What’s wrong with Gen Z? – Post-pandemic persistence of depression and anxiety symptoms among young adults in Germany

What’s wrong with Gen Z? – Post-pandemic persistence of depression and anxiety symptoms among young adults in Germany | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article What’s wrong with Gen Z? – Post-pandemic persistence of depression and anxiety symptoms among young adults in Germany Lena Peter, Emily Sitarski, Jasmin Hammann, Franziska Köhler-Dauner, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8056528/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted 7 You are reading this latest preprint version Abstract Background Adolescence and early adulthood are crucial periods marked by identity formation and increased vulnerability to mental health issues, with most mental disorders beginning before the age of 25. Today’s youth face amplified risks due to overlapping crises like the COVID-19 pandemic, climate change and economic instability, potentially disrupting age-typical developmental tasks and contributing to rising rates of anxiety and depression. This study aimed to investigate the longitudinal development of anxiety and depression symptoms across four generational cohorts. Methods This study drew on data from the German subsample of the ongoing “SOSEC – Social Sentiment in Times of Crises” project. In total, 25,143 individuals contributed 112,858 survey entries, responding to items on depression and anxiety symptoms based on modified versions of the PHQ-9 and GAD-2. Generational groups were determined by year of birth, with particular attention given to Generation Z. Linear mixed-effects models were applied to assess how generation, survey period, gender, and employment status influenced mental health symptoms. The analysis also included interaction terms and post-hoc comparisons between groups. Results Generation Z showed significantly higher and stable levels of depression and anxiety symptoms than all older generations across all survey periods (all p < .001). Women reported more symptoms than men and employment was linked to lower symptom levels. Conclusions The findings indicate a persistently elevated mental health burden among Generation Z, underscoring the need for early intervention, stepped-care approaches, and targeted prevention strategies tailored to this cohort’s developmental challenges. Protective factors such as employment highlight potential entry points for indicated prevention, while broader support during key life transitions, such as entering the workforce or higher education, can serve as universal preventive measures. Implementing multi-level, stepwise care and preventive interventions is crucial to mitigate long-term mental health consequences, strengthen resilience, and promote adaptive coping among young people facing ongoing societal crises. generational differences Generation Z mental health depression anxiety prevention Figures Figure 1 Figure 2 1. Introduction Adolescence and early adulthood are critical life phases in which individuals face a broad range of developmental tasks. In addition to achieving biological and sexual maturity, this period involves the consolidation of personal identity, the formation of intimate peer relationships and the gradual development of autonomy within a given socio-cultural context [ 1 , 2 ]. These formative years also play a central role in shaping long-term health behaviors and attitudes, as values and patterns established in this stage often persist into adulthood [ 3 ]. From a clinical perspective, adolescence and early adulthood represent a period of heightened vulnerability for the onset of mental disorders. It is estimated that half of all diagnosable mental health disorders begin during adolescence and that up to three-quarters manifest by the age of 25 [ 4 – 6 ]. While this developmental stage has always implied a certain psychological fragility, the pressure on today’s youth appears especially severe. In addition to the traditional developmental challenges, contemporary adolescents and young adults are confronted with what has been described as a “polycrisis” – a convergence of overlapping societal crises including the COVID-19 pandemic, climate change, geopolitical conflict, economic precarity and political instability [ 6 , 7 ]. These cumulative stressors have the potential to disrupt normative developmental trajectories and increase the risk of internalizing disorders such as depression and anxiety [ 8 ]. An increase in psychosocial disorders among young people has been documented since the mid-twentieth century [ 9 ] but the COVID-19 pandemic in particular has exemplified how such crises can disproportionately affect children, adolescents and young adults. National studies report rising rates of anxiety and depression symptoms during the pandemic, especially among younger individuals and women [ 10 , 11 ]. Findings across Europe similarly show a significant increase in symptoms of depression and anxiety among children and adolescents during this period [ 12 , 13 ]. Interestingly, for both depression and anxiety symptoms the effects were significantly higher, when the restrictions were more stringent or school-closures occurred [ 12 , 13 ]. Limited contact with peers, financial strain and returning to the parental home were identified as further risk factors for the decline of life satisfaction and mental health over the COVID-19 pandemic among young people [ 14 ]. From a developmental psychology perspective, these findings are hardly surprising, as children and adolescents are in a transitional phase and especially adolescents primarily navigate their age-typical developmental tasks within their peer group [ 2 , 15 , 16 ] Consequently, they were more strongly affected by pandemic-related contact restrictions and school-closures than adults, who were able to draw on social experiences and relationships. As a potential consequence, mental health problems among young people increased to levels atypical for their age, and this rise may be particularly persistent in this age cohort, as the pandemic disrupted age-typical developmental tasks. Generational comparisons further highlight the burden on younger cohorts. The 2022 McKinsey Health Survey shows that Generation Z reports significantly poorer mental health than Generations Y, X and the Baby Boomer cohort [ 17 ]. These findings are particularly troubling given the long-term implications of early-onset mental health problems, which can affect educational achievement, social integration and general health outcomes over the life course [ 18 , 19 ]. Moreover, the public discourse surrounding young people’s mental health is often laden with stigma and generational stereotypes. Narratives portraying Generation Z as emotionally fragile or ill-equipped to handle adversity not only lack empirical basis but may also undermine efforts to encourage help-seeking and open dialogue as well as reinforce self-stigmatization in young people facing mental health challenges. Stigma has been implicated in worsening mental health trajectories and treatment outcomes [ 20 , 21 ] as well as being a significant barrier to seeking treatment [ 22 ], reflecting the broader social and cultural barriers that influence psychological well-being. These findings underscore the importance of empirically grounded, generation-sensitive research to better understand how different age cohorts experience, respond to, and cope with societal crises. Since cross-sectional studies typically offer only a momentary snapshot, our analyses aimed to observe whether previously reported findings on this topic are reflected in our data. This study investigates the trajectories of depression and anxiety symptoms over a period of more than two and a half years in a large, representative German sample encompassing four generational cohorts. More specifically, it examines how these symptoms evolve during times of societal crisis and whether younger generations, particularly Generation Z, show higher levels of depression and anxiety than older cohorts. Based on previous evidence, we expect that Generation Z will report significantly higher levels of depression and anxiety symptoms compared to the older generations. 