A growing body of health care safety studies identify the mental complexities of nursing work and the conditions of distraction, interruption, and cognitive overload as a significant challenge to safe patient care (Eisenhauer, Hurley, & Dolan, 2007; Holden et al., 2011; Unver, Tastan, & Akbayrak, 2012). Yet, nursing work often involves some degree of interruption and distraction. Nurses must monitor and distinguish multiple inputs of data for their importance, while simultaneously attending to a patient or task. Therefore, an effort toward improving nurses' attentional efficiency is especially important in environments where external factors of error are impossible to entirely eliminate (Despins, Cawiezell, & Rouder, 2009). Strategies for enhancing the attentional efficiency of nursing students are relatively unexplored, despite reports that many graduates are underequipped to manage increasingly complex work settings that are known to exacerbate cognitive human error (Institute of Medicine, 1999).
Background and Literature Review
Discussing the importance of self-monitoring in clinical practice, Epstein, Seigel, and Silberman (2008) suggested that cognitive training, in the form of focused-awareness meditation, might be a useful way to enhance the attention, cognitive resilience, and thinking-in-action skills of health care professionals. Similarly, Cook, O'Connor, Render, and Woods (2004) noted that such training, aimed at improving health care professional resilience to interruption and distraction, may be a key strategy for improving patient safety. Focused-awareness meditation is a practice of the purposeful self-regulation of attention, a conscious intention to maintain present moment awareness that, with consistent practice, is suggested to heighten one's trait ability to pay attention in a discerning and concentrated way, despite external or internal distractors (Kabat-Zinn, 1995). This position was supported in the seminal work of cognitive neuroscience researchers (Davidson et al., 2003; Lazar et al., 2005), whose findings revealed significant attentional improvements in participants who meditated. Improvements were demonstrable on functional magnetic resonance imaging as increased cortical thickness in neural areas associated with attention; changes were explained as a neuroplasticity process by which repeated activation of certain neural circuits permanently strengthened synaptic connections. Over the past decade, additional experimental studies have reported similar findings associating meditation practice with the increased ability to sustain attention, filter informational cues, and regulate distracting stimuli (Chambers, Chuen Yee Lo, & Allen, 2008; Jha, Krompinger, & Baime, 2007; Kozasa et al., 2012; Manna et al., 2010; Moore, Gruber, Derose, & Malinowski, 2012; van den Hurk, Giommi, Gielen, Speckens, & Barendregt, 2010; Zeidan, Johnson, Diamond, David, & Goolkasian, 2010).
One form of focused-awareness meditation is mindfulness meditation (MM) based on the concept of mindfulness or “paying attention in a sustained and particular way: on purpose, in the present moment, and non-judgmentally” (Kabat-Zinn, 2012, p. 1). MM practice involves engagement and reengagement of attention to one's breathing, while simultaneously noticing internal and external stimuli. Practitioners of MM perform a formal sitting meditation for 10 to 60 minutes daily but also make continual mindful efforts throughout their day to maintain moment-to-moment awareness and attentive focus. Outcomes of MM practice are increased stability of attention, decreased susceptibility to distraction, and quicker noticing of mind wandering (Kabat-Zinn, 1990). Techniques specific to MM—engaging attentive focus, noticing intruding thoughts, and redirecting purposeful focus—closely align with the cognitive work of clinical practice, where a nurse strives to maintain attentive focus on a patient or task but also simultaneously notices the environment, sorts relevant stimuli from distractors, and repeatedly redirects focus back to a patient or task. Given the rational connection between a nurse's attention regulation capacity and safe patient care, the current study explored the use of MM for its effectiveness in enhancing measures of attentional efficiency in nursing students, and thereby evaluating its potential for inclusion in prelicensure RN curricula.
In this study, attention regulation was defined as an ability to maintain sustained and vigilant focus on a patient or task, while simultaneously monitoring and distinguishing between meaningful versus extraneous environmental cues. This study definition was guided by Posner's and Petersen's (1990) neurocognitive model of attention that explains the attention regulation process performed by three distinct neural networks operating together to achieve attentional efficiency. The alerting network supports vigilant attentional focus to a specific target, while orienting helps one select specific stimuli for the focus. These two networks interact with a third, more metacognitively complex component (i.e., executive network) with key functions that include prioritizing attentional focus, detecting incongruence, and resisting mind wandering.
Design and Research Questions
A randomized controlled trial with a between-subject, two-group comparison and pretest–posttest design was used to examine the primary research question: What is the effect of cognitive training in the form of MM as compared with standard nursing education on posttests of attentional network efficiency in prelicensure RN students? Prior research suggested that differences in perceived stress (Jha et al., 2007) or predispositional mindfulness traits (Eberth & Sedlmeier, 2012) may contribute to improved attention regulation. Therefore, stress and mindfulness were examined as additional variables in an exploratory research question: What is the relationship between the mindfulness characteristics and perceived stress of prelicensure RN students and measurements of attentional efficiency?
