# Young doctors' perspectives on antibiotic use and resistance: a multinational and inter-specialty cross-sectional European Society of Clinical Microbiology and Infectious Diseases (ESCMID) survey

Bojana Beović, May Doušak, Céline Pulcini, Guillaume Béraud, Jose Ramon Paño Pardo, David Sánchez-Fabra, Diamantis Kofteridis, Joana Cortez, Leonardo Pagani, Maša Klešnik, et al.

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Bojana Beović, May Doušak, Céline Pulcini, Guillaume Béraud, Jose Ramon Paño Pardo, et al. Young doctors' perspectives on antibiotic use and resistance: a multinational and inter-specialty cross-sectional European Society of Clinical Microbiology and Infectious Diseases (ESCMID) survey. Journal of Antimicrobial Chemotherapy, 2019, 74 (12), pp.3611-3618. 10.1093/jac/dkz375. hal-02297581

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# Young doctors' perspectives on antibiotic use and resistance: a multinational and inter-specialty cross-sectional European Society of Clinical Microbiology and Infectious Diseases (ESCMID) survey

Bojana Beović¹,²*, May Doušak³, Céline Pulcini⁴,⁵, Guillaume Béraud⁶⁻⁸, Jose Ramon Paño Pardo⁹,¹⁰, David Sánchez-Fabra⁹,¹⁰, Diamantis Kofteridis ¹¹, Joana Cortez¹², Leonardo Pagani ¹³, Maša Klešnik¹, Kristina Nadrah¹, Mitja Hafner Fink³, Dilip Nathwani¹⁴ and Samo Uhan³ on behalf of ESCMID Study Group for Antimicrobial Stewardship (ESGAP) and Trainee Association of ESCMID (TAE)

¹University Medical Centre Ljubljana, Ljubljana, Slovenia; ²Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia; ³Faculty of Social Sciences, University of Ljubljana, Ljubljana, Slovenia; ⁴Université de Lorraine, APEMAC, Nancy, France; ⁵CHRU-Nancy, Infectious Diseases Department, Nancy, France; ⁶University Hospital of Poitiers, Poitiers, France; ⁷Santé des populations et pratiques optimales en santé University Hospital of Québec-Laval University Research Center, Canada; ⁸EA 2694 Lille University, Lille, France; ⁹Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain; ¹⁰IIS Aragón, Zaragoza, Spain; ¹¹University Hospital of Heraklion, Heraklion, Crete, Greece; ¹²Bolzano Central Hospital, Bolzano, Italy; ¹³Integrated Programme for the Reduction of Maternal and Child Mortality, Instituto Marquês de Valle Flôr, Bissau, Guinea-Bissau; ¹⁴University of Dundee, Ninewells Hospital and Medical School, Dundee, UK

*Corresponding author. E-mail: bojana.beovic@kclj.si

Received 19 April 2019; returned 14 June 2019; revised 17 July 2019; accepted 31 July 2019

**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.

## Introduction

Antibiotic resistance has been recognized as a major global health threat and optimizing prescribing is one of the most effective measures to preserve the effectiveness of antibiotics.¹ The quality of prescribing depends mostly on those prescribers belonging to clinical medical specialties having direct contact with patients.² These doctors, who comprise the majority of antibiotic prescribers,

undergo long-term undergraduate and postgraduate training that shapes their professional knowledge and behaviour.

Several papers have shown that prudent antibiotic prescribing is not sufficiently covered in the undergraduate medical curricula,⁴ or during specialty training.⁴,⁵ Antibiotic prescribing is influenced not only by knowledge but also by the attitudes and beliefs of the prescribers.⁶,⁷ A review of studies of the social and professional influences on antibiotic prescribing by young doctors in postgraduate
training showed that they operate in a challenging context domi-
nated by hierarchical relationships, powerful prescribing norms, un-
clear roles and responsibilities, expectations about knowledge and
many uncertainties.⁸,⁹ Studies investigating the attitudes and per-
spectives of young doctors in training are mostly limited to single
hospitals or countries; only a few of them have pointed to any inter-
national¹⁰ and inter-specialty differences.¹¹

Following existing studies on the influence of sociocultural char-
acteristics of societies on human behaviour in various areas of life,
such as education, health and profession,¹² we designed a cross-
sectional survey of young doctors in training, from different spe-
cialties and countries, to inform the following research questions:
(i) which factors influence the culture and habits of antibiotic pre-
scribing? and (ii) can we support the hypothesis about socio-cul-
tural environment influences related to the country of
specialization or the effect of type of specialty on the antibiotic pre-
scribing behaviour of young doctors in training?

