Nevo, Igal MD; Fitzpatrick, Maureen MSN, ARNP; Thomas, Ruth-Everett RN, MSN; Gluck, Paul A. MD; Lenchus, Joshua D. DO, RPh; Arheart, Kristopher L. EdD; Birnbach, David J. MD, MPH
In 2009, the World Health Organization (WHO) called on all nations to improve and ensure sustainable hand hygiene compliance (HHC) among healthcare workers (HCW).1 Poor HHC is the single most important risk factor of healthcare-associated infection (HAI) and affects patients worldwide.2–5 Omissions are probably the single most common human error.6 Failure of HCW to maintain hand hygiene (HH) is one such error of omission.
Many factors are involved in HHC. Despite current Centers for Disease Control and Prevention (CDC) and WHO guidelines, HHC remains surprisingly low.1,4,5,7 Various interventions to increase HHC have had only limited success. These interventions have included educational programs,8–12 use of surveillance systems,13 electronic monitoring,14 audible alerts,15 and room design/sink placement.16 Results of several studies show that while some interventions significantly improved HHC, others did not; these further indicate that poor HHC is a complex problem.17 These interventions and other HH programs were piloted or implemented in situ in clinical settings, and their impact on HHC was tested in observational studies. The nature of activities in these real-life settings makes it difficult to isolate the effects of factors, such as culture, hierarchical structure, workload, work flow, architecture, and behavioral aspects.
Recently, it has been suggested that programs based on behavior modification theories may contribute to improving HHC.18–23 One such theory is the Health Belief Model, comprising several behavior constructs focusing on the individual's perception of societal influence, one's ability to overcome behavior barriers, and one's reaction to cues.24 According to health behavior models, compliance with external cues will depend on one's belief that the potential hazard actually carries a significant personal impact.25 Two other constructs influence the reaction to a cue: the false consensus effect (ie, others do the same) and the third-person effect (ie, underestimating self-susceptibility to influences). Therefore, a person will tend to overlook the effect of external cues that act on the prospective memory.
Prospective memory manages the cognitive processes involved in remembering or forgetting to perform actions intended to be performed at a later time.26 An effective external cue leads to the desired target activity if it supports the prospective memory by combining both the trigger for and the content of the desired activity.27,28 McDaniel et al.29 distinguished between focal cues (which overlap with information relevant to ongoing task) and nonfocal cues (which are present in the environment but not part of the information being considered by the person). Failure of prospective memory is relevant to patient safety.30 Reason6 identifies several factors, which may contribute to omissions that involve prospective memory.
Reason identifies several cognitive factors, which may contribute to omissions of prospective tasks. Among these factors, and of particular relevance to HHC, are information overload on the short-term memory, procedural steps that are functionally isolated, steps of secondary importance, and repeated or recursive steps.6 These psychologic properties may provide an explanation for poor HHC. HH may be prone to omission because of information overload; lack of perception of HH as an integral and important task in the patient-provider dyad; and perceiving HH as a repetitive task (and thus a tedious task). As a result, HHC before an encounter, and more often after, is frequently ignored.
To reduce prospective memory failure, researchers advocate using external cues that will also support behavioral changes.25,31 Effective cues should address the prospective memory target events and the intended activity.28 Reason6 proposed universal and secondary categories of attributes that qualify good cues. Universal reminders should apply to all cues regardless of their form, whereas the secondary attributes are applicable only in some cases. Good cues should catch the actor's attention at the critical time (conspicuous) and be positioned in proximity to the location of the necessary actions (contiguous). Referring to visual display, Proctor and van Zandt32 suggested that the two most important factors of visual cues are conspicuity and visibility. Conspicuity refers to placing the cue in a visible place, eg, Line-of-Sight. Visibility refers to the ability to see the cue under all expected viewing conditions. Multimodal cues, such as warning signs, are more effective than unimodal cues.33 Their effectiveness hinges on design characteristics.34 A warning sign is an example of a multimodal cue. Their efficacy hinges on several dimensions: the level of the hazard implied by the signal words, the extent to which they implied risk, and the extent to which they match the referent.25,33
The effect of external cues on HHC has not been previously studied. We hypothesized that cues at the point of care are important factors that may improve HHC. This study assessed the efficacy of various cues to improve HHC in a simulated patient environment. Two categories of focal cues were tested: unimodal and multimodal cues. We hypothesized that the latter would prove more efficacious than unimodal cues.
