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Background Few studies have investigated how the effectiveness of hand washing in removing hand contaminants is influenced by the performance and duration of each step involved. We conducted an observational study by recruiting participants from a university campus, with the aim to comprehensively evaluate how performance, duration and demographic factors influence hand washing effectiveness. Methods A total of 744 videos were collected from 664 participants in July-October 2022 and independently evaluated by two infection control experts through labelling videos for correct and incorrect performance of each step. The individual hand washing effectiveness was determined by quantifying the percentage of residual fluorescent gel on the dorsum and palm areas of each participant’s hands. A logistic regression analysis was conducted to identify factors that were significantly associated with better hand washing effectiveness. An exposure- response relationship was constructed to identify optimal durations for each step. Approximately 2300 hand images were processed using advanced normalization algorithms and overlaid to visualize the areas with more fluorescence residuals after hand washing. Results Step 3 (rub between fingers) was the most frequently omitted step and step 4 (rub the dorsum of fingers) was the most frequently incorrectly performed step. After adjustment for covariates, sex, performance of step 4 and step 7 (rub wrists), rubbing hands during rinsing, and rinsing time were significantly associated with hand washing effectiveness. The optimal overall hand washing time was 31 s from step 1 to step 7, and 28 s from step 1 to step 6, with each step ideally lasting 4–5 s, except step 3. The palms of both hands had less fluorescence residuals than the dorsums. The areas where residuals most likely appeared were wrists, followed by finger tips, finger webs and thumbs. Conclusions Performance and duration of some hand washing steps, sex and rinsing time were associated with hand washing effectiveness. The optimal duration might be applied to all seven steps to achieve the best decontamination results. Further studies are needed to refine hand hygiene standards and enhance compliance. Keywords Hand hygiene, Hand washing, Infection prevention and control, Standards *Correspondence: Lin Yang email@example.com Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 2 of 11 Background needed for each step and the factors influencing the Healthcare associated infections (HAI) have been asso- cleaning effectiveness of hand hygiene. ciated with longer hospital stay, increased mortality and In the study, we aimed to comprehensively evaluate the morbidity in patients, and cause high economic burden factors associated with hand wash effectiveness, using globally. The overall prevalence rate of HAI was esti - video recordings and a ultraviolet (UV) hand scanner mated to be 5.7% and 9.0% in Europe and Southeast Asia, to objectively measure residual florescent contaminants respectively [1, 2]. Zimlichman et al. estimated HAIs after hand washing. caused an annual economic cost of $9.8 billion in the United States . There is ample evidence to demonstrate Methods the effectiveness of hand hygiene on reducing HAI and Subject recruitment and data collection spreading of multi-drug resistant organisms (MRDO) . A convenient sampling method was used to recruit par- For example, a hospital-wide hand hygiene campaign was ticipants from the Hong Kong Polytechnic University found to reduce overall HAI prevalence and methicillin- campus using posters during 8 July – 14 October 2022. resistant staphylococcus aureus (MRSA) transmission People with clinical experiences or hands-on trainings rates by 40% and 57%, respectively . Therefore, hand of hand washing were excluded. After signing a consent hygiene is one of the core components of infection pre- form, participants were asked to provide demographic vention and control (IPC) programs in healthcare set- information such as age, sex, staff or students, and tings . departments/programs. As part of IPC auditing programs in healthcare set- Before washing hands, participants were requested to tings, current surveillance programs for hand hygiene put fluorescent lotion (GlitterBug™, Brevis Corporation, compliance in healthcare settings mainly focus on five the United States) on both