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Background: Much effort has been made over the last two decades to educate and train healthcare professionals working on antimicrobial resistance in French hospitals. However, little has been done in France to assess perceptions, attitudes and knowledge regarding multidrug resistant organisms (MDROs) and, more globally, these have never been evaluated in a large-scale population of medical and non-medical healthcare workers (HCWs). Our aim was to explore awareness among HCWs by evaluating their knowledge of MDROs and the associated control measures, by comparing perceptions between professional categories and by studying the impact of training and health beliefs. Methods: A multicentre cross-sectional study was conducted in 58 randomly selected French healthcare facilities with questionnaires including professional and demographic characteristics, and knowledge and perception of MDRO transmission and control. A knowledge score was calculated and used in a logistic regression analysis to identify factors associated with higher knowledge of MDROs, and the association between knowledge and perception. Results: Between June 2014 and March 2016, 8716/11,753 (participation rate, 74%) questionnaires were completed. The mean knowledge score was 4.7/8 (SD: 1.3) and 3.6/8 (SD: 1.4) in medical and non-medical HCWs, respectively. Five variables were positively associated with higher knowledge: working in a university hospital (adjusted odds ratio, 1.41, 95% CI 1.16–1.70); age classes 26–35 years (1.43, 1.23–1.6) and 36–45 years (1.19, 1.01–1.40); medical professional status (3.7, 3.09–4.44), working in an intensive care unit (1.28, 1.06–1.55), and having been trained on control of antimicrobial resistance (1.31, 1.16–1.48). After adjustment for these variables, greater knowledge was significantly associated with four cognitive factors: perceived susceptibility, attitude toward hand hygiene, self-efficacy, and motivation. Conclusions: We found a low level of MDRO awareness and knowledge of associated control measures among French HCWs. Training on hand hygiene and measures to control MDRO spread may be helpful in shaping beliefs and perceptions on MDRO control among other possible associated factors. Messages should be tailored to professional status and their perception. Other approaches should be designed, with more effective methods of training and cognitive interventions. Trial registration: Clinical Trials.gov NCT02265471. Registered 16 October 2014 - Retrospectively registered. Keywords: Healthcare workers, Health personnel/classification/education, Drug resistance, bacterial, Cross-infection/ *prevention & control, Cross-sectional studies, Hand disinfection, Health knowledge, attitudes, practice, Surveys and questionnaires, France * Correspondence: firstname.lastname@example.org AP-HP, Bichat-Claude Bernard Hospital, Infection Control Unit, 48 rue Henri Huchard, F-75018 Paris, France Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 2 of 10 Background Each initial randomised HCF (n =60) was contacted Antimicrobial resistance (AMR) is a growing problem through the local infection prevention and control (IPC) worldwide. Multidrug-resistant organisms (MDROs) are team. A total of 46 HCFs agreed to participate during the challenging healthcare workers (HCWs) in their daily prac- first round of randomisation. When an HCF declined to tice and there is an urgent need for improved infection pre- participate (n = 21), another HCF was randomly selected vention and control (IPC) practices and antimicrobial following the same scheme of stratification sampling. stewardship. Many guidelines and training materials have Twelve other HCFs agreed to participate across three been issued for the control of MDRO transmission. Suc- other rounds of sampling. The number of clinical units cessful interventions have served as a framework for the participating in the survey was correlated with the total implementation of further control programmes [1, 2]. How- number of beds in the facility, from 15 to 50% of clinical ever, recommendations alone are not enough to improve units randomly selected in large HCFs, to 100% in small compliance with best practices. As demonstrated in the HCFs. Adult and paediatric clinical units were eligible, in- context of hand hygiene, guidelines must be associated with cluding intensive care (ICU), medical and surgical units, an implementation process considering contextual and be- rehabilitation and long-term care, emergency, outpatient, havioural determinants . A strong association between and radiology units. Eligible HCWs included physicians knowledge, perceptions, and