Depression trajectories during the COVID-19 pandemic: a secondary analysis of the impact of cognitive-appraisal processes

Abstract

Purpose This study characterized depression trajectories during the COVID pandemic and investigated how appraisal and changes in appraisal over time related to these depression trajectories. Methods This longitudinal study of the psychosocial impact of the COVID-19 pandemic included 771 people with data at three timepoints over 15.5 months. The depression index was validated using item-response-theory methods and receiver-operating-characteristic curve analysis. The Quality of Life (QOL) Appraisal Profilev2 Short-Form assessed cognitive-appraisal processes. Sequence analysis characterized depression-trajectory groups, and random effects models examined appraisal main effects, appraisal-by-group, and appraisal-by-group-by-time interactions. Results Sequence analysis generated six trajectory groups: Stably Well (n = 241), Stably Depressed (n = 299), Worsening (n = 79), Improving (n = 83), Fluctuating Pattern 1 (No–Yes–No; n = 41), and Fluctuating Pattern 2 (Yes–No–Yes; n = 28). While all groups engaged in negative appraisal processes when they were depressed, the Stably Depressed group consistently focused on negative aspects of their life. Response-shift effects were revealed such that there were differences in the appraisal-depression relationship over time for standards of comparison and recent changes for the Stably Depressed, and in health goals for those Getting Better. Conclusion The present work is, to our knowledge, the first study of response-shift effects in depression. During these first 15.5 pandemic months, group differences highlighted the connection between negative appraisals and depression, and response-shift effects in these relationships over time. Egregious life circumstances may play a lesser role for the Stably Depressed but a greater role for people who have transient periods of depression as well as for those with improving trajectories (i.e., endogenous vs. reactive depression). How one thinks about QOL is intrinsically linked to mental health, with clear clinical implications.

Reserve-building as a buffer for depression among individuals living with disability: a longitudinal study of current activities related to brain health

“…Many factors may play a role in this rising prevalence, including grief over the loss of loved ones (Eisma et al, 2021 ), social isolation (Pietrabissa and Simpson, 2020 ), and long-term symptoms of COVID-19 (Penninx, 2021 ), among others. In earlier research done by our group and on which the present study builds, we found that employment status was an important predictor of depression (Schwartz et al, 2023a , b ). Specifically, people who were disabled from work due to a medical condition were more likely to be depressed throughout the pandemic than other employment groups (Schwartz et al, 2023a , b ).…”

“…In earlier research done by our group and on which the present study builds, we found that employment status was an important predictor of depression (Schwartz et al, 2023a , b ). Specifically, people who were disabled from work due to a medical condition were more likely to be depressed throughout the pandemic than other employment groups (Schwartz et al, 2023a , b ). Even after adjusting the longitudinal models for COVID-19-specific stressors (e.g., hardship, worry, and low social support) and cognitive appraisal processes, the association between being disabled and being depressed remained highly significant (Schwartz et al, 2023b ).…”

“…This secondary analysis utilized data collected for a longitudinal study of the psychosocial impact of the COVID-19 pandemic (see Ref. Schwartz et al, 2023a for details). The study sample included 771 individuals who provided data at three time points: baseline (late Spring 2020), follow-up 1 (Spring 2021), and follow-up 2 (Fall 2021).…”

Functional Status Correlates of Change and Stability in Appraisal after Spine Surgery: Earlier versus Later Effects

“…In this long research path, cognitive-appraisal processes were documented to explain substantial variance in a wide range of patient samples [ 21 ], and to help to explain why two individuals in identical health states rate their QOL differently [ 22 ]. Appraisal assessment helps to identify and explain how contextual and psychological factors matter in patients’ subjective evaluation of their physical and emotional health [ 21 , 22 , 23 ]. With this growth in the evidence base for appraisal, there has also been increasing parsimony in appraisal assessment [ 20 ] and in statistical methods for working with appraisal [ 23 ].…”

“…Appraisal assessment helps to identify and explain how contextual and psychological factors matter in patients’ subjective evaluation of their physical and emotional health [ 21 , 22 , 23 ]. With this growth in the evidence base for appraisal, there has also been increasing parsimony in appraisal assessment [ 20 ] and in statistical methods for working with appraisal [ 23 ]. These statistical methods have relied on data reduction and relatively complex multivariate analyses which, though useful for summarizing findings at the aggregate level, may also make the findings hard to parse for clinicians and others not familiar with complex statistical modeling.…”