Effective communication between a clinical provider and a patient can have a positive impact on patient outcomes.1,2 Although interviewing skills can be taught, some clinical providers require training to improve their ability to convey empathy while gathering relevant medical information.2,3 Therefore, many health professions schools rely on standardized patients to improve their clinical providers’ skills for conducting clinical interviews in an empathetic and patient-centered format.
Standardized patients are people who present medical cases in a standardized way for the purpose of training and assessing physicians, medical students, nurses, and other clinical providers.4,5 In a recent report by the American Association of Medical College, 94% of health professions schools and 65% of teaching hospitals surveyed use standardized patients.6 Today, standardized patients are incorporated into most health professions schools for teaching and assessment in formal examinations such as the Medical Council of Canada Qualifying Examination Part II,7 the Objective Structured Clinical Examination, and in the National Board of Medical Examiners United States Medical Licensing Examination Step 2 Clinical Skills for licensure.8
Standardized patients perform a unique and demanding job. They can perform as many as 3 roles during an encounter with a learner: these include portraying a patient, assessing the learner, and providing feedback about the learner’s performance. In portraying a patient, they must learn about their character’s personal history, the setting of the scenario, and their character’s ailment and convey the information in a convincing manner. In addition to memorizing character details and portraying the patient, at times, standardized patients must memorize checklist items and rate clinical provider performances based on these items. Standardized patients also have to be aware of their subjective impressions of how they felt they were treated by the learner. The scenarios they portray are not fully scripted9; rather, they are trained from a set of case details and core concepts that may or may not be addressed depending on how the learner conducts the interview. They are also trained to portray the case to meet the case learning objectives. Many standardized patients who participated in the study indicated that one of the most challenging requirements in role is improvising a plausible response when the learner asks an unanticipated question, which is outside the training protocols.
Although standardized patients provide the primary method for teaching and assessing interpersonal communication skills in the medical domain, there is little research concerning the cognitive challenges faced by standardized patients. Knowledge of basic psychological constructs such as attention and working memory may provide important insights into understanding how standardized patients manage this challenging task and then integrate this information into the training process and protocols.
Attention, Working Memory, and Mental Workload
Attention refers to the allocation of mental resources to different sources of information.10 According to multiple resource theory, there are different pools of attentional resources dedicated to different sources of information.11,12 The multiple resource theory12 is a unique theory of attention because it can be used to predict how performance is affected when performing different types of concurrent tasks. Specifically, the multiple resource theory predicts that 2 concurrent tasks can be time-shared with little or no interference when each task draws on separate pools of attentional resources. The multiple resource theory predicts that concurrent cognitive or perceptual tasks will result in performance decrements for one or both tasks if the task demands exceed the available resources. For example, a highly demanding task such as trying to recall information about the patient case may leave few spare resources for the standardized patient to perceive external stimuli.
Attentional resources also affect information in working memory. Baddeley and Hitch13 describe working memory as the storage, processing, and integration of incoming information with that stored in long-term memory. The multicomponent working memory model of Baddeley14,15 and Baddeley and Hitch13 is composed of several subsystems mediated by the central executive.16,17 Multiple tasks placing heavy demands on attention will drain the central executive’s limited resources and result in performance decrements.18 Therefore, increased demands on the central executive can have a negative effect on the ability to observe and assess another’s behavior.
Within the communications literature, the parallel process model describes a single system devoted to simultaneously encoding and decoding nonverbal communication messages.19,20 According to this model, “encoding” refers to message production and occurs when someone sends a message to another person, and “decoding” refers to the perception and interpretation of another’s message. Like the multiple resource theory and working memory models, the parallel process model suggests that people have limited cognitive resources to divide between encoding and decoding nonverbal behaviors and that the ability to observe and possibly assess another’s nonverbal behaviors may be compromised when engaged in an active conversation.
