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FEATURE ARTICLE

Perceptions of Cognitive Load and Workload in Nurse Handoffs A Comparative Study Across Differing Patient-Nurse Ratios and Acuity Levels Benjamin J. Galatzan, PhD, RN, Liang Shan, PhD, Elizabeth Johnson, PhD, MS-CRM, RN, Patricia A. Patrician, PhD, RN, FAAN

Medical errors, often resulting frommiscommunication and cognitive lapses during handoffs, account for numerous pre- ventable deaths and patient harm annually. This research examined nurses' perceived workload and cognitive load during handoffs on hospital units with varying patient acuity levels and patient-nurse ratios. Conducted at a southeast- ern USmedical facility, the study analyzed 20 handoff dyads using the National Aeronautics and Space Administration Task Load Index to measure perceived workload and cognitive load. Linear regressions revealed significant associations between patient acuity levels, patient-nurse ratios, and Na- tional Aeronautics and Space Administration Task Load In- dex subscales, specifically mental demand (P = .007) and performance (P = .008). Fisher exact test and Wilcoxon rank sum test showed no significant associations between these factors and nurses' roles (P > .05). The findings high- light the need for targeted interventions to manage work- load and cognitive load, emphasizing standardized handoff protocols and technological aids. The study underscores the variability in perceived workload and cognitive load among nurses across different units. Medical-surgical units showed higher cognitive load, indicating the need for im- proved workload management strategies. Despite limita- tions, including the single-center design and small sample size, the study provides valuable insights for enhancing handoff communications and reducing medical errors.

KEY WORDS: Cognitive load, Nurse handoffs, Nurse- patient ratios, Nursing informatics, Patient safety, Workload

M edical errors are responsible for an estimated 210 000 to 400 000 preventable deaths and patient harm each year.1,2 The primary root causes of these

Author Affiliations: University of Alabama at Birmingham School of Nursing (Drs Galatzan, Patrician, and Shan); and Montana State University College of Nursing, Bozeman (Dr Johnson).

Funding was provided by an internal faculty award from the University of Alabama at Birmingham School of Nursing.

The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Benjamin J. Galatzan, PhD, RN, University of Alabama at Birmingham School of Nursing, 1720 2nd Ave S, Birmingham, AL 35294 (galatzan@uab.edu).

DOI: 10.1097/CIN.0000000000001216

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errors are miscommunication and cognitive lapses.3–5 These lapses and miscommunications, particularly during handoffs, lead to delayed diagnosis and interventions, delayed or omitted tests, and medication errors.6–9 These issues often result in adverse patient outcomes, including direct patient harm, hospital-associated infections, and extended hospitalizations.10,11

As evident in the potential adverse events, nursing handoffs play a pivotal role in ensuring the continuity, safety, and quality of patient care. The transition of care communi- cation or handoff is the process of transferring responsibility for and care of the patient and communicating critical patient information from one nurse to another, often involving the synthesis and transfer of complex patient information.3,6,12

The mental effort involved in this process, or “cognitive de- mand,” challenges both the sender and the receiver because of the intricate details necessary for patient safety.13 The cog- nitive demand during handoffs can be affected by various fac- tors, such as the patient-nurse ratio, the complexity of patient cases, and the dynamics of the healthcare unit. “Cognitive load,” however, specifically refers to the mental resources needed to understand and utilize the information exchanged during handoffs. This load is shaped by intrinsic factors such as the severity of the patient's condition and extraneous factors such as staffing levels.14,15

The nursing units within a healthcare facility provide care to patients with varying levels of illness severity and care de- mands. An ICU provides care to critically ill patients requir- ing highly specialized and focused care, whereas a general medical-surgical unit provides care to patients with a wide range of medical issues that are not immediately life-threatening. In addition to acuity levels, nurse-patient ratios are often in- dicative of the workload of a nurse and vary across nursing units. Units with a high patient-to-nurse ratio indicate that the nurse is responsible for a larger number of patients, po- tentially increasing the volume and complexity of informa- tion to be communicated during handoff. With a lower patient-to-nurse ratio, the nurse is responsible for fewer patients, but often, the patient acuity is higher, and the complexity of the cases is greater, also affecting the hand- off process. These variances in patient acuity levels and

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https://orcid.org/0000-0002-0220-8388

mailto:galatzan@uab.edu

FEATURE ARTICLE

nurse-patient ratios could lead to differing degrees of in- formation complexity that a nurse must convey during handoffs, potentially affecting the nurse's perceived work- load and cognitive load.