Methods

Ethics

The study was approved by the National Medical Ethics Committee in
Slovenia (22p/08/14).

Participants, research design and the questionnaire

The research was focused on young medical doctors after graduation from
medical school and the start of specialty training, but before taking special-
ty board examinations (specialty assessment). We included participants
/trainees) from all medical specialties having daily contact with patients.
The research was designed as a survey based on a standardized online
questionnaire.

The questionnaire was sent to the study coordinators, who were mem-
bers of the ESCMID Study Group for Antibiotic Stewardship (ESGAP) in 12
countries (Austria, Bulgaria, Croatia, France, Greece, Italy, Portugal,
Slovenia, Spain, Sweden, Turkey and the UK), who forwarded the survey to
young trainee doctors in their own country using the available networks.
French data were analysed separately.¹³ Additionally, the survey was
advertised via Facebook groups. The survey was open from September
2015 to March 2016 and 12 reminders were sent to country coordinators.

The survey questionnaire was developed based on a literature re-
view⁹,¹⁰,¹⁴,¹⁵ and discussed by experts in medicine and survey method-
ology, who were authors of this study, through informal discussion. It was
prepared in the Slovenian (for Slovenia) and English (for other countries)
languages. In January 2016 the survey was translated into Spanish due to
the interest of the coordinator and slow response of Spanish-speaking par-
ticipants. The questionnaire was validated during a pilot phase that
included 34 participants. After the pilot phase, minor changes (Table S1,
available as Supplementary data at JAC Online) were made to the question-
naire and the final exploratory web survey consisted of 48 items covering
different topics: the decision-making process in prescribing antibiotics; self-
assessed knowledge; attitudes towards antibiotic resistance as a public
health issue; the perception of the role of antibiotic prescribing in the devel-
opment of resistance; the perception of prescribing patterns; the perceived
role of education; and the demographics of the participants (the question-
naire is available as Supplementary data at JAC Online). Most items used
four-point scales, with the exception of demographic variables and self-
assessed knowledge, which used a five-point scale. Topics were operation-
alized as blocks of questions, arranged on separate pages of the survey
questionnaire, which was then published as a customized 1KA survey.¹⁶ To
ensure only eligible respondents, two filter questions were included at the
beginning of the questionnaire.

Data analysis

After the survey had closed, data were then exported from the 1KA survey file and the three language versions were harmonized and merged into an SPSS file, with which further analyses were conducted. For the sake of the consistency and representability of the individual countries, we decided to include only participants from countries with >100 respondents. This enabled us to interpret the attitudes as the reflection of the culture on the country level.

Based on expert classification, a new variable comprising seven categories of specialty groups was derived from the raw data on specialties (paediatrics; family medicine; internal medicine; surgery; anaesthesiology, intensive care and emergency medicine; infectious diseases, clinical microbiology and tropical medicine; others). The groupings of the specialties are presented in Table S2.

In order to answer our research questions, we used the following ana-
lytical procedures:

* In the first step, a general descriptive overview of results by individual survey questions was prepared. Frequency distributions or average values were used.

* In the second step, we checked the structural equivalence and consistency of the measuring instrument (the questionnaire). The main objective in this phase was to check whether the respondents from different demographic groups (by country of specialization, type of specialization, year of training and gender) had understood the questions in the same way and consistently responded to individual questions within each dimension (group of questions covering the same issue), which was a precondition for valid between-group comparisons. Principal component analysis (PCA) was used. A more detailed description of PCA can be found elsewhere.¹⁷

* Development of composite indices for measuring different dimensions of the use of antibiotics was undertaken in the next step.

* Bivariate analyses (cross-tabulations, comparison of means) and multi-variate analyses [analysis of variance (ANOVA)] were used to investigate differences between different demographic groups of young doctors. To show the strength of associations, in the case of cross-tabulations Cramer's V was used, $\eta^2$ was used in the case of comparison of means and partial $\eta^2$ was used in the case of ANOVA. These indicators measure the strength of the association on a scale from 0 to 1 and are used in situations when at least one of the variables is categorical (Cramer's V) or where the independent variable is categorical ($\eta^2$). In social sciences we are talking about the existence of an association if Cramer's V exceeds the value of 0.1 or $\eta^2$ exceeds the value of 0.01.¹⁸

Results

Description of the data

The survey was completed by 2842 participants from 29 countries and 61 specialties. Further analysis was performed on 2366 (83.3%) participants from six countries with >100 respondents, presented in Table 1. In Greece the proportions of male and female respondents were the same; in all other countries the proportion of female respondents was higher. All years of training were included, with slightly fewer participants in the last 2 years of training. Excluding countries with a low number of respondents reduced the number of specialties to 56, which were later grouped into seven specialization groups (Table 1).

