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Learn more: PMC Disclaimer | PMC Copyright Notice J Adv Nurs . 2025 Aug 3;82(5):4506–4523. doi: 10.1111/jan.70110 Search in PMC Search in PubMed View in NLM Catalog Add to search Conducting Eye‐Tracking Research in Acute Care: A Scoping Review of Ethical, Feasibility and Acceptability Challenges Patrick Lavoie Patrick Lavoie 1 Faculty of Nursing, Université de Montréal, Montreal, Quebec, Canada 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Patrick Lavoie 1, 2, ✉ , Amélie Doherty Amélie Doherty 3 Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada Find articles by Amélie Doherty 3 , Lysanne Pariseau Lysanne Pariseau 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Lysanne Pariseau 2 , Julie Allard Julie Allard 4 Centre de Recherche du CHUM, Montreal, Quebec, Canada Find articles by Julie Allard 4 , Élodie Petit Élodie Petit 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Élodie Petit 2 , Delphine Roigt Delphine Roigt 5 Independent Ethical and Legal Advisor Find articles by Delphine Roigt 5 , Sophia Merisier Sophia Merisier 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Sophia Merisier 2 , Maude Crétaz Maude Crétaz 1 Faculty of Nursing, Université de Montréal, Montreal, Quebec, Canada 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Maude Crétaz 1, 2 , Imène Khetir Imène Khetir 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Imène Khetir 2 , Tanya Mailhot Tanya Mailhot 1 Faculty of Nursing, Université de Montréal, Montreal, Quebec, Canada 2 Montreal Heart Institute, Montreal, Quebec, Canada Find articles by Tanya Mailhot 1, 2 Author information Article notes Copyright and License information 1 Faculty of Nursing, Université de Montréal, Montreal, Quebec, Canada 2 Montreal Heart Institute, Montreal, Quebec, Canada 3 Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada 4 Centre de Recherche du CHUM, Montreal, Quebec, Canada 5 Independent Ethical and Legal Advisor * Correspondence: Patrick Lavoie ( [email protected] ) ✉ Corresponding author. Revised 2025 Jun 26; Received 2025 Apr 28; Accepted 2025 Jul 23; Issue date 2026 May. © 2025 The Author(s). Journal of Advanced Nursing published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. PMC Copyright notice PMCID: PMC13069235 PMID: 40755071 ABSTRACT Aim To identify and synthesise the ethical, feasibility and acceptability challenges associated with implementing eye‐tracking research with clinicians in acute care settings and to explore strategies to address these concerns. Design Scoping review using the Joanna Briggs Institute methodology. Data Sources Six databases (MEDLINE, CINAHL, EMBASE, Web of Science, APA PsycInfo and ProQuest Dissertations & Theses Global) were searched for peer‐reviewed articles. Reference lists of included studies were also hand‐searched. Methods Eligible studies involved clinicians using or interacting with eye‐tracking devices in acute care environments and addressed at least one ethical, feasibility, or acceptability consideration. Data were extracted and thematically analysed. Knowledge users, including clinicians, ethicists and a patient partner, were engaged during protocol development and findings synthesis. Results Twenty‐five studies published from 2010 to 2024 were included. Seven challenges were identified: obtaining ethical approval, managing consent, privacy and confidentiality concerns, collecting data in unpredictable environments, interference with care, participant comfort and data loss or unreliability. Knowledge users highlighted the importance of early institutional engagement, clear protocols, continuous consent and context‐sensitive ethical reflection. Conclusions Eye‐tracking offers valuable insights into clinician behaviour and cognition, but its implementation in acute care raises complex ethical and methodological issues. Responsible use requires anticipatory planning, stakeholder engagement and flexible yet rigorous protocols. Implications for the Profession and/or Patient Care By informing the development of ethically sound study protocols and consent practices, this work contributes to safer, more transparent and patient‐centred research that respects participant autonomy and protects clinical workflows. Registration The protocol was registered with the Open Science Framework ( https://osf.io/jn4yx ). Reporting Method Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA; Page et al., 2021) and its Extension for Scoping Reviews (Tricco et al., 2018). Patient and Public Contribution A patient partner was involved in protocol development, interpretation of findings and development of study recommendations. Their contributions included participating in advisory groups and providing feedback alongside clinicians and ethicists during focus groups. This input helped ensure the research addressed patient‐relevant priorities and informed the development of ethically responsible practices for conducting eye‐tracking research in clinical care settings. Keywords: acute care, ethics, eye movement measurement, eye‐tracking technology, feasibility studies, informed consent, research Summary. What problem did the review address? ○ This review addressed the ethical, feasibility and acceptability challenges of conducting eye‐tracking research with clinicians in acute care settings. ○ Despite growing interest in using eye‐tracking to understand clinical decision‐making, little guidance exists on navigating its ethical and logistical complexities in real‐world environments. What were the main findings? ○ The review identified seven challenges: obtaining ethical approval, managing consent, privacy and confidentiality concerns, collecting data in unpredictable environments, interference with care, participant comfort and data loss or unreliability. ○ Engaging knowledge users revealed that addressing these challenges requires early institutional buy‐in, continuous ethical reflection and context‐sensitive protocols. Where and on whom will the research have an impact? ○ This research will inform nursing and healthcare researchers, ethics committees and educators planning to integrate eye‐tracking into clinical studies. ○ Reflection points and recommended practices are proposed to support researchers in addressing these challenges to develop ethically responsible and methodologically feasible research protocols in acute care environments. What does this paper contribute to the wider global clinical community? ○ Provides the first comprehensive synthesis of ethical, feasibility and acceptability challenges specific to eye‐tracking research in acute care, offering guidance applicable across diverse healthcare systems. ○ Introduces practical, stakeholder‐informed strategies—inclusive of consent, data governance and workflow integration considerations—that can be adapted to various institutional and regulatory contexts. ○ Supports global research efforts to use eye‐tracking to improve clinician training, patient safety and decision‐making by promoting ethically sound and context‐sensitive implementation in real‐world clinical environments. 