2. Methods 2.1 Design This research was carried out as part of the “SOSEC – Social Sentiment in Times of Crises” project, a representative panel survey conducted in both Germany and the United States. The project aims to examine and compare trends in social sentiment across the two countries. To this end, roughly 1,500 participants in Germany and 3,000 participants in the United States take part in an online survey on a weekly to bi-weekly basis, which started in November 2022 and is still ongoing. For the present study, only the German dataset spanning November 2022 to April 2025 was analyzed. 2.2 Participants The survey commenced in November 2022, with respondents receiving the same set of questions through an app at weekly to bi-weekly intervals. By April 2025, a total of 75 survey waves had been completed, yielding 122,120 survey entries from 26,237 participants. Participants under 18 years of age and responses not completed on the day of the survey were excluded. The final dataset, containing complete information on the variables of interest, included 25,143 participants and 112,858 survey entries. 2.2 Measures Depression symptoms were measured with two adapted items out of the PHQ-9 [ 23 ] that were rated on a 7-point Likert scale ranging from 1 (fully agree) to 7 (disagree at all). The two items were “I have little interest or pleasure in doing things.” and “I feel down, depressed or hopeless.”. Anxiety symptoms were measured with the adapted items out of the GAD-2 [ 24 ] “I feel not able to stop or control worrying.” and “I feel nervous, anxious or on edge.” that were rated on that same 7-point Likert scale. The two-item scale measuring depression symptoms achieved a Spearman-Brown coefficient of 0.879 and the one measuring anxiety symptoms achieved a coefficient of 0.796, both indicating acceptable internal consistency. For further calculation, the items were reversed, and the mean value was calculated, so that higher values indicate higher approval. Generational groups were determined based on participants’ reported year of birth. Following Schnetzer [ 25 ], the cohorts were defined as Generation Z (1995–2007), Generation Y (1980–1994), Generation X (1965–1979), and Baby Boomers/Traditionalists (1925–1964). For the purposes of this study, the Traditionalist and Baby Boomer cohorts were merged to simplify the analysis and presentation of generational differences. Since the focus is on Generation Z, separating the two oldest groups was deemed unnecessary for addressing the research questions. 2.3 Analysis Statistical analyses were conducted using R version 4.4.3, with a significance level of α = .05 applied throughout. Hypotheses were evaluated using linear mixed-effects models via the lmerTest package [ 26 ]. Given that only 40.5% of participants completed the survey more than once, models assumed a fixed slope. To capture medium-term trends and minimize short-term variability, data were aggregated into three-month intervals, resulting in ten survey periods for the analysis. This aggregation also simplified the interpretation of generational trajectories and reduced model complexity. For sensitivity purposes, the data were additionally aggregated into two- and four-month intervals. As presented in Additional file 1, the overall patterns of results remained highly consistent, supporting the robustness of the three-month aggregation. Main effects and interaction terms were examined using analysis of variance with type III sums of squares, implemented via the anova() function from the car package [ 27 ]. The mean values of depression and anxiety symptoms served as dependent variables, while generation, survey period, gender, employment status and the interaction between generation and survey period were included as predictors. Post-hoc comparisons were performed using the emmeans package [ 28 ] to identify specific group differences. 3. Results 3.1 Descriptive statistics Participants ranged in age from 18 to 98 years. The largest proportion (36.7%) belonged to Generation Z, followed by 24.6% from Generation Y, 19.2% from Generation X, and 19.4% from the combined Baby Boomer/Traditionalist group. A majority of respondents were female (55.0%). Across survey entries, most participants reported being employed (63.4%). The mean value for depression symptoms was 3.08 (SD = 1.64) and for anxiety symptoms it was 3.39 (SD = 1.60). Individual participation in the survey ranged from 1 to 64 entries, with a mean of 4.49 (SD = 7.98). 3.2 Linear mixed-effects models Linear mixed-effects models were employed to evaluate the proposed hypotheses. Initially, the intraclass correlation was calculated using an intercept-only model for each outcome. For depression symptoms, the intercept-only model produced an intraclass correlation of 0.806, indicating that 80.6% of the total variance is due to differences between individuals. Anxiety symptoms showed a comparable pattern, with an intraclass correlation of 0.745. These results justify the use of linear mixed-effects models to account for the nested structure of repeated surveys within individuals. Analysis of depression symptoms revealed significant main effects for generation (χ² = 808.06, p < .001), survey period (χ² = 103.75, p < .001), gender (χ² = 71.13, p < 001), and employment status (χ² = 176.83, p < .001). Additionally, a significant interaction between generation and survey period emerged (χ² = 89.93, p < .001), indicating that depression symptom trajectories over time varied across generations. Female participants exhibited significantly higher depression symptom levels than males ( b = 0.16, SE = 0.02, t = 8.43, p < .001), whereas being employed was associated with lower levels of depression symptoms ( b = −0.26, SE = 0.02, t = −13.30, p < .001), controlling for all other predictors in the model. Post-hoc comparisons demonstrated that Generation Z consistently reported higher depression symptoms than all older generations across all survey periods (all p < .001). Differences between Generation Z and the Baby Boomer/Traditionalist cohort ranged from 1.055 to 1.408 scale points. Comparisons with Generation X yielded slightly smaller differences, ranging from 0.501 to 0.765 points, while differences with Generation Y were the smallest but still significant, ranging from 0.192 to 0.376 points. A full summary of the depression symptom results is presented in Additional file 2. In addition to generational differences, descriptive trends across the ten survey periods were examined. Among Generation Z, the predicted depression symptom levels slightly decreased between late 2022 and summer 2023, followed by a continuous increase through early 2025. Similar but less pronounced patterns were observed in Generations Y and X. Depression symptoms in Baby Boomers/ Traditionalists remained comparatively stable and consistently lower across all time points. Figure 1 displays the estimated means and 95% confidence intervals over time. Figure 1 Estimated marginal means and 95% CI of depression symptoms across all generations and survey periods [Figure 1] Notes. Values are based on fixed effects estimates from the linear mixed-effects model. A comparable pattern emerged for anxiety symptoms. Significant main effects were observed for generation (χ² = 745.30, p < .001), survey period (χ² = 40.66, p < .001), gender (χ² = 327.69, p < .001), and employment (χ² = 130.46, p < .001), as well as a significant interaction between generation and survey period (χ² = 86.57, p < .001). Females reported higher anxiety symptom levels than males ( b = 0.32, SE = 0.02, t = 18.10, p < .001), while employment was linked to lower anxiety levels ( b = −0.22, SE = 0.02, t = −11.42, p < .001), after accounting for other predictors. Post-hoc contrasts revealed that Generation Z consistently exhibited higher anxiety symptoms than each of the older generations throughout all survey periods (all p < .001). Estimated differences between Generation Z and Baby Boomers/Traditionalists ranged from 1.158 to 1.436 points, while differences with Generation X varied between 0.638 and 0.775 points. The smallest but still significant differences were observed in comparison with Generation Y, ranging from 0.313 to 0.412 points. A complete overview of the anxiety symptom results can be found in Additional file 3. Across the ten survey periods, anxiety symptoms showed small temporal fluctuations across all generations. In Generation Z, estimated means declined slightly from late 2022 to mid 2023, followed by a gradual and continuous increase through early 2025. A similar but less pronounced pattern was observed for Generation Y, with a mid period dip and subsequent rise toward the end of the observation window. Generation X showed comparable fluctuations, with a slight decrease early on and a subsequent increase in later survey periods. The Baby Boomers/ Traditionalists exhibited comparatively flatter trajectories, with only minimal variation over time and consistently lower symptom levels relative to the younger cohorts. These temporal trends are illustrated in Fig. 2, displaying the estimated means and 95% confidence intervals over time. Figure 2 Estimated marginal means and 95% CI of depression symptoms across all generations and survey periods [Figure 2] Notes. Values are based on fixed effects estimates from the linear mixed-effects model. 