ultimately actions has been (senior, junior, and medical students) and non-medical suggested in previous research on AMR [4, 5]. Some studies professionals i.e. nurses, nurse aides, nursing students, found an impact of knowledge,attitudes,and personal head nurses, hospital service agents (including cleaning perceptions, including perceived benefits and barriers, on staff and domestic services) and medical-technical agents the behaviours and practices of HCWs in IPC [6–9]. (including technical staff members, i.e. dieticians, X-ray Surveys on the knowledge and perception of AMR technicians, physiotherapists, psychologists, …)present have primarily focused on antibiotic prescription, ex- during the day and night shifts. HCWs in laboratories, cluding infection control measures . More recently, housekeeping personnel, and administrative personnel several studies have jointly assessed knowledge, attitudes, were excluded. and practices regarding both MDROs and transmission precautions [11–13]. The findings indicated that few Study design physicians were concerned with their own infection con- This cross-sectional study was performed from June trol practices, though they were aware of the threat of 2014 to March 2016. Interviewers included members of AMR. Most of them targeted junior doctors or medical the study team and members of the local IPC team. students . The day of the survey, interviewers went through the Our aim was to explore awareness among HCWs by different included units several times a day (including evaluating their general knowledge on MDROs and asso- the night) to ask participants to complete anonymously ciated control measures, comparing perceptions between a self-administered questionnaire requiring 10–15 min professional categories, and studying the impact of train- to fill. The total number of HCWs present on site the ing and beliefs. Hence, a questionnaire-based survey was day of the survey was used to compute the participation developed to identify the association between know- rate. This information was provided by the local human ledge, perceptions, and attitudes towards MDROs and resources services. control measures (gloves, hand hygiene). Questionnaire The questionnaire was structured in three different parts: Methods (i) professional characteristics including gender, age, pro- Hospitals and participants fessional status, job tenure, working unit, main activity of The study was conducted in 58 randomly selected French the unit, working shift, and previous training sessions healthcare facilities (HCFs). Among them, nine were during the last 3 years about hand hygiene and contact university hospitals or referral centres for cancer (UHs), precautions; (ii) assessment of knowledge on the transmis- 10 non-university public hospitals (NUPHs), 10 private sion and control of MDROs (Additional file 1: Table S1) HCFs, and 29 in a group mixing local hospitals (n =10), including hand hygiene (three questions), glove use (two nursing homes (n = 10), rehabilitation and long-term care questions), and epidemiology of MDROs (three ques- facilities (LTCFs, n = 9). Random sampling was used to tions); (iii) and the perception of AMR included (Add- select participating HCFs, stratified into five geographical itional file 1: Table S2) the perceived threat of MDROs areas corresponding to the French interregional coord- (three questions), individual cognitive factors for hand hy- inating centres for infection prevention and control giene compliance (eight questions), based on the theory of (CCLIN). This sample represented 2.0% of the total health belief model [15–17]. This model enabled the as- number of French HCFs (58/2931). sessment of the following criteria: perceived susceptibility, Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 3 of 10 perceived knowledge, intention to adhere (perceived prac- univariable analysis were then adjusted for significant vari- tice), attitudes toward hand hygiene, perceived behavioural ables in the first multivariable model. Reference groups norm, perceived subjective norm, self-efficacy, and motiv- for multivariate analysis were selected from an epidemio- ation (Additional file 1: Table S3) regarding one specific logical perspective. R software (v3.14) was used. topic. Items related to beliefs and perception were coded on a 7-point Likert scale, ranging from 1, “strongly dis- Results agree” to 7, “strongly agree” with the statement of the Healthcare facilities and participants item. The questions were selected by the steering group Among the 58 participating HCFs, a total of 8716 HCWs which included experts in infectious diseases, public completed the questionnaire. The overall participation