1. Introduction Eye‐tracking, a technology that records and analyses eye movements to determine where, when and how individuals direct their gaze, has emerged as a powerful tool to investigate visual attention, cognitive load and decision‐making across various fields. It captures a range of oculomotor metrics, including gaze fixation points, fixation duration, saccadic movements, blink rate and pupil dilatation—all of which offer insight into how individuals process information, shift attention and manage task demands. In healthcare, these measurements help researchers understand patterns of visual attention during complex procedures, identify cognitive overload and assess situational awareness. In nursing, eye‐tracking has been used to study clinical reasoning, task performance and expertise development in simulated and real‐world settings (Hu et al. 2024 ). Its ability to produce objective, real‐time data on visual behaviour shows promise for advancing education, assessment and feedback practices for novice and experienced clinicians (Ashraf et al. 2018 ; Hu et al. 2024 ). Moreover, eye‐tracking can support workflow analysis, optimise training environments and inform the design of decision support tools, thereby contributing to both research methodology and improvements in care delivery (Fong et al. 2016 ; Visweswaran et al. 2021 ). Initially limited to stationary configurations requiring fixed head positioning, eye‐tracking has evolved with the development of mobile systems that permit head and body movement. Modern mobile eye‐tracking glasses combine field‐of‐view video with pupil tracking, enabling visual behaviour to be captured in clinical environments. These advances offer opportunities to understand how clinicians allocate visual attention during patient care and may enhance education, decision‐making and interprofessional collaboration in acute care (Bapna et al. 2023 ; Hu et al. 2024 ). Despite its potential, integrating eye‐tracking into clinical environments presents substantial ethical, feasibility and acceptability challenges. One major concern is privacy, as the technology records ambient visual and audio data, potentially capturing sensitive patient information and raising data protection concerns (Larsen et al. 2020 ). Beyond documenting routine clinical actions, there is a risk of inadvertently recording errors, complications, or adverse events—scenarios that may carry medico‐legal implications if such footage is later used in investigations or legal proceedings. These concerns are particularly problematic in dynamic acute care settings, where obtaining prospective informed consent from all individuals appearing in the recordings may be impractical. From a feasibility standpoint, challenges include calibration difficulties, variable lighting conditions, motion‐related data loss and user discomfort (Klausen et al. 2016 ). Additionally, patients and clinicians may feel uneasy about surveillance or potential misuse of recorded data, which can impact participation and data quality. Questions also remain about the future use of eye‐tracking data—such as secondary analyses, integration into artificial intelligence systems, or commercialization—that may extend beyond the scope of initial consent. A previous systematic review focused on eye‐tracking feasibility in critical care, including anaesthesia, surgery and intensive care, identified only three studies conducted in real‐world clinical settings, with limited discussion of ethical and feasibility issues (Klausen et al. 2016 ). More recent studies, particularly from the United States, have highlighted ethical risks such as incidental capture of protected health information, challenges in securing informed consent and potential institutional liability (Larsen et al. 2020 ). However, a significant gap remains in understanding how these challenges manifest and are addressed across varying ethical and regulatory contexts, including but not limited to Canada. Canadian research is governed by the Tri‐Council Policy Statement 2 ( 2022 ) and provincial frameworks. Internationally, parallel issues are addressed by the European Union's General Data Protection Regulation and the United States Common Rule (45 CFR 46) . Notably, no studies have actively engaged stakeholders, such as clinicians, ethicists and patient partners, to identify feasible, context‐sensitive solutions to support the ethical and practical integration of eye‐tracking technologies in clinical settings. 1.1. Aims Given the increasing interest in using eye‐tracking to explore clinician cognition and perception in nursing and healthcare research (Hu et al. 2024 ), this scoping review aimed to (1) identify the ethical, feasibility and acceptability challenges associated with the use of eye‐tracking in acute care settings; and (2) examine potential solutions to address these challenges. By mapping these challenges and solutions, this review seeks to inform future nursing research and guide the responsible, ethically sound and practically feasible integration of eye‐tracking in clinical care environments. 