4. Discussion The aim of this study was to investigate the severity of symptoms of depression and anxiety in different generations and how these symptoms changed over a period of two and a half years. The results indicate a persistently elevated symptom level in Generation Z regarding depression as well as anxiety symptoms. Overall both, depression and anxiety symptoms, slightly increased over time in Generation Z, whereas for the Baby Boomers/ Traditionalists, for example, depression symptoms returned to their initial level in the last survey period and anxiety symptoms even decreased overall in descriptive terms. The results regarding generational differences in depression and anxiety symptoms are consistent with those of Fegert and colleagues [ 17 ], who also reported significantly poorer mental health in Generation Z than in all older Generations. Older data on the prevalence of depression symptoms in Germany provide comparable results, indicating that the prevalence of depression symptoms is highest among 18- to 29-year-olds and decreases with increasing age [ 29 ]. More recent data from the RKI [ 30 ] suggest an increased prevalence of depression symptoms in younger cohorts compared to older cohorts, especially for women. Regarding anxiety symptoms, the health report by the RKI [ 31 ] has found that prevalence decreases with age, at least for women. Taken together, the results of the present study are consistent with previous findings of increased psychological distress among younger cohorts. The descriptive reduction in both anxiety and depression symptoms from the end of 2022 to mid 2023, which can be observed across all generations, could be explained, for example, by the end of the COVID-19 pandemic and a subsequent stabilization of mental health which affected all generations. The subsequent increase in symptoms, particularly among Generation Z, coincides with accumulating socio-economic and geopolitical stressors, such as persistent inflation, the ongoing war in Ukraine, the escalation of the Middle East conflict, and rising political polarization in Germany. These contextual developments may have contributed to heightened psychological distress. 4.1 Limitations When interpreting the present results, several methodological constraints must be acknowledged. First of all, the longitudinal design of the study entails conceptual complexities. Multiple assessments do not only reflect cohort-related differences but inevitably capture momentary influences tied to specific economic, societal or social conditions. Consequently, the responses can mirror both relatively enduring generational characteristics and situational fluctuations triggered by current developments. This underlines that the observed trajectories may be shaped by the context of each survey period rather than by age cohort alone. This is also supported by the fact that the trajectories in the generations are in some cases very similar. Efforts to interpret those trajectories against the backdrop of global political developments remain hypothetical in nature. Although participation was incentivized, it was voluntary, meaning that potential self-selection processes cannot be ruled out. In the final dataset, 25,143 individuals were included, yet only 40.5% of them took part on more than one occasion. This indicates a notable degree of drop out. Across 75 survey waves, participants contributed on average 4.49 responses (SD = 7.98), a figure that calls for caution when drawing conclusions about changes over time. Further the number of repeated observations differed notably across generations. While members of Generation Z contributed on average fewer than two survey waves (M = 1.93, SD = 2.91), participation was more sustained in older cohorts. Generation Y averaged 3.75 observations (SD = 6.47), Generation X 5.92 (SD = 9.30) and Baby Boomers/ Traditionalists as many as 8.86 (SD = 11.80). These discrepancies imply that younger generations were less consistently represented over time, which may have affected the stability of their estimated trajectories and could contribute to differential precision across cohorts. Depression and anxiety symptoms were assessed using a mean value of two items which may not fully capture the multidimensional nature of those psychological constructs and limit construct validity [ 32 ]. Furthermore, validity may be limited because the results are based exclusively on quantitative self-report data, which may be distorted by socially desirable response behavior. 4.2 Conclusion and future directions This study provides robust evidence of generational differences in mental health, focusing on anxiety and depression across age groups. Generation Z consistently reported higher levels of depression and anxiety than older cohorts, potentially reflecting the unique pressures associated with this life stage as well as the long-term consequences of the COVID-19 pandemic in this age cohort. Longitudinal, population-based research is essential not only for identifying risk and resilience factors within and between generational groups, but also for observing the impacts of concurrent events that affect all generations equally. While such designs carry the limitation that situational fluctuations may co-occur, this feature also allows researchers to examine how different generations respond over time and how they navigate the return to post-pandemic normality. Our results support the statement of the Lancet Psychiatry Commission who emphasized that the Youth Mental Health Crisis is ongoing and requires urgent action [ 33 ]. This crisis might be reinforced by social and political factors, such as delayed or insufficient measures to address economic instability and limited resources that can exacerbate stress and anxiety. Media narratives that stigmatize young people are particularly harmful, overlooking the sacrifices Generation Z has made for the health and well-being of older generations, such as during the COVID-19 pandemic. Evidence that certain factors, such as being employed, are associated with lower symptom levels can inform preventive strategies. Supporting young people during key life transitions, such as entering the workforce or starting higher education, can serve both as indicated prevention for those at heightened risk and as universal prevention to strengthen coping during age-typical developmental challenges. The higher prevalence of symptoms among young people reflects a broader transitional problem in times of crises, highlighting the need for interventions that address the unique challenges of this life stage. Continuous monitoring of mental health trends and societal sentiment, as implemented in SOSEC, can act as an early warning system, guiding public health strategies and policy decisions to prevent further escalation of psychological strain among young people. Declarations Ethics approval and consent to participate: The ethics approval has been submitted by the German Association for Experimental Economic Research e.V., Institutional Review Board Certificate No. MSEIsPRB (https://gfew.de/ethik/MSEIsPRB), issued on September 13, 2023, and valid until September 12, 2025. The research was conducted in accordance with the Declaration of Helsinki. Informed consent to participate was obtained and documented by the panel provider CINT. Consent for publication: Not applicable. Availability of data and materials: The data that support the findings of this study are available from FZI Research Center for Information Technology, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of FZI Research Center for Information Technology. Competing interests: The authors declare that they have no competing interests. Funding: The present study draws on data from the ongoing Social Sentiment in Times of Crises (SOSEC), which is founded by the Alfred Landecker Foundation. Author’s contributions: JF conceptualized, organized and surveyed the SOSCE panel. LP and ES conceptualized this analysis and drafted the manuscript. Both contributed equally to this work and share first authorship. JH conducted the statistical analyses and assisted in drafting the manuscript. 