Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic

Einav Gozansky, Gal Moscona, Hadas Okon-Singer

Research output: Contribution to journalArticlepeer-review


This study aimed to define the psychological markers for future development of depression symptoms following the lockdown caused by the COVID-19 outbreak. Based on previous studies, we focused on loneliness, intolerance of uncertainty and emotion estimation biases as potential predictors of elevated depression levels. During the general lockdown in April 2020, 551 participants reported their psychological health by means of various online questionnaires and an implicit task. Out of these participants, 129 took part in a second phase in June 2020. Subjective loneliness during the lockdown rather than objective isolation was the strongest predictor of symptoms of depression 5 weeks later. Younger age and health related worry also predicted higher non-clinical levels of depression and emotional distress. The results support the diathesis-stress model, which posits that a combination of preexisting vulnerabilities along with stressors such as negative life events are among the factors affecting the development of psychopathology. Moreover, our results correspond with those of previous studies conducted worldwide during the COVID-19 pandemic. Taken together, these findings call for focusing on psychological factors, especially among younger people, to identify individuals at risk for future development of depression and to promote new strategies for prevention.

Original languageAmerican English
Article number680768
JournalFrontiers in Psychology
StatePublished - 17 May 2021


  • COVID-19
  • depression
  • emotion evaluation bias
  • intolerance of uncertainty
  • lockdown
  • loneliness
  • social isolation

All Science Journal Classification (ASJC) codes

  • General Psychology


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