Practice and culture of antibiotic prescribing: results at
the level of individual questions

Most respondents (52.1%) prescribed antibiotics at least once
a day, 32.9% respondents prescribed antibiotics several times
<table><caption>**Table 1.** Characteristics of final sample of trainee doctors included in the analysis (N=2366).</caption><thead><tr><th>Characteristic</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Country</td><td></td><td></td></tr><tr><td>Spain</td><td>818</td><td>34.6</td></tr><tr><td>France</td><td>653</td><td>27.6</td></tr><tr><td>Slovenia</td><td>444</td><td>18.8</td></tr><tr><td>Italy</td><td>187</td><td>7.9</td></tr><tr><td>Portugal</td><td>154</td><td>6.5</td></tr><tr><td>Greece</td><td>110</td><td>4.6</td></tr><tr><td>Year of training<sup>a</sup></td><td></td><td></td></tr><tr><td>first year</td><td>498</td><td>21.0</td></tr><tr><td>second year</td><td>536</td><td>22.7</td></tr><tr><td>third year</td><td>584</td><td>24.7</td></tr><tr><td>fourth year</td><td>447</td><td>18.9</td></tr><tr><td>fifth and sixth years</td><td>301</td><td>12.7</td></tr><tr><td>Gender</td><td></td><td></td></tr><tr><td>male</td><td>883</td><td>37.3</td></tr><tr><td>female</td><td>1483</td><td>62.7</td></tr><tr><td>Specialty group</td><td></td><td></td></tr><tr><td>family medicine</td><td>682</td><td>28.8</td></tr><tr><td>internal medicine</td><td>637</td><td>26.9</td></tr><tr><td>surgery</td><td>204</td><td>8.6</td></tr><tr><td>anaesthesiology, intensive care and emergency medicine</td><td>180</td><td>7.6</td></tr><tr><td>paediatrics</td><td>176</td><td>7.4</td></tr><tr><td>infectious diseases, clinical microbiology and tropical medicine</td><td>161</td><td>6.8</td></tr><tr><td>others</td><td>326</td><td>13.8</td></tr></tbody></table>

<sup>a</sup>Fifth and sixth years are combined due to different lengths of specializations.

a week and only a minority (15%) less frequently (n=2366). Young doctors from Italy reported most frequent prescribing and those from Slovenia the least ($\eta^2$=0.021 and Cramer's V=0.12). Trainees in infectious diseases and related specialties were more frequent prescribers than colleagues from surgery or internal medicine ($\eta^2$=0.047 and Cramer's V=0.155). More than half of the surveyed young doctors prescribed antibiotics completely (14.6%) or mainly (39.6%) as instructed by the mentor (n=2348). The results varied according to the country of training [young doctors from Slovenia were the least autonomous ($\eta^2$=0.024, Cramer's V=0.124)] and by type of specialization [surgeons and family medicine trainees being the most and anaesthesiologists the least independent prescribers ($\eta^2$=0.014, Cramer's V=0.095)]. There was some increase in independent prescribing from the first to the fourth year of training ($\eta^2$=0.053, Cramer's V=0.142). Fifty-eight percent of young doctors perceived that their supervisors used the guidelines when prescribing antibiotics, while others (42%) claimed that personal experience prevailed. The answers did not differ significantly or systematically according to gender, country, specialty or year of specialization.

The answers to other individual questions and their association with the four demographic variables are presented in Table 2 and more detailed results are in Table S3. In general, we found that all variables (questions) were associated (Cramer's V>0.1 or

$\eta^2$ > 0.01) with the country of specialization (41 variables), followed by specialty groupings (23 variables), the year of training (8 variables) and gender (only 3 variables).

## Main dimensions of practice and culture of antibiotic prescribing: results of PCA

In order to determine whether answers fitted the aspects of prescribing antibiotics that were included in the survey, we conducted a PCA. In a stepwise procedure (details in Table S4) the following five dimensions of antibiotic prescribing culture were clearly identified (explaining 63.84% of variance): (i) self-assessed knowledge of prescribing antibiotics (SA_KNW); (ii) consideration of side effects when deciding to prescribe antibiotics (DM_SEFF); (iii) perception of different prescription patterns (PATTRN); (iv) consideration of patient's sickness (degree of illness) when deciding to prescribe antibiotics (DM_SICK); and (v) perception of the problem of antibiotic resistance (RESIST) (Table S4).