Understanding the nurse's perception of the workload and cognitive load of the handoff process is essential in im- proving the quality of care and patient safety. A consistently high level of perceived cognitive load and workload can lead to a negative impact on the nurse's sense of well-being, burn- out, fatigue, and job satisfaction.16–19 In addition to nurses’ well-being, a consistently perceived high level of workload and cognitive load can impact patient safety, quality of care, and workflow efficiency.16,18,19 The aim of this study was to examine the RN's perception of the workload and cognitive load of the handoff process on three different units with vary- ing degrees of nurse-patient ratios and patient acuity level. The two main research questions were as follows:

1. What is the perceived workload and cognitive load of both the sender and receiver during the change-of-shift handoff, as measured by the National Aeronautics and Space Administration Task Load Index (NASA TLX)?

2. How do varying patient acuity levels and patient- nurse ratios affect the perceived workload and cognitive load, as measured by the NASA TLX, during the change-of-shift handoff?

METHODS Design The research utilized the Nurse-to-Nurse Transition of Care Communication Framework to structure the study. This framework serves as a tool to analyze the handoff communi- cation between nurses when a patient experiences a transi- tion of care either intrahospital or interhospital.10 The study used a quantitative descriptive design to investigate nurses' perceived workload of performing the handoff on three dif- ferent units with varying degrees of patient acuity levels and patient-nurse ratio. This study was part of a larger mixed-methods research project concerning the change-of- shift handoff communication.

Setting The study was conducted at a major medical facility in the southeastern United States, known for its comprehensive academic, clinical research, and referral services. The units selected for this study were based on their differing patient- nurse ratios and patient acuity levels, including a cardiovas- cular ICU (CICU), a step-down trauma unit, and a general medical-surgical unit. The CICU had a 1:1 to 1:2 RN- patient ratio for both day and night shifts, representing a low patient-nurse ratio and high acuity level. The step- down trauma unit had a 1:3 to 1:4 RN-patient ratio for

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the day shift and a 1:4 to 1:5 RN-patient ratio for the night shift, indicating a medium patient-nurse ratio and medium acuity level. The medical-surgical unit had a 1:6 to 1:7 RN-patient ratio on the day shift and a 1:7 to 1:9 RN- patient ratio on the night shift, reflecting a high patient- nurse ratio and low acuity level. These categorizations high- light the unique characteristics of each unit under the study setting and underscore the varying demands on nurse work- load and cognitive load during handoffs.

Definition and Impact of Patient Acuity

Patient acuity is defined as the complexity and severity of pa- tients' conditions, requiring varying levels of nursing care and resources.20,21 According to the Easley-Storfjell Patient Classification Instrument and Holzemer's Outcomes Model for Health Care Research, patient acuity is considered a structure of care that can influence nursing processes and outcomes, such as workload distribution, patient safety, and quality of care.20 The patient acuity for the three units involved in the study was categorized as high for the CICU, moderate/medium for the step-down unit, and medium/ low for the general medical-surgical units.21 We acknowl- edge that acuity levels can fluctuate on any given unit, but these categories align with the critical nature of each unit.

Handoffs took place face-to-face at the bedside, away from the bedside, or a combination of both. Notably, all three units lacked a standardized handoff tool. Nurses used their own personal handoff template (brainsheet); the elec- tronic health record was not used. Approval for the study was obtained from both the institutional review board of the organization and the academic institution.

Recruitment and Sample The participants in the study consisted of RNs responsible for conducting the handoff. The study aimed to include 60 RNs and 30 handoffs. The sample size was determined through information power analysis, taking into account the focused and specific objectives of the study, the charac- teristics of the participants (RNs involved in the handoffs), the application of a defined theoretical framework, the qual- ity of the dialogue, and the strategic analytical methods used.22,23 The researchers used a convenience sampling method to identify eligible participants, and no advertising was used for this study. To be eligible for participation, the RNs needed to fulfill the following inclusion criteria: (1) worked full-time on the designated unit or be a traveler/ agency RN assigned to that unit; (2) possessed a minimum of 3 months' experience on the unit, having completed their orientation or being a traveler/agency RN assigned to the unit; (3) proficient in speaking and reading English; and (4) had provided care or were continuing to provide care for a patient who had experienced a clinical event (CE). A critical

