How Did the COVID-19 Lockdown Pandemic Affect the Depression Symptomatology in Mediterranean Older Adults with Metabolic Syndrome?
Bibliographic record
Abstract
Background and Aims: To control the COVID-19 spread, in March 2020, a forced home lockdown was established in Spain. In the present study, we aimed to assess the effect of mobility and social COVID-19-established restrictions on depressive symptomatology in older adults with metabolic syndrome. We hypothesize that severe restrictions might have resulted in detrimental changes in depressive symptomatology. Methods: 2,312 PREDIMED-Plus study participants (men = 53.9%; mean age = 64.9 ± 4.8 years) who completed a COVID-19 lockdown questionnaire to assess the severity of restrictions/lockdown and the validated Spanish version of the Beck Depression Inventory-II (BDI-II) during the three established phases concerning the COVID-19 lockdown in Spain (prelockdown, lockdown, and postlockdown) were included in this longitudinal analysis. Participants were categorized according to high or low lockdown severity. Analyses of covariance were performed to assess changes in depressive symptomatology across lockdown phases. Results: < 0.001); a nonsignificantly larger decrease was observed in participants allocated in the low-lockdown category (low: -0.59 (-0.95, -0.23), high: -0.43 (-0.67, -0.19)). Similar decreases in depression symptomatology were found for the physical environment dimension. The post- and prelockdown phase BDI-II scores were roughly similar. Conclusions: The COVID-19 pandemic lockdown was associated with a decrease in depressive symptomatology that returned to prelockdown levels after the lockdown. The degree of lockdown was not associated with depressive symptomatology. The potential preventive role of the physical environment and social interactions on mental disorders during forced home lockdown should be further studied. This trial is registered with ISRCTN89898870. Retrospectively registered on 24 July 2014.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".