of their hands and scan their moments for hand hygiene, but few attention is paid hands using the hand scanner (Semmelweis Scanner™, upon the results of individual hand hygiene performance RDI Systems Ltd, Ireland) to ensure that sufficient pow - in clinical practice . The World Health Organization der covered all hand areas including both wrists. Partici- (WHO) guidelines on hand hygiene in health care rec- pants then performed seven steps of hand wash without ommends six-step techniques for effective hand hygiene: onsite training nor receiving instruction from research- (1) rub both hands palm to palm; (2) rub the dorsum of ers. The accuracy of this hand scanner in hand washing each hand with the palm of the other hand, with fingers assessments has been validated by comparing with tradi- interlaced; (3) rub palm to palm, with fingers interlaced; tional testing methods such as bacteria agar culture . (4) rub the dorsums of fingers against the opposite palm, The camera installed above water basins started to record with fingers interlocked; (5) rub one thumb by palm of both hands when research assistants turned on water the other hand, and rub the other thumb; (6) rub the tips faucets, and stopped after participants rinse their hands of your fingers [ 8]. Previous laboratory studies found that with water. After washing hands, participants scanned the six-step hand hygiene procedure should take 20–30 s their both hands using the hand scanner again, to record if using alcohol-based hand rub (ABHR), or 40–60 s if the percentages of hand areas with residual fluorescent washing hands with soap and water, in order to ensure gel of palm and dorsum of left and right hands after hand effective removal of transient microorganisms acquired washing, respectively. A few participants had more than from direct contact with patients, contaminated surfaces, one attempts of hand washing which were separately or the environment . Some health authorities, includ- labelled and analyzed. ing the Center for Health Protection (CHP) in Hong Two IPC experts independently judged the correctness Kong, also recommends one extra step of rubbing wrists of hand washing steps by watching recorded hand wash- so that there are a total of seven steps . Most previous ing videos of all participants. They labeled the videos by studies focused on the total duration of hand hygiene [7, fragments according to seven steps, and corresponding 10]. start and end time points of each fragment were marked Prevous studies have reported a few factors associated to calculate total duration time. The correctness of hand with hand washing effectiveness. For example, rubbing washing performance for each video fragment was fur- hands under running added additional physical friction ther scored with 0 for missing step, 1 for correct step, 2 which improved the decontamination outcome of hands for wrong step, and 3 for no-label due to blocked views. . An institution-based study found that medical stu- We further classified individual hand washing effective - dents had better knowledge and performance of hand ness for each step into four types by combining all video washing compared to the students from other disciplines fragment scores related to this step: 1) completely cor- . A few studies also found age and gender differences rect (all fragments were labeled with 1; 2) partially cor- in knowledge, practive and effectivenss hand hygiene [ 13, rect (some videos were labeled with 1 and the rest were 14]. However, no studies have evaluated the duration 2); 3) completely wrong (all fragments were labeled with Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 3 of 11 2); 4) missing (all fragments were labeled with 0). Total washing steps, rubbing hands when rinsing, duration of duration of each step (at the smallest unit of one second), rinsing hands, and total duration time of all steps. Two rinsing time, and rubbing hands when rinsing were also multivariate logistic regression models were fitted to recorded when labelling videos. the data, respectively. The first was a full model which included all variables that were statistically significant Visualization of hand areas with contaminant residuals (p < 0.05) in univariate logistic regression analyses. The We visualized common areas of left and right hand palm generalized variance inflation factor (GVIF) was calcu - and dorsum, by combining all hand images