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Supplementary Files AdditionalFile1.pdf File name: Additional file 1 File format: PDF Title: Table 1a – Sensitivity analysis of the survey period for depression symptoms Description: Sensitivity analysis examining whether the results of linear mixed-effects models, with depression symptoms as the dependent variable, differ when the survey period is divided into two-, three-, or four-month intervals. Title: Table 1b – Sensitivity analysis of the survey period for anxiety symptoms Description: Sensitivity analysis examining whether the results of linear mixed-effects models, with anxiety symptoms as the dependent variable, differ when the survey period is divided into two-, three-, or four-month intervals. AdditionalFile2.pdf File name: Additional file 2 File format: PDF Title: Table 2 – Post-hoc contrasts for depression symptoms Description: Contains post-hoc contrasts for depression symptoms, showing pairwise comparisons between generational groups across all survey periods, with Generation Z as the reference group. AdditionalFile3.pdf File name: Additional file 3 File format: PDF Title: Table 3 – Post-hoc contrasts for anxiety symptoms Description: Contains post-hoc contrasts for anxiety symptoms, showing pairwise comparisons between generational groups across all survey periods, with Generation Z as the reference group. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8056528","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":552160702,"identity":"15088200-cd44-4fcb-9224-610d4f2389a9","order_by":0,"name":"Lena Peter","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABGklEQVRIie2Pv0sDMRTHEwq55dlbX0mx/0LgoBQs+oe43BE4lxx2EicpBG7yx3p/Sel4pWvoLLgowk0OdREHiybnoUsUR4d8IOQ98j58XwgJBP4h/e+yVxMi0iEjVNtuYk/qVVh3oy1Tp0Cn4F8UEG4KXN7vSnS12tLl9CLm5oXPZjn0udaClnhMIll7FdhIpCbHwXWx4JVQwIYrnVqlmEPjjWGoBNJyjcLsLTiIc2CY6fXOKfbJq4yekldavuORgeZLqdsUPN36U2BsU2oUAMwqqlU+F0Pl/z6o8SQzclAZlhyAyFtFkA0WJTTexeLIJLfPy8M4vuw93MGb3B9VJ49IzqbFTSTvvTGObO5d4Md5C/UqgUAgEOj4ANZ1Tj+ikD1TAAAAAElFTkSuQmCC","orcid":"","institution":"University of Ulm","correspondingAuthor":true,"prefix":"","firstName":"Lena","middleName":"","lastName":"Peter","suffix":""},{"id":552160703,"identity":"a5bbe5c4-98ad-4761-8eda-5f3b7e0dd7c3","order_by":1,"name":"Emily Sitarski","email":"","orcid":"","institution":"University of Ulm","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"Sitarski","suffix":""},{"id":552160704,"identity":"96193736-2296-4453-875c-fb611c563112","order_by":2,"name":"Jasmin Hammann","email":"","orcid":"","institution":"University of Ulm","correspondingAuthor":false,"prefix":"","firstName":"Jasmin","middleName":"","lastName":"Hammann","suffix":""},{"id":552160705,"identity":"d794b837-5b59-4477-a700-72ff6d1109a7","order_by":3,"name":"Franziska Köhler-Dauner","email":"","orcid":"","institution":"University of Ulm","correspondingAuthor":false,"prefix":"","firstName":"Franziska","middleName":"","lastName":"Köhler-Dauner","suffix":""},{"id":552160706,"identity":"b5395003-5bd5-48c4-918b-29aa2ec85c89","order_by":4,"name":"Jörg M. Fegert","email":"","orcid":"","institution":"University of Ulm","correspondingAuthor":false,"prefix":"","firstName":"Jörg","middleName":"M.","lastName":"Fegert","suffix":""},{"id":552160707,"identity":"4a6589fd-7b8d-41e4-af21-720c9ce7f4cf","order_by":5,"name":"Jonas Fegert","email":"","orcid":"","institution":"Karlsruhe Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"","lastName":"Fegert","suffix":""}],"badges":[],"createdAt":"2025-11-07 11:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8056528/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8056528/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-026-27600-0","type":"published","date":"2026-04-30T15:57:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":97147937,"identity":"346dba9d-5a48-4d47-8656-52279951e9f4","added_by":"auto","created_at":"2025-12-01 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10:17:03","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95684,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/3bd2c49fa75f10212f5fcbc1.html"},{"id":97147938,"identity":"d96dcdd0-79a9-4dc5-972d-01433fd3ac5f","added_by":"auto","created_at":"2025-12-01 10:17:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEstimated marginal means and 95% CI of depression symptoms across all generations and survey periods\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes. \u003c/em\u003eValues are based on fixed effects estimates from the linear mixed-effects model.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/82881e6d982d38049ed85759.png"},{"id":97147829,"identity":"0e55ebf9-776f-4103-a91b-4e2eda300aaa","added_by":"auto","created_at":"2025-12-01 10:16:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13733,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEstimated marginal means and 95% CI of depression symptoms across all generations and survey periods\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes. \u003c/em\u003eValues are based on fixed effects estimates from the linear mixed-effects model.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/69dd92143f78b61c74ab102b.png"},{"id":108438799,"identity":"98f9335f-0d08-466f-a5c0-1a8db9811639","added_by":"auto","created_at":"2026-05-04 16:10:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":254736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/711ce8ec-dcb0-4ab3-a0ec-e797e93f3e16.pdf"},{"id":97147855,"identity":"ba8efe9a-8fcb-4179-beb7-db706c9fddcd","added_by":"auto","created_at":"2025-12-01 10:17:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":120457,"visible":true,"origin":"","legend":"\u003cp\u003eFile name: Additional file 1\u003c/p\u003e\n\u003cp\u003eFile format: PDF\u003c/p\u003e\n\u003cp\u003eTitle: Table 1a\u003cstrong\u003e – \u003c/strong\u003eSensitivity analysis of the survey period for depression symptoms\u003c/p\u003e\n\u003cp\u003eDescription: Sensitivity analysis examining whether the results of linear mixed-effects models, with depression symptoms as the dependent variable, differ when the survey period is divided into two-, three-, or four-month intervals.\u003c/p\u003e\n\u003cp\u003eTitle: Table 1b – Sensitivity analysis of the survey period for anxiety symptoms\u003c/p\u003e\n\u003cp\u003eDescription: Sensitivity analysis examining whether the results of linear mixed-effects models, with anxiety symptoms as the dependent variable, differ when the survey period is divided into two-, three-, or four-month intervals.\u003c/p\u003e","description":"","filename":"AdditionalFile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/957ddb0e0bcf3c1a90e1bcbc.pdf"},{"id":97147940,"identity":"8f8344c3-924c-46fb-8c51-cbc4a9a101ee","added_by":"auto","created_at":"2025-12-01 10:17:06","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":127540,"visible":true,"origin":"","legend":"\u003cp\u003eFile name: Additional file 2\u003c/p\u003e\n\u003cp\u003eFile format: PDF\u003c/p\u003e\n\u003cp\u003eTitle: Table 2\u003cstrong\u003e – \u003c/strong\u003ePost-hoc contrasts for depression symptoms\u003c/p\u003e\n\u003cp\u003eDescription: Contains post-hoc contrasts for depression symptoms, showing pairwise comparisons between generational groups across all survey periods, with Generation Z as the reference group.\u003c/p\u003e","description":"","filename":"AdditionalFile2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/dc6913ca6a7f57c78b3a5a48.pdf"},{"id":97147803,"identity":"58ea001f-9c04-4f48-8283-457d30d5b54f","added_by":"auto","created_at":"2025-12-01 10:16:58","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":135401,"visible":true,"origin":"","legend":"\u003cp\u003eFile name: Additional file 3\u003c/p\u003e\n\u003cp\u003eFile format: PDF\u003c/p\u003e\n\u003cp\u003eTitle: Table 3 – Post-hoc contrasts for anxiety symptoms\u003c/p\u003e\n\u003cp\u003eDescription: Contains post-hoc contrasts for anxiety symptoms, showing pairwise comparisons between generational groups across all survey periods, with Generation Z as the reference group.