We assessed the efficacy of various cues in simulated settings to avoid the difficulties frequently encountered with in situ observations of HHC.13–15 Researchers from the UM-JMH Center for Patient Safety (CPS) set up the study in two hospital rooms of a fully operational medical-surgical unit at the hospital. The selected floor was running at typical capacity; so, there were HCW and patients in the unit, bolstering the reality of the simulated setting. Actors, following a specific script, were used to simulate patients.
One hundred fifty physicians and nurses from a tertiary care teaching hospital volunteered to participate in this simulation-based, quasiexperimental controlled study that was approved by the local institutional review board. The study participants were recruited from the healthcare personnel who work on the same or identical medical-surgical units of the hospital. To avoid any potential coercion, the hospital's administrators were not involved in the study, except to select the units and the two specific rooms to be used.
The study was conducted in private patient rooms. There were no modifications to the patient rooms, other than the cues for HH. To avoid bias with regard to HH, participants were informed that the study focused on the effect of room design on work flow and were asked to perform as they would in a real clinical situation. The two patient rooms were closed for the day of the study, but actors and props were used so that they appeared to be active patient rooms.
One week after the completion of the study, participants were anonymously surveyed about HH. After the survey, they were debriefed about this study and the purpose of the survey.
The clinical scenarios were designed such that each participant had to perform an abbreviated physical examination on a standardized patient (SP). Participants were expected to maintain hand hygiene before and after the examination.
Regardless of the cue, each participant was presented with one scenario only. The specific scenarios were plausible clinical situations that required patient contact and were within the scope of practice of each respective participant. Physician participants (n = 75) were asked to evaluate a postoperative patient who was complaining of palpitations. Nurse participants (n = 75) were asked to perform an initial admission assessment of a patient scheduled for surgery.
To establish baseline HHC (Baseline), the control group examined the SP in the hospital room whose setting was not altered; the room included a sink and a soap dispenser across from the patient bed. The standard alcohol-based hand sanitizer dispenser remained wall mounted next to the door, which is its usual location in all patient rooms in the hospital. In this location, the dispenser is not in the direct line of sight on entering the room. An 8 × 17-in poster affixed above the dispenser in every hospital room (including the test room) states, “Clean hands here” (Fig. 1). This setting was used to evaluate baseline (Baseline) HHC.
The door to the patient room remained closed during the examination. After 5 minutes, the participants were informed by a member of the CPS research team (standing outside the room) that the examination period was complete. While the examination was conducted, other participants awaiting their turn were kept at a distance from the examination room so that there was no communication between participants.
Different factors influence HHC. The study focused on cues that either attract attention to the dispenser or to the potential consequences of noncompliance. Four different cues that may improve HHC were tested and later compared with baseline:
1. Dispenser in baseline location and enhanced with flashing lights (Baseline & Flicker): The standard dispenser and poster remained wall mounted in the usual location. However, the dispenser was enhanced with eight bright green light emitting diodes (LEDs) that flickered brightly at about 60 flashes per minute. The LED lights were arranged in an arrow shape pointing to the dispensing orifice (Fig. 2).
2. Dispenser in line of sight (Line-of-Sight): The standard dispenser and the poster were repositioned. In the new location, the front of the dispenser and the poster were in the line of sight on entering the room (Fig. 3).
3. Dispenser in line of sight and enhanced with flashing lights (Line-of-Sight & Flicker): The dispenser and the poster were mounted in line of sight as above, and the dispenser was enhanced with bright flashing LED lights arranged in an arrow shape (Fig. 4).
