Changing landscape of respiratory conduct and its stressful impact during covid-19 crisis
Bibliographic record
Abstract
Background: The country was placed under a nationwide lockdown on April 1st, which was then extended twice more until May 9th. When the lockdown came to an end, it was gradually lifted. Following the initial wave, the nation has fought COVID-19 by implementing "smart lockdowns" and enforcing standard operating procedures (SOPs). Aims: To assess participants' respiratory etiquette, anxiety, and depression in the context of the COVID pandemic after the constraint of lockdown has been lifted. Methods: From May 2020 to February 2021, a total of 120 participants participated in this cross-sectional study. Data collection is done through the use of a proforma. Anxiety and depression were measured using the GAD-7 and PHQ-9 scales, which were used in conjunction with each other. It was disseminated by a deliberate snowball sampling procedure. Consent was obtained through the use of Google Forms. Results: Only 30 percent of the 120 participants wore a mask at all times. Anxiety and despair were experienced by 49 percent and 42 percent of those surveyed, respectively. Anxiety and depression were shown to be related with 35-50 year old females, HCPs, and family members who tested positive for COVID-19. Conclusions: Following the lockdown, participants' respiratory hygiene etiquette may have deteriorated, maybe due to their decreased anxiety about COVID-19 infection. Females, HCPs, and family members who tested positive for COVID-19 were shown to have higher levels of anxiety and sadness than other groups. Keywords: Anxiety, depression, Covid 19
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".