2. Methods This scoping review was conducted following the Joanna Briggs Institute methodology (Peters et al. 2020 ) and is reported according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA; Page et al. 2021 ) and its Extension for Scoping Reviews (Tricco et al. 2018 ). The protocol was registered with the Open Science Framework ( https://osf.io/jn4yx ). The review was initially conceptualised as a systematic review of reasons (Strech and Sofaer 2012 ) to analyse ethical arguments regarding eye‐tracking use in clinical settings. However, as the review progressed, it became clear that the existing literature did not present arguments for or against eye‐tracking research. Instead, it primarily described implementation processes and the challenges encountered. Consequently, the methodology was adapted to a scoping review, which was better suited to mapping the field, exploring how research has been conducted, and identifying key factors shaping its ethicality, feasibility and acceptability (Munn et al. 2018 ). 2.1. Knowledge User Engagement In line with integrated knowledge translation principles, knowledge users were involved in protocol development and findings synthesis (Pollock et al. 2022 ). During protocol development, we consulted a nurse educator and a clinical ethicist, who had previously collaborated with the research team—one through prior eye‐tracking research (Lavoie et al. 2023 , 2024 ) and the other as an institutional ethics advisor. Their input informed the refinement of the study objectives and inclusion criteria. During synthesis, preliminary findings were presented in two 60‐min focus groups involving the initial two advisors, along with a patient partner with legal expertise, a nurse manager and two additional clinical ethicists. These sessions served to contextualise and refine the findings within the Canadian healthcare and regulatory environment. Participants contributed to the interpretation of findings and were involved in drafting the results and discussion. All were acknowledged as co‐authors and were offered compensation for their involvement. 2.2. Search Methods Relevant keywords and Medical Subject Headings (MeSH) were identified based on three conceptual domains: clinicians and patients (population), eye‐tracking research (concept) and acute care environments (context). Initial terms were derived from a preliminary scan of MEDLINE (Ovid) and CINAHL Complete (EBSCOHost) and iteratively refined to optimise sensitivity and specificity (Bramer et al. 2018 ). The final strategy (Appendix S1 ) was developed for MEDLINE (Ovid) and adapted for CINAHL Complete (EBSCOHost), EMBASE (Ovid), Web of Science (Clarivate), APA PsycInfo (Ovid) and ProQuest Dissertation & Theses Global. Reference lists of included studies were also hand searched to identify additional eligible publications. 2.3. Inclusion and Exclusion Criteria Studies were included if they involved clinicians or students wearing or interacting with eye‐tracking devices in acute care settings, including hospitals, inpatient units and operating theatres. Although the original intent was to include patient data, most patient‐focused studies related to diagnostic or therapeutic monitoring, particularly in neurological or psychiatric contexts. Given the distinct ethical considerations in those populations, such studies were excluded. Studies conducted in non‐acute settings (e.g., home care, outpatient clinics), educational environments (e.g., simulations, skills labs, VR/AR), or using highly controlled tasks (e.g., image analysis without patient interaction) were excluded. Only studies that explicitly addressed at least one of the following—ethical, feasibility, or acceptability challenges—in relation to eye‐tracking research were included. All empirical study designs, including dissertations and theses, were eligible. Reviews, conference abstracts, editorials and opinion pieces were excluded. Studies were included if published in English or French, with no date restrictions. Where multiple publications reported on the same study, the most comprehensive source was retained. 2.4. Study Selection All records were imported into Covidence (Veritas Health Innovation). Two reviewers independently conducted a pilot screening of 100 titles and abstracts to refine the inclusion and exclusion criteria. Titles and abstracts were then screened independently and in duplicate. Full‐text articles were retrieved for all potentially relevant studies and reviewed independently by two reviewers. Disagreements were resolved through discussion, with arbitration by a third reviewer when needed. 2.5. Data Extraction Data were extracted using MAXQDA 2024 (VERBI GmbH). A custom data extraction form was developed, piloted on five studies by two independent reviewers, and refined before extraction. Extracted data included: (a) general characteristics: year, country, study design and objectives; (b) population characteristics: discipline and sample size; (c) eye‐tracking attributes: device, setting, type of data collected and length of data analysed; and (d) ethical, feasibility, or acceptability challenges and any proposed solutions. Both explicit and inferred challenges were coded, including those directly experienced by researchers and those discussed as potential risks. One reviewer conducted the initial extraction, which was verified by a second and reviewed for accuracy and completeness by a third. In keeping with the objectives of scoping reviews, a quality appraisal was not conducted, as the aim was to map challenges rather than assess the methodological rigour of individual studies (Peters et al. 2020 ). 2.6. Data Synthesis The synthesis drew on the systematic review of reasons methodology (Strech and Sofaer 2012 ), in which a “reason” is defined as an explicit or implicit rationale supporting or opposing a particular position. While the review did not yield fully developed arguments, this framework was used to structure the analysis of reported challenges and solutions. All relevant excerpts were coded into broad and narrow categories (e.g., the narrow issue “medication errors” was nested under the broader category “interference with patient care”). Solutions were linked to the corresponding challenge, whether directly or inferentially stated by the authors. When a solution was presented without a challenge, we sought to infer the underlying issue, even if it was not explicitly stated (e.g., securing the eye‐tracking equipment to avoid movement‐related calibration issues). The research team iteratively refined this coding structure until a consensus was reached. The final framework was then reviewed with knowledge users to validate and contextualise the findings. A narrative synthesis follows, describing the most frequently reported challenges, integrating insights from the stakeholder focus groups and quantifying the number of studies referencing each issue. 