Placing the dispenser in line of sight (Line-of-Sight and Line-of-Sight & Flicker cues) improved conspicuity; and the addition of flickering LEDs (Baseline & Flicker and Line-of-Sight & Flicker) improved the visibility factor.
4. Warning Sign (Warning Sign): The patient room was identical to the baseline setting. In addition to the instructions given to all groups before entering the room, each participant in this cohort was asked to read a new warning sign affixed to the door to the patient's room before the study began. The 8.5 × 14.5-in sign was typed in red and black letters (font size 76) and stated, “Warning! This Room is Under Electronic Surveillance for Hand Hygiene Compliance. Failure to perform HH within 10 seconds of entry will trigger an alarm. The violation will be reported!” (Fig. 5). (No surveillance system, alarm, or any other electronic device was actually installed in the room.) Inside, the room remained unchanged; the dispenser and the poster above it remained in the usual location.
The requirement to read the Warning Sign outside the room relies on two important concepts.32 First, it would be unrealistic to have a new surveillance and/or alarm system installed in a room, without informing the staff ahead of time. The second reason is to avoid potential confounding factors. If a participant entered the room without being shown the sign, it would have been impossible to conclude whether lack of HHC was related to failure to read the sign or disbelief that HHC was being monitored. In addition, the entrance to the patient room is in a small alcove with dim lighting, which might have reduced the visibility of the Warning Sign.
One hundred fifty HCW (75 physicians and 75 nurses) participated in this study. They were randomly assigned into one of the five groups, with a total of 30 participants in each group—15 physicians and 15 nurses. Each simulation was limited to 5 minutes and was terminated by a study coordinator who was outside the patient room. The study had to be conducted in a limited time frame to minimize the effect on the hospital's workflow and the potential of interaction between participants.
The SP, who was a member of CPS, tracked whether each participant maintained HH before and after the examination. Data were recorded anonymously after the participant left the room and before the next participant entered the patient room. A participant was considered to comply with HH requirement whether he/she used the wall mounted alcohol-based hand rub dispenser or the soap and water at the sink. CPS is located off the hospital's premises, and its members who participated in this study were not part of the hospital's staff and not known by the participants.
A generalized linear model was used to perform a repeated measures logistic regression on the data. The between-subjects factor was the cue, and the within-subject factor was pre- or post-examination HH. Planned contrasts were used to compare pre- and postexamination performance for each cue and the performance on each cue within examination time. The 0.05 probability level was used to determine statistical significance. SAS version 9.2 (SAS Institute, Inc., Cary, NC) was used for all analyses.
One hundred fifty HCW (75 physicians and 75 nurses) participated in the study. Overall baseline HHC (Baseline) was 36.7% pre-examination and 33.3% postexamination (Table 1). All cues increased the pre-examination HHC (Baseline & Flicker = 53.3%, Line-of-Sight = 60%, Line-of-Sight & Flicker = 66.7%, and Warning Sign = 93.3%) (Table 1). Baseline & Flicker and Warning Sign also improved postexamination HHC to 50% and 93.3%, respectively (Table 1). Pre-examination HHC was significantly better than postexamination when using the Line-of-Sight (P < 0.01) and Line-of-Sight & Flicker (P < 0.01) (Table 1). Comparing each cue with Baseline, the Line-of-Sight & Flicker cue significantly improved pre-examination HHC (P = 0.02), and the Warning Sign significantly improved both pre- (P < 0.001) and postexamination HHC (P < 0.001) (Table 1). Between-cues analysis, the Warning Sign was significantly more efficacious in improving HHC both before (P < 0.02) and after examination (P < 0.001) (Table 1).
This study demonstrated that cues may improve HHC. All four cues improved HHC rate but differed in their degree of efficacy. Three cues, Line-of-Sight, Baseline & Flicker, and Line-of-Sight & Flicker, were unimodal (visual) cues35; the Warning-Sign was a multimodal cue, which incorporated the visual modality and a potential sanction.27,36 Therefore, the two groups will be discussed separately.
