Prevalence of mobile device use among healthcare providers in the operating theatres: Perceptions and distractions





Highlights




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    Specialists experienced significantly more distractions than technicians, particularly from mobile phone use such as calls, gaming, and media viewing, and from loud music.


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    In contrast, residents and technicians showed minimal differences in distraction levels, though residents reported slightly more distractions from awake patients.


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    Over 70 % of experts identified mobile phone activities like playing games and watching series as disruptive, indicating a consensus on the negative impact of these distractions on surgical performance.



Abstract


Background


Distractions in the operating theatre can significantly impair surgical performance and patient safety. This study investigates the various sources of distractions, particularly focusing on technological and non-technological factors, and their differential impact across various occupational roles within anesthesiology.


Methods


A cross-sectional study was conducted involving 169 anes- thesiology professionals categorized into three groups: residents, technicians, and specialists. Data were collected via structured questionnaires, capturing both quantitative and qualitative aspects of workplace distractions. Statis- tical analysis included ANOVA, Kruskal-Wallis tests, Pearson’s chi-square test, and multivariate analysis of covariance, adhering to STROBE guide- lines.


Results


The multivariate analysis of covariance revealed significant occupational effects on distraction-related variables (Pillai’s Trace = 0.323, F(32, 298) = 1.80, p = 0.007). Significant findings included higher levels of mobile phone use for texting, gaming, and media consumption among specialists compared to other groups. Texting on the phone (F(2, 163) = 6.37, p = 0.002), playing games on phone (F(2, 163) = 8.39, p < 0.001), and watching movies/series on phone (F(2, 163) = 4.15, p = 0.018) were notably higher among specialists.


Conclusion


The study highlights the need for comprehensive inter- ventions to mitigate the effects of distractions in surgical environments, in- cluding policy formulation for mobile device usage and strategies to improve team dynamics and environmental conditions. Future research should focus on longitudinal assessments to evaluate the effectiveness of interventions and explore the broader implications across different healthcare settings.


1


Introduction


Human factors (HF) are universally recognized as pivotal in ensuring the safe delivery of healthcare. Research across numerous studies underscores the negative impact of interruptions and distractions on anesthetic and surgical performance, as well as on the cohesion and effectiveness of team dynamics in the operating theater. Mobile phones, while beneficial for communication and information access, can also introduce significant distractions that may compromise both patient safety and the quality of care.


Distractions in the operating room (OR) have profound implications for patient safety, the efficiency of surgical procedures, and the overall performance of surgical teams. These disruptions arise from diverse sources such as environmental noise, equipment malfunctions, and the use of personal electronic devices, each capable of shifting focus away from critical tasks. This shift can increase the risk of errors and extend the duration of surgeries.


Various elements contribute to distractions in the OR, including patient care activities, technological interactions, ambient noise, frequent alarms, interpersonal dynamics, and individual behaviors. According to Riutort, these distractions play a role in approximately 5 % of the human factor errors in the OR. Common distractions encompass loud background noises, casual conversations, usage of phones and pagers, and frequent staff movements in and out of the OR. These factors are not only disruptive but also directly linked to critical operational inefficiencies, potentially leading to significant miscommunication among surgical team members, decreased vigilance, and delayed responses to non-routine events, all crucial for maintaining patient safety.


Distractions in clinical environments can severely impair decision-making and prolong task completion times. For instance, a study by Murji et al. demonstrated that pager distractions during simulated surgeries significantly increased the incidence of unsafe clinical decisions and adversely affected task completion times. Additionally, distractions in the OR are linked to increased mental workload and stress, as well as diminished team- work among medical personnel. Notably, distractions stemming from case- irrelevant conversations and equipment issues were found to particularly af- fect teamwork dynamics and elevate stress levels, highlighting critical areas for operational improvements. In addition to impacting surgical safety and efficiency, the general public often views the use of mobile devices by healthcare providers as unprofessional and distracting, negatively impacting their perception of the providers’ empathy and profes-sionalism.


This interplay of distractions necessitates comprehensive understanding and strategic interventions to mitigate their adverse effects and enhance the quality of care in surgical environments. Our aim is to thoroughly understand the range of opinions on these distractions, identify their perceived sources and impacts, and potentially help to explore strategies that could mitigate their effects in surgical environments.