The demands placed on working memory and attention are sometimes described by the construct, mental workload. More specifically, mental workload refers to the effort experienced by an individual resulting from the interaction between a person and a task.21 Mental workload is likely to increase with high task demands, especially if the task demands exceed the available resources.22 According to Wickens,11,12 a person is likely to experience high mental workload when performing 2 tasks that compete for similar resources, which exceed those available.22,23
The Effects of Multiple Tasks and Improvisations
Collectively, these theories make several predictions regarding the attentional demands placed on individuals who must portray a character, improvise plausible responses, and observe and rate another’s behavior. Consistent with the working memory model of Baddeley14,15 and the multiple resource theory model of Wickens,11,12 individuals should have more attentional resources to devote to observing when that is their only task. By contrast, if an individual must time-share observing with another task (eg, portraying a character), the combined task requirements might exceed available resources and compromise performance. Evidence for compromised performance when 2 visual tasks exceed attentional capacity has been found in aviation24 and surgery.25 Along similar lines, the parallel process model of nonverbal communication19,20 suggests that people only need to decode during passive observation conditions but must both encode and decode during active observation conditions. Therefore, individuals should be less observant, provide less accurate ratings of another’s behavior, and report higher levels of mental workload under active conditions when they must time-share portrayal and observation tasks than when performing an observation task by itself.
Likewise, the working memory and multiple resource theory models can be used to predict the effects of improvisations. Specifically, the need to improvise responses should place greater demands on an individual’s attentional and working memory resources than on following a script from memory. When confronted with unanticipated questions, individuals must construct responses based on the current situation and information stored in long-term memory. Thus, they are likely to focus their attention inward and have fewer resources available for observing another’s behavior and may also experience higher levels of mental workload. By contrast, when individuals can draw upon information in long-term memory to answer questions, they should have more resources available to attend to another’s behavior and find the experience to be less mentally demanding.
These predictions were tested in a study by Newlin-Canzone et al26 who examined the ability of undergraduate students to observe and rate an interviewer. Participants were asked to participate in 2 simulated job interviews requiring responses that either had to be memorized ahead of time or improvised on the spot. During the interview, they assessed the interviewer’s nonverbal behaviors, which required them to both portray and assess communication behaviors. As a control measure, they also performed the observation task alone by viewing 2 video-taped interviews (with and without improvisations). Consistent with the predictions of multiple resource theory,11,12 working memory,14,15 and the parallel process model,19,20 participants observed fewer nonverbal behaviors and provided less accurate ratings when required to simultaneously participate in an interview and observe the interviewer, particularly when they needed to improvise responses. These effects were corroborated with higher reported levels of mental workload and suggest that generating responses on the spot can be a difficult task that diverts attentional resources away from observing another’s behavior.
The purpose of the present study was to reexamine the effects of active and passive observing and improvised responses with standardized patients in clinical scenarios. Consistent with the working memory model of Baddeley,14,15 the multiple resource theory of Wickens,11,12 and the parallel process model,19,20 it was expected that standardized patients would observe fewer nonverbal behaviors, provide less accurate ratings of the learner’s communication, and report higher mental workload after the active observation conditions. It was also expected that standardized patients would observe fewer nonverbal behaviors, provide less accurate ratings of nonverbal communication, and report higher mental workload during encounters requiring improvisation because of greater demands on their attentional and working memory resources.
A 2 types of observation (passive or active)–by–2 types of encounter (with and without improvisations) within-subjects design was used for this study. Type of observation was a within-subjects variable with 2 levels so that active observers participated in the encounter and passive observers watched the encounter. Type of encounter was also a within-subjects variable with 2 levels, with or without improvisation. During the active observation phase, participants participated in one encounter involving no improvisations and another encounter with improvisations. Participants also passively observed 2 encounters, one with and one without improvisations. The 2 types of encounters and types of observations were counterbalanced across participants by alternating their assignments to the experimental conditions.
Twenty standardized patients (13 females [65%] and 7 males [35%]) from the Eastern Virginia Medical School Skills (EVMS) Sentara Center for Simulation and Immersive Learning participated in this institutional review board–approved study. Their ages ranged from 23 to 71 years (mean [SD], 49.60 [14.36] years). Their experience as standardized patients ranged from 3 to 181 months (mean [SD], 46.43 [42.56] months). Participants were paid $30 for their time.