Sixty associate degree nursing students enrolled in their first semester at a college in the northeastern United States were recruited from 230 eligible participants. Institutional review board approval was obtained, and all participants provided written informed consent. It was made clear to participants they were under no obligation to participate in the study and would incur no effect on course grades or progression in the nursing program whether or not they participated.
Instruments and Procedures
The Attention Network Test (ANT) (Fan, McCandliss, Sommer, Raz, & Posner, 2002) was used to measure students' pre- and postattentional efficiency in three attention networks: alerting, orienting, and executive function. The ANT is a 30-minute psychophysical computer measurement of participant accuracy and reaction time in response to a randomly appearing visual focal marker (i.e., directional arrow) during conditions influenced by distractors or prewarning cues. Larger alerting and orienting network scores represented increased attentional efficiency, whereas lower scores on executive function indicated greater efficiency. The ANT has been used in over 60 neuropsychological studies with reliabilities noted by network: alerting (.52), orienting (.61), and executive function (.77) (Fan et al., 2002), as well as good face validity (MacLeod et al., 2010).
The 10-item version of the Perceived Stress Scale (PSS-10) (Cohen, Kamarck, & Mermelstein, 1983) assessed participants' pre- and postperceptions of stress. The PSS-10 survey has been used across health, psychology, and sociology disciplines with a high internal consistency (Cronbach alpha = .86) (Cohen et al., 1983) and content validity (Roberti, Harrington, & Storch, 2006).
The Five-Facet Mindfulness Questionnaire (FFMQ) (Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006) measured pre- and postindividual variances in dispositional mindfulness. It has been used in many mindfulness studies with reliabilities from .90 (deBruin, Topper, Muskens, Bogels, & Kamphuis, 2012) to .92 and construct validity (Baer et al., 2008).
A researcher-designed survey was used to gather baseline information on gender, age, ethnicity, and prior experience in meditation. After completing the PSS-10, FFMQ, and ANT pretests, participants were randomly assigned to either an MM or a wait-list control group. The MM group received online instruction on MM techniques and guidelines for performing a 10-minute daily meditation practice. These instructional modules were developed by the first author, who was formally trained in MM techniques and practiced MM daily. In addition, an audio file of a professionally guided MM (available for download) (Moore, 2014) was included for participants to use on their personal computers or smart devices. The MM group was instructed to meditate daily for 10 minutes over 4 weeks and to keep a practice log. Control group participants were instructed not to participate in any meditation practice but would receive training after the study concluded. After the 4 weeks, all participants completed the posttest PSS-10, FFMQ, and ANT and a postintervention survey on the amount of time they spent meditating.
Group differences on attentional efficiency were examined with analyses of covariance (ANCOVA) procedures on each of the ANT network posttest scores (i.e., alerting, orienting, and executive function) while controlling for pretest ANT scores and PSS-10 and FFMQ baseline scores entered as covariates. Group differences on perceived stress and mindfulness characteristics were explored in a one-way multivariate analysis of covariance (MANCOVA) with PSS-10 and FFMQ baseline scores as covariates and posttest PSS-10 and FFMQ scores collectively considered as dependent variables.
Sixty students who agreed to participate were randomly assigned to either the MM (n = 32) or control group (n = 28) after completing pretests. Eight students did not complete the study (i.e., four from each study group). One student withdrew from the nursing program, two reported insufficient meditation time, and five others were unresponsive to posttesting requests. These eight students did not differ in baseline characteristics from the 52 students who completed the study; the MM (n = 28) and control (n = 24) groups remained well-matched on demographics. Most students were women (n = 43) and Caucasian (n = 30); 36 (69%) were between ages 18 and 40 years, and 48 (92%) had little to no prior meditation experience. As presented in the Table, the MM group exhibited higher executive function efficiency on the ANT pretest, t (50) = 2.39, p = .021, compared with the control group, but this was controlled by ANCOVA procedures. Significant group differences were noted on the posttests of executive attention, perceived stress, and mindfulness characteristics, as determined by paired t tests. After 4 weeks of meditation, students in the MM group exhibited greater efficiency of executive attention, lower perceived stress, and improved mindfulness, compared with the control group.