The low baseline HHC rates are consistent with previously published studies, which found that HHC rates seldom exceed 50%.2–5,7–12 When testing the Line-of-Sight and Line-of-Sight & Flicker cues (which are not visible when exiting the room), postexamination HHC sharply dropped to Baseline rates, further suggesting that baseline HHC rates were not a coincidental result.
This study suggests that positioning the dispenser in direct line of sight (Line-of-Sight and Line-of-Sight & Flicker cues) may improve HHC. The improvement over baseline, although statistically significant only for the Line-of-Sight & Flicker cue, confirms findings reported in other studies. In a previous study among physicians, HHC was significantly higher when the dispenser was in line of sight as compared with off-line of sight (P = 0.001).37 The difference in level of significance between the two studies may possibly be attributed to the placement of the alcohol-based hand rub dispenser. In this study, the dispenser was across from the entrance but away from the patient; in the previous study, the dispenser was adjacent to the patient bed. These findings are concordant with Reason's suggested attributes of good reminders—conspicuous and contiguous.6
All three visual cues, Line-of-Sight, Baseline & Flicker, and Line-of-Sight & Flicker, achieved smaller increases of HHC in comparison with the Warning Sign. Placing the dispenser in line of sight on entering the room (Line-of-Sight and Line-of-Sight & Flicker cues) increased pre-examination HHC compared with baseline. However, this improvement was short-lived as evidenced by the postexamination HHC dropping to baseline compliance rates. Regardless of the cue, these low HHC rates might have been caused by the visual unavailability of the cues related to the room's architecture. When placed in line of sight, the dispenser was more visible on entering the room but partially hidden and therefore relatively ineffective when leaving the room. The improvement of HHC over baseline when using the flickering cues (Baseline & Flicker and Line-of-Sight & Flicker) may be due to the green LEDs, which improve visibility and conspicuity (photopic sensitivity). The significant improvement of pre-examination HHC achieved with the Line-of-Sight & Flicker cue may be attributed to a combined effect of improved conspicuity (flickering) and visibility (location). Individually, line of sight and flickering LEDs did not achieve significant HHC improvement. The relative inefficacy of the flickering LEDs alone may possibly be attributed to the psychophysical characteristics: low flashing frequency (60 flashes per minute), the LEDs' color, the LEDs that comprised the flashing arrow did not flicker in unison, and insufficient light intensity. Another factor may be a lack of contrast compared with the background color of the dispenser and the wall. Some researchers recommend higher flashing frequencies of red or blue lights (to leverage on scotopic vision).38,39 Insufficient attention to ergonomic issues may be a contributing factor to the low HHC baseline rate, despite the standard poster above the dispenser in all the hospital rooms. As has been previously suggested, this poster is designed using light colors and low contrast, which may affect its efficacy, especially after prolonged exposure.40
Artificially terminating the simulation after 5 minutes may have also contributed to low postexamination HHC. However, two facts contradict this. Postexamination HHC was significantly lower only when the cues were in line of sight (Line-of-Sight and Line-of-Sight & Flicker), which were less visible when exiting the room. With the other cues, postexamination HHC was similar to the baseline rate (Baseline & Flicker) and significantly higher with the Warning Sign cue. Therefore, we believe that the characteristics and the location of a cue, rather than time constraints imposed by the study, contributed to the efficacy of a cue.