taken by lated for each candidate variable to evaluate the potential the hand scanner after hand washing. The images were multicollinearity . The second model was a simplified first converted to grayscale by removing unrelated color model by selecting variables with backward selection and information and focusing on intrinsic characteristics of minimal Akaike information criterion (AIC). Odds ratio these images. We randomly selected the images of one (OR) was derived from the logistic regression models to participant as templates, and the rest images were sub- estimate the effect of individual factors. sequently registered to the corresponding template one The exposure-response curve between duration of each by one, using the advanced normalization tools . This step and hand washing performance was subsequently image registration process consisted of two steps: affine constructed by adding a restricted cubic splines function registration and nonlinear registration. Affine registra - to the multivariate logistic regression model that also tion was to achieve a preliminary alignment of the input included sex, department and any other potential inde- images with the template images, by applying transla- pendent factors. tion, rotation, scaling, and shearing transformations. The We conducted a sensitivity analysis by removing all subsequent nonlinear registration employed a deform- outliers as revealed in the box plots of duration of each able registration approach to achieve more precise and step, and repeated all the above statistical analyses. To elaborate registration. Specifically, the symmetric nor - show the robustness of our findings against the cut- malization (SyN) algorithm , which incorporates off values in defining the good and poor hand wash - both forward and backward mappings for bidirectional ing groups as outcome, we also conducted sensitivity registration and alignment, was utilized to capture defor- analyses by changing the cut-off values to the median of mations present in the hand images. The nonlinear regis - maximum and average residual percentages of individ- tration process addressed variations in hand shape, size, ual participants (0.835% and 0.37%), respectively. In this and local deformations, resulting in a highly accurate study, p < 0.05 was considered statistically significant. R alignment of the input images to the template images. software V.4.1.1 (R Foundation for Statistical Computing) All registered images were then normalized to a com- was used for all analyses. mon intensity range of 0 (no fluorescence residual) to 1 The study was approved by the Hong Kong Polytechnic (maximum fluorescence residual among all participants), University Institutional Review Board (Reference Num- and finally overlaid in a color map to visualize the areas ber: HSEARS20220519005). with fluorescence residuals. Results Statistical analysis We collected 744 videos from 664 participants. The age We defined the outcome measurement as classification of these participants ranged from 20 to 22 years (median of individual participants into the good and poor hand 21.0 years). The majority were females (537, 72.9%) and washing groups by the maximum of the percentages of nursing students (658, 92%) (Table 1). The non-nursing hand areas of palm or dorsum of left and right hands participants included students and staff from business, with residual fluorescent gel after hand washing. Specifi - sciences, engineering, social science and supporting cally, we adopted the cut-off of 1%, which approximated departments. 399 videos (53.6%) were defined as good the median values of maximum residual percentage of hand wasing effectiveness (residual percentage ranged individual participants. That is to say, if one participant from 0.03 to 1%), and 345 videos (46.4%) as poor (resid- had > 1% of his/her hand areas of palm or dorsum of left ual percentage ranged from 1.01 to 97.2%). 