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criterion for participants in this study was that the patient must have experienced a CE during the current shift, before the nursing shift change, and continued to receive care on the unit. A CE is identified by occurrences such as fever; al- terations in bodily outputs (eg, urine, stool, vomit); changes in consciousness levels; and instances of bleeding, pain, or shifts in respiratory conditions.24 These incidents are unex- pected during patient treatment, necessitating immediate medical response and carrying the potential to escalate into sentinel events if not managed promptly. The occurrence of a clinical event was a key factor in this study, providing a lens through which to investigate the conveyance of critical patient information during the handoff, as well as to assess the cognitive demands and perceived workload associated with the handoff process.

To mitigate any potential bias or distortion of results, each nurse participant was permitted to take part in the study only once. The sample size for this study was 20 handoff dyads, in- volving the three units. A handoff dyad comprised at least one RN sending the handoff (sender) and one RN receiving the handoff (receiver). The total RN sample size was 41 including 20 RNs sending and 21 RNs receiving the handoff communi- cation. One of the handoff dyads consisted of three RNs, with one sending and two receiving the handoff.

Instrument The NASA TLX mobile application25 was used to evaluate the RNs' perceived workload and cognitive load associated with the nursing handoff. The NASA TLX was completed through a mobile application on an iPad programmed spe- cifically for the study. It was originally developed for the avi- ation industry to assess perceived workload after completing a task.26–28 The NASATLX has since been used in a variety of applications, including computer science, nursing,29 med- icine, and military.27,28,30

The NASA TLX contains six subscales: mental demand (cognitive effort required), physical demand (physical effort required), temporal demand (time pressure felt), perfor- mance (satisfaction with one's performance), effort (overall exertion required), and frustration (stress and irritation expe- rienced).31 This instrument has demonstrated high construct validity when used to assess the workload of nurses working in the ICU setting, pediatric ICU, and neonatal ICU29

and high criterion (concurrent) validity when assessing the workload of anesthesiologists.28 The NASA TLX has dem- onstrated moderate to good reliability with an intraclass cor- relation coefficient range of 0.71 to 0.8130 and an interrater reliability range of 0.77 to 0.83.26,32

Data Collection The primary investigator (PI) and two trained research assis- tants (RAs) followed a systematic data collection protocol. All

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data and informed consent were obtained by either the PI or the RAs. To identify RN handoff dyads meeting the inclu- sion criteria, the PI or RAs arrived at the unit 1 hour before the next shift started. The PI or RAs engaged in a discussion with the off-going RN to ascertain if any patient had experi- enced a CE during that shift. Once an eligible patient was identified, the PI or RAs individually approached the outgo- ing and incoming RNs assigned to that patient to assess eligi- bility, provide a study explanation, and obtain consent. The PI and RA emphasized that participating in the study was voluntary and would not impact job status. They also en- sured that all identifiers such as those of patients, families, RNs, and other healthcare personnel would be removed.

The PI created the study as per the NASA TLX user guide in the online mobile application using the research iPads.33 The PI or RAs entered the study name, study group, and subject ID (for example, ICU01031722).33 After the handoff was completed, the RN participant completed the NASA TLX on the research iPad in a private location of their choosing. Furthermore, demographic information for each participant was collected prior to the completion of the NASA TLX. As an expression of gratitude and compen- sation for their time and involvement, all participants were offered a $25 Visa gift card. This procedure was followed with each dyad until the data collection phase was con- cluded. The data were collected over a 4-month period.

Data Management The data from each completed online questionnaire were downloaded as a CSV file to the PI's password-protected laptop for additional data processing. Upon completion of the study, all data on the iPad app were deleted, and all NASA TLX data were transferred to the PI's secured institution-provided and managed Box drive (secure cloud storage with user and password-controlled access).