This structure of dimensions fitted quite well with the structure of antibiotic prescribing culture that we operationalized in the questionnaire. The same structure could also be identified for each individual demographic group of respondents. We were able to conclude that the questionnaire was understood in the same way among respondents.

Five composite indexes, representing the five dimensions resulting from the PCA referred to above, were developed for further analyses. Values for all dimensions were fairly high; mean values are above the middle of the scale in all five indices (Table S4).

## Influence of demographic factors on the culture of antibiotic prescribing: results of multivariate analyses of the level of composite indices

We performed multivariate analysis (ANOVA) separately for each of the five dimensions of antibiotic prescribing culture. Thus, we prepared five models with composite indices SA_KNW, DM_SEFF, PATTRN, DM_SICK and RESIST as the dependent variables. We did not include interactions in the models, but only the main effects of four factors (independent variables): country, specialization group, year of specialization and gender. We were therefore able to observe the 'direct' effect of each individual factor controlled for the other three factors included in the model.

The results confirmed the findings of the bivariate analyses at the level of individual survey questions. Country of specialization had the strongest influence (partial $\eta^2$=0.010-0.111), followed by specialization group (0.013-0.32), while, on the other hand, year of specialization and gender had little or no influence (Figure 1 and Table S5). The year of specialization had the strongest effect on self-assessed knowledge (0.071). Some relevant influence of gender on self-assessed knowledge was also found (0.013). Looking from the perspective of dependent variables, demographic variables best explained the scores for self-assessment of knowledge ($R^2$=0.153) (with the strongest effect being year of specialization) and the perception of bacterial resistance ($R^2$=0.142) (with country having the strongest effect by far). For the other three variables, the explanatory power of the model was much weaker (Table S5).
<table><caption>**Table 2.** Summary results for all individual variables on the culture of antibiotic prescription (mean values, bivariate associations with key demographic variables).</caption><thead><tr><th>Question</th><th></th><th>Mean (SD)</th><th>Country of specialization<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Specialty group<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Year of specialization<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Gender<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="12">I. My decision for treatment is based on ...