14% of the and right hands with residual fluorescent gel after hand participants performed all seven steps correctly and met washing, he/she would be classified into the poor hand the minimal duration of 20 s for hand rubbing. None of washing performance group. them completely removed fluorescent contaminants (i.e. We explored potential influencing factors related to zero residual after washing). Most people (85.2%) per- hand washing effectiveness by fitting univariate logistic formed step 1 (rub palm to palm) completely correctly, regression models with only one variable in each model. whereas step 3 (rub between fingers) was the most fre - The variables included demographics, video label of quently (16.8%) ignored step (Fig. 1). There were 39.1% each step, duration of performing correct, wrong hand of the participants who performed step 4 (rub dorsum of Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 4 of 11 Table 1 Comparison of characteristics and variables between the participants with good and poor hand washing effectiveness Variables All Good effectiveness Poor effectiveness Odds Ratio (n = 744) (n = 399) (n = 345) (95%CI) Age, years, median (IQR) 21 (20–22) 21 (20–22) 21 (20–22) 1.00 (0.98–1.03) Sex, female, n (%) 537/737 (72.9) 327/397 (82.4) 210/340 (61.8) 2.89 (2.07–4.07) Nursing students, n (%) 658/715 (92.0) 368/391 (94.1) 290/324 (89.5) 1.88 (1.09–3.29) Step 1, n (%) Missing 6/744 (0.8) 3/399 (0.8) 3/345 (0.9) Reference Completely correct 634/744 (85.2) 339/399 (85.0) 295/345 (85.5) 1.15 (0.21–6.25) Partially correct 22/744 (3.0) 13/399 (3.3) 9/345 (2.6) 1.44 (0.22–9.46) Completely wrong 82/744 (11.0) 44/399 (11.0) 38/345 (11.0) 1.16 (0.20–6.58) Step 2, n (%) Missing 14/744 (1.9) 5/399 (1.3) 9/345 (2.6) Reference Completely correct 434/744 (58.3) 242/399 (60.7) 192/345 (55.7) 2.27 (0.77–7.49) Partially correct 90/744 (12.1) 48/399 (12.0) 42/345 (12.2) 2.06 (0.66–7.14) Completely wrong 206/744 (27.7) 104/399 (26.1) 102/345 (29.6) 1.84 (0.61–6.15) Step 3, n (%) Missing 125/744 (16.8) 60/399 (15.0) 65/345 (18.8) Reference Completely correct 298/744 (40.1) 156/399 (39.1) 142/345 (41.2) 1.19 (0.78–1.81) Partially correct 60/744 (8.1) 34/399 (8.5) 26/345 (7.5) 1.42 (0.76–2.65) Completely wrong 261/744 (35.1) 149/399 (37.3) 112/345 (32.5) 1.44 (0.94–2.21) Step 4, n (%) Missing 95/744 (12.8) 45/399 (11.3) 50/345 (14.5) Reference Completely correct 343/744 (46.1) 192/399 (48.1) 151/345 (43.8) 1.41 (0.90–2.23) Partially correct 15/744 (2.0) 12/399 (3.0) 3/345 (0.9) 4.44 (1.31–20.42) Completely wrong 291/744 (39.1) 150/399 (37.6) 141/345 (40.9) 1.18 (0.74–1.88) Step 5, n (%) Missing 46/744 (6.2) 17/399 (4.3) 29/345 (8.4) Reference Completely correct 474/744 (63.7) 262/399 (65.7) 212/345 (61.4) 2.11 (1.14–4.01) Partially correct 19/744 (2.6) 10/399 (2.5) 9/345 (2.6) 1.90 (0.64–5.70) Completely wrong 205/744 (27.6) 110/399 (27.6) 95/345 (27.5) 1.98 (1.03–3.88) Step 6, n (%) Missing 58/744 (7.8) 25/399 (6.3) 33/345 (9.6) Reference Completely correct 512/744 (68.8) 277/399 (69.4) 235/345 (68.1) 1.56 (0.90–2.71) Partially correct 38/744 (5.1) 27/399 (6.8) 11/345 (3.2) 3.24 (1.38–7.99) Completely wrong 136/744 (18.3) 70/399 (17.5) 66/345 (19.1) 1.40 (0.76–2.62) Step 7, n (%) Missing 31/744 (4.2) 9/399 (2.3) 22/345 (6.4) Reference Completely correct 602/744 (80.9) 328/399 (82.2) 274/345 (79.4) 2.93 (1.37–6.80) Partially correct 24/744 (3.2) 17/399 (4.3) 7/345 (2.0) 5.94 (1.91–20.35) Completely wrong 87/744 (11.7) 45/399 (11.3) 42/345 (12.2) 2.62 (1.11–6.60) Correct duration, seconds, median (IQR) Step 1 3 (2–5) 3 (2–5) 3 (2–5) 0.95 (0.91–0.99) Step 2 4 (0–8) 4 (0–7) 4 (0–8) 0.99 (0.96–1.01) Step 3 0 (0–3) 0 (0–3) 0 (0–4) 0.96 (0.91–1.00) Step 4 0 (0–6) 2 (0–6) 0 (0–6) 1.00 (0.97–1.03) Step 5 4 (0–7) 4 (0–7) 4 (0–7) 1.00 (0.97–1.03) Step 6 4 (0–7) 4 (1–7) 4 (0–7) 0.99 (0.96–1.01) Step 7 5 (3–8) 5 (3–8) 5 (3–8) 0.99 (0.96–1.02) Partially correct/completely wrong duration, seconds, median (IQR) 0 (0–0) 0 (0–0) 0 (0–0) 1.01 (0.90–1.13) Step 1 Step 2 0 (0–3) 0 (0–3) 0 (0–3) 0.98 (0.95–1.01) Step 3 0 (0–2) 0 (0–2) 0 (0–2) 1.01 (0.96–1.06) Step 4 0 (0–3) 0 (0–3) 0 (0–4) 0.98 (0.94–1.02) Step 5 0 (0–1) 0 (0–1) 0 (0–1) 1.00 (0.95–1.05) Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 5 of 11 Table 1 (continued) Variables All Good effectiveness Poor effectiveness Odds Ratio (n = 744) (n = 399) (n = 345) (95%CI) Step 6 0 (0–0) 0 (0–0) 0 (0–0) 1.00 (0.96–1.05) Step 7 0 (0–0) 0 (0–0) 0 (0–0) 1.01 (0.91–1.11) Rubbing when rinsing hands, n (%) 646/744 (86.8) 361/399 (90.5) 285/345 (82.6) 2.00 (1.30–3.11) Rinsing time 17 (13-24.25) 18 (13–25) 16 (12–23) 1.02 (1.01–1.04) One hand washing attempt, n (%) 658/744 (88.4) 379/399 (95.0) 279/345 (80.9) 0.22 (0.13–0.37) Total duration of step 1–7 regardless of correctness 35 (23–51) 34 (23–50) 36 (23–53) 1.00 (0.99–1.00) Total duration of correct steps 1–7 27 (14–41) 26 (14–39) 27 (14–44) 1.00 (0.99–1.00) Total