\u003c/p\u003e","description":"","filename":"AdditionalFile3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8056528/v1/ca87afb4d76998434ee3f875.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"What’s wrong with Gen Z? – Post-pandemic persistence of depression and anxiety symptoms among young adults in Germany","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAdolescence and early adulthood are critical life phases in which individuals face a broad range of developmental tasks. In addition to achieving biological and sexual maturity, this period involves the consolidation of personal identity, the formation of intimate peer relationships and the gradual development of autonomy within a given socio-cultural context [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These formative years also play a central role in shaping long-term health behaviors and attitudes, as values and patterns established in this stage often persist into adulthood [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFrom a clinical perspective, adolescence and early adulthood represent a period of heightened vulnerability for the onset of mental disorders. It is estimated that half of all diagnosable mental health disorders begin during adolescence and that up to three-quarters manifest by the age of 25 [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While this developmental stage has always implied a certain psychological fragility, the pressure on today\u0026rsquo;s youth appears especially severe. In addition to the traditional developmental challenges, contemporary adolescents and young adults are confronted with what has been described as a \u0026ldquo;polycrisis\u0026rdquo; \u0026ndash; a convergence of overlapping societal crises including the COVID-19 pandemic, climate change, geopolitical conflict, economic precarity and political instability [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These cumulative stressors have the potential to disrupt normative developmental trajectories and increase the risk of internalizing disorders such as depression and anxiety [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAn increase in psychosocial disorders among young people has been documented since the mid-twentieth century [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] but the COVID-19 pandemic in particular has exemplified how such crises can disproportionately affect children, adolescents and young adults. National studies report rising rates of anxiety and depression symptoms during the pandemic, especially among younger individuals and women [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Findings across Europe similarly show a significant increase in symptoms of depression and anxiety among children and adolescents during this period [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Interestingly, for both depression and anxiety symptoms the effects were significantly higher, when the restrictions were more stringent or school-closures occurred [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Limited contact with peers, financial strain and returning to the parental home were identified as further risk factors for the decline of life satisfaction and mental health over the COVID-19 pandemic among young people [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFrom a developmental psychology perspective, these findings are hardly surprising, as children and adolescents are in a transitional phase and especially adolescents primarily navigate their age-typical developmental tasks within their peer group [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Consequently, they were more strongly affected by pandemic-related contact restrictions and school-closures than adults, who were able to draw on social experiences and relationships. As a potential consequence, mental health problems among young people increased to levels atypical for their age, and this rise may be particularly persistent in this age cohort, as the pandemic disrupted age-typical developmental tasks.\u003c/p\u003e\u003cp\u003eGenerational comparisons further highlight the burden on younger cohorts. The 2022 McKinsey Health Survey shows that Generation Z reports significantly poorer mental health than Generations Y, X and the Baby Boomer cohort [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These findings are particularly troubling given the long-term implications of early-onset mental health problems, which can affect educational achievement, social integration and general health outcomes over the life course [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMoreover, the public discourse surrounding young people\u0026rsquo;s mental health is often laden with stigma and generational stereotypes. Narratives portraying Generation Z as emotionally fragile or ill-equipped to handle adversity not only lack empirical basis but may also undermine efforts to encourage help-seeking and open dialogue as well as reinforce self-stigmatization in young people facing mental health challenges. Stigma has been implicated in worsening mental health trajectories and treatment outcomes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] as well as being a significant barrier to seeking treatment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], reflecting the broader social and cultural barriers that influence psychological well-being.\u003c/p\u003e\u003cp\u003eThese findings underscore the importance of empirically grounded, generation-sensitive research to better understand how different age cohorts experience, respond to, and cope with societal crises. Since cross-sectional studies typically offer only a momentary snapshot, our analyses aimed to observe whether previously reported findings on this topic are reflected in our data. This study investigates the trajectories of depression and anxiety symptoms over a period of more than two and a half years in a large, representative German sample encompassing four generational cohorts. More specifically, it examines how these symptoms evolve during times of societal crisis and whether younger generations, particularly Generation Z, show higher levels of depression and anxiety than older cohorts. Based on previous evidence, we expect that Generation Z will report significantly higher levels of depression and anxiety symptoms compared to the older generations.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Design\u003c/h2\u003e\u003cp\u003eThis research was carried out as part of the \u0026ldquo;SOSEC \u0026ndash; Social Sentiment in Times of Crises\u0026rdquo; project, a representative panel survey conducted in both Germany and the United States. The project aims to examine and compare trends in social sentiment across the two countries. To this end, roughly 1,500 participants in Germany and 3,000 participants in the United States take part in an online survey on a weekly to bi-weekly basis, which started in November 2022 and is still ongoing. For the present study, only the German dataset spanning November 2022 to April 2025 was analyzed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Participants\u003c/h2\u003e\u003cp\u003eThe survey commenced in November 2022, with respondents receiving the same set of questions through an app at weekly to bi-weekly intervals. By April 2025, a total of 75 survey waves had been completed, yielding 122,120 survey entries from 26,237 participants. Participants under 18 years of age and responses not completed on the day of the survey were excluded. The final dataset, containing complete information on the variables of interest, included 25,143 participants and 112,858 survey entries.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measures\u003c/h2\u003e\u003cp\u003eDepression symptoms were measured with two adapted items out of the PHQ-9 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] that were rated on a 7-point Likert scale ranging from 1 (fully agree) to 7 (disagree at all). The two items were \u0026ldquo;I have little interest or pleasure in doing things.