Data Analysis The demographic and NASA TLX data were analyzed using IBM SPSS Statistics (version 28; IBM Inc., Armonk, NY, USA) and R (version 4.3.1; R Foundation for Statistical Computing, Vienna, Austria). The demographic data were analyzed and evaluated using descriptive statistics. To exam- ine whether and how the two factors (patient-nurse ratio and patient acuity level) and NASA TLX subscales differentiate between the roles of the nurses (sender vs receiver), Fisher ex- act test was used. This test explored the association between the role and categorical variables (eg, different units). The Wilcoxon rank sum test compared the means between the two roles, given the relatively small sample size. To explore how the factors (patient-nurse ratio and patient acuity level) are associated with the NASA TLX subscales and test whether these associations differ by the role of nurses, linear

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Table 1. Demographics

Characteristics n Percentage

Unit All units 41 ICU 18 Trauma-step down 12 Medical-surgical 11

Sex Female 33 80.5 Male 8 19.5

Ethnicity White 31 75.6 Black 10 24.4

Years of experience nursing All units (mean) 5.51 ICU (mean) 4.99 Trauma-step down (mean) 1.24 Medical-surgical (mean) 10.35

Years of experience on unit All units (mean) 2.44 ICU (mean) 4.41 Trauma-step down (mean) 1.09 Medical-surgical 1.81

Educational level ADN 11 26.8 BSN 26 63.4 MSN 4 9.8

FEATURE ARTICLE

regression models were used. Initially, these models tested for any interaction effect between the role of nurses and the factors (patient-nurse ratio and patient acuity level); how- ever, no interaction effect was found to be significant. Subse- quently, separate linear regression models were run for each NASA TLX subscale as the outcome variable, with the fac- tors (patient-nurse ratio and patient acuity level) as predic- tors, controlling for the role of the nurses.

Table 2. Role During Handoffs

Variables Overall (N = 41)a Sender (n = 20

Unit Step-down trauma unit 12 (29%) 6 (30%) CICU 19 (46%) 9 (45%) Medical-surgical unit 10 (24%) 5 (25%)

Mental demand 47 (22) 45 (22) Physical demand 25 (22) 18 (18) Temporal demand 41 (25) 35 (22) Performance 18 (13) 17 (9) Effort 53 (23) 55 (25) Frustration 23 (22) 22 (18) an (%) for categorical variables; M (SD) for continuous variables. bFisher exact test for categorical variables; Wilcoxon rank sum test for continu cCramer V for categorical variables; Cohen's d for continuous variables.

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RESULTS Demographics The total sample size was 41 RNs/20 handoff dyads with the following breakdown from each unit: CICU (n = 18), step- down trauma (n = 12), and medical-surgical (n = 11). The sample consisted of 80.5% female nurses. A majority of the sample were White non-Hispanic (75.6%). The highest edu- cation level of the participants was a BSN (63.4%). The mean number of years of experience of the participants was 5.51. The mean number of years of experience on the unit was 2.44. Table 1 provides a detailed breakdown of the demographics.

Roles No statistical significance (P> .05) was found between different roles of handoffs regarding the unit type (CICU, step-down trauma, and medical-surgical) and the six NASA TLX sub- scales. However, receivers perceived a higher average physical demand (31 vs 18) with a modest P value (P = .055) and a me- dium effect size (Cohen's d = 0.63; Table 2).

Workload and Cognitive Load Among the Three Units The results show that most of the NASA TLX subscales do not differ by different units, after controlling for the nurses' roles. However, the average mental demand is statistically significantly different among the three units after controlling for the nurses' roles, as does the average performance. Table 3 provides the mean scores for mental demand, per- formance, and frustration level. Specifically, there are no sig- nificant differences in the average mental demand between the CICU (low patient-nurse ratios and high acuity) and step-down trauma (medium patient-nurse ratios and medium acuity) units (P= .98), but medical-surgical (high patient-nurse ratios and low acuity) units exhibit significantly higher mental demand than the rest (P = .01, CICU vs medical-surgical

)a Receiver (n = 21)a Pb Effect Sizec

>0.99 0.03 6 (29%)

10 (48%) 5 (24%)

49 (23) 0.55 0.16 31 (24) 0.055 0.63 47 (27) 0.18 0.48 19 (17) 0.99 0.12 52 (21) 0.56 0.09 24 (25) 0.78 0.06

ous variables.