<br>1—disagree strongly,<br>4—agree strongly</td><td>... my concern that I might miss/overlook something</td><td>2.67<br>(0.953)</td><td>0.166<br>0.254</td><td>no</td><td>no</td><td>no</td></tr><tr><td>... how sick the patient is</td><td>3.25<br>(0.800)</td><td>0.074<br>0.189</td><td>0.021<br>0.105</td><td>no</td><td>no</td></tr><tr><td>... the patient's immunodeficiency</td><td>3.59<br>(0.612)</td><td>no<sup>a</sup></td><td>0.022<br>0.103</td><td>no</td><td>no</td></tr><tr><td>... the patient's expectations</td><td>1.77<br>(0.818)</td><td>0.018<br>0.140</td><td>no</td><td>no</td><td>no</td></tr><tr><td>... local policy/guidance</td><td>3.18<br>(0.776)</td><td>0.264<br>0.335</td><td>0.010<br>0.122</td><td>no</td><td>no</td></tr><tr><td>... my senior's expectations</td><td>2.66<br>(0.830)</td><td>0.043<br>0.180</td><td>no</td><td>0.013<br>0.077</td><td>no</td></tr><tr><td>... clinical picture, laboratory results, imaging techniques</td><td>3.76<br>(0.482)</td><td>0.057<br>0.169</td><td>no</td><td>no</td><td>no</td></tr><tr><td>... the potential emergence of bacterial resistance to antibiotics</td><td>3.41<br>(0.676)</td><td>0.019<br>0.118</td><td>0.023<br>0.104</td><td>no</td><td>no</td></tr><tr><td>... the potential occurrence of <i>C. difficile</i> as a consequence of my antibiotic choice</td><td>2.84<br>(0.869)</td><td>0.048<br>0.166</td><td>0.055<br>0.142</td><td>no</td><td>no</td></tr><tr><td>... the potential side effects of the antibiotic treatment</td><td>3.17<br>(0.673)</td><td>0.012<br>0.117</td><td>no</td><td>no</td><td>no</td></tr><tr><td rowspan="12">II. Do I have the necessary knowledge to ...<br>1—not sufficient,<br>5—excellent</td><td>... decide whether or not a patient needs antibiotic treatment</td><td>3.83<br>(0.681)</td><td>0.016<br>0.095</td><td>no</td><td>0.037<br>0.109</td><td>no</td></tr><tr><td>... choose the most appropriate antibiotic</td><td>3.40<br>(0.831)</td><td>0.027<br>0.095</td><td>0.026<br>0.101</td><td>0.034<br>0.107</td><td>0.012<br>0.126</td></tr><tr><td>... decide on the proper dosage and dosing intervals of antibiotics</td><td>3.49<br>(0.952)</td><td>0.067<br>0.132</td><td>0.012<br>0.073</td><td>0.078<br>0.152</td><td>no</td></tr><tr><td>... decide on the proper duration of antibiotic treatment</td><td>3.41<br>(0.874)</td><td>0.041<br>0.110</td><td>0.018<br>0.090</td><td>0.034<br>0.104</td><td>no</td></tr><tr><td>... properly choose between parenteral and oral antibiotic treatment</td><td>3.64<br>(0.890)</td><td>0.016<br>0.069</td><td>no</td><td>0.029<br>0.093</td><td>no</td></tr><tr><td>... to appropriately interpret microbiology results</td><td>3.73<br>(0.858)</td><td>0.035<br>0.106</td><td>no</td><td>no</td><td>0.012<br>0.125</td></tr><tr><td rowspan="2">III. De-escalation<br>1—disagree strongly,<br>4—agree strongly</td><td>In the case of positive microbiology results I tend to de-escalate antibiotic treatment if possible (changing to narrow spectrum)</td><td>3.54<br>(0.674)</td><td>0.032<br>0.141</td><td>0.050<br>0.140</td><td>no</td><td>no</td></tr><tr><td>For patients receiving parenteral treatment, I use every opportunity to switch to oral therapy</td><td>3.23<br>(0.728)</td><td>0.036<br>0.131</td><td>no</td><td>no</td><td>no</td></tr><tr><td rowspan="4">IV. Bacterial resistance to antibiotics is ...<br>1—not a problem,<br>5—major problem</td><td>... a global problem</td><td>3.81<br>(0.428)</td><td>0.011<br>0.074</td><td>no</td><td>no</td><td>no</td></tr><tr><td>... a problem in your country</td><td>3.56<br>(0.591)</td><td>0.092<br>0.180</td><td>0.012<br>0.081</td><td>no</td><td>no</td></tr><tr><td>... a problem in your workplace</td><td>3.26<br>(0.756)</td><td>0.106<br>0.194</td><td>0.043<br>0.128</td><td>no</td><td>no</td></tr></tbody></table>