The program director from the Center provided 4 case scenarios for the experiment: 2 were very predictable (required no improvisations) and 2 were very unpredictable (required 10 improvisations). An encounter that required the standardized patient to improvise 10 times was considered very unpredictable according to the director of the Center. The investigators created scripted questions that would require the participants to improvise with information that was not included in the case details. The case details contained patient demographics, a summary of the case, and a scripted opening sentence. The case details consisted of a history of present illness that included a description of symptoms. The medical history described the patient’s past health issues. The case details also included the communication instrument used at EVMS, the Master Interview Rating Scale items (see later).
Standardized Learner’s Script
Another standardized patient was designated as the standardized learner and played the part of the student clinical provider. The standardized learner was a 22-year-old male and had worked as a standardized patient for a year and a half.
The standardized learner used the same script for each scenario so that different standardized patients experienced the same scripted scenarios. The scripts included scripted questions with the corresponding nonverbal behaviors such as tapping a pen and crossing of the arms. The encounters were scripted so that 10 nonverbal behaviors occurred while the participant improvised a response and 10 occurred when the participant had a prepared response. The participant improvised responses to unexpected questions such as, “What was your last blood pressure reading?” and “Can you tell me what you had to eat today?” Owing to the study parameters/design, the standardized learner was not allowed to deviate from the script and respond to the standardized patients as would occur in a normal situation with a learner. A standardized patient educator reviewed videos of every encounter to ensure consistency of the standardized learner across the different scenarios and participants.
The Master Interview Rating Scale
The Master Interview Rating Scale consists of 27 clinical skills items. It was developed at the EVMS Center as a tool for standardized patients to assess the clinical interview (Master Interview Rating Scale, 2005). This checklist is based on the Arizona Clinical Interview Rating Scale.27 The Arizona Clinical Interview Rating Scale consists of 16 clinical skills scored on rating scales with a range from poor (1) to excellent (5).27
In the present study, an abbreviated version of the Master Interview Rating Scale consisting of only 6 items was used. These items were selected because they addressed the standardized patient’s perceptions of the learner’s interpersonal communication. Specifically, the abbreviated Master Interview Rating Scale addressed the questioning skills—types of questions posed by the learner, verbal facilitation skills and encouragement, nonverbal facilitation skills, empathy and acknowledging patient cues, overall interview technique, and the logical organization of the questioning.
The participants were instructed to indicate which nonverbal behaviors they perceived after each interview. They were not initially told that they would be required to complete this query until after they completed the first encounter. The query includes a list of nonverbal behaviors (eg, turning away from the participant or tapping a foot).
NASA Task Load Index
The participants rated their perceived mental workload on the NASA Task Load Index (NASA-TLX) after each interview.28 This instrument measures subjective mental workload and consists of 6 subscales as follows: mental, physical, and temporal demand; performance; effort; and frustration. They indicated on a scale of 0 (low) to 20 (high) their perceived demands on each subscale. This instrument has been shown to be valid and has a test/retest reliability of 0.83.28
The participants were assigned 2 cases for which they had the least amount of experience before the experiment; however, some participants had previously portrayed one of these cases. Although every effort was made to minimize experience with the cases, participants who had familiarity with the cases were not excluded. Specifically, 8 participants had no experience with the cases, 10 participants had worked with the cases fewer than 5 times, and 2 participants had worked with 1 case more than 5 times. The participants received case details and Master Interview Rating Scale items several days before the experiment. The participants used these case details to answer the standardized learner’s questions. The participants were trained on the 2 cases that they would actively portray. However, they were not trained on the cases that they would passively observe but were able to review the details for these cases. The training followed the typical procedure for a low-stakes encounter. First, the participants learned the case and discussed how they would portray the patient with the trainer. Participants were not specifically trained to improvise for this study; however, it should be noted that all standardized patients receive instruction on how to improvise when asked unexpected questions as part of their general training. Furthermore, although Master Interview Rating Scale items were identified during the training, there was a conscious decision to omit discussions specifically focused on nonverbal behaviors. As part of the normal training process, the standardized patients participate in a dry run; however, the dry run was eliminated to meet the study objectives. Specifically, the investigators wanted to limit variability in the training process. Each standardized patient has different experiences during the dry run, and participants may have gained more familiarity with the case than other participants.