This study demonstrated the efficacy of the Warning Sign to trigger HHC. Only one exposure before entering the patient room was sufficient to produce compliance after 5 minutes, even when participants were rushed out. The single trigger (initial exposure to the Warning Sign) was sufficient to obtain a sustained effect on the prospective memory for 5 minutes without additional external reminders (for rehearsal).28,29 The effect of the Warning Sign may be attributed to several factors. The design and the format of the sign emphasized important elements of the message using large fonts and colors.32,34 The sign serves as a visual cue that explicitly provided instruction and reminded the participant to maintain HH; thus, it targets the event and the activity.28,33 The content of the sign indicated the presence of a surveillance system enhanced with an alarm and reporting for noncompliance. As such, the Warning Sign addressed three behavioral constructs: cue to action (external trigger); perceived susceptibility (how likely will noncompliance lead to sanctions); and perceived severity (one's belief regarding how serious the sanctions may be).24 The explicit warning also indicated the potential personal hazard for the participant. An additional factor may have contributed to the high HHC rate produced by the Warning Sign. Some professionals may fail to read warnings, possibly because they are engaged in an “automatic” behavior of goal-oriented seeking (an automatic mode of activity during which one may ignore or become “blinded” to other environmental cues). In their own mind, they are focused on the “goal” to evaluate the SP. The request to read the Warning Sign before entering the room may have interrupted the “automatic” work habit, leading the participants to a different mode of more involved behavior, which resulted in maintaining HHC.40 Elucidating what aspects of the cue contributed to the observed response was beyond the scope of this study.
Despite the content of the Warning Sign, HHC did not reach 100% compliance. One physician and one nurse did not maintain HH before and after examination, either because of failure to read or to understand the threatening message of the sign. These outliers may also indicate that any future solution involving warning signs or surveillance systems may encounter recalcitrant HCW. Finally, we cannot exclude the possibility that the high HHC rate may be due to a confounding factor (ie, reading the sign before entering the room). Although the effect of confounding factors cannot be totally excluded, the high HHC rate both before and after examination makes such an effect unlikely.
The effect of sample size on obtaining nonsignificant changes with all the cues cannot be ignored. For example, to observe a 20% change from baseline would have required more than 72 participants in the Baseline & Flicker cue group. Therefore, the entire study would have required more than 350 participants. However, because we want to achieve 100% HHC, a 20% change would not be clinically significant and would be unacceptable in current clinical practice. A selection bias related to the Warning Sign cannot be excluded. To maintain complete anonymity, we did not collect demographic data and therefore could not compare group composition. However, the randomized selection of participants makes such bias unlikely.
This study demonstrated that certain visual cues may be important factors in improving HHC, which is the most critical behavior in reducing HAI. Also, the habituation effect may diminish the cognitive visibility of a visual cue (analogous to “banner blindness,”41), which may subsequently reduce the long-term behavioral effect on HHC.40,42 The effective cues should be more than a simple visual and/or audible cue; they should also target additional behavioral constructs and be designed according to evidence-based human factor engineering guidelines. It should be emphasized that use of cues in the context of behavior modification models may be in line with some behavior modification theories (eg, Health Belief Model). Larger-scale studies should be conducted to identify behavioral variations in HHC between professions and for finding appropriate solutions to this problem.
This study also demonstrates the use and the advantage of using a simulated environment to evaluate human factors that relate to a specific aspect of patient safety.43 Conducting the simulation in a patient room provided a realistic environment, allowing us to assess the efficacy of each behavioral cue separately. Furthermore, the high HHC rates in the Warning Sign group indicate that participants were able to suppress their disbelief and considered the situation realistic. In addition, simulation made it possible to test such diverse cues and identify their advantages and weaknesses at early stage. Alternatively, testing each cue or other behavioral solutions in situ in a hospital room with a real patient would be effort intensive and would require participation of observers, which may introduce a bias due to Hawthorne effect.
To significantly improve and sustain HHC, we must either have effective reminders at the point of care or the individual healthcare providers must internalize HH and make it a habit. This study evaluated four reminders at the point of care: (1) moving the dispenser to the line of sight on entering the room, (2) placing flashing lights on the dispenser, (3) moving the dispenser with flashing lights to the line of sight, and (4) a warning sign informing the provider that he/she is under surveillance for HHC and that noncompliance will trigger an alarm and be reported. Thus, external cues, especially those that address additional behavioral constructs, may effectively improve HHC. The most significant immediate improvement in HHC was achieved with the sign, which informed participants of potential sanctions for noncompliance. Further studies are needed to assess whether the improved HHC is sustainable. We anticipate installing such a surveillance system in the near future. Further studies will be needed to assess the sustainability of this improvement.
