Mental health is an important component of public health, especially in times of crisis. However, monitoring public mental health is difficult because data are often patchy and low-frequency1,2,3. Here we complement established approaches by using data from helplines, which offer a real-time measure of ‘revealed’ distress and mental health concerns across a range of topics4,5,6,7,8,9. We collected data on 8 million calls from 19 countries, focusing on the COVID-19 crisis. Call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase was driven mainly by fear (including fear of infection), loneliness and, later in the pandemic, concerns about physical health. Relationship issues, economic problems, violence and suicidal ideation, however, were less prevalent than before the pandemic. This pattern was apparent both during the first wave and during subsequent COVID-19 waves. Issues linked directly to the pandemic therefore seem to have replaced rather than exacerbated underlying anxieties. Conditional on infection rates, suicide-related calls increased when containment policies became more stringent and decreased when income support was extended. This implies that financial relief can allay the distress triggered by lockdown measures and illustrates the insights that can be gleaned from the statistical analysis of helpline data.
The state of population mental health is difficult to measure. This could lead policymakers to neglect mental health issues relative to aspects that can be measured more easily—especially during fast-moving crisis situations1,2,3. We propose using helpline data as a source of real-time information on the state of public mental health. Helpline data have two main advantages. First, helpline calls can be considered as a manifestation of revealed distress and mental health concerns. Callers incur the mental and time cost of reaching out without having been prompted to do so. Therefore, helpline calls resemble clinical data by offering a measure of mental health that is unaffected by researchers’ study design and framing. Second, information about helpline calls is recorded digitally with daily frequency and covers a wide range of conversation topics.
Telephone helplines are well-established institutions for mental health protection and suicide prevention in many countries, and they offer support immediately, anonymously, cheaply and accessibly10,11,12. Some helplines specialize in particular issues such as suicide, children or violence against women. Suicide helplines, for example, have been shown to reduce suicide rates13, and call volumes of suicide prevention helplines have been shown to relate to the incidence of actual suicides14.
Using this approach in relation to the COVID-19 crisis, we documented the growth and composition of helpline calls as well as their pandemic-related determinants. Helplines take on particular relevance in a pandemic, when face-to-face contacts carry infection risks and may even be impossible owing to stay-at-home orders4,5,6,7,8,9. We collected data from 23 helplines in 14 European countries, the USA, China, Hong Kong, Israel and Lebanon. The total dataset covers 8 million individual calls made between 2019 and early 2021 (Extended Data Table 1). The panel structure of the data enables us to exploit differences in the timing of local infection waves and policy measures to isolate their separate effects on helpline calls. This is a first-order issue for policymakers, as interventions designed to contain infections might also affect mental health by exacerbating unemployment, financial stress, loneliness, relationship problems and pre-existing mental vulnerabilities. These are, in turn, well-recognized risk factors for suicide15,16,17,18,19,20,21,22.
We consider the analysis of helpline calls as a complement, and not a substitute, for established approaches. Mental health surveys23,24,25,26 and suicide statistics27,28,29 are highly informative, but they tend to be low frequency and available with a lag. Higher-frequency monitoring has been performed in the context of the COVID-19 pandemic on the basis of online searches as recorded by Google Trends30,31,32,33, by tracking visits to emergency departments34,35, and by monitoring calls to the police for help with domestic disputes36,37,38. Helpline data contribute a measurement tool that is both broadly available and well targeted on the mental health concerns of a particularly vulnerable segment of the population.
Results
Increased call volumes across helplines
When we pool and size-weight the data for the 21 helplines for which we have daily data (Extended Data Table 1a, b), we observe a peak call volume, reached six weeks after the outbreak of the pandemic, that exceeds the pre-pandemic level by 35% (95% confidence interval (CI): 22.6, 48.3; P < 0.001) (Fig. 1a). With the country-specific outbreak defined as the date when more than 1 SARS-CoV-2 infection per 100,000 inhabitants was recorded39, we see a significant increase of 13.5% (95% CI: 1.6, 25.5; P = 0.027) for the first time in week 3. After the peak in week 6, volumes gradually decreased again, to 6.2% (95% CI: −0.2, 12.6; P = 0.058) above pre-pandemic levels39 by around week 11. When we instead define the starting point of the pandemic as the entry into force of the first shelter-in-place (SIP) order40, we observe an increase of 11.2% (95% CI: 3.1, 19.4; P = 0.007) (Fig. 1b) by week 2, steadily elevated call volumes from week 3 (+27%; 95% CI: 19.1, 35.0; P < 0.001) until about week 8 (+22.6%; 95% CI: 15.2, 30.1; P < 0.001), and a decrease thereafter40. The different time profiles are mainly explained by the fact that on average, SIP orders were issued 2 to 3 weeks after local outbreaks (Extended Data Fig. 1, Extended Data Table 1).
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