Upon arrival at the Center, the participants read and signed their consent forms and then provided information about their standardized patient experiences on a background information form. Each standardized patient participated in all 4 encounters; 2 of these encounters were in the passive observation phase, and 2 were in the in the active observation phase. Each encounter lasted approximately 5 minutes. Participants were active in 2 different cases, one with no improvisations and one with high improvisations. Participants also passively observed 2 different cases, again one with and without high improvisations. This ensured that the participants never observed the same case twice. The total time to complete the experiment was approximately 1.5 hours.
Active Observation Phase
During the active observation phase, the participants performed the portrayal and assessment tasks. They performed as standardized patients in one encounter with no improvisations and in a second encounter with improvisations. The participants were allowed to review the case details before beginning the encounter. They portrayed their cases in an examination room at the Center. The participants completed the abbreviated Master Interview Rating Scale, the postinterview query, and the NASA-TLX after all encounters.
Passive Observation Phase
Participants read the instructions for the passive observation phase before observing a video tape of another standardized patient in 2 encounters, one with and one without improvisations. They completed all questionnaires after they viewed the videos, and they were unable to rewind or review the videos.
An initial screening of the data revealed 7 statistical outliers; that is, data greater than 3 SDs above or below the mean.29 All outliers were replaced with a score one unit higher or lower than the next most extreme deviant score in the data set.30 The descriptive statistics showed that all the data were normally distributed after replacing the outliers. The data were analyzed with a 2 types of encounter (with and without improvisations)–by–2 types of observation (passive and active) repeated-measures analysis of variance (ANOVA).
The Cronbach α for the abbreviated Master Interview Rating Scale was 0.87, which represents a high level of internal consistency. The results of the ANOVA did not show any significant effects on the participant’s rating of the standardized learner’s communication (P > 0.05). These results included the overall communication ratings and the individual Master Interview Rating Scale items.
Nonverbal Behavior Query
The investigator reviewed every encounter and identified all nonverbal behaviors that occurred. The proportion of nonverbal behaviors correctly identified was generated by summing the number of behaviors correctly identified and dividing the sum by the total nonverbal behaviors that occurred during the interview. The results of the ANOVA for these data showed a significant main effect for type of observation on the participants’ ability to correctly identify nonverbal behaviors (F1,19 = 138.15, P < 0.001, partial η2 = 0.88, power = 1.00). Participants correctly identified significantly fewer nonverbal behaviors when they occurred during an active observation (mean [SD], 0.24 [0.09]) than when they occurred during a passive observation (mean [SD], 0.54 [0.14]). The results also showed that participants correctly identified significantly fewer nonverbal behaviors when the behaviors occurred during an improvisational encounter (mean [SD], 0.36 [0.11]) than those that occurred during an encounter without improvisations (mean [SD], 0.42 [0.12]) (F1,19 = 6.56, P < 0.05, partial η2 = 0.26, power = 0.68).
The investigator reviewed videos of the encounters and recorded all nonverbal behaviors and compared this list with the behaviors identified by the participants. Any nonverbal behaviors reported by the participants that did not occur during the interview were recorded as incorrectly identified behaviors. Overall, the mean (SD) number of incorrectly identified behaviors was 4.15 (2.53). The results of the ANOVA did not show any significant effects (P > 0.05).