The authors thank Lisa Rosen, MA, and Thomas Church, BFA, for their contribution in conducting the study and preparing the manuscript.
1. Kilpatrick C. Save lives: clean your hands. A global call for action at the point of care. Am J Inf Control
2. Boyce JM, Pittet D; Health care Infection Control Practices Advisory Committee; HICPAC/SHEA/APIC/IDSA Hand Hygiene Task Force. Guideline for hand hygiene in health-care settings: recommendations of the Health care Infection Control Practices Advisory Committee and the HICPAC/SHEA/APIC/IDSA Hand Hygiene Task Force. Society for Health care Epidemiology of America/Association for Professionals in Infection Control/Infectious Diseases Society of America. MMWR Recomm Rep
3. Gerberding JL. Hospital-onset infections: a patient safety issue. Ann Intern Med
4. Gould D, Chudleigh JH, Moralejo D, Drey N. Interventions to improve hand hygiene compliance in patient care. Cochrane Database Syst Rev
6. Reason J. Combating omission errors through task analysis and good reminders. Qual Saf Health Care
7. Larson EL, Quiros D, Lin SX. Dissemination of the CDC's hand hygiene guideline and impact on infection rates. Am J Infect Control
8. Pessoa-Silva CL, Hugonnet S, Pfister R, et al. Reduction of health care-associated infection risk in neonates by successful hand hygiene promotion. Pediatrics
9. Ebnöther C, Tanner B, Schmid F, La Rocca V, Heinzer I, Bregenzer T. Impact of an infection control program on the prevalence of nosocomial infections at a tertiary care center in Switzerland. Infect Control Hosp Epidemiol
10. Cantrell D, Shamriz O, Cohen MJ, Stern Z, Block C, Brezis M. Hand hygiene compliance by physicians: marked heterogeneity due to local culture? Am J Infect Control
11. Herud T, Nilsen RM, Svendheim K, Harthug S. Association between use of hand hygiene products and rates of health care-associated infections in a large university hospital in Norway. Am J Infect Control
12. Saint S, Bartoloni A, Virgili G, et al. Marked variability in adherence to hand hygiene: a 5-unit observational study in Tuscany. Am J Infect Control
13. Benton C. Hand hygiene—meeting the JCAHO safety goal: can compliance with CDC hand hygiene guidelines be improved by a surveillance and educational program? Plast Surg Nurs
14. Swoboda SM, Earsing K, Strauss K, Lane S, Lipsett PA. Isolation status and voice prompts improve hand hygiene. Am J Infect Control
15. Venkatesh AK, Lankford MG, Rooney DM, Blachford T, Watts CM, Noskin GA. Use of electronic alerts to enhance hand hygiene compliance and decrease transmission of vancomycin-resistant Enterococcus in a hematology unit. Am J Infect Control
16. Vernon MO, Trick WE, Welbel SF, Peterson BJ, Weinstein RA. Adherence with hand hygiene: does number of sings matter. Infect Control Hosp Epidemiol
17. Backman C, Zoutman DE, Marck PB. An integrative review of the current evidence on the relationship between hand hygiene interventions and the incidence of health care-associated infections. Am J Infect Control
18. O'Boyle C, Henley S, Larson E. Understanding adherence to hand hygiene recommendations: the theory of planned behavior. Am J Infect Control
19. Pittet D, Simon A, Hugonnet S, Pessoa-Silva CL, Sauvan V, Perneger TV. Hand hygiene among physicians: performance, beliefs, and perceptions. Ann Intern Med
20. Whitby M, McLaws M, Ross R. Why healthcare workers do not wash their hands: a behavioral explanation. Infect Control Hosp Epidemiol
21. Cole M. Using motivational paradigm to improve hand washing compliance. Nurse Educ Pract
22. Whitbey M, Pessoa-Silva CL, McLaws ML, et al. Behavioural considerations for hand hygiene practices: the basic building blocks. J Hosp Inf
23. Sax H, Allegranzi B, Uckay I, Larson E, Boyce J, Pittet D. My five moments for hand hygiene: a user-centered design approach to understand, train, monitor and report hand hygiene. J Hosp Infect
24. Champion VL, Skinner CS. The health belief model. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior and Health Education—Theory, Research and Practice
. 4th ed. San Fransisco, CA: Jossey-Bass (J. Wiley & Sons); 2008.