2


Materials and methods


This study adhered to the ethical principles outlined in the Declaration of Helsinki. Approval was granted by the Sanko University Clinical Research Ethics Committee on June 8, 2023 (Approval No: …). We conducted our research in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines to ensure robust and transparent reporting of results.


2.1


Study design


This cross-sectional study was designed to investigate the possible en- vironmental distractions on the performance of anesthesiology professionals during surgical procedures.


2.2


Data collection


Data were collected using structured questionnaires, designed to capture both quantitative and qualitative aspects of workplace distractions.


2.3


Study participants


Participants included 169 anesthesiology professionals categorized into three groups: 19 residents, 97 technicians, and 53 specialists.


2.4


Statistical methods


Descriptive Statistics Continuous variables were summarized using medians and 25th – 75th percentiles to describe the distribution. Categorical variables were presented as frequencies and percentages. These descriptive statistics provided an initial overview of the data across the three professional groups: residents, technicians, and specialists. We opted to report median and 25th – 75th percentiles for continuous variables upon identifying non-normal distributions through exploratory data analysis. This decision was corroborated by Shapiro-Wilk tests and visual assessments using histograms and Q-Q plots. These evidences confirm that the median and percentiles offer a more reliable representation of central tendency and dispersion in our data than mean and standard deviation.


Comparison of Groups For normally distributed continuous variables, ANOVA was employed to assess differences among the occupational groups. For variables not meeting the assumptions of normality, the Kruskal- Wallis test, a nonparametric equivalent to ANOVA, was utilized. Categorical data were analyzed using Pearson’s chi-square test, or Fisher’s exact test when expected frequencies were low, to compare proportions across groups.


Covariate Analysis Potential covariates including age, civil status, number of children, and work experience were initially evaluated for their association with the dependent variables. Covariates that demonstrated sig- nificant associations or substantially altered the relationships between the primary variables and outcomes were retained in the final models.


Multivariate Analysis To facilitate the analysis, we created two composite variables by combining related items from the questionnaire. Digital Engagement was constructed by aggregating the following variables: phoneTexting, phoneGame, phoneCall, phoneFormalOrAccount , and phoneMoviesSeries . This composite measure represents the overall level of participants’ engagement with digital activities. Similarly, Work-Related Stress was formed by combining the variables: listToLoudMusic, crowdedOpTheatre, chatOrArguments, paperworks, impendingChallengProcedureAnx, academicPreparation, sleepDepDueToWork, teamDiscord , and awakePatient . This composite reflects the participants’ overall experience of stress related to their work environment. The items were combined by calculating the mean score for each composite variable, ensuring that all components contributed equally to the overall measure. These composite variables were then used in the subsequent MANCOVA to assess the effects of occupation and work years on digital engagement and work-related stress. This was followed by univariate ANOVAs to explore the effects of occupation on individual dependent variables, providing a detailed insight into specific influences.


Adjustment for Multiple Comparisons To control for the risk of Type I errors due to multiple comparisons, a Bonferroni correction was ap- plied, adjusting the significance levels for the number of tests conducted. For the first question with six multiple-choice options, the adjusted significance level was set at approximately 0.0083 (0.05/6). For the second question with three options, the adjusted significance level was approximately 0.0167 (0.05/3). Only p-values below these adjusted thresholds were considered statistically significant in our analyses.


All statistical analyses were performed using R software version 3.6.0 and python. The pandas library was utilized for data manipulation, numpy for numerical calculations, and matplotlib for generating visualizations. These visualizations were further enhanced using the SciencePlots package to ensure clarity. LATEX was employed for typesetting the manuscript.


3


Results


3.1


Demographics and characteristics of participants


Detailed demographic and professional characteristics, along with statis- tical comparisons, are provided in Table 1 . The table highlights significant differences among the groups in terms of age, partner status, work experience, and number of children, with all p -values < 0.001.


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May 22, 2025 | Posted by in ANESTHESIA | Comments Off on Prevalence of mobile device use among healthcare providers in the operating theatres: Perceptions and distractions

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