The impact of social isolation and changes in work patterns on ongoing thought during the first COVID-19 lockdown in the United Kingdom
Bibliographic record
Abstract
The COVID-19 pandemic led to lockdowns in countries across the world, changing the lives of billions of people. The United Kingdom's first national lockdown, for example, restricted people's ability to socialize and work. The current study examined how changes to socializing and working during this lockdown impacted ongoing thought patterns in daily life. We compared the prevalence of thought patterns between two independent real-world, experience-sampling cohorts, collected before and during lockdown. In both samples, young (18 to 35 y) and older (55+ y) participants completed experience-sampling measures five times daily for 7 d. Dimension reduction was applied to these data to identify common "patterns of thought." Linear mixed modeling compared the prevalence of each thought pattern 1) before and during lockdown, 2) in different age groups, and 3) across different social and activity contexts. During lockdown, when people were alone, social thinking was reduced, but on the rare occasions when social interactions were possible, we observed a greater increase in social thinking than prelockdown. Furthermore, lockdown was associated with a reduction in future-directed problem solving, but this thought pattern was reinstated when individuals engaged in work. Therefore, our study suggests that the lockdown led to significant changes in ongoing thought patterns in daily life and that these changes were associated with changes to our daily routine that occurred during lockdown.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".