duration of step 1–6 regardless of correctness 29 (19–43) 28 (19–42) 31 (19–45) 0.99 (0.99–1.00) Total duration of correct steps 1–6 21 (11–32) 20 (11–31) 22 (10–35) 0.99 (0.99–1.00) Fig. 1 Percentage of participants in different performance categories by seven steps fingers) in a completely wrong way, and 12.1% performed Performance of step 4 to 7 and correct performance step 2 (dorsum of each hand) partially correctly. duration of step 1 were associated with hand washing In univariate analysis, females, nursing students, effectiveness. No statistically significant differences were rubbing hands when rinsing with water, total rinsing found in total duration of hand washing (either including time, and one hand washing attempt were significantly or excluding incorrect performance duration) between associated with better hand washing results (Table 1). Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 6 of 11 the participants with good or poor hand washing effec - performance of each step on hand wash effectiveness, tiveness (Table 1). after adjustment for sex, age, department, number of The multivariate model included the variables of sex, attempts, rubbing hands when rinsing, rinsing time and nursing students, correctness of step 4, 5, 6 and 7, dura- duration of other steps. The duration that was associated tion of step 1, rubbing hands when rinsing, and only one with the best effect (i.e. highest OR) was two seconds for attempt of hand washing (Table 2). None of these vari- step 3, four seconds for step 1 and step 4, five seconds for ables was excluded after checking multicollinearity in step 6 and step 7, six seconds for step 2, respectively. The this model (Addtional file 1). After backward selection, curve of step 5 reached a plateau beyond five seconds. the effect estimates from the simplified model were sig - The effect estimates associated with total duration of step nificant for female (vs. male OR) = 2.60, 95% CI 1.80 to 1 to step 6 peaked at 28 s, and 31 s if step 7 is included. 3.78), step 4 performance (partially correctly vs. miss- The results of sensitivity analyses by removing outliers ing OR = 6.23, 95% CI 1.55 to 32.99), step 7 performance were consistent with main findings (Additional file 2). (completely correctly vs. missing OR = 2.77, 95% CI 1.12 Approximately 2300 hand images (four images from to 7.23, or partially correctly vs. missing OR = 5.89, 95% each participant) were processed and registered using CI 1.65 to 23.29), rubbing hands when rinsing (OR = 2.00, the advanced normalization algorithms. All the normal- 95% CI 1.25 to 3.23), and rinsing duration (OR = 1.02, ized images were overlaid for the palm and dorsum of 95% CI 1.01 to 1.04). More than one hand washing left/right hands, respectively (Fig. 3). The palms of both attempts (OR = 0.25, 95% CI 0.14 to 0.46) and longer step hands had less fluorescence residuals than the dorsum. 1 duration (OR = 0.95, 95% CI 0.90 to 1.00) were signifi - The areas where residuals most likely appeared were cantly associated with poor hand washing effectiveness wrists, followed by finger tips, finger webs and thumbs. (Table 2). Figure 2 shows the exposure-response curve of total duration of correct hand washing and duration of correct Table 2 Results of multivariate logistic regression models Characteristics Full model Simplified model OR (95%CI) P value OR (95%CI) P value Male Reference Reference Female 2.70 (1.86–3.95) < 0.001 2.60 (1.80–3.78) < 0.001 Others Reference Nursing students 1.32 (0.61–2.82) 0.476 - - Step 4 Missing Reference - Reference - Completely correct 1.27 (0.68–2.35) 0.449 1.41 (0.80–2.47) 0.233 Partially correct 5.65 (1.34–31.03) 0.027 6.23 (1.55–32.99) 0.017 Completely wrong 1.00 (0.54–1.81) 0.990 1.15 (0.66–1.99) 0.623 Step 5 Missing Reference - - - Completely correct 1.57 (0.63–3.93) 0.330 - - Partially correct 1.73 (0.45–6.99) 0.433 - - Completely wrong 1.41 (0.58–3.49) 0.450 - - Step 6 Missing Reference - - - Completely correct 0.75 (0.34–1.66) 0.485 - - Partially correct 1.58 (0.55–4.63) 0.399 - - Completely wrong 0.69 (0.30–1.56) 0.382 - - Step 7 Missing Reference - Reference - Completely correct 2.35 (0.77–7.38) 0.134 2.77 (1.12–7.23) 0.031 Partially correct 4.29 (1.05–18.8) 0.046 5.89 (1.65–23.29) 0.008 Completely wrong 2.23 (0.72–7.08) 0.165 2.42 (0.93–6.66) 0.076 Step 1 correct duration 0.94 (0.90–0.99) 0.030 0.95 (0.90–1.00) 0.039 Rubbing hands when