Subjective Mental Workload
The overall mental workload score was generated by summing all 6 subscales of the NASA-TLX. Results of an ANOVA failed to show any significant effects on participants’ overall subjective mental workload (P > 0.05). The individual subscales of the NASA-TLX were also analyzed. Regarding the mental demand subscale, the results showed a significant interaction between type of observation and type of encounter (F1,19 = 13.09, P < 0.01, partial η2 = 0.41, power = 0.93) (Fig. 1). Results of simple effects analyses showed that participants indicated significantly higher mental demand after active improvisational encounters (mean [SD], 13.08 [3.08]) than active encounters without improvisations (mean [SD], 9.77 [4.90]) (F1,38 = 13.10, P < 0.01) and passive improvisational encounters (mean [SD], 11.06 [5.07]) (F1,38 = 4.88, P < 0.05). The results also showed a significant main effect for the type of encounter on the participants’ mental demand (F1,19 = 12.05, P < 0.01, partial η2 = 0.39, power = 0.91). Participants indicated significantly higher mental demand after improvisational encounters (mean [SD], 12.07 [4.70]) than encounters without improvisations (mean [SD], 10.58 [4.32]). There was no main effect for the type of observation (P > 0.05).
The goal of the present study was to examine the effects of active and passive observing and improvised responses on the workload and ability of standardized patients to observe and rate a learner’s communication behaviors to improve training protocols. As predicted, the participants observed fewer nonverbal behaviors during active observations. This is consistent with the multiple resource theory,11,12 the parallel process model of Patterson,19,20 and the working memory model of Baddeley,14,15 all of which suggest that there are limited cognitive resources to divide among multiple tasks. Overall, participants missed a significant number of behaviors during active observations, particularly subtle eye movements such as excessive eye blinking and raising eyebrows. In addition, participants reported higher mental demand after active encounters. These results suggest that time-sharing the portrayal and assessment tasks required a fair amount of mental effort. However, the results were limited to the mental demand subscale and were not observed in the overall mental workload scores (although the pattern of results for overall mental workload scores was consistent with predictions). It is possible that differences among the 6 subscales weakened the overall mental workload score for these types of tasks. The absence of these effects may be due to the participants having had some experience with multitasking the portrayal and assessment activities.
Regarding improvisations, the results provide partial support for the hypothesis that participants would provide less accurate ratings and observe fewer nonverbal behaviors after improvisational encounters. The results showed that participants observed fewer nonverbal behaviors during improvisational interviews and particularly during the active encounters. In fact, they missed nearly every behavior that occurred while they improvised a response, including conspicuous behaviors such as crossing of the arms. The results were corroborated to some extent by the subjective workload scores. The participants reported higher mental demand after improvisational interviews, but again, the effect was not observed in the overall mental workload scores.
Although improvisations affected the nonverbal behavior measure, they did not influence the participants’ ability to rate the standardized learner. On the one hand, it is possible that the requirement to improvise does not directly translate into overall impressions of the learner. On the other hand, it is also possible that participants used a task switching strategy rather than dividing their attention.31,32 One participant indicated that she routinely switches between the tasks of observing the learner and portraying the case. She mentioned that she “mentally flags” different points throughout the encounter that specifically relate to a Master Interview Rating Scale item.
Collectively, the results of the present study were partially consistent with those reported by Newlin-Canzone et al.26 In both studies, the participants’ ability to detect nonverbal behaviors suffered during both active observations and improvisational encounters. These findings demonstrate that the attentional demands of portraying and assessing negatively affect the ability to observe another person’s nonverbal cues for both inexperienced undergraduates and standardized patients. There were some discrepancies between the 2 studies regarding mental workload. Unlike the first study, the results of the present study did not yield any significant differences in overall mental workload scores. Although the pattern was consistent between the 2 studies, the effects were limited to the mental demand subscale in the present study. On the other hand, Newlin-Canzone et al found that undergraduates provided lower interviewer ratings after active observations and improvisational encounters. The discrepancies between the 2 studies may reflect differences in experience between the participant samples. Newlin-Canzone et al used inexperienced undergraduates in their job interview study, whereas all participants in the present study were working standardized patients who had experience with the types of tasks under investigation.
The results of the present study have theoretical implications for understanding the cognitive resources needed to simultaneously produce and interpret nonverbal communication. The results indicated that multitasking communication tasks can impair one’s ability to observe another’s communication behaviors and can also result in increased mental workload. These findings support the parallel process model19,20 that predicts people have limited cognitive resources to devote to sending (encoding) and interpreting (decoding) nonverbal communication. Furthermore, they provide additional support for the idea that limited cognitive and perceptual resources can be divided among communication production, observing and assessing another’s communication behaviors, particularly when one must improvise responses.
