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Effects of influenza self-test results on healthcare-seeking and transmission-related behavioural intentions: An experimental study

This experimental study with 1,200 UK adults demonstrates that positive influenza self-test results significantly increase intentions to seek healthcare and reduce transmission behaviors, while negative results decrease transmission-reducing intentions, highlighting the need for clear guidance to maximize public health benefits and minimize unintended consequences.

Original authors: Sherina Lowe, Rhiannon Phillips, Jiawen Liu, Michael L. Beeton, Kathy Hughes, Lewis Bott

Published 2026-07-10

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Sherina Lowe, Rhiannon Phillips, Jiawen Liu, Michael L. Beeton, Kathy Hughes, Lewis Bott

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you're feeling terrible: your head is pounding, your throat feels like it's full of sand, and you're burning up with a fever. Now, picture two different paths your day could take. In one path, you just feel sick and wonder what to do. In the other, you grab a little box from the shelf, take a quick test, and get a piece of paper telling you exactly what's wrong.

A team of researchers decided to see what happens when people get that piece of paper. They didn't just ask people what they would do; they ran a giant, digital experiment with 1,200 adults in the UK. They asked everyone to imagine they were sick and report what they'd do without a test. Then, they asked the exact same people to imagine the same symptoms again, but this time, they were randomly told they had either a "Positive" result (you have the flu) or a "Negative" result (you don't have the flu).

Here is the twist: The paper suggests that getting a test result acts like a magic switch that flips your brain's behavior, but the switch doesn't always point in the direction the health officials want.

The "Positive" Switch: A Double-Edged Sword

When the participants got a Positive result, it was like a giant red siren went off in their heads.

The Good News: They suddenly wanted to do the right thing to stop the virus from spreading. Their intention to stay home from work and avoid friends jumped up significantly. The data shows a massive boost here, with a score increase of 0.668 on their "stop the spread" scale.
The Not-So-Good News: That same red siren made them want to rush to the doctor's office or the hospital emergency room (A&E). The study found that people with a positive result were much more likely to say, "I'm going to the GP" or "I'm going to A&E," with a score increase of 0.169.

Why is this a problem? The paper points out that current health advice for regular people (who aren't super vulnerable) says: "Stay home, rest, and maybe ask a pharmacist." It does not usually say "Go to the emergency room." So, the test result made people want to visit places they probably didn't need to visit, potentially clogging up the system.

The "Negative" Switch: The False Reassurance Trap

Now, imagine the test came back Negative.

The Surprise: The participants didn't suddenly run to the doctor. Their plans to see a GP or go to A&E stayed exactly the same as if they hadn't taken a test at all. The change was tiny, almost zero (0.010).
The Danger: However, the "stop the spread" switch got turned down. People who got a negative result said they were less likely to stay home or avoid friends compared to when they had no test at all. Their score dropped by 0.260.

The Paper's Warning: The authors suggest this is risky. Just because a test says "No Flu" doesn't mean you aren't contagious with something else (like a different virus). But the paper argues that the negative result gave people a false sense of security, making them feel safe enough to go back to their normal social lives, even though they might still be sick.

Who is this about?

The study looked at the whole group and found these patterns held true for most people. Interestingly, the researchers checked if "clinically vulnerable" people (like those over 65 or with weak immune systems) acted differently.

The Finding: The paper suggests that the "rush to the doctor" reaction was mostly driven by people who weren't clinically vulnerable. For the vulnerable group, the study found no significant link between getting a positive test and a sudden jump in wanting to see a doctor; their behavior didn't change significantly based on the result.
The Age Factor: The study also noted that older participants generally wanted to see a doctor less often than younger ones, regardless of the test result.

What the Paper Rules Out

It's important to know what this study didn't find.

It's not about symptom severity: The paper explicitly rules out the idea that people with positive results felt worse physically. The symptoms were the same in the story for everyone. The change in behavior came purely from the label of the test result, not from feeling more sick.
It's not a guarantee of real life: The authors are careful to say these are intentions (what people said they would do in a story), not a record of what they actually did in the real world. They also note that in the real world, positive tests might be rarer than in their experiment, which could change the numbers.
It's not a ban on testing: The paper does not argue that self-testing is bad. Instead, it suggests that without clear instructions on how to read the results, the test might cause more confusion than clarity.

The Bottom Line

The paper suggests that influenza self-tests are like a powerful tool that can either help or hurt, depending on how you read the manual.

If you get a Positive: You are more likely to stay home (good!) but also more likely to clog up the emergency rooms (bad!).
If you get a Negative: You might stop taking precautions and go out, even if you're still contagious (risky!).

The researchers conclude that as these tests become more common, we need better guidance. We need to tell people exactly what to do when they see a "Positive" or "Negative" line, so the test helps us stay safe without accidentally making the healthcare system crash or giving us a false sense of safety. The study doesn't say the tests are broken; it just says we need to teach people how to use them properly.

