Self-Medication-Related Behaviors and Poland’s COVID-19 Lockdown
Bibliographic record
Abstract
(1) Background: The SARS-CoV-2 pandemic has changed the functioning of Polish health systems. Telemedicine has been developed and access to prescription drugs (Rx) has been facilitated. This study examined whether these changes and the imposition of a three-month lockdown caused Polish people to engage in more self-medication-related behaviors. (2) Method: After the fourth (final) stage of defrosting the Polish economy, an online survey of a quota sample of 1013 Polish respondents was conducted. (3) Results: Almost half of the respondents (45.6%) indicated that they had engaged in at least one behavior associated with inappropriate self-medication during the lockdown (e.g., 16.6% took medication as a precaution, and 16.8% took an Rx formulation without consultation). Some of these people had never engaged in such behaviors prior to the lockdown. Linear regression showed that higher values of a composite (“lockdown”) index of self-medication-related behaviors occurring during lockdown were predicted by greater religiosity and the presence of children in a household. Also, independent samples t-tests showed that people who were afraid for their financial future and people who feared for their health obtained higher lockdown index scores than people not having such worries. (4) Conclusions: Self-medication-related behaviors were more common among Poles before lockdown than during the lockdown (which is unsurprising given that the lengths of the periods compared were hugely different), worryingly, many people exhibited such behaviors for the first time during the lockdown.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".