Real versus illusory personal growth in response to COVID-19 pandemic stressors
Bibliographic record
Abstract
BACKGROUND: There is considerable evidence of widespread emotional distress associated with the COVID-19 pandemic. A growing number of studies have assessed posttraumatic growth related to the current pandemic; but, none have considered whether reported growth is real or illusory (i.e., characterized by avoidant or defensive coping that results in higher levels of distress). The purpose of this study was to extend this literature by assessing growth specific to the pandemic in people reporting high levels of COVID-related stress and estimating the extent of real and illusory COVID-19-related growth. METHODS: Participants were 893 adults from Canada and the United States with high levels of COVID-related stress who provided complete responses on measures of posttraumatic growth, disability, and measures of general and COVID-related distress as part of a larger longitudinal survey. RESULTS: Approximately 77 % of participants reported moderate to high growth in at least one respect, the most common being developing greater appreciation for healthcare workers, for the value of one's own life, for friends and family, for each day, as well as changing priorities about what is important in life and greater feelings of self-reliance. Consistent with predictions, cluster analysis identified two clusters characterized by high growth, one comprising 32 % of the sample and reflective of real growth (i.e., reporting little disability and stable symptoms across time) and the other comprising 17 % of the sample and reflective of illusory growth (i.e., reporting high disability and worsening symptoms). These clusters did not differ in terms of socially desirable response tendencies; but, the illusory growth cluster reported greater increases in alcohol use since onset of the pandemic. CONCLUSION: Consistent with research regarding personal growth in response to prior pandemics and COVID-19, we found evidence to suggest moderate to high levels of COVID-related growth with respect to appreciation for healthcare workers, life, friends and family, and self-reliance. Findings from our cluster analysis support the thesis that many reports of COVID-related personal growth reflect ineffectual pandemic-related coping as opposed to true growth. These findings have important implications for developing strategies to optimize stress resilience and posttraumatic growth during chronically stressful events such as pandemics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".