health, infection control and statistics. Questions on rate was 74% (8716/11,753), ranging from 35 to 100% infection control (hand hygiene and gloves) and the across individual HCFs, with participations of 55% epidemiology of AMR were selected according to (1291/2335) for the medical healthcare workers (MWs) current national guidelines. The questionnaire was first and 79% (7425/9418) for the non-medical healthcare tested among individuals from various professional workers (NMWs). The characteristics of the population backgrounds, and some questions were revised slightly are presented in Table 1. Most participants were female according to their comments. (7103/8716; 83%), representing 50% (63/291) and 88% (6469/7425) of MWs and NMWs, respectively. The me- Statistical analysis dian age was 33 (Q1; Q3, 27; 47) years old and 37 (28; Continuous variables were expressed as mean and stand- 48) years old in MWs and NMWs, respectively. Overall, ard deviation (SD) or median and interquartile range (Q1: 5753 (68%) and 2787 (34%) HCWs declared having been 25th percentile; Q3: 75th percentile), and categorical vari- trained on hand hygiene and control of AMR over the 3 ables as frequency (percentage). Comparisons between years prior to the survey, respectively. two groups were made using the Chi2 test or Student’st test or their corresponding non-parametric versions, Fish- Awareness and associated factors er’s test or the Wilcoxon rank sum test, as appropriate. The mean KS on AMR and control measures was 4.7/8 Comparisons between more than two groups were made among MWs and 3.6/8 among NMWs (P < 0.0001) (Table 2). using the Hochberg method for multiple comparisons in They both differed between the type of HCFs (p < 0.001), order to adjust for the alpha level. The principal endpoint with a medical KS significantly higher in UHs, and a non- was the knowledge score (KS) defined by the sum of cor- medical KS significantly lower in the LTCF group. rect answers out of eight questions (Additional file 1: Most respondents wrongly thought that hand hygiene Table S1). The KS was compared among HCF categories, was more important after than before contact with a pa- age classes, professional statuses, working units, and other tient (58% MWs, 52% NMWs); alcohol-based hand rub professional characteristics, using the Kruskal–Wallis test. (AHR) was correctly considered more effective than The KS was then categorised in two classes by its me- antiseptic or plain soap (76% MWs, 50% NMWs) (Add- dian value, KS lower than four or KS equal to or greater itional file 1: Table S1). A large proportion, (> 90%) than four. Multivariate logistic regression models were believed that gloves were indicated for contact precau- used to assess the association between professional char- tions. Standard precautions (hand hygiene after contact acteristics and KS. with the patient’s environment and no glove wearing for For multivariate analyses, variable selection was done in contact with the patient’s intact skin) were correctly order to select the best subset of predictors of knowledge. known (higher than 80% in both MWs and NMWs). Initial selection was determined by the clinical value of Knowledge on the MDRO epidemiology was greater predictors. Then, final selection of explanatory variables in among MWs; 85% of MWs and 67% of NMWs consid- the multivariate analysis was done using stepwise methods ered that methicillin-resistant Staphylococcus aureus based on the AIC (Akaike Information Criterion). All (MRSA) was mainly hand-transmitted. A large propor- questions about perception and beliefs on the 7-point tion of respondents thought that rates of both MRSA Likert scale were dichotomised: no agreement with the (89% MWs, 95% NMWs) and extended-spectrum beta- proposition (“Strongly disagree”, “Disagree”, “Somewhat lactamase-producing Enterobacteriaceae (ESBLPE) (83% disagree”, “Neither agree nor disagree”,and “Somewhat MWs, 42% NMWs) were increasing in France. agree”) and agreement with the proposition (“Agree” and In the univariate analysis (Table 3), variables associ- “Strongly agree”). The latter denoted strong positive ated with a KS ≥ 4 were: the category of HCF, male gen- agreement with the proposition. All other quotations der, an age between 26 and 35 years, the medical scores (from 1 to 5) were considered negative according professional status, a shorter current job tenure, working to previous studies in the field of infection control . in an ICU and having been trained on AMR control Significant associations between perception and KS in the measures. In the multivariate logistic regression analysis, Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 4 of 10 Table 1 Population