\u0026rdquo; and \u0026ldquo;I feel down, depressed or hopeless.\u0026rdquo;. Anxiety symptoms were measured with the adapted items out of the GAD-2 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] \u0026ldquo;I feel not able to stop or control worrying.\u0026rdquo; and \u0026ldquo;I feel nervous, anxious or on edge.\u0026rdquo; that were rated on that same 7-point Likert scale. The two-item scale measuring depression symptoms achieved a Spearman-Brown coefficient of 0.879 and the one measuring anxiety symptoms achieved a coefficient of 0.796, both indicating acceptable internal consistency. For further calculation, the items were reversed, and the mean value was calculated, so that higher values indicate higher approval.\u003c/p\u003e\u003cp\u003eGenerational groups were determined based on participants\u0026rsquo; reported year of birth. Following Schnetzer [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], the cohorts were defined as Generation Z (1995\u0026ndash;2007), Generation Y (1980\u0026ndash;1994), Generation X (1965\u0026ndash;1979), and Baby Boomers/Traditionalists (1925\u0026ndash;1964). For the purposes of this study, the Traditionalist and Baby Boomer cohorts were merged to simplify the analysis and presentation of generational differences. Since the focus is on Generation Z, separating the two oldest groups was deemed unnecessary for addressing the research questions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted using R version 4.4.3, with a significance level of α\u0026thinsp;=\u0026thinsp;.05 applied throughout. Hypotheses were evaluated using linear mixed-effects models via the \u003cem\u003elmerTest\u003c/em\u003e package [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Given that only 40.5% of participants completed the survey more than once, models assumed a fixed slope. To capture medium-term trends and minimize short-term variability, data were aggregated into three-month intervals, resulting in ten survey periods for the analysis. This aggregation also simplified the interpretation of generational trajectories and reduced model complexity. For sensitivity purposes, the data were additionally aggregated into two- and four-month intervals. As presented in Additional file 1, the overall patterns of results remained highly consistent, supporting the robustness of the three-month aggregation. Main effects and interaction terms were examined using analysis of variance with type III sums of squares, implemented via the anova() function from the \u003cem\u003ecar\u003c/em\u003e package [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The mean values of depression and anxiety symptoms served as dependent variables, while generation, survey period, gender, employment status and the interaction between generation and survey period were included as predictors. Post-hoc comparisons were performed using the \u003cem\u003eemmeans\u003c/em\u003e package [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] to identify specific group differences.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Descriptive statistics\u003c/h2\u003e\u003cp\u003eParticipants ranged in age from 18 to 98 years. The largest proportion (36.7%) belonged to Generation Z, followed by 24.6% from Generation Y, 19.2% from Generation X, and 19.4% from the combined Baby Boomer/Traditionalist group. A majority of respondents were female (55.0%). Across survey entries, most participants reported being employed (63.4%). The mean value for depression symptoms was 3.08 (SD\u0026thinsp;=\u0026thinsp;1.64) and for anxiety symptoms it was 3.39 (SD\u0026thinsp;=\u0026thinsp;1.60). Individual participation in the survey ranged from 1 to 64 entries, with a mean of 4.49 (SD\u0026thinsp;=\u0026thinsp;7.98).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Linear mixed-effects models\u003c/h2\u003e\u003cp\u003eLinear mixed-effects models were employed to evaluate the proposed hypotheses. Initially, the intraclass correlation was calculated using an intercept-only model for each outcome. For depression symptoms, the intercept-only model produced an intraclass correlation of 0.806, indicating that 80.6% of the total variance is due to differences between individuals. Anxiety symptoms showed a comparable pattern, with an intraclass correlation of 0.745. These results justify the use of linear mixed-effects models to account for the nested structure of repeated surveys within individuals.\u003c/p\u003e\u003cp\u003eAnalysis of depression symptoms revealed significant main effects for generation (χ\u0026sup2; = 808.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), survey period (χ\u0026sup2; = 103.75, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), gender (χ\u0026sup2; = 71.13, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;001), and employment status (χ\u0026sup2; = 176.83, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Additionally, a significant interaction between generation and survey period emerged (χ\u0026sup2; = 89.93, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), indicating that depression symptom trajectories over time varied across generations. Female participants exhibited significantly higher depression symptom levels than males (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16, SE\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), whereas being employed was associated with lower levels of depression symptoms (\u003cem\u003eb\u003c/em\u003e\u0026nbsp;=\u0026nbsp;\u0026minus;0.26, SE\u0026nbsp;=\u0026nbsp;0.02, \u003cem\u003et\u003c/em\u003e\u0026nbsp;=\u0026nbsp;\u0026minus;13.30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), controlling for all other predictors in the model.\u003c/p\u003e\u003cp\u003ePost-hoc comparisons demonstrated that Generation Z consistently reported higher depression symptoms than all older generations across all survey periods (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Differences between Generation Z and the Baby Boomer/Traditionalist cohort ranged from 1.055 to 1.408 scale points. Comparisons with Generation X yielded slightly smaller differences, ranging from 0.501 to 0.765 points, while differences with Generation Y were the smallest but still significant, ranging from 0.192 to 0.376 points. A full summary of the depression symptom results is presented in Additional file 2.\u003c/p\u003e\u003cp\u003eIn addition to generational differences, descriptive trends across the ten survey periods were examined. Among Generation Z, the predicted depression symptom levels slightly decreased between late 2022 and summer 2023, followed by a continuous increase through early 2025. Similar but less pronounced patterns were observed in Generations Y and X. Depression symptoms in Baby Boomers/ Traditionalists remained comparatively stable and consistently lower across all time points. Figure\u0026nbsp;1 displays the estimated means and 95% confidence intervals over time.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 1\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEstimated marginal means and 95% CI of depression symptoms across all generations and survey periods\u003c/em\u003e\u003c/p\u003e\u003cp\u003e[Figure 1]\u003c/p\u003e\u003cp\u003e\u003cem\u003eNotes.\u003c/em\u003e Values are based on fixed effects estimates from the linear mixed-effects model.\u003c/p\u003e\u003cp\u003eA comparable pattern emerged for anxiety symptoms. Significant main effects were observed for generation (χ\u0026sup2; = 745.30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), survey period (χ\u0026sup2; = 40.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), gender (χ\u0026sup2; = 327.69, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and employment (χ\u0026sup2; = 130.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), as well as a significant interaction between generation and survey period (χ\u0026sup2; = 86.57, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Females reported higher anxiety symptom levels than males (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.32, SE\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18.10, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), while employment was linked to lower anxiety levels (\u003cem\u003eb\u003c/em\u003e\u0026nbsp;=\u0026nbsp;\u0026minus;0.22, SE\u0026nbsp;=\u0026nbsp;0.02, \u003cem\u003et\u003c/em\u003e\u0026nbsp;=\u0026nbsp;\u0026minus;11.42, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), after accounting for other predictors.