3. Results The search, conducted in March 2025, identified 2741 potentially relevant records. After removing duplicates, 2536 records remained for title and abstract screening, leading to the full‐text assessment of 171 articles. Of these, 21 met the inclusion criteria. An additional four (4) studies were identified through citation searching, resulting in a final sample of 25 studies (Figure 1 ). FIGURE 1. Open in a new tab Flow diagram of study selection. 3.1. Study Characteristics Table 1 provides an overview of the included studies, with further details in Table 2 . Most studies ( n = 15, 60%) were published after 2020 and originated from Europe ( n = 11, 44%) or North America ( n = 9, 36%). Observational designs predominated ( n = 22, 88%), with sample sizes ranging from 1 to 62 (median = 12). Medical professionals were the most frequently studied population ( n = 11, 44%), followed by nurses and health care assistants ( n = 9, 36%). Most studies were conducted in operating rooms ( n = 8, 32%) or intensive care units ( n = 7, 28%). TABLE 1. Study characteristics. Characteristics Total ( n = 25) Country Europe 11 (44%) North America 9 (36%) Asia 2 (8%) Australia 1 (4%) South America 1 (4%) Multi‐site 1 (4%) Design Observational 22 (88%) Randomised controlled trial 1 (4%) Qualitative 1 (4%) Sample size, median (range) 12 (1–62) Profession Physicians and surgeons 11 (44%) Nurse and health care assistants 9 (26%) Perfusionists 3 (12%) Various 2 (8%) Data collection settings Operating room 8 (32%) Intensive care unit 7 (28%) Emergency room 4 (16%) Neonatal intensive care unit 3 (12%) Delivery room 2 (8%) Acute care unit 1 (4%) Type of eye‐tracking device Glasses 24 (96%) Computer based 1 (4%) Recording length Procedure‐based 18 (72%) Shift‐based 5 (20%) Time‐based 2 (8%) Data analysed Full dataset 12 (48%) Event‐based 10 (40%) AOI‐based 2 (8%) Not reported 1 (4%) Open in a new tab TABLE 2. Detailed study characteristics. Reference Country Design Purpose Participants ( n ) Setting Device Data recorded Data analysed 1 IRB approval Consent Challenges Ahmadi et al. ( 2022 ) United States Observational Explore nurses' workload using fixational, saccadic and pupillary responses Registered nurses ( n = 21) Cardiovascular ICU Glasses 21 shifts, 12 h each Full dataset (15 recordings; 252 h) IRB approval Written consent (nurses) Environmental unpredictability Interference with patient care Participant's comfort Data loss or unreliable data Afkari and Bednarik ( 2023 ) Luxembourg Observational Understand how scrub nurses maintain situational awareness during surgeries with a surgical microscope Assisting scrub nurse ( n = 1) Operating room Glasses One tumour removal surgery, 90 min Full dataset (90 min, 1 recording) IRB approval Written consent (nurse, operating room team members); no patient data collected Environmental unpredictability Interference with patient care Participant's comfort Borten et al. ( 2024 ) Brazil Observational Evaluate the gaze patterns and pain perception of adults assessing critically ill neonates and examine differences in gaze behaviour based on the presence of pain Paediatricians ( n = 21), nurses ( n = 23); Additionally, 18 parents wore eye‐tracking devices . Neonatal ICU Glasses 44 pain evaluations, 20 s each Full dataset (44 recordings) IRB approval Written consent (paediatrician, nurses, parents of the observed infant) Data loss or unreliable data Buehler et al. ( 2021 ) Switzerland Observational Examine visual patterns during central venous catheter insertion and investigate differences in gaze patterns between more and less experienced trainees ICU trainee doctors ( n = 18) ICU Glasses 18 central venous catheter insertions Full dataset (18 recordings) IRB approval Written consents (physicians, patients or legal representatives) Interference with patient care Data loss or unreliable data Buehler et al. ( 2021 ) Switzerland Observational Analyse gaze patterns during ventilation and compare inexperienced with experienced nurses Nurses ( n = 28) ICU Glasses 28 sessions, 60 min each AOI‐based (respirator interface and ventilator; 28 recordings) IRB approval Written consent (nurses, patients) Environmental unpredictability Interference with patient care Participant's comfort Evans‐Harvey et al. ( 2020 ) United Kingdom Observational Investigate the relationship between surgeons' visual gaze behaviour and technical skill during laparoscopic cholecystectomy Surgeons ( n = 10) Operating room Glasses 17 laparoscopic cholecystectomies Event‐based (3 operative steps; 13 recordings) IRB approval Consent (surgeon, primary assistant, patient) Privacy concerns Environmental unpredictability Data loss or unreliable data Grundgeiger et al. ( 2010 ) Australia Observational Investigate the management and effect of interruptions in intensive care units Nurses ( n = 10) ICU Glasses 10 morning shifts, 4 h each Event‐based (9 morning shifts, 1644 min) IRB approval Written consent (nurses, patients' next of kin) Environmental unpredictability Participant's comfort Data loss or unreliable data Grundgeiger et al. ( 2017 ) Germany Observational Investigate the effects of simulated vs. real cases and experience on visual attention distribution during general anaesthesia induction Anaesthetists ( n = 24) Operating room Glasses 25 general anaesthesia inductions Full dataset (24 recordings; avg. 11.76 ± 2.86 min) IRB approval Written consent (anaesthetists) Environmental unpredictability Data loss or unreliable data He et al. ( 2014 ) United States Observational Study the impact of interruptions on visual scanning patterns Nurses ( n = 21) Emergency department Glasses 21 medication administration sessions Full dataset (17 recordings) IRB approval Written consent (nurses) Environmental unpredictability Data loss or unreliable data Herrick et al. ( 2020 ) United States and the Netherlands Randomised controlled trial Compare visual attention during delivery room resuscitation with