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Table 3. NASA TLX Mean Scores

Units Mental Demand

Frustration Level Performance

ICU 41.32 15.26 14.21 Trauma-step down

40 35 27.5

Medical- surgical

65.5 23 13

Abbreviation: CICU, cardiovascular ICU.

difference 24.29 [7.87], step-down trauma vsmedical-surgical difference 25.50 [8.63]). Note that the P values are obtained after multiple testing adjustments by the Tukey method. The performance subscale showed no difference between the CICU (low patient-nurse ratio and high acuity) and medical-surgical (high patient-nurse ratio and low acuity) units (P = .96). However, the step-down trauma (medium patient-nurse ratio and medium acuity) unit has significantly higher mean performance loads than the other two units (P = .01, step-down trauma vs CICU difference 13.34 [4.46]; P = .02, step-down trauma vs medical-surgical differ- ence 14.50 [5.18]).

In summary, the medical-surgical unit has significantly higher mental demand workload, whereas the step-down trauma unit has significantly higher performance loads. These differences highlight the unique demands and chal- lenges faced by each unit type. The estimated means of the mental demand and performance for each unit are summa- rized in Table 2.

DISCUSSION The present study investigated the variance in perceived workload and cognitive load across three different hospital units: medical-surgical, ICU (CICU), and step-down trauma, with a focus on the handoff process. The research sought to uncover the perceived workload and cognitive load experi- enced during the handoff, with a specific emphasis on how the units with different patient-to-nurse ratios and patient acu- ity levels may influence these dynamics, including the roles of the sender and receiver.

The study observed no significant differences in temporal demand and effort across the units, suggesting that the time constraints and physical exertions associated with handoffs are perceived consistently, regardless of the unit type. This indicates that the duration and physical strain of handoff procedures are perceived similarly across departments. Fur- thermore, it suggests that the processes and time allocations for handoffs are fairly standardized across the different units.

A significant divergence emerged in the mental demand aspect of the NASA TLX, with medical-surgical units experiencing a notably higher cognitive load (M = 65.5)

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compared with CICU and step-down trauma units. This finding aligns with the complex nature of medical-surgical units where staff may deal with a higher patient-nurse ratio and a greater variety of patient conditions, leading to an in- creased demand on the nurse's mental and cognitive process- ing.34 The differences in mental demand between medical- surgical and step-down trauma, as well as medical-surgical and CICU, underscore the potential influence of higher patient-to-nurse ratios on workload demands and cognitive load on the nurse. Intriguingly, this finding is further rein- forced by the lack of significant variation in mental demand between the CICU and the step-down trauma unit, despite the higher levels of patient acuity. The nurse-patient ratios for these units were one RN to two patients in the CICU, one RN to three to four patients in the step-down unit com- pared with one RN to six to seven patients in the medical- surgical unit. The significant discrepancies between medical- surgical and the other two units underscore the need for targeted strategies to manage cognitive load in the medical- surgical settings, possibly by adding nursing staff or shifting the RNs' workload to other healthcare workers. The conse- quences of increased patient-to-nurse ratios, as reported by others, include cognitive overload, burnout, communication errors, and adverse patient outcomes.16,18

Surprisingly, the study found no significant disparities in frustration levels among the units. The step-down trauma unit experienced the highest levels (M = 35), followed by medical-surgical (M = 23) and CICU (M = 15.26), yet these differences were not statistically significant. This finding was unexpected given the assumption that higher patient-to- nurse ratios and varying patient acuity levels would lead to higher frustration levels, particularly in less experienced nurses. Based on the demographics of this sample, the step- down trauma unit has a higher acuity level than the medical- surgical unit and a higher patient-nurse ratio than the CICU while also being on average the least experienced. It was an- ticipated that the combination of these factors would result in significant differences in frustration, reflecting the addi- tional cognitive and emotional stressors faced by nurses in units with higher patient loads and complexity. The lack of significant variation suggests that factors other than patient-to-nurse ratios and acuity levels, such as team dy- namics, support systems, and individual coping mecha- nisms, might play a critical role in mitigating frustration across different units. Moreover, it may indicate that nurses, regardless of unit, have developed effective strate- gies to manage their workload and maintain a consistent level of frustration.13,19

Furthermore, the study did not find significant differences between the roles of the sender and receiver in the handoff process, indicating that the cognitive load and workload are perceived similarly regardless of whether the nurse is

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FEATURE ARTICLE

giving or receiving the handoff. This finding is important be- cause it highlights that interventions aimed at reducing cog- nitive load during handoffs should be holistic and universal, addressing the needs of both senders and receivers equally. Because there is no significant difference in the perceived cognitive load between the roles, interventions should focus on the overall handoff process to ensure that both roles are supported.

