Objective:

To assess how person-centered psychological clusters emerge and evolve across the initial two waves of the COVID-19 pandemic.

Approach:

• Study Design: Longitudinal study assessing 338 adults across two pandemic waves (2020 and 2021) using validated instruments for PTSS, coping strategies, and pandemic stress.
• Clustering Methodology: Machine learning clustering (K-means and Gaussian mixture models) evaluated solutions k = 2–6 using various statistical criteria.

Key Findings:

• Three statistically defined clusters emerged at both waves: a low-distress, high-coping cluster (labeled 'resilient'; Wave 1: 35.5%; Wave 2: 29.00%); a low-coping cluster (40.04%; 49.11%); and a high-distress cluster (25.06%; 21.89%).
• Overall, 55.3% (95% CI [50.0%, 60.5%]) remained in the same cluster across waves.
• Among those initially in the resilient cluster, 55.8% transitioned to higher-distress clusters by Wave 2.
• The low-coping cluster showed the greatest stability (68.9%), and 50.6% of those initially in the high-distress cluster transitioned to lower-distress clusters.

Interpretation:

Psychological responses to prolonged crises are dynamic and heterogeneous, influenced by coping capacity and socioeconomic factors.

Limitations:

• Observational design limits causal inferences.
• Convenience sampling may affect generalizability.

Conclusion:

These findings suggest that further research with more frequent assessments and experimental designs is needed.