Pretest and Posttest Means (SD) and t Test Results for Outcome Variables
ANCOVA was performed to control for ANT pretest scores, as well as baseline PSS-10 and FFMQ scores, between the two groups. Under these conditions, posttests of executive attention efficiency varied significantly by group, F(1, 49) = 4.26, p = .044, and the strength of the relationship between group assignment and intervention was moderate, ηp2 = .080. Participants in the MM group had more improvement to executive attention than those in the control group with an adjusted mean difference of 17.4 (SE = 8.42). Neither the alerting nor orienting networks demonstrated any significant group differences. MANCOVA was performed on a combined dependent variable of PSS-10 and FFMQ posttest scores due to their strong negative correlation, η= −6.54, p = .000, and to control for PSS-10 and FFMQ pretest scores. This combined dependent variable varied significantly by group, F(2, 47) = 7.16, p = .002, and the strength of this relationship was large, ηp2 = .234. The MM group had significantly higher scores on measurements of mindfulness characteristics (p = .013), as well as significantly less perceived stress (p = .000), after 4 weeks of meditation than the control group participants.
The observed improvement to executive attention in the meditation group coincides with other cognitive neuroscience experimental studies (Chan & Woollacott, 2007; Jha et al., 2007; Kozasa et al., 2012; van den Hurk et al., 2010; Zeiden et al., 2010) and may be important to consider in the context of nursing work. Executive attention is the type of cognitive processing required under technically difficult conditions involving critical decision making, trouble shooting, and prioritizing one's attention among competing stimuli (Norman & Shallice, 1980) and is antecedent to the situational awareness needed for safe and accurate patient care (Sitterding, Broome, Everett, & Ebright, 2012). Additional research on the effects of MM on safety at the point of care—perhaps in simulation exercises—is necessary to further investigate the correlation between executive attention, situational awareness, and patient-related safety outcomes.
The positive interventional effects of MM in reducing participant stress are consistent with other studies (Beddoe & Murphy, 2004; Jain et al., 2007; Song & Lindquist, 2015), with bearing on the preparation of safe health care practitioners. Stress impedes accurate decision making and cognitive processing yet has been historically downplayed as something to which health care workers are expected to become accustomed (Sexton, Thomas, & Helmreich, 2000). Further study of the link between self-care practices such as MM is needed for students' and nurses' mental health benefits, as well as the equated value it might extend to their safe care of others.
Higher mindfulness scores of meditators may also have implications for safe nursing practice, as the mindfulness trait carries with it a heightened monitoring ability and metacognitive skill (Shapiro, Brown, & Astin, 2011). Recent nursing studies have begun to examine the effects of MM training on patient safety outcomes, with results revealing decreased patient safety events on behavioral health units after mindfulness staff training (Brady, O'Connor, Burgermeister, & Hanson, 2012; Hallman, O'Connor, Hasenau, & Brady, 2014).
An a priori sample size (N = 82) was calculated for a medium effect size of .25, alpha of .05, and power of .95, but ultimately, only 52 students completed the study, thus reducing post hoc power. Using face-to-face MM sessions, along with individual practice, may encourage future participation and retention. Some restriction of results is also possible, in that 14% of the meditators reported a lack of full treatment adherence (meditating only 3 to 4 days per week). Low ANT Cronbach alphas in this study (alerting = .61, orienting = .60, executive function = .84) and in others (Fan et al., 2002) warrants consideration and cross validation with other measures of attention. In addition, a need exists for the recruitment of more diverse participant groups to determine the effect of culture on study variables.
The study's preliminary findings will require further investigation and replication. Yet, cognitive training in the form of MM holds promise as a method for enhancing the executive attention efficiency of prelicensure RN students, in addition to improving their mindfulness characteristics and a self-regulating stress reduction benefit—all of which may help cultivate more intrinsically safe nurses of the future. Integrating a hybrid online MM course into nursing safety-education curricula may be a feasible option that would add minimal burden to its already content-laden nature. Other possible applications include incorporating brief MM sessions into courses (e.g., before examinations) or prior to a simulation exercise or clinical practice.
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Pretest and Posttest Means (SD) and t Test Results for Outcome Variablesa
|Mindfulness Meditation Group||Control Group||Mindfulness Meditation Group||Control Group|
|Alerting||39.5 (23.9)||31.8 (27.9)||38.6 (24.7)||36.0 (19.2)||−.419||.677|
|Orienting||32.9 (23.4)||37.4 (21.5)||39.9 (21.4)||37.2 (21.0)||−.462||.646|
|Executive||119.4 (40.7)||147.7 (44.6)||95.9 (28.6)||125.9 (39.7)||3.26||.003**|
|PSS-10||20.9 (6.9)||19.9 (4.8)||15.9 ( 6.7)||21.3 (5.8)||3.09||.003**|
|FFMQ||132.3 (16.6)||130.7 (17.4)||140.8 (17.8)||130.4 (17.5)||2.11||.04*|