LIMITATIONS Although providing valuable insights into nurse-to-nurse handoff communications and associated workload, this study is subject to several limitations that merit consideration. The potential bias in this study primarily relates to the single- center nature of the research and the sample selection method. First, the research design was descriptive and quan- titative, which, although beneficial for identifying statistical relationships, does not allow for the exploration of causality. The setting of the study in a single, major medical facility in the southeastern United States may also constrain the gener- alizability of the results. The facility's specific operational practices, cultural context, and patient demographics might differ significantly from those of other regions or institutions. The sample size of 20 handoff dyads/41 RNs is relatively small. A larger sample size could provide amore robust anal- ysis and a more reliable representation of the nurse popula- tion. In addition, the study did not assess the nurses' baseline comfort level with clinical events, which could influence their perceived workload and frustration levels. To mitigate po- tential bias and enhance the robustness of the findings, future research should address these limitations through methodo- logical diversification, larger and more varied samples, and multisite studies to enhance the external validity and applica- bility of the results.

IMPLICATIONS FOR PRACTICE AND RESEARCH Implications for Practice Given the observed differences in mental demand across units, with medical-surgical units showing higher cognitive load compared with ICU and step-down trauma units, sev- eral key points should be considered by healthcare adminis- trators and policymakers. We recommend focusing research and practice efforts on workload management, standardiza- tion of handoffs, and cognitive load reduction. For instance, standardized handoff tools and training programs should be designed to enhance the efficiency and accuracy of the hand- off process as a whole, ensuring that all nurses are equipped to manage the cognitive demands effectively. Evidence-based strategies to manage workload more effectively include the use of technological tools to augment nurse judgment and re- call, staffing decision tree protocols, and support staff roles.

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Future Research Directions Although we did not find significant differences between sender and receiver roles in the handoff process, our findings do reveal important unit-based differences. Future research should include prospective studies to quantify the impact of varying patient-to-nurse ratios on nurse performance, cogni- tive workload, and patient outcomes. Furthermore, future studies should include larger, more diverse samples across multiple healthcare settings to enhance the generalizability of the findings. Standardization of handoffs should be imple- mented, including formalizing time allocations and proce- dural steps to ensure a consistent approach across all units. In addition, future studies should examine the effects of stan- dardized handoff protocols across different units to under- stand their impact on cognitive load and nurse satisfaction. In addition to standardization and nurse-patient ratios, in- terventions aimed at reducing cognitive load, such as techno- logical cognitive-aid tools, structured communication tools, and training programs, should be further examined.

CONCLUSION The critical nature of handoff communication within nurs- ing practice cannot be overstated, especially given its direct relationship with patient safety and quality of care. This study has underscored the variability in perceived workload and cognitive load among nurses across different acute care units, highlighting the influence of nurse-patient ratios and the complexity of patient conditions on these perceptions. Whereas temporal demands and physical efforts of handoffs appeared consistent across units, the mental demand showed significant variation, with medical-surgical units experienc- ing higher cognitive loads. These findings are a testament to the intricate balance required in nurse staffing and hand- off communication strategies during transitions of patient care. The implications of this study are twofold. For clinical practice, there is a clear need for targeted strategies to man- age cognitive load, particularly in units with higher patient- to-nurse ratios. For research, these results highlight areas for further investigation, such as the development and imple- mentation of technological interventions aimed at optimiz- ing handoff processes and evaluating the impact of such in- terventions on patient outcomes.

Healthcare facilities recognize the consequences of cogni- tive overload, such as burnout and communication errors, and take definitive action to address these issues. The devel- opment of standardized handoff tools and the incorporation of technological aids could serve as viable solutions to miti- gate the risk of errors and enhance the overall well-being of nurses. In summary, the findings of this study contribute valuable insight into the ongoing efforts to improve handoff communications in nursing. By continuing to refine our un- derstanding of the factors affecting handoff quality, the

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healthcare industry can make strides toward reducing medi- cal errors and ensuring high standards of patient care.

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