and without a visible respiratory monitor Neonatal resuscitation leaders ( n = 11) Delivery room Glasses 15 neonatal resuscitations Event‐based (first 5 min; 14 recordings) IRB approval Consent (resuscitation leaders) Data loss or unreliable data Hofmaenner et al. ( 2020 ) Switzerland Observational Assess feasibility, usability, and safety of ET for gaze pattern and human‐interface interaction analysis during extubation Physicians ( n = 22) ICU Glasses 22 extubations Full dataset (22 recordings) IRB approval Written consent (physicians, patients or legal representatives) Environmental unpredictability Interference with patient care Participant's comfort Data loss or unreliable data Hofmaenner et al. ( 2021 ) Switzerland Observational Analyse visual attention during routine patient care for invasively ventilated patients Nurses ( n = 30) ICU Glasses 30 × 60‐min sessions Full dataset (28 recordings; 65.6 min avg., 1837 min total) IRB approval Written consent (nurses, patients' legal representatives) Environmental unpredictability Participant's comfort Interference with patient care Data loss or unreliable data Johannessen et al. ( 2020 ) Canada Observational Compare cognitive load rating scale with physiological data from wearable devices in a real clinical setting Expert trauma physicians ( n = 3) Emergency department Glasses 9 trauma resuscitations Full dataset (9 recordings) IRB approval Not reported Environmental unpredictability Interference with patient care Koh et al. ( 2011 ) Singapore Observational Examine differences in scrub nurses' visual attention and task management, with a focus on interruptions during the count task Nurses ( n = 20) Operating room Glasses 20 caesarean section surgeries Full dataset (20 recordings, 2403 s avg) IRB approval Written consent (nurses); consent (surgical team members); verbal consent (patient) Environmental unpredictability Interference with patient care Larsen et al. ( 2020 ) USA Observational Understand triggers of stress, fatigue and burnout through analysis of physiological metrics Nurses ( n = 28) Cardiovascular ICU Glasses 28 × 12‐h shift Not reported IRB approval Written consent (nurses); notification/opt‐out (staff, patients, guests) Privacy concerns Interference with patient care Participant's comfort Data loss or unreliable data Law et al. ( 2018 ) Canada Observational Test ET to examine visual attention during neonatal resuscitation Neonatal fellow ( n = 1), respiratory therapists ( n = 2), neonatal nurse practitioners ( n = 2), neonatal consultants ( n = 1) Neonatal ICU Glasses 6 neonatal resuscitations Event‐based (first 5 min; 5 recordings) IRB approval Written consent (parents); verbal agreement (clinicians) Environmental unpredictability Data loss or unreliable data Law and Schmölzer ( 2020 ) Canada Observational Examine visual attention and team communications during endotracheal intubation Intubators ( n = 17) Neonatal ICU Glasses 27 intubations Full dataset (24 recordings; 365 to 601 s, median 500 s) IRB approval Written consent (intubators); notification/opt‐out (other professionals) Environmental unpredictability Interference with patient care Data loss or unreliable data Nielsona et al. ( 2013 ) United States Observational Determine the time spent by physicians on screen‐based lab results in a live clinical setting Attending physicians ( n = 14) Emergency department Computer‐based 15 × 9.5‐h shifts AOI‐based (lab results; 4–80 events/shift, avg. 21.7 events/shift) Not reported Consent (physicians) Privacy concerns Interference with patient care Data loss or unreliable data Pawelke et al. ( 2022 ) Germany Observational Investigate if a perfusion simulator compares to a real operating room regarding subjective perception and eye movement Perfusionists ( n = 8) Operating room Glasses 8 heart operations Event‐based (operation phases; 4 recordings) IRB waiver Information with dropout option (perfusionists) Environmental unpredictability Data loss or unreliable data Poulsen et al. ( 2021 ) Denmark Observational Explore time spent by hospital personnel dispensing medicine in a drug change situation Nurses ( n = 10) Cardiology ward Glasses 20 shifts (2/participant) Event‐based (drug dispensing; 196 events, 8.6–90 s) IRB waiver Written consent (nurses) Environmental unpredictability Interference with patient care Data loss or unreliable data Tomizawa et al. ( 2012 ) Japan Observational Analyse the eye movements of perfusionists to identify critical information and gaze patterns Perfusionists ( n = 4) Operating room Glasses 4 × 1‐day observations Event‐based (10‐min around extracorporeal circulation start; 4 recordings) Special permission by local stakeholders Not reported Interference with patient care Data loss or unreliable data Vine et al. ( 2014 ) United Kingdom Observational Compare eye movements of surgeons performing simulated and real transurethral resections of the prostate to assess the content validity of a virtual reality simulator Surgeons ( n = 3) Operating room Glasses 15 transurethral resections of the prostate procedures Event‐based (2 min of uninterrupted resection; 15 recordings) IRB approval Written consent (surgeons, patients) Interference with patient care Weinberg et al. ( 2020 ) United States Observational Characterise neonatal team leaders' visual attention during resuscitation and assess differences based on intervention type and training level Neonatal attendings ( n = 6) and fellows ( n = 6) Delivery room Glasses 21 resuscitations Event‐based (first 5 min; 18 recordings) IRB approval Consent (attending, fellows) Data loss or unreliable data White et al. ( 2018 ) Canada Qualitative Understand expert physicians' cognitive processes during trauma resuscitation and assess ET feasibility Trauma team leaders ( n = 4) Emergency trauma bay Glasses 10 trauma resuscitations Full dataset (10 recordings) IRB approval Not reported Environmental unpredictability Interference with patient care Participant's comfort Zimmermann et al. ( 2020 ) Switzerland Observational Investigate expert operators' visual strategies during catheter‐based cardiovascular interventions and compare them to novices Operators ( n = 5) Catheterization laboratory Glasses 33 catheter‐based interventions Event‐based (transseptal puncture; 