Feasibility and Preliminary Results of Effectiveness of Social Media-based Intervention on the Psychological Well-being of Suspected COVID-19 Cases during Quarantine
Bibliographic record
Abstract
Novel coronavirus disease 2019 (COVID-19) has been declared as a pandemic by WHO.1 With high transmission efficiency and infectivity, quarantine for suspected COVID-19 patients is considered a powerful preventive measure to control the spread of this disease.1 Quarantined patients are more likely to have feelings of depression, anxiety, and anger.2 A previous study found that an intervention based on cognitive behavioral therapy was effective in reducing similar mental health symptoms during the Ebola outbreak.3 Video messaging using smartphones was shown to be effective in improving knowledge, attitudes, and behaviors during the Ebola outbreak.4 This article describes a study on suspected COVID-19 patients during quarantine using WeChat-based individual counseling in a tertiary care teaching hospital in China to explore the feasibility and to evaluate the potential effectiveness of the intervention on psychological well-being of suspected COVID-19 patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".