characteristics Total (58 HCFs) University hospitals/ Non-university Small, rehabilitation, Private clinics Cancer centres (n =9) hospitals (n = 10) nursing hospitals (n = 29) (n = 10) Participants n (%) - Total 8716 (100) 4015 (46) 2187 (25) 1885 (22) 629 (7) - Medical 1291 (15) 818 (20) 285 (13) 99 (5) 89 (14) - Non-medical 7425 (85) 3197 (80) 1902 (87) 1786 (95) 540 (86) Male gender n (%) - Total 1499 (17) 771 (19) 371 (17) 219 (12) 138 (22) - Medical 637 (50) 375 (47) 143 (51) 54 (56) 65 (75) - Non-medical 862 (12) 396 (12) 228 (12) 165 (9) 73 (14) Age median (Q1;Q3) - Total 37 (28; 48) 34 (27; 46) 39 (30; 47) 40 (29; 50) 39 (30; 51) - Medical 33 (27; 47) 29 (25; 38) 41 (30; 50) 52 (42; 60) 54 (41; 61) - Non-medical 37 (28; 48) 35 (28; 47) 39 (30; 47) 39 (29; 49) 37 (29; 50) Professional status n (%) - Senior physician 787 (9) 395 (10) 213 (10) 93 (5) 86 (14) - Junior doctor 332 (4) 271 (7) 57 (3) 2 (0) 2 (0) - Medical student 165 (2) 149 (4) 12 (1) 3 (0) 1 (0) - Nurse 2842 (34) 1468 (37) 751 (35) 352 (20) 271 (44) - Nurse aide 2231 (26) 800 (20) 674 (31) 641 (36) 116 (19) - Hospital service agent 707 (8) 208 (5) 123 (6) 322 (19) 54 (9) - Medical-technical agent 506 (6) 245 (6) 93 (4) 157 (9) 11 (2) - Non-medical student 407 (5) 178 (5) 105 (5) 93 (5) 31 (5) - Other 487 (6) 233 (6) 111 (5) 103 (6) 40 (7) Job tenure (median (Q1; Q3)) - Total 10 (4; 20) 8 (3; 20) 11 (5; 20) 10 (4; 20) 12 (5; 26) - Medical 6 (2; 19) 4 (2; 11) 12 (3; 20) 24 (10; 30) 26 (13; 32) - Non-medical 10 (4; 20) 10 (4; 20) 11 (5; 20) 10 (4; 18) 10 (4; 22) Working unit n (%) - Medicine 2742 (33) 1720 (45) 790 (38) 104 (6) 128 (21) - Intensive care unit 776 (9) 535 (14) 175 (8) 0 (0) 66 (11) - Emergency 395 (5) 245 (6) 139 (7) 2 (0) 9 (2) - Rehabilitation, long-term care 2491 (30) 227 (6) 522 (25) 1687 (92) 55 (9) - Surgery 1610 (19) 923 (24) 366 (17) 0 (0) 321 (53) - Gynaecology-Obstetrics 123 (1) 66 (2) 47 (2) 1 (0) 9 (1) - Psychiatry 96 (1) 58 (1) 23 (1) 15 (1) 0 (0) - Other 158 (2) 84 (2) 45 (2) 14 (1) 15 (2) Q1: 25th percentile; Q3: 75th percentile five variables remained positively associated with greater p < 0.0001). Working in rehabilitation and long-term knowledge: working in a UH (adjusted odds ratio, 1.41; care units (0.81, 0.68–0.96, p =0.014) was negatively 95% CI, 1.16–1.70; p < 0.005); age classes 26–35 years associated with a higher KS. (1.43, 1.23–1.67, p < 0.0001) and 36–45 years (1.19, 1.01–1.40, p = 0.037); medical professional status (3.70, Knowledge score and perceptions 3.09–4.44, p < 0.0001), working in an ICU (1.28, 1.06– After adjustment for variables significantly associated 1.55, p = 0.011) and having been trained on control of with better knowledge (type of HCF, male gender, age, AMR within the previous 3 years (1.31, 1.16–1.48, medical professional status, working unit, and having Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 5 of 10 Table 2 Knowledge score (KS) regarding antimicrobial resistance and infection control measures N (%) Knowledge score (mean (SD)) p-value (global) Type of healthcare facility - University hospitals / cancer centres 4015 (46) 4.0 (1.4) p < 0.001 - Non-university hospitals 2187 (25) 3.7 (1.4) - Small, rehabilitation, nursing hospitals 1885 (22) 3.4 (1.5) - Private clinics 629 (7) 3.8 (1.4) Professional status - Medical (total) 1284 (15) 4.7 (1.3) p < 0.0001* - Senior physician 787 (61) 4.6 (1.4) - Junior doctor 332 (26) 4.9 (1.2) - Medical student 165 (13) 4.6 (1.3) - Non-medical (total) 7180 (85) 3.6 (1.4) - Nurse 2842 (40) 4.1 (1.3) - Nurse aide 2231 (31) 3.3 (1.3) - Hospital service agent 707 (10) 2.6 (1.3) - Medical-technical agent 506 (7) 3.6 (1.4) - Non-medical student 407 (6) 3.9 (1.3) - Other 487 (7) 4.0 (1.5) Working unit - Medicine 2742 (32) 3.9 (1.4) p < 0.0001 - Surgery 1610 (18) 3.8 (1.4) - Intensive care unit 776 (9) 4.2 (1.5) - Rehabilitation, long-term care 2491 (29) 3.5 (1.5) - Emergency 395 (5) 4;1 (1.4) - Gynaecology-Obstetrics 123 (1) 3.6 (1.4) - Psychiatry 96 (1) 3.5 (1.5) - Other 158 (2) 3.5 (1.6) Previous training for hand hygiene (last 3 years) - Yes 5753 (68) 3.8 (1.5) p < 0.0001 - No 2769 (32) 3.7 (1.4) Previous training in control of AMR (last 3 years) - Yes 2787 (34) 4.0 (1.5) p < 0.0001 - No 5413 (66) 3.7 (1.4) *p value medical vs. non-medical received training sessions), a higher KS was significantly Discussion associated with four cognitive factors: perceived suscep- To date, this is the first study evaluating the associ- tibility (2.33, 95% CI, 1.95–2.78, p < 0.0001), positive atti- ation between knowledge of AMR epidemiology, the tude toward hand hygiene (1.98, 1.65–2.37, p < 0.0001), associated control measures, and the individual cogni- self–efficacy (1.22, 