31 recordings) IRB approval Written consent (surgeons, patients) Environmental unpredictability Interference with patient care Data loss or unreliable data Open in a new tab Note: If this number does not match the total number of recordings, it indicates that some recordings were not analysed or that data were lost. Abbreviations: AOI, area of interest; ET, eye‐tracking; ICU, intensive care unit. 1 The quantity of data analysed reflects any data loss. The most common research focus was gaze patterns and visual attention ( n = 10, 40%). Other studies explored expertise levels ( n = 3, 12%), workload and cognitive load ( n = 2, 8%), feasibility of eye‐tracking ( n = 2, 8%), simulator versus real‐life settings ( n = 2, 8%) and work interruptions ( n = 2, 8%). One study each (4%) investigated gaze‐technical skill relationships, time and motion, technology influence and cognitive processes. Nearly all studies ( n = 24, 96%) used eye‐tracking glasses, with only one (4%) utilising a computer‐based system to determine the time physicians spent reviewing on‐screen laboratory results in a clinical setting (Nielsona et al. 2013 ). Most ( n = 18, 72%) recorded data from the start to the end of a procedure (e.g., extubation, surgery), while others recorded for half or all of a shift ( n = 5, 20%) or a fixed time of approximately 60 min ( n = 2, 8%). Data analysis approaches varied: 12 studies (48%) analysed the entire dataset, 10 (40%) focused on specific events (e.g., the first 5 min of a procedure), and 2 (8%) examined gaze behaviour within designated areas of interest (e.g., ventilators, monitors). Seven challenges were identified across the 25 studies: obtaining Institutional Review Board (IRB) approval, consent processes, privacy concerns, data collection in unpredictable environments, potential interference with patient care, participant comfort, and data loss or unreliability. 3.2. Obtaining IRB Approval Most studies ( n = 21, 84%) reported receiving IRB approval, while two studies (8%) obtained waivers, and one (4%) received approval from local management. One study (4%) did not report on ethical approval. Although IRB approval was commonly reported, the process was often described in limited detail. One exception was the study by Larsen et al. ( 2020 ), which detailed multiple in‐person meetings with the IRB during the early design phase to clarify protocol requirements, including demonstrations of the eye‐tracking equipment and explanations of data collection procedures. Knowledge users expressed surprise that some studies had received IRB exemptions, noting that research involving healthcare professionals often blurs the boundaries between quality improvement and formal research. They emphasised the importance of applying rigorous ethical standards regardless of study classification and advocated for mandatory IRB consultation. Some suggested that the involvement of a bioethicist during the design phase could help anticipate and address potential ethical concerns. Securing IRB approval was viewed as closely linked to institutional feasibility. Knowledge users highlighted the importance of obtaining support from local management and clinical teams to promote study acceptability and facilitate recruitment. They noted that researcher engagement—such as presenting the study to clinical teams and maintaining open communication—was critical to securing local buy‐in, reducing participant attrition and enhancing study feasibility. In one study, Larsen et al. ( 2020 ) discussed the risk of underutilising eye‐tracking data if restricted to a single project, prompting the creation of an IRB‐approved data bank to enable future research using eye‐tracking data. Knowledge users acknowledged the value of such repositories but emphasised the need for clear guidelines on data retention, accessibility and confidentiality. They noted frequent confusion between data banks (designed for broader research use) and databases (created for specific projects). While data banks provide structured long‐term storage, they require significant management and oversight. To balance flexibility with ethical oversight, knowledge users recommended including clauses in consent forms that allow for secondary data use over a defined period before transitioning to a formal repository if needed. This approach offers greater flexibility while still enabling future research opportunities. 3.3. Consent Process Approaches to obtaining consent from participants varied across the included studies. Most studies ( n = 20, 80%) reported securing written consent from clinicians wearing eye‐tracking devices, while one study (4%) relied solely on verbal agreement without signed documentation. Four studies (16%) did not mention their consent procedures. Consent processes for individuals appearing in the clinician's visual field also differed. Thirteen studies (52%) obtained written consent from patients, including legal representatives in cases involving children or individuals unable to consent. One study (4%) used verbal consent from patients, and another (4%) reported that no patient data were recorded. For other clinicians or staff captured in the visual field, four studies (16%) sought written consent—three of which were conducted in operating rooms. Three studies (12%) used notification strategies, such as informing staff, visitors and bystanders of ongoing data collection and offering them the opportunity to opt out or avoid being recorded. Knowledge users strongly endorsed written consent as the standard, particularly for those actively involved in the clinical interaction. They distinguished between active participants—who should provide explicit consent—and incidental figures (e.g., bystanders, visitors, or non‐participating clinicians), who should, at minimum, be informed and allowed to decline participation. Where foreseeable, they advocated for obtaining consent from all individuals entering shared clinical spaces. Consent forms were expected to detail the type of data collected (e.g., audio, video, gaze tracking), data retention periods, storage procedures and any post‐processing of images or recordings. Knowledge users recommended including specific provisions for anticipated events, such as the unplanned entry of individuals