Technical Summary: Effects of Influenza Self-Test Results on Healthcare-Seeking and Transmission-Related Behavioural Intentions

Problem Statement

Seasonal influenza imposes a significant global health burden, necessitating both vaccination and behavioural interventions to mitigate transmission and manage healthcare demand. While self-testing kits for Influenza A and B have recently become commercially available to the public, there is a critical gap in understanding how individuals interpret and act upon these results outside of pandemic contexts. Existing evidence suggests that self-testing could yield public health benefits (e.g., timely treatment, prompt self-isolation) but also carries risks, such as delayed care due to false negatives or unnecessary healthcare utilization due to false positives or uncertainty. Without empirical data on how self-test results influence downstream behavioural intentions, it is difficult to design appropriate regulations or effective public health guidance. This study addresses the lack of evidence regarding the behavioural consequences of influenza self-testing in a non-pandemic setting.

Methodology

The study employed a scenario-based experimental design with a UK age-representative sample of N = 1,200 adults recruited online via Prolific. The design utilized a mixed approach:

Within-subjects factor: Self-test condition (No-test vs. Test).
Between-subjects factor: Test result (Positive vs. Negative), with random allocation.
Procedure: Participants first completed a baseline scenario describing influenza-like symptoms (headache, sore throat, fever, cough, fatigue) without self-testing. They were then randomly allocated to a second scenario where they were informed they had taken a self-test yielding either a positive or negative result.
Measures: Participants reported their intentions on a 7-point Likert scale regarding:
1. Healthcare-seeking: Contacting a GP, calling NHS 111, seeking pharmacist advice, and attending Accident & Emergency (A&E).
2. Transmission-related behaviour: Reducing social contact and taking time off work.
Analysis: Data were analyzed using Linear Mixed-Effects Models (LME) to account for repeated measures and individual differences, with age as a covariate. Follow-up item-level analyses used Wilcoxon signed-rank tests with Bonferroni adjustment. The study also stratified analyses by clinical vulnerability status.

Key Results

The study found that self-test results significantly altered behavioural intentions, with divergent effects based on the test outcome:

Healthcare-Seeking Intentions:
- Positive Results: Participants receiving a positive result reported significantly higher healthcare-seeking intentions compared to the no-test condition ( $b = 0.169$ , $p < .001$ ). This included increased intentions to see a GP ( $p < .001$ ) and attend A&E ( $p < .001$ ).
- Negative Results: No significant difference in healthcare-seeking intentions was observed between the negative test condition and the no-test condition ( $b = 0.010$ , $p = .761$ ).
- Age Effect: Older participants showed smaller increases in healthcare-seeking intentions following a positive result compared to younger participants.
Transmission-Related Intentions:
- Positive Results: Significantly increased intentions to reduce transmission (e.g., reducing social contact, taking time off work) ( $b = 0.668$ , $p < .001$ ).
- Negative Results: Significantly decreased intentions to engage in transmission-reducing behaviours ( $b = -0.260$ , $p < .001$ ). Participants were less likely to reduce social contact or take time off work when they received a negative result compared to the baseline.
Vulnerability Subgroups:
- The pattern of increased healthcare-seeking for positive results and reduced transmission precautions for negative results was primarily driven by non-vulnerable participants.
- Clinically vulnerable participants did not show a significant interaction between test condition and result for healthcare-seeking, though they did show similar transmission-related behavioural shifts.

Key Contributions

Empirical Evidence on Self-Testing: This is one of the first studies to isolate the causal effect of influenza self-test results on behavioural intentions in a non-pandemic context, moving beyond acceptability studies to measure specific downstream actions.
Identification of Behavioral Divergence: The study demonstrates that self-testing does not uniformly drive "correct" public health behavior. While positive results encourage isolation (a benefit), they also drive potentially unnecessary visits to GPs and A&E (a cost). Conversely, negative results fail to maintain necessary precautionary behaviors, potentially leading to continued transmission.
Refinement of Theoretical Frameworks: The findings support the Common-Sense Model of Self-Regulation (CSM), suggesting that a diagnostic label (positive test) alters illness identity and perceived severity, thereby shifting coping behaviors regardless of actual symptom severity.

Significance and Claims

The authors claim that the data presents a dual-edged sword for public health: influenza self-testing offers benefits but also incurs costs depending on result interpretation.

Misalignment with Guidance: The study highlights a misalignment between user behavior and current NHS guidance. Positive results drove users toward A&E and GPs, whereas guidance for non-vulnerable individuals emphasizes self-care and pharmacy advice.
Risk of False Reassurance: Negative results led to a reduction in precautionary behaviors. The authors note that this is problematic because negative results do not guarantee the absence of influenza (due to sensitivity limitations) or other transmissible respiratory infections (e.g., COVID-19, RSV).
Policy Implications: The paper argues that as self-testing becomes widespread, clear guidance on result interpretation is essential. Specifically, guidance must address how to respond to negative results to prevent the erosion of precautionary behaviors and clarify that negative results do not rule out other infections.
Pandemic Preparedness: The findings suggest that testing strategies depend not only on diagnostic accuracy but also on behavioral responses. Future pandemic preparedness must incorporate behavioral evidence alongside epidemiological modeling, rather than treating behavioral responses as secondary implementation considerations.

The study concludes modestly that while self-testing is not inherently negative, its implementation requires careful management of communication and guidance to maximize public health benefits and minimize unintended consequences, such as unnecessary healthcare strain or reduced isolation.