2026 ECNP Congress

EP02-2020

Wartime adaptation profiles in Ukrainian adults: social support, information engagement, sleep recovery and hypervigilance

Olena Yelizarova — S. Hozak, T. Stankevych, A. Parats · State Institution «Marzieiev Institute for Public Health of the National Academy of Medical Sciences of Ukraine», Health Promotion Department, Kyiv, Ukraine

2026 ECNP Congress

Background

Resilience under prolonged societal stress is a major focus of psychiatric and neuroscience research. Current evidence suggests that resilience is not a single uniform trait: different forms of psychological resilience may have partly distinct genetic and environmental sources [1], while individual, social and societal factors jointly shape responses to crises [2]. In large-scale crisis settings, invasive biomarker assessment or genotyping is rarely feasible; therefore, observable emotional and behavioural indicators may serve as field phenotypes of stress adaptation. Perceived social support may reflect social buffering and sensitivity to available resources, whereas engagement with war-related information may index threat exposure, information load and threat-monitoring behaviour [3–5]. The ongoing war in Ukraine provides a real-world context for studying how these markers combine into adaptation profiles under prolonged adversity.

Aims

To identify psychosocial and behavioural wartime adaptation profiles in Ukrainian adults using perceived social support and information engagement as phenotypic markers, and to compare these profiles by anxiety, depressive symptoms, sleep recovery and hypervigilance.

Methods

We analysed repeated online surveys of Ukrainian adult parents of school-age children conducted in 2022–2025 (N=10,406). Adaptation profiles were identified by k-means clustering using perceived social support and news/information engagement. Profiles were labelled resource-oriented, low-support isolated, overloaded-vulnerable and flexible self-regulators. Adult symptoms were assessed with PHQ-2 and GAD-2; hypervigilance/threat monitoring with the corresponding PC-PTSD-5 item. Sleep recovery was the main functional adaptation marker. Logistic regression compared profiles with flexible self-regulators, adjusting for year, sex, age, BMI, chronic diseases, education, residence and migration status.

Results

Flexible self-regulators showed the most favourable profile, combining better sleep recovery, lower anxiety and depressive symptom burden, and the lowest hypervigilance/threat monitoring. Resource-oriented adults did not have significantly higher adjusted odds of depressive symptoms compared with flexible self-regulators (OR=1.04, 95% CI 0.91–1.18), but showed higher odds of anxiety symptoms (OR=1.22, 95% CI 1.07–1.40), suggesting socially supported mobilisation rather than full recovery. Low-support isolated adults had higher adjusted odds of depressive symptoms (OR=2.43, 95% CI 2.06–2.85), anxiety symptoms (OR=2.33, 95% CI 2.00–2.76) and poor sleep recovery (OR=3.12, 95% CI 2.58–3.77). Overloaded-vulnerable adults showed a similar risk pattern, with higher odds of depressive symptoms (OR=2.23, 95% CI 1.94–2.56), anxiety symptoms (OR=2.37, 95% CI 2.05–2.73) and poor sleep recovery (OR=2.99, 95% CI 2.53–3.54). Odds of depressive and anxiety symptoms decreased across survey years, whereas poor sleep recovery was not significantly associated with year.

Conclusions

Wartime adaptation in Ukrainian adults appears heterogeneous and is not adequately captured by a single resilience score. Perceived social support and information engagement identified profiles with distinct patterns of anxiety, depression, sleep recovery and hypervigilance/threat monitoring. Resource-oriented adaptation may reflect mobilisation with residual anxiety, while low-support isolated and overloaded-vulnerable profiles indicate different pathways to increased transdiagnostic risk. These profiles may support targeted psychosocial prevention and longitudinal research on stress regulation under prolonged societal adversity.

Declaration of generative AI and AI-assisted technologies. ChatGPT (OpenAI) was used to support conceptual structuring, language editing and wording refinement. All analyses, source verification, interpretation and final decisions were performed by the authors, who take full responsibility for the content.

References

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