Continued
<table><caption>**Table 2. Continued**</caption><thead><tr><th>Question</th><th></th><th>Mean (SD)</th><th>Country of specialization<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Specialty group<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Year of specialization<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th><th>Gender<br>η<sup>2</sup><br>Cramer's V<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="4"><strong>V. Importance of appropriate prescription</strong></td><td>Inappropriate use of antibiotics is an important reason for the development of bacterial resistance to antibiotics</td><td>3.86<br>(0.354)</td><td>0.063<br>0.156</td><td>no</td><td>no</td><td>no</td></tr><tr><td>1—disagree strongly, 4—agree strongly</td><td>3.64<br>(0.552)<br>3.46<br>(0.603)<br>2.39<br>(0.714)</td><td>0.080<br>0.172<br>0.031<br>0.197<br>0.019<br>0.125</td><td>no</td><td>no</td><td>no</td></tr><tr><td>Unnecessary antibiotic treatment can be (directly) harmful for individual patients</td><td>3.64<br>(0.552)</td><td>0.080<br>0.172</td><td>no</td><td>no</td><td>no</td></tr><tr><td>Doctors prescribe antibiotics more often than necessary</td><td>3.46<br>(0.603)</td><td>0.031<br>0.197</td><td>no</td><td>no</td><td>no</td></tr><tr><td rowspan="4"><strong>VI. Limiting antibiotic use</strong></td><td>I (myself) prescribe antibiotics more often than necessary</td><td>1.97<br>(0.763)</td><td>0.086<br>0.203</td><td>no</td><td>no</td><td>no</td></tr><tr><td>Limiting the use of antibiotics is harmful for the patient</td><td>1.97<br>(0.763)</td><td>0.086<br>0.203</td><td>no</td><td>no</td><td>no</td></tr><tr><td>I try to avoid antibiotics that need approval</td><td>2.04<br>(0.794)</td><td>0.081<br>0.213</td><td>0.033<br>0.124</td><td>no</td><td>no</td></tr><tr><td>Limiting the use of antibiotics will help reduce bacterial resistance</td><td>2.04<br>(0.794)</td><td>0.081<br>0.213</td><td>0.033<br>0.124</td><td>no</td><td>no</td></tr><tr><td rowspan="4"><strong>VII. Prescribing patterns</strong></td><td>1—disagree strongly, 4—agree strongly</td><td>3.50<br>(0.620)<br>2.73<br>(0.975)</td><td>0.026<br>0.145<br>0.035<br>0.150</td><td>no</td><td>no</td><td>no</td></tr><tr><td>Limiting the duration of antibiotic treatment will help reduce bacterial resistance</td><td>3.50<br>(0.620)<br>2.73<br>(0.975)</td><td>0.026<br>0.145<br>0.035<br>0.150</td><td>0.051<br>0.139</td><td>0.014<br>0.079</td><td>no</td></tr><tr><td>When rotating through different departments, I notice that they each have their own 'prescribing habits' in antibiotic use</td><td>3.36<br>(0.654)</td><td>0.045<br>0.143</td><td>no</td><td>no</td><td>no</td></tr><tr><td>I notice that certain departments consider their patients 'different' and they do not follow guidelines</td><td>2.82<br>(0.842)</td><td>0.006<br>0.128</td><td>0.012<br>0.078</td><td>no</td><td>no</td></tr><tr><td rowspan="4"><strong>VIIc. When choosing an antibiotic, I prescribe antibiotic...</strong></td><td>1—disagree strongly, 4—agree strongly</td><td>2.88<br>(0.737)</td><td>0.022<br>0.149</td><td>0.024<br>0.106</td><td>no</td><td>no</td></tr><tr><td>1—completely on my own, 4—as told by my mentor</td><td>2.56<br>(0.887)</td><td>0.024<br>0.124</td><td>0.014<br>0.095</td><td>0.053<br>0.142</td><td>no</td></tr><tr><td>VIId. When prescribing antibiotics, supervising specialists/senior colleagues prescribe...</td><td>2.35<br>(0.901)</td><td>no</td><td>no</td><td>no</td><td>no</td></tr><tr><td>1—adhere to the guidelines, 4—according to personal experience</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4"><strong>When choosing an antibiotic, I tend to...</strong></td><td>1—disagree strongest, 4—agree strongly</td><td>3.43<br>(0.561)<br>2.88<br>(0.692)</td><td>0.017<br>0.109<br>0.089<br>0.206</td><td>0.012<br>0.079<br>no</td><td>no</td><td>no</td></tr><tr><td>1—choose an antibiotic according to prescribing patterns (habits) of the department or hospital where I work</td><td>3.43<br>(0.561)<br>2.88<br>(0.692)</td><td>0.017<br>0.109<br>0.089<br>0.206</td><td>0.012<br>0.079<br>no</td><td>no</td><td>no</td></tr><tr><td>1—choose an antibiotic that I feel comfortable with</td><td>3.43<br>(0.561)<br>2.88<br>(0.692)</td><td>0.017<br>0.109<br>0.089<br>0.206</td><td>0.012<br>0.079<br>no</td><td>no</td><td>no</td></tr><tr><td>I believe that good knowledge of antibiotics is important for my work</td><td>3.43<br>(0.561)<br>2.88<br>(0.692)</td><td>0.017<br>0.109<br>0.089<br>0.206</td><td>0.012<br>0.079<br>no</td><td>no</td><td>no</td></tr><tr><td rowspan="4"><strong>VIII. Education</strong></td><td>1—disagree strongly, 4—agree strongly</td><td>3.84<br>(0.404)<br>3.15<br>(0.719)</td><td>0.012<br>0.087<br>0.036<br>0.139</td><td>0.016<br>0.092<br>0.011<br>0.078</td><td>no</td><td>no</td></tr><tr><td>I am aware of the guidelines and recommendations for antibiotic use in the hospital where I work</td><td>3.84<br>(0.404)<br>3.15<br>(0.719)</td><td>0.012<br>0.087<br>0.036<br>0.139</td><td>0.016<br>0.092<br>0.011<br>0.078</td><td>no</td><td>no</td></tr><tr><td>I wish to get more training/education on antibiotics</td><td>3.67<br>(0.530)</td><td>0.032<br>0.116</td><td>0.016<br>0.078</td><td>no</td><td>0.011<br>0.109</td></tr><tr><td>I get a lot of information on antibiotics and their potential use from representatives of pharmaceutical companies</td><td>3.67<br>(0.530)<br>1.93<br>(0.789)</td><td>0.032<br>0.116<br>0.024<br>0.119</td><td>0.016<br>0.078<br>no</td><td>no</td><td>no</td></tr></tbody></table>

