Background
Antibiotics may be indicated in patients with COVID-19 due to suspected or confirmed bacterial superinfection.
Objectives
To investigate antibiotic prescribing practices in patients with COVID-19.
Methods
We performed an international web-based survey and investigated the pattern of antibiotic use as reported by physicians involved in treatment of COVID-19. SPSS Statistics version 25 was used for data analysis.
Results
The survey was completed by 166 participants from 23 countries and 82 different hospitals. Local guidelines for antibiotic use in COVID-19 patients were reported by 61.8% (n = 102) of participants and for 82.9% (n = 136) they did not differ from local community-acquired pneumonia guidelines. Clinical presentation was recognized as the most important reason for the start of antibiotics (mean score = 4.07 and SD = 1.095 on grading scale from 1 to 5). When antibiotics were started, most respondents rated as the highest the need for coverage of atypical pathogens (mean score = 2.8 and SD = 0.99), followed by Staphylococcus aureus (mean score = 2.67 and SD = 1.05 on bi-modal scale, with values 1 and 2 for disagreement and values 3 and 4 for agreement). In the patients on the ward, 29.1% of respondents chose not to prescribe any antibiotic. Combination of β-lactams and macrolides or fluoroquinolones was reported by 52.4% (n = 87) of respondents. In patients in the ICU, piperacillin/tazobactam was the most commonly prescribed antibiotic. The mean reported duration of antibiotic treatment was 7.12 (SD = 2.44) days.
Conclusions
The study revealed widespread broad-spectrum antibiotic use in patients with COVID-19. Implementation of antimicrobial stewardship principles is warranted to mitigate the negative consequences of antibiotic therapy.
Background
Postgraduate training has the potential to shape the prescribing practices of young doctors.
Objectives
To investigate the practices, attitudes and beliefs on antibiotic use and resistance in young doctors of different specialties.
Methods
We performed an international web-based exploratory survey. Principal component analysis (PCA) and bivariate and multivariate [analysis of variance (ANOVA)] analyses were used to investigate differences between young doctors according to their country of specialization, specialty, year of training and gender.
Results
Of the 2366 participants from France, Greece, Italy, Portugal, Slovenia and Spain, 54.2% of young doctors prescribed antibiotics predominantly as instructed by a mentor. Associations between the variability of answers and the country of training were observed across most questions, followed by variability according to the specialty. Very few differences were associated with the year of training and gender. PCA revealed five dimensions of antibiotic prescribing culture: self-assessment of knowledge, consideration of side effects, perception of prescription patterns, consideration of patient sickness and perception of antibiotic resistance. Only the country of specialization (partial η2 0.010–0.111) and the type of specialization (0.013–0.032) had a significant effect on all five identified dimensions (P < 0.01). The strongest effects were observed on self-assessed knowledge and in the perception of antibiotic resistance.
Conclusions
The country of specialization followed by the type of specialization are the most important determinants of young doctors’ perspectives on antibiotic use and resistance. The inclusion of competencies in antibiotic use in all specialty curricula and international harmonization of training should be considered.
After decades of survey quality research and many experiments on the mode of data collection as a source of data inequivalence, there is still no exact explanation of how the mixed-mode design impacts the collected data. While not providing a definitive answer, we propose a new explanation of the mode effect and how it correlates with other sources of errors in surveys. By reviewing the relevant literature, we develop theoretical arguments indicating that the mode of data collection is in fact a moderator of context effects, a view that can provide an answer to the question concerning the origin of the data cacophony in mixed-mode comparative studies.
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