The multicomponent working memory model13 was also useful in predicting the impact of portraying and observing nonverbal communication on limited and shared cognitive resources. The findings support past research suggesting that social and facial decoding is a cognitive task that relies on working memory resources.33 Specifically, the present results suggest that observing and assessing another person’s communication behaviors may indeed rely heavily on working memory resources.
Furthermore, the need to improvise responses requires additional central executive resources to integrate information from long-term memory with information from the current situation.9 In contrast, during rote interviews, participants were able to rely on information drawn primarily from long-term memory.34 Overall, the findings suggest that the multiple resource theory, working memory, and parallel process models are applicable to observing and assessing communication behaviors and can be used to understand the unique cognitive demands of standardized patients.
Limitations and Future Research
Although the results generally supported the hypotheses, there were some limitations to the study. First, it is important to understand that some of the experimental procedures adopted in this study were unlike typical encounters involving standardized patients. These departures from standard procedures were necessary to control extraneous variables. For example, the standardized learner followed a script for each encounter. Although this procedure helped standardized the experience across participants, it also constrained more natural interactions. Moreover, a dry run was eliminated from the training process, again to help make the preparations for participation more uniform across participants. It is possible that under normal conditions, the standardized patients may feel more comfortable with the cases and experience different levels of mental workload. In the future, it would be beneficial to examine the present protocol in more ecologically valid standardized patient encounters.
Second, the nonverbal behavior query relied on the participants’ retrospective memory of the nonverbal behaviors that they observed. Despite counterbalancing the experimental conditions, the results indicated that participants were able to identify more behaviors in the last encounter compared with the first few encounters. This retrospective query was chosen because selecting the behaviors in real time would draw the participants’ attention away from the encounter. In the future, it would be useful to probe the standardized patient’s immediate memory by pausing the interview and having them record the nonverbal behaviors in real time as the interview unfolds.
Third, although every effort was made to select cases that the participants had not portrayed extensively, the sample of participants who volunteered to participate did have different levels of experience with the 2 cases they portrayed in the active observation conditions. Although most participants had little or no experience with these cases, in the future it would be important to use novel cases with which all standardized patients were equally unfamiliar.
Fourth, assessment of communication was limited to nonverbal behaviors. The nonverbal component of communication is critical in patient-clinical provider encounters because patients use nonverbal behaviors to express their concerns and to interpret their clinical provider’s verbal message,35 particularly when they do not understand the clinical provider.36 Overall, patients rely on nonverbal communication to express their fears, relate to their clinical provider, and understand their situation when the verbal message is unclear.37 Thus, although nonverbal communication is important, it would be useful to extend the study to include verbal behaviors because this is a key component in communication.
Last, theories of attention, working memory, and mental workload were useful in predicting challenges faced by standardized patients to observe a learner when assessing and portraying; yet, the same could be true for the learners. Indeed, learners have a mentally demanding job that requires them to demonstrate empathy and good communication skills while listening to the patient’s concerns. A logical extension of this research would be to examine the cognitive challenges imposed on the learners during a clinical interview.
The findings have several important practical implications for the training of standardized patients. First, the results showed that standardized patients failed to detect at least half of the learner’s nonverbal behaviors when passively watching encounters and nearly 75% when participating in the interaction. Performance was even worse when they were required to improvise. Many standardized patients missed obvious behaviors such as when the learners crossed their arms. These findings suggest that the ability of standardized patients to detect and recall nonverbal behaviors may be compromised during their encounter perhaps because the standardized patients either did not perceive the behaviors initially or because the behaviors they did perceive could not be recalled after the session. In either case, standardized patients are often required to provide a global rating of their interaction with the learner after their encounter. It is also possible that standardized patients typically provide an overall impression of their interaction with the clinical provider and they ignore specific behaviors. The present findings suggest the attentional demands of the portrayal task may impact the ability of standardized patients to notice and/or recall important aspects of a learner’s nonverbal behavior that could potentially affect how they rate the learner’s communication skills.