<footnote><sup>a</sup>We are talking about the existence of an association if Cramer's V exceeds the value of 0.1 or η² exceeds the value of 0.01.<sup>18</sup></footnote>
Discussion

The key finding of our study is the impact of the country of special-
ization on antibiotic prescribing.

This was also identified as the most important variable associ-
ated with the five dimensions of antibiotic prescribing culture.
However, we cannot state a single pattern of influence for all
dimensions of prescribing culture (dependent variables) since we
detected a slightly different ‘pattern’ of influence and dimensions
of culture of prescribing among countries of specialization. Indeed,
international differences in perception of antibiotic resistance in
the workplace were found in a study that compared Scottish and
French trainee doctors, and they also differed in attitudes to seek-
ing advice from seniors and other professionals.¹⁰

In respect of antibiotic prescribing, specialty training was the se-
cond most important demographic factor identified in our study.
For example, we found trainees in family medicine and surgery to
be the most autonomous prescribers and, as expected, trainees in
infectious diseases, clinical microbiology and tropical medicine
were the most confident about their level of knowledge related to
antibiotic prescribing, were more concerned about *Clostridioides
(Clostridium) difficile* infection, were more likely to de-escalate and
were more aware of the impact of limitation of treatment duration
on antibiotic resistance. Some other studies have also shown asso-
ciations between self-assessed knowledge and specialty
training.¹⁹,²⁰

Perception of resistance in the different specialties was only
marginally different. The association between the type of specialty
and the five dimensions identified by PCA was modest. The differ-
ences seem to be attributable mostly to the familiarity with topics
that are expected to be better covered in infectious diseases and
related specialties, less than to any inter-specialty cultural differ-
ences.²¹ A few studies have addressed the differences in special-
ties for antibiotic prescribing and resistance. For example, Cortoos
et al.¹¹ found lower use of guidelines but higher acceptance of con-
sultations by surgeons than by internal medicine residents, and
surgeons sought advice more often in a study by Srinivasan et al.²²

In our study, trainee doctors with more years of training were
more autonomous prescribers, a finding in line with the changing
relationship between decision making and prescribing in advanc-
ing grades of doctor observed in a recent study.²³ The number of
years of training was only associated with self-perceived know-
ledge. Gender appeared to have very little influence in our study,
although there was significantly higher self-perceived knowledge
in male trainees, with female trainees expressing greater need for
additional training in this area; these differences had already been
observed in a recent study on preparedness for antibiotic prescrib-
ing in students.²⁴

The majority of the respondents claimed that clinical presenta-
tion and the issue of antibiotic resistance dominated their deci-
sions on antibiotic treatment, as opposed to patient and senior
expectations and concerns not to miss anything. This is different
from a US trainee study where decisions were mostly based on the
fear of missing an infection and severity of illness or immunocom-
promised state of the patient. However, in keeping with our results
patient expectation did not play a significant role.¹⁵

Our study also found that antibiotic prescribing was mostly
influenced by guidelines, in contrast with an Irish study where the
influence of seniors was a more important determinant,²⁵ and a

French study that revealed the influence of the trainees' own
experiences.²⁶

In line with the findings of several previous studies, our study
observed that antibiotic resistance was the least recognized as a
problem at the doctor's workplace. Repeatedly, young and senior
doctors claimed that resistance is more a problem on the national
or global level.²⁷ Overprescribing of antibiotics by other doctors as
opposed to the surveyed doctors seemed to predominate, consist-
ent with the findings reported by May and co-workers.²⁸ The weak-
est parts of self-assessed knowledge in our study were the choice
of antibiotic and treatment duration. Treatment duration was also
recognized as one of most difficult decisions by French and
Scottish trainees.¹⁰,²⁶ Additional training in antibiotic use was
requested by most of the respondents in our study as well in other
studies.¹⁵,²⁹,³⁰ In our study, the role of the pharmaceutical industry
in education on antibiotics was rated as low, consistent with find-
ings from several other studies.¹⁰,²¹,³⁰,³¹

Due to the importance of the country of specialization in
explaining the differences regarding prescribing culture, we as-
sume that factors should also be investigated at a macro level. At
least two types of phenomena may be relevant: (i) facts about pre-
scribing antibiotics and antibiotic resistance; and (ii) norms and
prevailing values in a country.