1.09–1.38, p < 0.001), and motivation tive factors, including both MWs and NMWs from a (1.42, 1.24–1.62, p < 0.0001) (Table 4). national representative population of HCFs. The 74% participation rate was unexpectedly high and may be Perceptions of the antimicrobial resistance threat ascribable to the active participation of IPC teams Most participants perceived AMR as a national problem and the direct physical contact of investigators with (Additional file 1: Table S2) (98% MWs, 88% NMWs), ward staff. This large panel therefore accurately re- while fewer (66% MWs, 40% NMWs) viewed AMR as a flects the situation in France and enabled comparison local problem, with a low impact on their daily practices of the KS in different categories of HCFs and types of (65% MWs, 38% NMWs). healthcare units. Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 6 of 10 Table 3 Factors associated with greater knowledge of antimicrobial resistance and infection control measures Population-based variables Population (n, %) Univariate analysis Multivariate analysis (OR (95% CI)) (adjusted OR (95% CI)) KS < 4 KS ≥ 4 Type of HCF - University hospitals / Cancer centres 1385 (34) 2630 (66) 2.04 (1.83–2.28) 1.41 (1.16–1.70) - Non-university hospitals 978 (45) 1209 (55) 1.33 (1.18–1.51) 0.99 (0.83–1.19) - Small, rehabilitation, nursing hospitals 977 (52) 908 (48) 1.00 1.00 - Private clinics 259 (41) 370 (59) 1.54 (1.28–1.84) 1.08 (0.84–1.39) Gender - Male 477 (32) 1022 (68) 1.63 (1.44–1.83) 1.13 (0.97–1.29) - Female 3064 (43) 4039 (57) 1.00 1.00 Age (years) - < 25 511 (41) 726 (59) 1.00 1.00 -26–35 853 (34) 1634 (66) 1.35 (1.17–1.55) 1.43 (1.23–1.67) -36–45 747 (41) 1066 (59) 1.00 (0.87–1.16) 1.20 (1.02–1.41) -46–55 764 (45) 937 (55) 0.86 (0.74–1.00) 1.11 (0.94–1.31) - > 55 291 (48) 321 (52) 0.78 (0.64–0.94) 0.80 (0.64–1.00) Professional status - Medical 218 (17) 1073 (83) 4.12 (3.53–4.79) 3.70 (3.09–4.44) - Non-medical 3381 (46) 4044 (54) 1.0 1.0 Job tenure (years) - < 3 469 (36) 831 (64) 1.00 NA -3–10 1070 (40) 1628 (60) 0.86 (0.7–1.0) - > 10 1428 (41) 2026 (59) 0.80 (0.7–0.9) Working unit - Medicine 1015 (37) 1727 (63) 1.00 1.00 - Surgery 617 (38) 993 (62) 0.95 (0.83–1.07) 0.99 (0.86–1.15) - Intensive care unit 227 (30) 549 (71) 1.42 (1.19–1.68) 1.28 (1.06–1.55) - Rehabilitation, long-term care 1273 (51) 1218 (49) 0.56 (0.50–0.62) 0.81 (0.68–0.96) - Emergency 138 (35) 257 (65) 1.09 (0.88–1.36) 0.90 (0.70–1.16) - Gynaecology-Obstetrics 54 (45) 69 (56) 0.75 (0.52–1.08) 0.98 (0.66–1.45) - Psychiatry 42 (44) 54 (56) 0.76 (0.50–1.13) 0.91 (0.58–1.43) - Other 77 (49) 81 (51) 0.62 (0.45–0.85) 0.78 (0.55–1.11) Previous training in hand hygiene (last 3 years) - No 1172 (34) 1597 (32) 1.00 1.00 - Yes 2311 (66) 3442 (68) 1.09 (1.00–1.20) 1.11 (0.98–1.24) Previous training in control of antimicrobial resistance (last 3 years) - No 2283 (69) 3130 (64) 1.00 1.00 - Yes 1001 (31) 1786 (36) 1.30 (1.18–1.43) 1.31 (1.16–1.48) KS Knowledge score, OR Odds ratio, CI Confidence interval, NA Not applicable (numerous missing data) We found poor knowledge of current AMR epidemi- profile perceived poor compliance with hand hygiene as a ology and modest knowledge of best practices in preven- breach in patient safety, with a willingness to comply with tion of cross-transmission. Variations were observed across hand hygiene recommendations. The 26–35-year age class professional categories, highlighting two profiles. Profes- working in UHs was associated with greater knowledge, sionals with the highest knowledge profile were young possibly reflecting improved and fresh education on the medical doctors, working in an ICU, recently trained and topic during medical or nursing studies. On the other with awareness of and readiness to act against AMR. This hand, low knowledge was found among nurse aides from Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 7 of 10 Table 4 Behavioural factors associated with greater knowledge of antimicrobial resistance and infection control measures Population-based Population (n (%)) Univariate analysis Multivariate analysis variables (OR (95% CI)) (adjusted OR (95% CI)) KS < 4 KS ≥ 4 Perceived susceptibility - No agreement 503 (14) 528 (6) 1.00 1.0 - Agreement 3096 (86) 4789 (94) 2.37 (2.05–2.75) 2.33 (1.95–2.78) Perceived knowledge - No agreement 1257 (35) 1910 (37) 1.00 1.0 - Agreement 2342 (65) 3207 (63) 0.90 (0.82–0.98) 1.06 (0.95–1.18) Intention to adhere - No agreement 1232 (34) 1809 (35) 1.00 NA - Agreement 2367 (66) 3308 (65) 0.95 (0.87–1.04) Attitude toward hand hygiene - No agreement 442 (12) 348 (7) 1.00 1.0 - Agreement 3157 (88) 4769 (93) 1.92 (1.66–2.22) 1.98 (1.65–2.37) Perceived behavioural norm - No agreement 1755 (49) 2701 (53) 1.00 1.0 - Agreement 1844 (51) 2415 (47) 0.85 (0.78–0.93) 0.95 (0.86–1.05) Perceived subjective norm - No agreement 2025 (56) 3066 (60) 1.00 1.0 - Agreement 1574 (44) 2051 (40) 0.86 (0.79–0.94) 0.98 (0.89–1.09) Self-efficacy - No agreement 944 (26) 1226 (24) 1.00 1.0 - Agreement 2655 (74) 3891 (76) 1.13 (1.02–1.24) 1.22 (1.09–1.38) Motivation - No agreement 647 (18) 758 (15) 1.0 1.0 - Agreement 2952 (82) 4359 (85) 1.26 (1.12–1.41) 1.42 (1.24–1.62) Adjusted odds ratio: adjusted for type of HCF, gender, age, professional status, working unit and training See Additional file 1: Table S3 for the formulation of the eight questions about perceptions KS Knowledge score, OR Odds ratio, CI Confidence interval, NA Not applicable (numerous missing data) small LTCFs. Nurse aides are key people for infection consequence, educational messages provided by IPC control. They routinely contribute to patient care and teams should be simplified, focused on the reasons for diaper changes, with a high risk of hand contamin- and consequences of poor hand hygiene practices and be ation and subsequent transmission . This strongly tailored to the healthcare professionals involved. suggests that knowledge should primarily be improved Furthermore, less than 50% of HCWs thought that hand in that population. Small HCFs should also be a tar- hygiene was more important after than before a contact get for education as they may suffer of a lack of IPC with patients. These results illustrate a general misconcep- human resources. tion of hand hygiene best practices, even though reported Fifteen years after the introduction of AHR in consumption of AHR in France is fairly high compared to French healthcare settings [17, 19], knowledge of hand other European countries . Healthcare-associated hygiene best practices still appeared poor. AHR was infections are the result of a complex chain, including considered less effective than antiseptic or plain soap the many individuals involved in patient care. The con- in a significant proportion of respondents, as high as sequences of poor hand hygiene compliance are intan- 50% of NMWs, which was very disappointing given gible for front-line staff, not considering the actual the multiple national campaigns promoting AHR and burden of AMR for patients as a consequence of their the use of AHR consumption as a national quality in- individual practices. The perception of AMR as a na- dicator. Two previous studies reported that medical tional problem but not a local or individual one sup- students considered poor hand hygiene compliance as one ports this hypothesis. Accurate feedback of local data of the least important contributors to AMR [11, 20]. In may improve awareness of HCWs . Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 8 of 10 .HCWs still believe they need to wear gloves for con- Action Process Approach (HAPA) led to better compli- tact precautions despite its withdrawal from French rec- ance with hand hygiene, with in turn a decrease in the ommendations in 2010. Several guidelines have recently MDRO infection rate. been issued for the control of MDRO transmission, with Understanding the impact of individual infection control evolving recommendations (e.g. the debated need for behaviours on AMR spread may increase the likelihood of contact precaution for ESBLP-E. coli)[1, 23]. These re- compliance. An adapted approach is needed to heighten an current changes in recommendations may be confusing individual’s understanding. A unique strategy is not suffi- for HCWs, complicating the implementation of good cient in a such context and efforts should be made to im- practices. Sixty-eight percent of HCWs reported having plement personalised and multiple tools. One approach received training on hand hygiene during the last 3 could be supported by evidence-based medicine. A recent years. This proportion, albeit high, may be considered study stated that recommendations appear to be imposed insufficient. Education and training of HCWs are one on medical students and junior physicians without refer- pillar of infection control programmes and efforts must ence to the scientific evidence, which therefore does not be made to implement regular courses and target all encourage high compliance with hand hygiene . Feed- HCW categories . However, formal training should back of local data could increase awareness among HCWs, be included in a larger programme including combined while demonstrating threats in their own setting and the measures, according to the rules of bundling and multi- consequences of their own practices. On the other hand, faceted interventions: reminders at the workplace, audit social norms (perceived behavioural and subjective