Furthermore, the standardized patients were more observant of the learner when performing only the assessment task. These results suggest that there may be benefits to separating the portrayal and assessment tasks.
The results also affirm that standardized patients would benefit from training specifically aimed at handling improvisations. As noted previously, one standardized patient indicated that she relied on her previous experiences to quickly retrieve a generic response from their long-term memory. Another current practice in some standardized patient programs supports this idea.38 Currently, some standardized patients are trained to think like the character and explore different facets of this person. The standardized patient trainer often asks, “What do you think is her favorite flavor of ice cream?” This process teaches the standardized patients to think about the character in detail so they are better prepared for unanticipated questions. Increased training with improvisations may alleviate attentional and working memory demands so that the standardized patients will have more spare resources to devote to observing the learner. Finally, the results showed that standardized patients did experience higher levels of mental workload, particularly mental demand, when improvising responses. Consequently, it is beneficial to make standardized patients aware of the challenges associated with their job and that they may be less perceptive than they believe. Awareness of their own fallibility may influence standardized patients to change some habits. For example, standardized patients may not be aware that they often look away from the learner when improvising and could be trained to more effectively switch between the portrayal and observation tasks by taking advantage of times when there is little for them to portray (eg, such as when the learner is writing notes in a chart). Furthermore, it is important to clearly identify the required observations by the standardized patient during the training and not assume that the standardized patient is able to innately observe learner performances.
The need to simultaneously portray a character and assess a learner may affect the ability of standardized patients to accurately observe the learner’s nonverbal behaviors especially when they are required to improvise responses to unexpected questions. The challenge of simultaneously performing both portrayal and assessment tasks while improvising responses is corroborated by increases in subjective reports of mental demand. Thus, it may be important to make standardized patients aware of the potential for errors under these conditions and establish methods for training them how to manage their cognitive workload.
1. Duggan AP, Parrott RL. Physician’s nonverbal rapport building and patients talk about the subjective component of illness. Hum Commun Res 2001; 27: 299–311.
2. Charon R. The patient-physician relationship. Narrative medicine: a model for empathy, reflection, profession, and trust. JAMA 2001; 286: 1897–1902.
3. Smith RC, Lyles JS, Mettler J, et al. The effectiveness of intensive training
for residents in interviewing. A randomized controlled study. Ann Intern Med 1998; 128: 118–126.
4. Beullens J, Rethans JJ, Goedhuys J, Buntinx F. The use of standardized patients in research in general practice. Fam Pract 1997; 14: 58–62.
5. Cleland J, Abe K, Rethans J. The use of simulated patients in medical education: AMEE Guide No. 42. Med Teacher 2009; 31: 477–486.
6. Passiment M, Sacks H, Huang G. Medical Simulation in Medical Education: Results of an AAMC Survey. Association of American Medical Colleges; 2011.
7. Medical Council of Canada Qualifying Examination Part II, retrieved from Available at: http://www.mcc.ca/en/exams/qe2/
. Accessed November 18, 2012.
8. Boulet JR, Smee SM, Dillon GF, Gimpel JR. The use of standardized patient
assessment for certification and licensure decisions. Simul Healthc 2009; 4: 35–42.
9. Wallace P. Coaching Standardized Patients. New York, NY: Springer Publishing Company; 2007.
10. Kahneman D. Attention
and Effort. Englewood Cliffs, NJ: Prentice-Hall; 1973.
11. Wickens CD. Processing resources in attention
. In: Parasuraman R, Davies DR, eds. Varieties of Attention
. Orlando FL: Academic Press; 1984: 63–102.
12. Wickens CD. Multiple resources and performance prediction. Theor Issues Ergon Sci 2002; 3: 159–177.
13. Baddeley AD, Hitch GJ. Working memory
. In: Bower GA, ed. Recent Advances in Learning and Motivation. New York, NY: Academic Press; 1974; 8: 47–90.
14. Baddeley AD. Working Memory
. Oxford, England: Clarendon; 1986.