Looking at some of the statistical data about antibiotic use and
resistance³²,³³ supports our thesis about the importance of macro
(country level) phenomena. Antibiotic overuse was perceived to be
least problematic by Slovenian trainees. At the same time the use
of antibiotics in Slovenia according to the European Surveillance of
Antibiotic Consumption Network³² was lower than in other partici-
pating countries. This suggests that the respondents correctly per-
ceive the situation in their country or working environment. A
systematic analysis of such relationships between the results of
our study and antibiotic use and resistance is warranted.

When we consider prescribing culture, we cannot overlook the
findings of various international comparative social studies on
human values. For example, Hofstede et al.¹² spoke about the im-
portance of values for understanding the behaviour of individuals
in health and education. Several studies have found interesting
relationships between the attitudes towards antibiotic use and
antibiotic prescribing practices. The differences in outpatient anti-
biotic use can be explained by power distance, uncertainty avoid-
ance, hierarchy, masculinity and religion,⁶ and the frequency of
prolonging antibiotic surgical prophylaxis beyond 24 h is concord-
ant with uncertainty avoidance.⁷ In our study, for example,
self-assessed knowledge was lowest in more individualist coun-
tries (in our case, France and Italy), which ties in with Hofstede's in-
terpretation that the main purpose of education in individualist
societies is learning 'how to learn'.¹² Again, a more systematic ana-
lysis of the relationship between the results of the study and socio-
cultural dimensions is needed.

Given the fact that lists of all young medical doctors were not
available to the researchers in the majority of countries used in this
study, the sample is non-probabilistic. When we investigated the
relations between phenomena (variables), especially with multi-
variate methods, this was less of an issue. Some poor understand-
ing of the questions may be anticipated due to the language
barrier. Because of different organization of postgraduate training
we were not able to make the distribution of the questionnaire in
the participating countries uniform, and we also did not focus on
<figure><img src="image_2.png" /><figcaption>**Figure 1.** Association between four demographic variables (gender, country, year of specialization and specialty group) and five dimensions of antibiotic prescription culture (composite indices) (effect size of demographic variables is presented with partial η²).</figcaption></figure>

specific specialties. We must also draw attention to limitations due to only six countries, mainly southern and continental European countries, being involved in the study and an uneven number of participants per country. Inclusion of other countries, such as the UK or Scandinavian countries, may give different results related to different educational system and sociocultural aspects. However, the findings can be a good starting point for new research involving more countries with a large enough sample of surveyed trainees.

In conclusion, this is the first study to explore the differences in antibiotic prescribing practices, attitudes and beliefs in young doctors with regard to their specialty and country of training. The results clearly showed that the culture formed within the national context (national culture) prevails over the occupational and organizational culture related to the specialties. The differences between specialties in our study call for education in responsible antibiotic prescribing at an international level and in all specialty curricula. Internationally defined specialty curricula (UEMS) and antibiotic prescribing competencies³⁴,³⁵ that should be included in all specialty training would provide a good starting point.

## Acknowledgements

Preliminary results of the study were presented as posters at the Twenty-Sixth European Congress of Clinical Microbiology and Infectious Diseases, Amsterdam, The Netherlands, 2016 (Abstract P1302) and at the Twenty-Seventh European Congress of Clinical Microbiology and Infectious Diseases, Vienna, Austria, 2017 (Abstract P1116).

## Funding

The major part of the work has been a part of the routine work of the organizations involved. The study was partially supported by a non-restricted grant from Merck Sharp & Dohme, inovativna zdravila d.o.o. to the Faculty of Medicine, University of Ljubljana, and by Slovenian Research Agency Research Program Slovene Public Opinion (P5-0151) at the Faculty of Social Sciences, University of Ljubljana.

## Transparency declarations

None to declare.

## Author contributions

B. B. designed the study, oversaw the survey, contributed to the analysis of the results and drafted the manuscript. M. D. led the survey, analysed the results and contributed to the manuscript. C. P. contributed to the questionnaire, distributed the survey and revised the manuscript. G. B. distributed the survey and revised the manuscript. J. R. P. P. distributed the survey and translated it into Spanish. D. S.-F. distributed the survey and helped with the translation into Spanish. D. K. distributed the survey. J. C. distributed the survey. L. P. distributed the survey. M. K. helped with the design of the questionnaire. K. N. helped with the distribution of the survey. M. H. F. designed the analysis and contributed to the manuscript. D. N. revised the questionnaire and revised the manuscript. S. U. revised the questionnaire, overlooked the analysis of the data and revised the manuscript.
**Supplementary data**

Tables S1 to S5 and the questionnaire are available as Supplementary data at JAC Online.

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