during recording, and guidance for managing sensitive content. The importance of continuous consent was emphasised, particularly when unexpected data are captured. Knowledge users stressed the need to create a safe environment where participants can withdraw at any time, request the exclusion of specific segments, or opt‐out without consequence. In situations where unanticipated data are captured, participants should have the opportunity to re‐evaluate their consent. Knowledge users cautioned against relying solely on notification posters, noting that these should serve as artefacts of researcher engagement and collaboration with clinical teams rather than substitutes for active consent procedures. Only two studies disclosed the research purpose to participants, while one study (4%) deliberately withheld this information. Larsen et al. ( 2020 ) advised against participant recruitment by local management to reduce the risk of coercion. Knowledge users concurred, noting that while managers can facilitate communication, they should not be involved in direct recruitment, as this may unduly influence staff participation. 3.4. Privacy and Confidentiality Concerns Although privacy was a primary concern among knowledge users, it was explicitly addressed in only one included study (Larsen et al. 2020 ), which discussed the risks associated with capturing video and audio in clinical settings, particularly concerning potentially sensitive or identifiable information. Ensuring participant confidentiality was also challenging due to the visibility of eye‐tracking devices, making it difficult to conceal study participation. Several strategies were described to mitigate privacy risks during data collection. These included pausing recordings during patient interactions (Nielsona et al. 2013 ), refraining from entering patient rooms without explicit invitation (Larsen et al. 2020 ), or removing the eye‐tracking device during sensitive moments (Larsen et al. 2020 ). Despite these efforts, privacy management after data collection remained complex. For example, attempts to anonymise video footage by blurring faces were found to be technically demanding and time‐consuming, particularly when automated processing tools were ineffective. As an alternative, Larsen et al. ( 2020 ) restricted data access to authorised users via secure systems. Knowledge users acknowledged the need to protect privacy but cautioned that excessive restrictions could hinder the generation of valuable insights. While some suggested that participants be allowed to wear the device and later decide whether to retain recordings, others preferred a model where participants could request the deletion of specific segments without requiring complete deletion. Reviewing all recordings with participants was considered potentially burdensome and unnecessary if consent procedures clearly outlined their rights to withdraw at any time. Legal implications were also noted. Knowledge users raised the possibility that eye‐tracking recordings may be subject to legal disclosure in judicial proceedings. While research data are typically protected, courts could order access under specific circumstances. A critical legal distinction was identified: in Canada, patients and families have the right to record their care, whereas professional confidentiality standards bind clinicians. This distinction highlights broader ethical questions of data ownership and researcher responsibility in eye‐tracking studies. To address these concerns, knowledge users reiterated the importance of clear and transparent consent documentation. Consent forms should explicitly state: (a) the type of data being recorded (e.g., visual field, audio, patient interaction); (b) the duration and security of data storage; (c) participants' rights to request data deletion or editing; and (d) any conditions under which confidentiality might be overridden (e.g., immediate threats to patient safety). Some studies discussed limitations on data sharing and publication due to privacy risks. One study required explicit participant consent before publishing visual data (Law and Schmölzer 2020 ), another opted not to share raw recordings (Evans‐Harvey et al. 2020 ), and a third sought additional ethics board review before data dissemination (Larsen et al. 2020 ). Knowledge users agreed that written consent should always be obtained before using video data in any public format, including academic publications or presentations. 3.5. Collecting Eye‐Tracking Data in Unpredictable Environments Sixteen studies (64%) reported challenges in collecting eye‐tracking data in complex and unpredictable clinical settings. Variability in environmental conditions (e.g., lighting), diversity among participants, fluctuating patient conditions and inconsistencies in the timing and nature of care activities complicated data collection and analysis. Multiple simultaneous events, moving objects and numerous individuals in the visual field created additional noise in the data. Additionally, unpredictable events could influence participant behaviour, which researchers could not control. Access to live surgical procedures was particularly sensitive. Capturing specific clinical events was also tricky, as their occurrence could not always be anticipated. Despite these challenges, researchers acknowledged that such variability reflects real clinical practice (Hofmaenner et al. 2020 ; Koh et al. 2011 ), enhancing the ecological validity of findings. Some studies addressed these issues by proposing standardisation of care activities (Hofmaenner et al. 2020 ), restricting data collection to fixed time windows (Buehler et al. 2021 ; Grundgeiger et al. 2010 ; Hofmaenner et al. 2021 ), or modifying the environment setup, particularly in operating rooms, to reduce variability (Evans‐Harvey et al. 2020 ). Others focused on analysing specific procedures or selected time segments to improve consistency (Hofmaenner et al. 2020 ). While some researchers recommended computational techniques to control for environmental factors (Ahmadi et al. 2022 ), data heterogeneity often limited the feasibility of automation (Law and Schmölzer 2020 ). Strategies to increase the likelihood of capturing relevant events included starting recordings