15. Baddeley AD. Human Memory: Theory and Practice. London, England: Erlbaum; 1990.
16. Baddeley AD. The episodic buffer: a new component of working memory
? Trends Cogn Sci 2000; 4: 417–423.
17. Baddeley AD. Working Memory
, Thought and Action. Oxford, England: Oxford University Press; 2007.
18. McCutchen D, Covill A, Hoyne SH, Mildes K. Individual differences in writing: implications of translating fluency. J Educ Psychol 1994; 86: 256–266.
19. Patterson ML. Invited article: a parallel process model of nonverbal communication
. J Nonverb Behav 2006; 19: 3–29.
20. Patterson ML. The evolution of theories of interactive behavior. In Manusov V, Patterson ML, eds. The SAGE Handbook of Nonverbal Communication
. Thousand Oaks, CA: SAGE Publications; 2006: 21–39.
21. Gopher D, Donchin E. Workload: an examination of the concept. In: Boff KR, Kaufman L, Thomas JP, eds. Handbook of Perception and Human Performance. Cognitive Processes and Performance. New York, NY: Wiley; 1986; 2: 41-1–41-9.
22. O’Donnell RD, Eggemeier FT. Workload assessment methodology. In: Boff KR, Kaufman L, Thomas JP, eds. Handbook of Perception and Performance. New York, NY: Wiley; 1986; 2: 42/1–42/9.
23. Navon D, Gopher D. On the economy of the human processing system. Psychol Rev 1979; 86: 214–253.
24. Wickens C, Colcombe A. Dual-task performance consequences of imperfect alerting associated with a cockpit display of traffic information. Hum Factors 2007; 49: 839–850.
25. Stefanidis D, Scerbo MW, Smith W, Acker CE, Montero PN. Simulator training
to automaticity leads to improved skill transfer compared with traditional proficiency-based training
: a randomized controlled trial. Ann Surg 2012; 255: 30–37.
26. Newlin-Canzone ET, Scerbo MW, Gliva-McConvey G, Wallace A. Attentional and mental workload
demands in nonverbal communication
. In: Proceedings of the Human Factors and Ergonomics Society 55th Annual Meeting. Las Vegas, NV: Human Factors and Ergonomics Society; 2011: 1190–1194.
27. Stillman PL, Brown DR, Redfield DL, Sabers DL. Construct validation of the Arizona Clinical Interview Rating Scale. Educ Psychol Meas 1977; 37: 1031–1038.
28. Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock PA, ed. Human Mental Workload
. Advances in Psychology. Oxford, England: North-Holland; 1988: 139–183.
29. Tabachnick BG, Fidell LS. Computer-Assisted Research Design and Analysis. Boston, MA: Allyn and Bacon; 2001.
30. Dixon WJ, Yuen KK. Trimming and winsorization: a review. Stat Papers 1974; 15: 157–170.
31. Monsell S. Task switching. Trends Cogn Sci 2003; 7: 134–140.
32. Rubinstein JS, Meyer DE, Evans JE. Executive control of cognitive processes in task switching. J Exp Psychol Hum Percept Perform 2001; 27: 763–797.
33. Philips LH, Channon S, Tunstall M, Hedenstrom A, Lyons K. The role of working memory
in decoding emotions. Emotion 2008; 8: 184–191.
34. Baddeley AD. Is working memory
still working? Eur Psychol 2002; 7: 85–97.
35. Ishikawa H, Hashimoto H, Kinoshita M, Fujimori S, Shimizu T, Yano E. Evaluating medical students’ non-verbal communication
during the objective structured clinical examination. Med Educ 2006; 40: 1180–1187.
36. Friedman HS. Nonverbal communication
between patients and medical practitioners. J Soc Issues 1979; 35: 82–99.
37. Buller DB, Street RL. Physician-patient relationships. In: Feldman RS, ed. Applications of Nonverbal Behavioral Theories and Research. Hillsdale, NJ: Erlbaum; 1992: 119–141.
38. Wallace AM, Lyman L. Standardizing the Unknown: Training
Patients to Respond Similarly to Unscripted Questions. Las Vegas, NV: 8th Annual Conference of the Association of Standardized Patient