rinsing 2.04 (1.27–3.31) 0.003 2.00 (1.25–3.23) 0.004 Rinsing duration 1.02 (1.01–1.04) 0.002 1.02 (1.01–1.04) 0.002 One hand washing attempt 0.27 (0.14–0.48) < 0.001 0.25 (0.14–0.46) < 0.001 Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 7 of 11 Fig. 2 Exposure-response curve on hand washing effectiveness by total duration and duration of each step. The blue lines are odd ratio point estimates and grey bands highlight the 95% confidence interval Discussion contaminants after washing). To our best knowledge, In this study, we found that female, correct performance this is the first study to conduct an in-depth analysis on of steps 4 and 7, shorter duration of step 1, longer rinsing a large sample of video recordings and hand images, with time, and rubbing hands when rinsing were significantly the aim to explore the influencing factors of hand wash - associated with better hand washing results (less residual ing effectiveness by seven step. Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 8 of 11 Fig. 3 Overlaid color map images of palm and dorsum of left/right hand after normalization. The color ranges from 0 (no fluorescent residual) to 1 (maximum fluorescent residual) The use of fluorescent gel in hand washing was found fluorescent gel assessment technique. However, there to be an effective and novel approach to improve hand were no previous studies that investigated the impact of hygiene education. Vanyolos et al. and Szilágyi et al. used step-by-step hand hygiene durations on effective removal fluorescent gel with UV light to assess quality of hand - of hand contaminants as we did in this study. washing and found that females wash their hands better One of the unresolved issues in hand hygiene studies than males, and persons with nurse background had the is lack of strong evidence to support the current recom- best handwashing practices [19, 20]. Our results showed mendations on duration of hand hygiene . The WHO that wrists and fingertips had the most residuals after recommends that the duration of the entire procedure hand washing. Similar findings were reported by Szilágyi for hand washing lasts 40–60 s (from wet hands with et al. who found that the most common missed area were water to dry hands), but not giving detailed instructions the wrists and fingernails, and by a local study identified on duration of each step . It is of note that such rec- fingertips as the most missed areas [ 20, 21]. The results in ommendations were supported by a few experimental this study were comparable to other studies using similar studies on hand wash effectiveness in reducing (but not Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 9 of 11 eliminating) certain bacteria [23, 24]. We used regres- had attended lectures on hand hygiene but never received sion models to assess the dose-response relationship with any hand-on trainings nor had any clinical experiences adjustment of other covariates, and found that the opti- before joining the study. Hence our findings might not mal duration was 31 s for all seven steps and 28 s for the be generalizable to other populations such as healthcare first six steps combined and ranged from two to six sec - professionals and the general public. Second, we used UV onds for each step. A review by the United States Centers light, in combination with a florescent lotion or gel that for Disease Control and Prevention (USCDC) found that is applied to the hands before washing, to mimic residual the average duration of hand washing episodes ranged bacteria or other contaminants after washing. However, from 6.6 to 24.0 s in previous observational studies , fluorescent lotion contaminants may not reflect the true which was also shorter than the optimal duration found effectiveness in clinical practices and more studies from in our study. It is of note that 15–20 s of minimal scrub- other populations are needed to confirm our research bing time are recommended by most hand hygiene guide- findings. In future, we may consider using bacteria cul - lines for ABHR, including the USCDC , the Society ture as endpoints to confirm our findings. Neverthe - for Healthcare Epidemiology (SHEA) , the European less, bacteria culture requires extra costs and manpower, Center for Disease Prevention and Control (ECDC) , therefore fluorescent lotion and hand scanners have and the CHP in Hong Kong . However, few of these become more