Psychological Support and Psychotherapy during the COVID-19 Outbreak: First Response of Practitioners
Bibliographic record
Abstract
Providers of psychological support and psychotherapy during the COVID-19 pandemic unfolding were facing the new unavoidable reality, which required making urgent changes in their practice. The paper aimed to study the "first responses” of psychologists and psychotherapists to the COVID-19 pandemic situation with its uncertainty before the lockdown. An online survey was developed and distributed among psychologists and psychotherapists from Ukraine from 14 to March 16, 2020. Results showed that among survey respondents (n=145), 35.9% had already changed their practice somehow, and 75.2% had been considering how their practice might be modified. The more often the COVID-19 pandemic was discussed by patients, the more often it affected the style and technique of the corresponding specialists, thereby pushing psychotherapists to change the format of their work. Practice restrictions due to quarantine measures affected more affiliated consultants, while difficulties with setting (e.g., canceled sessions, financial issues) were more frequent among private practice consultants, and both proposed online consultations to their patients. In conclusion, the pandemic situation caused relevant modifications in the organization of psychological and psychotherapeutic support even during the first weeks of the COVID-19 outbreak in Ukraine. The first responses of practitioners were related to (a) their experience and type of affiliation, (b) the main approach, (c) the subjective readiness or non-readiness to modify the usual form of work, (d) the way of interpreting the patient’s anxieties, (e) the lethal cases of coronavirus in the area of living.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".