25. Adams A, Bochner S, Lenka B. The effectiveness of warning signs in hazardous work places: cognitive and social determinants. Appl Ergon
26. Loukopoulos LD, Dismukes RK, Barshi I. The Multitasking Myth—Handling Complexity in Real-World Operations.
Burlington, VT: Ashgate Publishing Co.; 2009.
27. Vortac OU, Edwards MB, Manning CA. Functions of external cues in prospective memory. Memory
28. Guynn MJ, McDaniel MA, Einstein GO. Prospective memory: when reminders fail. Mem Cognit
29. McDaniel MA, Einstein GO, Rendell PC. The puzzle of inconsistent age-related declines in prospective memory—a multiprocess explanation. In: Kliegel M, McDaniel MA, Einstein GO, eds. Prospective Memory
. New York: Psychology Press, Taylor & Francis Group.
30. Dieckmann P, Redersen S, Wehener T, Rall M. Prospective memory failures as an unexplored threat to patient safety: results from a pilot study using patient simulators to investigate the missed execution of intentions. Ergonomics
31. Monaghan S, Blaszczynsky A. Elecronic gaming machine warning messages: information versus self-evaluation. J Psychol
32. Proctor RW, van Zandt T: Human Factors in Simple and Complex Systems
. 2nd ed. Boca Raton, FL: CRC Press, Taylor & Francis Groups; 2008.
33. Hellier E, Aldrich K, Wright DB, Daunt D, Edworthy J. A multidimensional analysis of warning signal words. J Risk Res
34. Hellier E, Edworthy J, Derbyshire N, Costello A. Considering the impact of medicine label design characteristics on patient safety. Ergonomics
35. Spence C, Ho C. Multisensory warning signals for even perception and safe driving. Theor Issues Ergon Sci
36. Baker K, Rochester L, Nieuwboer A. The immediate effect of attentional, auditory, and a combined cue strategy on gait during single and dual tasks in Parkinson's Disease. Arch Phys Med Rehabil
37. Birnbach DJ, Nevo I, Scheinman S, Fitzpatrick M, Shekhter I, Lombard JL. Patient safety begins with proper planning: a quantitative method to improve hospital design. Qual Saf Health Care
38. Stanton N. Key topics in alarm design. In: Stanton N. ed. Human Factors in Alarm Design.
London, Bristol: Taylor & Francis; 1994.
39. Chan A, Ng A. Perception of implied hazard for visual and auditory alerting signals. Saf Sci
40. Clarck DR, Lehto MR. Information design: warning signs and labels. In: Karwowski W, ed. International Encyclopedia of Ergonomics and Human Factor Engineering
. 2nd ed. London, New York: Taylor & Francis; 2001.
41. Benway, JP. Banner blindness: the irony of attention grabbing on the World Wide Web. Proceedings of the Human Factors and Ergonomics Society 42nd Annual Meeting 1998;42:463–467.
42. Kim, S, Wogalter, MS. Habituation, dishabituation, and recovery effects in visual warnings. Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting 2009;53:1612–1616.
43. Gaba DM. The future vision of simulation in healthcare. Simul Healthc
© 2010 Lippincott Williams & Wilkins, Inc.