 Data," was authored by Gulzar Shah and Indira Karibayeva. Drawing on nationally representative survey data from 6,252 US adults, the researchers found that social media platforms received the largest share of responsibility, while younger adults and people with different educational backgrounds expressed contrasting expectations about institutional accountability.

The findings introduce a largely overlooked dimension of digital health governance. Efforts to combat misinformation traditionally emphasize identifying false claims, improving digital literacy, and correcting misleading content. However, the effectiveness and public acceptance of these approaches may also depend on whether citizens believe individuals or institutions should intervene. The research suggests that responsibility perceptions are socially patterned, although their influence on actual behavior remains untested.

Platforms Lead the Accountability Debate, but No Actor Commands a Majority

Health misinformation has become an increasingly complex public health challenge as social media brings medical advice, scientific information, personal experiences, and unsupported health claims into the same digital spaces. During the COVID-19 pandemic, the rapid circulation of misleading information prompted international concern over an information environment capable of undermining public understanding and health decisions.

The study shifts attention from who encounters or shares false information to whom people expect to prevent its spread. Researchers analyzed the National Cancer Institute's Health Information National Trends Survey 6, conducted between March and November 2022, using statistical methods designed to account for the survey's nationally representative sampling structure.

The results reveal a fragmented landscape of accountability. Social media platforms were identified as primarily responsible by 31.40% of respondents, followed by individual users at 18.55%, government at 15.87%, medical providers and health care systems at 13.79%, and news media at 12.60%. Another 3.97% selected other actors, while 3.81% provided no substantive answer.

Platforms therefore occupy the leading position in public expectations, but fewer than one-third of adults identified them as the principal responsible actor. The distribution suggests that Americans recognize several potential sources of accountability, even when required to choose only one.

The survey measured primary responsibility rather than willingness to share responsibility. Respondents could not indicate that platforms, governments, health professionals, and users should act together. Consequently, the findings cannot establish whether the public favors exclusive institutional control or coordinated intervention.

The researchers interpret the results within a digital environment where content moderation, algorithmic amplification, institutional communication, and individual sharing practices interact. Responsibility becomes difficult to assign when misleading information can originate from one source, circulate through another, and reach audiences through multiple channels.

A Generational Divide Emerges Over Who Should Police False Health Claims

Age emerged as an important correlate of responsibility perceptions, although the strength of the statistical evidence depended on how researchers classified respondents. Adults younger than 50 generally placed greater relative responsibility on individual users than adults aged 65 and above.

Among respondents aged 18–34, the adjusted odds of identifying social media platforms rather than individual users as primarily responsible were 41% lower than among adults aged 65 or older. The corresponding odds were 43% lower for government, 52% lower for news media, and 69% lower for medical providers and health care systems.

Adults aged 35–49 demonstrated a similar pattern, with particularly pronounced differences involving medical institutions and news organizations. Respondents aged 50–64 occupied a more intermediate position, showing statistically significant differences for medical providers and news media but not for platforms or government.

One possible interpretation identified by the researchers concerns different experiences of digital information environments. Younger adults may be more familiar with social media as spaces where individuals produce, distribute, and evaluate content, potentially encouraging expectations of personal responsibility. Older adults may place greater emphasis on established institutions and professional expertise.

These explanations remain hypotheses rather than demonstrated mechanisms. The statistical models did not directly measure differences in social media engagement, contact with health professionals, or confidence in evaluating online medical claims.

The evidence also contains important qualifications. Although age was significantly associated with responsibility attribution in the primary model, the overall association was not statistically significant when alternative age categories were used or when analysis was restricted to social media users.

The researchers caution against treating the generational divide as uniformly established across all analytical conditions. Its directional consistency is noteworthy, but further investigation is required before age-based differences can reliably inform targeted interventions.

Education Exposes a Stronger Divide in Institutional Expectations

Educational attainment produced a more consistent association with responsibility judgments, revealing differences in how Americans distribute accountability between individuals and established institutions.

Compared with college graduates, respondents with less than a high school education had approximately 3.13 times the adjusted odds of identifying government rather than individual users as primarily responsible. Their corresponding odds were 3.24 times higher for news media and 2.12 times higher for social media platforms.

High school graduates also showed stronger relative preferences for institutional responsibility, particularly government and news organizations. Unlike the overall age association, the education relationship remained statistically significant across the researchers' sensitivity analyses.

The pattern raises questions about the relationship between educational background, digital health literacy, perceived control, and expectations of institutional protection. The researchers suggest these factors could help explain why people with lower educational attainment are more likely to identify institutions as the main responsible actors.

However, the study did not directly measure these proposed explanations. Nor does it establish that respondents with less education are necessarily more vulnerable to false medical claims. Its findings concern responsibility judgments, not misinformation recognition, exposure, or susceptibility.

The association involving news media is particularly significant for understanding modern health communication. Digital audiences frequently encounter material from news organizations within social media feeds, potentially making the boundaries between publishers, platforms, and individual distributors harder to distinguish.

The researchers suggest that social media literacy and news literacy may therefore need to be considered together. Public health communication strategies could benefit from helping users evaluate not only the credibility of particular claims but also their sources and routes of circulation.

Other demographic characteristics produced substantially weaker evidence. The adjusted analysis found no statistically significant overall association between responsibility perceptions and sex, race or ethnicity, marital status, full-time employment, or household income.

Some individual comparisons suggested differences involving marriage or lower income, but the researchers explicitly treated these as exploratory. Their broader statistical tests did not support general conclusions about those characteristics.

The difference demonstrates why identifying populations exposed to misinformation and identifying populations with different accountability expectations are separate research questions. The social factors shaping vulnerability to misleading content need not mirror those shaping beliefs about who should correct it.

The Governance Challenge: Shared Responsibility in an AI-Driven Information System

The findings support consideration of a coordinated approach involving social media platforms, public health agencies, medical professionals, journalists, and individual users. Rather than demonstrating the superiority of any single intervention, the research identifies why policies centered exclusively on personal responsibility may overlook public expectations of institutional accountability.

For platforms, the researchers highlight transparent moderation, clearer identification of disputed health claims, algorithmic accountability, and cooperation with public health authorities. Health systems could strengthen patient education and encourage discussions about medical information encountered online, while news organizations could improve the clarity and accuracy of health reporting.

The educational findings also provide a rationale for examining accessible communication, practical source-verification guidance, and interventions that acknowledge differences in digital health literacy. Age-related patterns suggest potential value in testing peer-based approaches for younger audiences and institution-led communication for older adults.

However, none of these strategies was experimentally evaluated. The study cannot determine whether tailoring interventions to demographic characteristics improves misinformation recognition, changes sharing behavior, or strengthens institutional trust.

Generative artificial intelligence introduces an additional challenge. The researchers note that AI-generated answers increasingly blur distinctions between hosting information and producing it, potentially complicating responsibility when misleading health claims emerge from automated systems.

Because the survey was conducted in 2022, it could not separately measure public expectations concerning AI-generated medical information. Future research must examine whether users assign responsibility to technology developers, digital platforms, medical professionals, or other institutions when automated systems produce inaccurate health guidance.

The study also has methodological limitations. Its cross-sectional design prevents causal conclusions, the household response rate was 28.1%, and the adjusted analysis excluded respondents with missing information. A single forced-choice question further restricts understanding of how people distribute responsibility across multiple actors.

These limitations do not erase the observed educational associations, but they constrain how confidently the findings can inform policy. Replication, more detailed measures of shared responsibility, and direct evaluations of communication interventions remain necessary.