Investigating the Impact of Psychological Interventions in Response to Depression, Stress, Anxiety, Post Traumatic Stress Disorder and Cognitive Functioning in Covid-19 Recovered Patients
Bibliographic record
Abstract
The COVID-19 outbreak, in addition to the threat to physical health, may also negatively affect mental health.In this study, we intended to study the changes in psychological parameters in covid-19 recovered patients after they get the psychological intervention. This study conducted in three phases. In the first phase, Depression, Anxiety and Stress Scale - 21 (DASS-21), Post traumatic stress disorder (PTSD) Checklist PCL-5 and Montreal Cognitive Assessment were administered on a total of 477 covid-19 recovered patients. After a gap of 3 months, through clinical interview it was found out that 220 patients needed intervention. In the second phase of the study, psychological intervention was given to 190 patients. In the final phase, after a gap of three months from the intervention phase, all the tests were re-administered on the patients. Data were scored and analyzed using descriptive statistics. Result showed that significant difference was found in the score of depression, anxiety, stress and PTSD. Depression, anxiety, stress, PTSD scores were significantly reduced after intervention. (p < 0.01). No significant difference was observed between the MOCA score. These findings of the study suggest that, psychological intervention may have a beneficial effect on COVID-19 patients’ mental health.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".