norms) and feedback, use of AHR consumption as a perform- are independent of awareness, but surveys have demon- ance indicator, leadership, incentive and rewards … . strated that they shape hygiene behaviours [17, 29]. For in- For example, AHR consumption is a publicly released stance, perceived peer handwashing frequency significantly quality indicator for all healthcare facilities in France, impacted the behaviour of professionals. Intervention re- and facilities are urged to use AHR consumption as an garding social norms could be a complementary approach. internal quality indicator; most healthcare facilities are Our survey had some limitations. Firstly, the study was registered to take part in national hand hygiene day, on performed in France and was probably not representative the 5th of May, as well as in the national yearly week of of the healthcare systems of other countries. Indeed, to patient safety. Until now, educational programmes have our knowledge, only one study has been conducted in usually been based on classic presentations with lectures several European countries, but focused on antibiotic pre- given to a passive audience. New technologies such as scribing and AMR among medical students . Secondly, simulation, virtual reality, serious games and e-learning the questionnaire was unique and questions could have applications, playing with the trainee’s emotions, bring been understood differently by individuals according to new possibilities to the field of medical training and their professional status. Hence, use of a 7-point scale per- could lead to valuable improvement in learning out- mitted a large range of responses and more precision . comes . After adjustment for confounding variables, Thirdly, it is likely that the respondents were more moti- a higher KS was significantly associated with four cogni- vated and better informed than non-respondents, thus tive factors: perceived susceptibility, attitude toward increasing the rate of positive responses. However, the hand hygiene, self-efficacy, and motivation. Our survey, high participation rate could offset this bias. Finally, some as previously described , suggests a perceived lack in answers may have been collective rather than individual, patient safety by HCWs when hand hygiene in inad- thereby falsely increasing KS. equately performed. One may consider that the per- ceived susceptibility, i.e. the perceived risk to patient, which was the strongest factor linked to higher know- Conclusions ledge, derived from the higher knowledge by itself. In view of insufficient knowledge among HCWs, training Nevertheless, it is unknown whether the other cognitive should be extended to all HCW categories, and simpli- factors impact higher knowledge, or whether higher fied to address simple control measures. New strategies knowledge obtained from other sources, such as training to enhance awareness should probably incorporate dif- sessions or medical education, translates into more belief ferent professional beliefs and contextual institutional in and perception of the importance of hand hygiene. factors, suggesting new possible areas of intervention. The interactions probably are intricate, suggesting that Non-medical HCWs with a lower educational level and training on hand hygiene and AMR is critical in shaping small HCFs should be prioritised, by adapting IPC tools beliefs in and perceptions of the control of AMR. A new and education methods used in large university hospi- approach based on psychologically tailored hand hygiene tals. Designing new strategies for the effective imple- interventions regarding MDRO has recently been de- mentation of evidence-based infection control practices scribed . Tailored intervention based on the Health is essential and should be a priority at all levels. Vaillant et al. Antimicrobial Resistance and Infection Control (2019) 8:173 Page 9 of 10 Supplementary information Authors’ contributions Supplementary information accompanies this paper at https://doi.org/10. GB and JCL conceived the study and are the principal investigators. MEF, FT, 1186/s13756-019-0625-0. PA, CP, ESW, JR, JRZ contributed to the design of the study. LV coordinated recruitment and acquisition of study data. MEF managed the study data and did the statistical analyses. JCL, LV, GB, MEF contributed to the analysis of Additional file 1: Table S1. Knowledge of antimicrobial resistance and study data. All authors contributed to the interpretation of the data and infection control measures. Table S2. Perceptions regarding antimicrobial approved the final version of the manuscript after critical review. resistance and control measures. Table S3. Questions on perception