\u003c/p\u003e\u003cp\u003ePost-hoc contrasts revealed that Generation Z consistently exhibited higher anxiety symptoms than each of the older generations throughout all survey periods (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Estimated differences between Generation Z and Baby Boomers/Traditionalists ranged from 1.158 to 1.436 points, while differences with Generation X varied between 0.638 and 0.775 points. The smallest but still significant differences were observed in comparison with Generation Y, ranging from 0.313 to 0.412 points. A complete overview of the anxiety symptom results can be found in Additional file 3.\u003c/p\u003e\u003cp\u003eAcross the ten survey periods, anxiety symptoms showed small temporal fluctuations across all generations. In Generation Z, estimated means declined slightly from late 2022 to mid 2023, followed by a gradual and continuous increase through early 2025. A similar but less pronounced pattern was observed for Generation Y, with a mid period dip and subsequent rise toward the end of the observation window. Generation X showed comparable fluctuations, with a slight decrease early on and a subsequent increase in later survey periods. The Baby Boomers/ Traditionalists exhibited comparatively flatter trajectories, with only minimal variation over time and consistently lower symptom levels relative to the younger cohorts. These temporal trends are illustrated in Fig.\u0026nbsp;2, displaying the estimated means and 95% confidence intervals over time.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 2\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEstimated marginal means and 95% CI of depression symptoms across all generations and survey periods\u003c/em\u003e\u003c/p\u003e\u003cp\u003e[Figure 2]\u003c/p\u003e\u003cp\u003e\u003cem\u003eNotes.\u003c/em\u003e Values are based on fixed effects estimates from the linear mixed-effects model.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe aim of this study was to investigate the severity of symptoms of depression and anxiety in different generations and how these symptoms changed over a period of two and a half years. The results indicate a persistently elevated symptom level in Generation Z regarding depression as well as anxiety symptoms. Overall both, depression and anxiety symptoms, slightly increased over time in Generation Z, whereas for the Baby Boomers/ Traditionalists, for example, depression symptoms returned to their initial level in the last survey period and anxiety symptoms even decreased overall in descriptive terms.\u003c/p\u003e\u003cp\u003eThe results regarding generational differences in depression and anxiety symptoms are consistent with those of Fegert and colleagues [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who also reported significantly poorer mental health in Generation Z than in all older Generations. Older data on the prevalence of depression symptoms in Germany provide comparable results, indicating that the prevalence of depression symptoms is highest among 18- to 29-year-olds and decreases with increasing age [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. More recent data from the RKI [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] suggest an increased prevalence of depression symptoms in younger cohorts compared to older cohorts, especially for women. Regarding anxiety symptoms, the health report by the RKI [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] has found that prevalence decreases with age, at least for women. Taken together, the results of the present study are consistent with previous findings of increased psychological distress among younger cohorts.\u003c/p\u003e\u003cp\u003eThe descriptive reduction in both anxiety and depression symptoms from the end of 2022 to mid 2023, which can be observed across all generations, could be explained, for example, by the end of the COVID-19 pandemic and a subsequent stabilization of mental health which affected all generations. The subsequent increase in symptoms, particularly among Generation Z, coincides with accumulating socio-economic and geopolitical stressors, such as persistent inflation, the ongoing war in Ukraine, the escalation of the Middle East conflict, and rising political polarization in Germany. These contextual developments may have contributed to heightened psychological distress.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Limitations\u003c/h2\u003e\u003cp\u003eWhen interpreting the present results, several methodological constraints must be acknowledged. First of all, the longitudinal design of the study entails conceptual complexities. Multiple assessments do not only reflect cohort-related differences but inevitably capture momentary influences tied to specific economic, societal or social conditions. Consequently, the responses can mirror both relatively enduring generational characteristics and situational fluctuations triggered by current developments. This underlines that the observed trajectories may be shaped by the context of each survey period rather than by age cohort alone. This is also supported by the fact that the trajectories in the generations are in some cases very similar. Efforts to interpret those trajectories against the backdrop of global political developments remain hypothetical in nature.\u003c/p\u003e\u003cp\u003eAlthough participation was incentivized, it was voluntary, meaning that potential self-selection processes cannot be ruled out. In the final dataset, 25,143 individuals were included, yet only 40.5% of them took part on more than one occasion. This indicates a notable degree of drop out. Across 75 survey waves, participants contributed on average 4.49 responses (SD\u0026thinsp;=\u0026thinsp;7.98), a figure that calls for caution when drawing conclusions about changes over time.\u003c/p\u003e\u003cp\u003eFurther the number of repeated observations differed notably across generations. While members of Generation Z contributed on average fewer than two survey waves (M\u0026thinsp;=\u0026thinsp;1.93, SD\u0026thinsp;=\u0026thinsp;2.91), participation was more sustained in older cohorts. Generation Y averaged 3.75 observations (SD\u0026thinsp;=\u0026thinsp;6.47), Generation X 5.92 (SD\u0026thinsp;=\u0026thinsp;9.30) and Baby Boomers/ Traditionalists as many as 8.86 (SD\u0026thinsp;=\u0026thinsp;11.80). These discrepancies imply that younger generations were less consistently represented over time, which may have affected the stability of their estimated trajectories and could contribute to differential precision across cohorts.\u003c/p\u003e\u003cp\u003eDepression and anxiety symptoms were assessed using a mean value of two items which may not fully capture the multidimensional nature of those psychological constructs and limit construct validity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, validity may be limited because the results are based exclusively on quantitative self-report data, which may be distorted by socially desirable response behavior.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Conclusion and future directions\u003c/h2\u003e\u003cp\u003eThis study provides robust evidence of generational differences in mental health, focusing on anxiety and depression across age groups. Generation Z consistently reported higher levels of depression and anxiety than older cohorts, potentially reflecting the unique pressures associated with this life stage as well as the long-term consequences of the COVID-19 pandemic in this age cohort. Longitudinal, population-based research is essential not only for identifying risk and resilience factors within and between generational groups, but also for observing the impacts of concurrent events that affect all generations equally. While such designs carry the limitation that situational fluctuations may co-occur, this feature also allows researchers to examine how different generations respond over time and how they navigate the return to post-pandemic normality.