Research Got Talent: Misinformation Susceptibility’s Hidden Drivers

New research with Australian men shows how trust, media environments, and online communities shape misinformation susceptibility – and where interventions can make the most difference.

Misinformation campaigns often focus on debunking claims after the fact or encouraging people to “fact check more.” Our research emphasises the importance of a different leverage point: how trust forms, which environments shape habits, and how people learn what to believe. For organisations working on digital resilience, these factors often matter more than the content of any single debunking campaign.

As part of the Research Got Talent program, we partnered with the Museum of Sticks & Stones (MoSS) to examine misinformation susceptibility amongst Australian men. The focus reflected our charity’s broader work on the manosphere, toxic online communities, and misogyny, and their growing concern about how these ecosystems intersect with media distrust, identity, and polarisation.

Men are often invoked in discussions about misinformation and online harm but rarely examined in detail. For this project, we looked at how men navigate information in practice: what they notice, what they trust, what persuades them, and how platform environments shape their everyday judgements.

Our aim was practical. Rather than debating what is or isn’t fake news, we set out to identify the strongest signals of susceptibility and resilience – and what those patterns mean for education, communication, and media literacy design.

How the study worked

We used a mixed‑methods approach.

First, we ran an online survey of 500 Australian men aged 18+, measuring misinformation susceptibility alongside media habits, attitudes, and trust. The sample was age‑quota based and weighted to reflect the Australian male population across age, education, language background, state or territory, and region.

Second, we conducted eight in‑depth interviews, guided by the survey results and focused on younger men. This focus reflected clear quantitative patterns: age showed the strongest association with susceptibility in the survey, and media preferences were one of the most important drivers.

Findings were analysed using the COM‑B framework (Capability, Opportunity, and Motivation), which helped connect individual skills, trust patterns, and emotional responses with broader media and platform environments. For MoSS, this mattered because it frames misinformation resilience as something shaped by design choices, not just information gaps.

Measuring susceptibility

The survey used the Misinformation Susceptibility Test (MIST), where respondents judged the veracity of 20 news headlines (10 real, 10 fake). Scores ranged from 5 to 20, with an average of 13.6.

For analysis, those scoring 12 or below were treated as susceptible (41% of the sample), while those scoring 16 or above were resilient (32%). That distribution alone signals a meaningful risk group, rather than a fringe problem.

What predicted risk

Age was the single strongest predictor of misinformation susceptibility. Younger participants were, on average, more susceptible than older participants.

Crucially, age appeared to operate as a proxy rather than a cause. It tracked differences in information environments, platform reliance, trust cues, emotional engagement, and related “life experience” factors, rather than a lack of intelligence or awareness.

A key driver analysis reinforced this picture. After age, the strongest predictors included:

• Primary news source (e.g., ABC, SkyNews, the Herald Sun)

• Level of digital dependence (i.e., dependence on online social support, rather than offline)

• Reliance on mainstream versus alternative media

• Trust in influencers versus trust in scientists and researchers

Some common assumptions did not hold. Self‑reported confidence in fact‑checking showed only small differences in performance, and frequency of fact‑checking was not strongly associated with higher resilience. Saying you “check multiple sources” was not protective by itself.

The implication is blunt: telling people to fact check more is unlikely to shift susceptibility unless evaluation skills and trust cues change as well.

Trust: the dividing line

Interviews helped explain why this was the case.

Across all participants, “evidence” was commonly cited as a marker of credibility. But resilient participants described evidence in more conditional terms. They recognised that information can be misleading when taken out of context, selectively framed, or used to provoke emotion rather than inform.

Resilient participants also applied cross‑checking more deliberately. They compared sources with different editorial positions and looked for convergence across diverse outlets. Some susceptible participants, on the other hand, described cross‑checking in broader or more social terms, such as relying on Reddit comment sections, familiarity, or online volume of agreement.

Trust in experts emerged as a protective factor. Higher resilience was associated with trusting scientists and researchers, often grounded in an understanding of epistemic norms such as peer review, accountability, and reputational risk. In contrast, greater trust in influencers and social media voices functioned as a risk factor, and these interview participants often referenced popularity or familiarity as indicators of credibility.

The difference was not trust versus scepticism, but calibrated trust – knowing why some sources deserve more weight than others.

The environment matters

Information environments showed clear associations with risk.

Reliance on mainstream news sources was associated with greater resilience, while reliance on alternative sources was linked to higher susceptibility (with caution around smaller subgroups).

The relationship between susceptibility and social media use followed a clear gradient. Those who never used social media for news recorded the highest resilience scores; those who relied on it heavily recorded lower scores. Interviews also highlighted a key difference lay in how platforms were used. Resilient participants framed social media as a gateway to mainstream journalism, while susceptible participants treated it more often as the news source itself.

Patterns of feed curation also mattered. Respondents who rarely blocked opposing views showed higher resilience, consistent with the idea that narrowing exposure (e.g., echo chambers) can increase susceptibility.

What this means for decision-makers

Three implications stand out for policymakers, educators, and researchers:

First, teach applied evaluation skills. Participants supported moving beyond generic warnings towards explaining how content is constructed to persuade – through framing, imagery, and emotional cues.

Second, design for social media, not around it. Younger audiences expect fast, accessible formats on the platforms they already use. Static toolkits were widely viewed as ineffective.

Third, target trust cues directly. Interventions should surface the heuristics people rely on – familiarity, popularity, authority – and make explicit why some cues track credibility better than others.

Two intervention concepts emerged from this work. One was a school‑based “Fake News Competition” that builds resilience through students creating misinformation themselves – as a way of reverse engineering resilience by exposing them to persuasive design. The other was for MoSS to leverage its public debate forum (The Parley) to model evidence‑based disagreement and collective sense‑making.

A final takeaway

This research reinforces a simple but challenging point. Misinformation susceptibility is not about intelligence, intent, or awareness. It is about environments, trust, and habits.

If we want to reduce the spread and impact of misinformation, the goal should not be to teach people to distrust everything. It should be to help them understand what to trust, why to trust it, and when to slow down enough to question what their feed is doing for them.

That’s where resilience is found.