of antimicrobial resistance and control measures. Funding This study was supported by a public grant from the French Ministry of Health (PREPS 2012–002-0077). Abbreviations Availability of data and materials AHR: Alcohol-based hand rub; AMR: Antimicrobial resistance; Tools (knowledge and perception questionnaires) are included in this ESBLP: Extended-spectrum beta-lactamase-producing; HAPA: Health Action published article and its supplementary information files. The datasets Process Approach; HCF: Healthcare facility; HCW: Healthcare worker; generated and/or analysed during the current study are not publicly ICU: Intensive care unit; IPC: Infection prevention and control; KS: Knowledge available. score; LTCF: Long-term care facilities; MDRO: Multidrug-resistant organisms; MRSA: Methicillin-resistant Staphylococcus aureus; MW: Medical healthcare Ethics approval and consent to participate worker; NMW: Non-medical healthcare worker; NUPH: Non-university public This project (Clinical trial NCT02265471) was approved by the Ethics hospitals; Q1: 25th percentile; Q3: 75th percentile; SD: Standard deviation; Committee of the HUPNVS (CEERB Paris Nord, 16–018). The anonymity of all UH: University hospitals or referral centres for cancer respondents was guaranteed, and only non-identifying characteristics were requested. An information form was administered to each participant. The study was approved by the French Data Protection Authority (CNIL). Acknowledgements We are enormously grateful to the IPC teams, healthcare professionals, and Consent for publication volunteers for their participation. Not applicable. The Percept-R Study Group: Aveline Isabelle (Clinique d’Alençon), Bracco Christelle (Clinique médicale et cardiologique d’Aressy), Lacombe Manuelle Competing interests (La Morlande, Avallon), Colin Yolande (Centre médical L’Arbizon, Bagnères de The authors declare that they have no competing interests. Bigorre), Poulingue Géraldine (Centre Hospitalier de Barentin), Lesourd Fabien (Polyclinique du Plateau, Bezons), Rogues Anne-Marie (CHU de Author details Bordeaux), Magne Béatrice (Hôpital local de Bort-Les-Orgues), Mouzaoui Marc AP-HP, Bichat-Claude Bernard Hospital, Infection Control Unit, 48 rue Henri (Hopital de Boscamnan), Daniel Petrelli (Centre Médical Chant’Ours, Briançon), Huchard, F-75018 Paris, France. Department of Medicine, NIHR, Imperial Picot Franck (CH de Brive), Canivet Anne (Centre François Baclesse, Caen), College London, Health Protection Research Unit in Antimicrobial Resistance Stoeckel Vincent (CH de Chalons en Champagne), Marchal Lydia (Etablissement and Healthcare Associated Infection Imperial College London, South Public Intercommunal 3H Santé, Cirey sur Vezouze), Boris Alexandre Kensington Campus, London SW7 2AZ, UK. AP-HP, Bichat-Claude Bernard (Clinique du Dc Jean Causse, Colombiers), Tiv Michel (Centre Georges- Hospital, Unité de Recherche Clinique Paris Nord Val de Seine and CIC-EC François Leclerc, Dijon), Piriou Gilles (CH de Douarnenez), Lallart 1425, 48 rue Henri Huchard, F-75018 Paris, France. Medecine Sorbonne Dominique-Louis (Centre Sainte Barbe, Fouquières les Lens), Lecoq University, AP-HP, Regional centre for Prevention of Healthcare-associated Marianne (Centre Les Jonquilles, Gainnevielle), Pina Patrick (Hôpital local infections, 8 rue Maria Helena Vieira da Silva, 75014 Paris, France. EA 4360 Hôpital Saint Louis, Jouars Pontchartrain), Barege Patrice (Clinique Sainte- APEMAC, CHRU de Nancy, University of Lorraine, Infectious and Tropical Anne, Langon), Josso Christophe (Hôpital intercommunal de la presqu’ile Diseases Unit, 34 Cours Léopold, 54000 Nancy, France. Sorbonne University, Estadieu, Le Croisic), Herbin Claire (EHPAD Public du Luc en Provence), U1135, Team E13, CR7 INSERM, AP-HP, Pitié-Salpêtrière Hospital, Degallaix Dominique (CH Robert Bisson, Lisieux), Doublier Laetitia (Hôpital Bactériologie-Hygiène, 47-83 Boulevard de l’Hôpital, 75013 Paris, France. Local Lucien Boissin, Longuejumelles), Constantin Nicole (CH de Lourdes), AP-HP, Avicenne Hospital, Infection Control Unit, 125 Rue de Stalingrad, Ludvig-Serge Aho-Glélé (CHU Dijon), Parer Sylvie (CHU de Montpellier), 93000 Bobigny, France. University of Paris, INSERM, IAME, UMR 1137, Paris, Minchella Amandine (ICM Institut Régional du Cancer de Montpellier), France. University of Bourgogne Franche-Comté SPMS, Dijon, France. Romand Karine (Centre Hospitalier Paul Nappez, Morteau), Bentchikou INSERM, UMR 1123, AP-HP, Pitié-Salpêtrière Hospital, Centre de Hicham (Centre de Réadaptation de Mulhouse), Petitfrère Manuel (Clinique Pharmacoépidémiologie (Cephepi), 75013 Paris, France. 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