\u003c/p\u003e\u003cp\u003eOur results support the statement of the Lancet Psychiatry Commission who emphasized that the Youth Mental Health Crisis is ongoing and requires urgent action [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This crisis might be reinforced by social and political factors, such as delayed or insufficient measures to address economic instability and limited resources that can exacerbate stress and anxiety. Media narratives that stigmatize young people are particularly harmful, overlooking the sacrifices Generation Z has made for the health and well-being of older generations, such as during the COVID-19 pandemic.\u003c/p\u003e\u003cp\u003eEvidence that certain factors, such as being employed, are associated with lower symptom levels can inform preventive strategies. Supporting young people during key life transitions, such as entering the workforce or starting higher education, can serve both as indicated prevention for those at heightened risk and as universal prevention to strengthen coping during age-typical developmental challenges. The higher prevalence of symptoms among young people reflects a broader transitional problem in times of crises, highlighting the need for interventions that address the unique challenges of this life stage. Continuous monitoring of mental health trends and societal sentiment, as implemented in SOSEC, can act as an early warning system, guiding public health strategies and policy decisions to prevent further escalation of psychological strain among young people.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe ethics approval has been submitted by the German Association for Experimental Economic Research e.V., Institutional Review Board Certificate No. MSEIsPRB (https://gfew.de/ethik/MSEIsPRB), issued on September 13, 2023, and valid until September 12, 2025. The research was conducted in accordance with the Declaration of Helsinki. \u0026nbsp; Informed consent to participate was obtained and documented by the panel provider CINT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from FZI Research Center for Information Technology, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of FZI Research Center for Information Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe present study draws on data from the ongoing Social Sentiment in Times of Crises (SOSEC), which is founded by the Alfred Landecker Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor’s contributions:\u0026nbsp;\u003c/strong\u003eJF conceptualized, organized and surveyed the SOSCE panel. LP and ES conceptualized this analysis and drafted the manuscript. Both contributed equally to this work and share first authorship. JH conducted the statistical analyses and assisted in drafting the manuscript. FKD, JMF and JF provided critical revisions and supervised the project. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eErikson EH. Identity: Youth and crisis. New York: Norton; 1968.\u003c/li\u003e\n \u003cli\u003eChristie D, Viner R. Adolescent development. BMJ. 2005;330(7486):301\u0026ndash;304. doi:10.1136/bmj.330.7486.301\u003c/li\u003e\n \u003cli\u003eRichter M. Gesundheitsverhalten im Jugendalter: Risiken und Schutzfaktoren. In: Hurrelmann K, Klocke A, Melzer W, editors. Jugendgesundheitssurvey. Gesundheitsverhalten und gesundheitliche Risiken bei Jugendlichen in Deutschland. Juventa; 2005. p. 15\u0026ndash;34.\u003c/li\u003e\n \u003cli\u003eCaspi A, Houts RM, Ambler A, Danese A, Elliott ML, Hariri A, et al. Longitudinal assessment of mental health disorders and comorbidities across 4 decades among participants in the Dunedin Birth Cohort Study. 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Available from: https://gbe.rki.de\u003c/li\u003e\n \u003cli\u003eRobert Koch-Institut. Angstsymptome: Pr\u0026auml;valenz (ab 18 Jahre). Gesundheitsberichterstattung des Bundes. 2024 [cited 2025 Oct 2]. Available from: https://gbe.rki.de\u003c/li\u003e\n \u003cli\u003eEisinga R, Grotenhuis MT, Pelzer B. The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown? Int J Public Health. 2013;58(4):637\u0026ndash;642. doi:10.1007/s00038-012-0416-3\u003c/li\u003e\n \u003cli\u003eMcGorry PD, Mei C, Dalal N, Alvarez-Jimenez M, Blakemore SJ, Browne V, et al. The Lancet Psychiatry Commission on youth mental health. Lancet Psychiatry. 2024;11(9):731-774.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"generational differences, Generation Z, mental health, depression, anxiety, prevention","lastPublishedDoi":"10.21203/rs.3.rs-8056528/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8056528/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAdolescence and early adulthood are crucial periods marked by identity formation and increased vulnerability to mental health issues, with most mental disorders beginning before the age of 25. Today\u0026rsquo;s youth face amplified risks due to overlapping crises like the COVID-19 pandemic, climate change and economic instability, potentially disrupting age-typical developmental tasks and contributing to rising rates of anxiety and depression. This study aimed to investigate the longitudinal development of anxiety and depression symptoms across four generational cohorts.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study drew on data from the German subsample of the ongoing \u0026ldquo;SOSEC \u0026ndash; Social Sentiment in Times of Crises\u0026rdquo; project. In total, 25,143 individuals contributed 112,858 survey entries, responding to items on depression and anxiety symptoms based on modified versions of the PHQ-9 and GAD-2. Generational groups were determined by year of birth, with particular attention given to Generation Z. Linear mixed-effects models were applied to assess how generation, survey period, gender, and employment status influenced mental health symptoms. The analysis also included interaction terms and post-hoc comparisons between groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eGeneration Z showed significantly higher and stable levels of depression and anxiety symptoms than all older generations across all survey periods (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Women reported more symptoms than men and employment was linked to lower symptom levels.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe findings indicate a persistently elevated mental health burden among Generation Z, underscoring the need for early intervention, stepped-care approaches, and targeted prevention strategies tailored to this cohort\u0026rsquo;s developmental challenges. Protective factors such as employment highlight potential entry points for indicated prevention, while broader support during key life transitions, such as entering the workforce or higher education, can serve as universal preventive measures. Implementing multi-level, stepwise care and preventive interventions is crucial to mitigate long-term mental health consequences, strengthen resilience, and promote adaptive coping among young people facing ongoing societal crises.\u003c/p\u003e","manuscriptTitle":"What’s wrong with Gen Z? – Post-pandemic persistence of depression and anxiety symptoms among young adults in Germany","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 10:08:30","doi":"10.21203/rs.3.rs-8056528/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"4243082525349626756777688281668179195","date":"2025-11-26T19:09:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80963624934559420357946374393186478645","date":"2025-11-26T09:42:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-26T01:50:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T04:38:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-21T04:14:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-20T18:24:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-11-20T18:21:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0402872b-a6dc-4e5c-a690-317b4afeb574","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:10:35+00:00","versionOfRecord":{"articleIdentity":"rs-8056528","link":"https://doi.org/10.1186/s12889-026-27600-0","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2026-04-30 15:57:26","publishedOnDateReadable":"April 30th, 2026"},"versionCreatedAt":"2025-12-01 10:08:30","video":"","vorDoi":"10.1186/s12889-026-27600-0","vorDoiUrl":"https://doi.org/10.1186/s12889-026-27600-0","workflowStages":[]},"version":"v1","identity":"rs-8056528","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8056528","identity":"rs-8056528","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}