commonly adopted in healthcare settings guidelines provided strong evidence to support these for routine monitoring of hand hygiene practices. recommendation. Future studies are needed to investi- gate the optimal duration of hand washing and ABHR to Conclusions achieve the highest effectiveness in removing hand con - Our study is among the first to explore the optimal dura - taminants in real clinical settings. tion of each step to maximize hand washing effectiveness. In our study, only 14.4% of participants performed Performance and duration of some hand washing steps, seven steps all correctly. Although the majority have sex and rinsing time were associated with hand washing received prior trainings in lectures or tutorials, none effectiveness. Further studies are needed to refine hand have previously taken individual hands-on trainings hygiene standards and enhance compliance. for hand washing. This reflects trainings via lectures Abbreviations or group tutorials may not be sufficient for students to 95% CI 95% confidence interval comprehend hand washing techniques. We also found ABHR alcohol-based hand rub AIC Akaike information criterion that attempting more than once was statistically signifi - ECDC European Center for Disease Prevention and Control cantly associated with poor hand washing effectiveness. CHP Center for Health Protection This reveals it is difficult to master hand washing steps GVIF generalized variance inflation factor HAI healthcare associated infections in a short time. More targeted training should be imple- IPC infection prevention and control mented to achieve effective hand washing [ 29]. MRDO multi-drug resistant organisms Few hand hygiene guidelines have taken into consid- MRSA methicillin-resistant staphylococcus aureus OR odds ration eration of wrist areas. Although wrists are less likely to SHEA Society for Healthcare Epidemiology directly contact with surfaces, patients, and medical SyN symmetric normalization equipment, as compared to palm, dorsum of hands and USCDC Centers for Disease Control and Prevention, United States UV ultraviolet fingers, the risk of contamination and spreading bacte - WHO World Health Organization ria by wrists of healthcare workers cannot be completely ignored. A meta-analysis reported the weighted pooled compli- Supplementary Information The online version contains supplementary material available at https://doi. ance rate for nurses was 52% and for doctors was 45% org/10.1186/s13756-023-01293-1. , which were lower than 60%, the optimal threshold of hand hygiene compliance rate for healthcare workers Additional file 1: Table A1 . Generalized variance inflation factors for fac - tors associated with hand washing effectiveness. associated with the lowest hospital-acquired infections incidence rate . Further studies may provide more Additional file 2: Fig. A1: Exposure-response curve on hand washing ef- fectiveness by total duration and duration of each step when outliers were information as to whether the standards of hand hygiene removed. The blue lines are odd ratio point estimates and grey bands should be fine-tuned to improve hand hygiene compli - highlight the 95% confidence interval. ance. For example, give a clearer requirement for rinsing time and duration of each step. As time pressure could be Acknowledgements a major barrier to compliance, this could have a positive We thank Kit Ying So, Keith Fung, Carol Man, May Yu and Wendy Wong for their influence on the frequency of hand hygiene [ 32]. assistance in data collection. Our study has several potential caveats. First, most par- ticipants were nursing students from one university, who Shi et al. Antimicrobial Resistance & Infection Control (2023) 12:85 Page 10 of 11 Authors’ contributions integrated-health-services/infection-prevention-control/core-components This paper was conceptualized by LY and CS. Data collection was performed [Accessed 30 May 2023]. by CS, MOD, HT, YM, YX, JC and TL. Data was analyzed by CS, HT, JZ, LC and 7. World Health Organization ( WHO). WHO guidelines on hand hygiene in JQ. The manuscript was drafted by LY and edited by CS and DP. 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Antimicrobial Resistance and Infection Control – Springer Journals
Published: Aug 30, 2023
Keywords: Hand hygiene; Hand washing; Infection prevention and control; Standards
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