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A UK study published in BMJ Mental Health found that psychological distress rose over 2009–2023, with more consistent increases after 2015. In its statistical analysis, the June 2016 Brexit referendum and the first COVID-19 lockdown were associated with the largest immediate rises; smaller gradual increases followed Russia’s invasion of Ukraine and the UK government’s September 2022 mini-budget. Distress remained above pre-pandemic levels at the study’s end. The findings describe population-level associations, not proof that any single event caused mental illness in an individual.
What the study measured
Annie Jeffery and colleagues analyzed UK Household Longitudinal Study data from 87,857 people aged 16 and older. Participants were observed in survey waves from 2009 to 2024, while the study’s reported overall trend in psychological distress covers 2009 to 2023.
The researchers used the 12-item General Health Questionnaire (GHQ-12), a screening measure of psychological distress scored from 0, the least distress, to 36, the most. It is not a diagnosis of a mental health condition. The study estimated that mean distress increased by 1.085 GHQ-12 points from 2009 to 2023 (95% credible interval 0.987 to 1.184). Scores were comparatively stable until 2015 and rose more consistently thereafter; the estimated increase by 2019 relative to 2009 was 0.617 points.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →The paper, “Impact of 15 years of social, political and economic shocks on population mental health in the UK: a longitudinal, Bayesian quasi-experimental analysis,” was published in BMJ Mental Health on 24 July 2026.
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Which events were examined
The researchers set interruption dates for five major events. They used Bayesian interrupted time-series models to estimate whether distress shifted immediately around an event and whether its subsequent month-to-month trend changed.
| Event | Date used in the analysis |
|---|---|
| EU referendum result | 24 June 2016 |
| First COVID-19 lockdown | 26 March 2020 |
| Second COVID-19 lockdown | 6 January 2021 |
| Russia’s invasion of Ukraine | 24 February 2022 |
| UK government mini-budget | 23 September 2022 |
The authors modeled the shocks separately because placing all event variables into one interrupted time-series model risked collinearity. They also conducted a secondary before-and-after comparison that mutually adjusted for the shocks. The estimates below are therefore not a simple ranking of each event’s independent causal effect.
Immediate changes and later trends differed by event
An immediate level change is an estimated shift around the selected interruption date. A slope change is an estimated change in the subsequent monthly trend. They answer different questions: an event can have no detectable immediate shift but still be associated with a gradual change afterward.
| Event | Estimated immediate GHQ-12 change | Estimated subsequent trend |
|---|---|---|
| Brexit referendum | Increase of 0.117 points (95% CrI 0.029 to 0.205) | No value stated in the study summary |
| First COVID-19 lockdown | Increase of 0.649 points (95% CrI 0.531 to 0.767) | Decline of 0.03 points per month (95% CrI −0.04 to −0.02) |
| Second lockdown | No evidence of an immediate overall change | No value stated in the study summary |
| Russia’s invasion of Ukraine | No evidence of an immediate overall change | Increase of 0.010 points per month (95% CrI 0.004 to 0.023) |
| September 2022 mini-budget | No evidence of an immediate overall change | Increase of 0.015 points per month (95% CrI 0.005 to 0.034) |
The clearest immediate estimate was for the first lockdown, followed by the referendum. After the lockdown-associated jump, the modeled average score declined gradually, but it did not return to pre-pandemic levels by the end of the study. The absence of evidence for an immediate jump after the second lockdown, Ukraine invasion or mini-budget does not rule out later or indirect effects; for the latter two events, the estimated change appeared in the monthly trend instead.
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What the GP-help equivalents mean
The Guardian translated the study’s modeled changes into equivalents of about 120,000 more people seeking GP help for depression after the Brexit referendum and about 900,000 after the first lockdown. It also reported equivalents of about 15,000 more per month after Russia’s invasion of Ukraine and 23,000 more per month after the mini-budget. These are modeled translations reported by the newspaper, not counts of additional GP appointments or observed people who sought care.
The distinction matters because the study measured GHQ-12 distress scores, not GP attendance. A small shift in a population average may correspond to many people shifting across a screening threshold, but it does not mean each person experienced a clinically meaningful deterioration or needed treatment.
How results varied across groups
The study found that the overall pattern did not apply evenly across demographic and socioeconomic groups.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitches- Young people: Participants aged 16–24 had the greatest increase in distress over the study period, with distress peaking in 2020. Their distress was already increasing before the selected shocks, so the findings do not attribute that longer-term rise to those events alone.
- Women and men: After the first lockdown, the estimated immediate increase was larger for women (0.862 GHQ-12 points) than for men (0.385 points).
- Long-term sick or disabled participants: This group reported the highest distress across the follow-up.
- Deprivation: Greater deprivation was associated with worse distress over time, and deprivation-related inequalities persisted.
These subgroup findings describe differences across the follow-up or for a particular event; they should not be read as evidence that the same groups had the strongest response to every shock.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the findings can—and cannot—show
An interrupted time-series analysis can test whether a population measure changed around a defined event and whether its trend shifted afterward. The authors interpret the pattern as evidence that major shocks can contribute to changes in population mental health. But this observational, quasi-experimental design cannot establish that an event caused an individual’s distress, identify which participants were personally affected, or diagnose anyone.
- The measure is limited: GHQ-12 is one screening measure and cannot capture every form of distress or establish a clinical diagnosis.
- Timing is uncertain: The chosen interruption date may not match when psychological effects began. Anticipatory responses or delayed effects may be missed.
- Trends were simplified: Post-event changes were modeled as linear trends, which may not reflect a more complicated course.
- Some later events have less evidence: There were relatively few survey observations around and after the Ukraine invasion and mini-budget, which may have limited the ability to detect changes.
- Other influences remain relevant: Younger participants’ distress was rising before the selected shocks, and the analysis cannot isolate all other factors shaping mental health over 15 years.
Study lead Annie Jeffery told the Guardian: “We have shown that major government decisions and current global events can have substantial impacts on people’s mental health.” Andy Bell, chief executive of the Centre for Mental Health, stressed the cumulative context, telling the newspaper: “It’s also clear that rising distress in the population is not due to a single cause but the effect of all these things added together, made worse by years of austerity giving fewer buffers against ‘shocks’ like this.”
The strongest supported conclusion is that UK population distress rose over time and that some major events coincided with measurable shifts in its level or trajectory. The study does not show that Brexit, COVID-19, the Ukraine invasion or the mini-budget alone caused a lasting decline in every person’s mental health.
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