before scheduled activities, such as elective intubations or trauma alerts (Johannessen et al. 2020 ; Law and Schmölzer 2020 ; White et al. 2018 ), and extending recording periods to accommodate variability (Poulsen et al. 2021 ). Researchers later excluded irrelevant footage during analysis (Evans‐Harvey et al. 2020 ). Baseline measures were often difficult to obtain, particularly in emergencies (Johannessen et al. 2020 ). Two studies (8%) excluded emergency procedures to avoid these complexities (Law and Schmölzer 2020 ; Zimmermann et al. 2020 ). Knowledge users acknowledged the trade‐offs between ecological validity and experimental control. While standardisation enhances data consistency, it may limit the ability to observe real‐world complexity. They emphasised that unpredictable environments should not be viewed solely as barriers but as essential for understanding clinical practice in context. Although operating theatres often afford a higher degree of control, over‐standardisation was seen as potentially counterproductive. Research conducted in authentic clinical environments was considered valuable for capturing how professionals navigate uncertainty and complexity in everyday practice. 3.6. Interference With Patient Care Concerns have been raised about eye‐tracking disrupting patient care. While seven studies (28%) stated that most clinicians did not perceive the device as distracting or intrusive, three out of 22 participants in one study reported feeling disturbed or restricted by the device during care provision (Hofmaenner et al. 2020 ). To minimise disruption, researchers employed strategies such as initiating recordings before procedures and stopping them during natural breaks or transitions (Buehler et al. 2021 ; Johannessen et al. 2020 ; Larsen et al. 2020 ; White et al. 2018 ). Some studies reduced the duration of data collection to limit intrusion (Buehler et al. 2021 ), paused recordings when patient care could be compromised (Tomizawa et al. 2012 ), or limited the researchers' presence in the clinical environment (Koh et al. 2011 ; Larsen et al. 2020 ). Concerns also arose about whether eye‐tracking could pose safety risks or contribute to adverse events. In one study, an IRB restricted participation to experienced surgeons, citing potential safety risks of eye‐tracking during surgery (Vine et al. 2014 ). However, four studies (16%) explicitly reported no such issues (Buehler et al. 2021 ; Hofmaenner et al. 2021 ; Larsen et al. 2020 ; Zimmermann et al. 2020 ). In research on medication administration, observers were instructed to avoid interference but remained prepared to intervene in case of potential errors (Poulsen et al. 2021 ). Knowledge users largely agreed that patient care must take precedence over research activities. They emphasised the importance of allowing participants to remove the device at any time should they feel uncomfortable or if it interferes with their ability to deliver care. Researchers were advised to be present only for equipment setup and to remain nearby to provide support if technical issues arose. They also expressed limited enthusiasm for visual markers, such as vests, to indicate that recording was in progress, as their effectiveness in reducing interference was unclear. The exclusion of less‐experienced clinicians from research was also questioned. Knowledge users expressed concern that restricting participation to experts, as in Vine et al. ( 2014 ), could introduce bias and limit the applicability of findings. They argued that if the goal of research is to inform practice improvement, then including a broader range of experience levels is essential. A broader dilemma emerged regarding observing clinical incidents, errors, or suboptimal care. Knowledge users debated whether researchers—particularly those who are also clinicians—had a duty to report what they observed. While the primary aim of research is to generate knowledge, it should not be a quality assurance or oversight mechanism. Furthermore, knowledge users emphasised that routine clinical variations should not be treated as formal incidents. At the same time, there was a concern that identifying individual errors could create a culture of blame and deter future participation. To address this, knowledge users recommended developing study protocols with clear principles to guide decision‐making. If a serious safety issue is identified, they suggested having a predefined mechanism for reporting it, ideally in collaboration with local stakeholders. However, they argued that not all observed issues warrant intervention, and decisions should be made in consultation with clinical teams, applying a principle of proportionality that considers the certainty of the event, the severity of risk and the timing. They also underscored the importance of defining in consent forms how confidentiality will be maintained and under what circumstances it may be broken. Some risks may be foreseeable based on the nature and design of a study, but protocols should also include mechanisms for addressing unforeseen events, requiring reflection within the research team. In some cases, delaying data review was suggested as a buffer for decision‐making. Still, the effectiveness of this approach depends on the nature of the project and the urgency of potential findings. 3.7. Participant's Comfort Concerns regarding physical and psychological discomfort associated with wearing eye‐tracking devices in clinical environments were raised across some studies. In one trauma resuscitation study, participants reported no issues related to device use (White et al. 2018 ). In another, a nurse removed the glasses mid‐procedure after 90 min, potentially due to fatigue or discomfort (Afkari and Bednarik 2023 ). To enhance comfort, some researchers introduced habituation periods before data collection (Hofmaenner et al. 2021 , 2020 ) and limited session duration to a maximum of 60 min (Buehler et al. 2021 ). Psychological unease was another consideration, as the presence of eye‐tracking devices and research personnel could be unsettling in clinical environments. In one study, 77% of participants reported no additional stress, while 23% did (Hofmaenner et al. 2020 ), though it was unclear whether the device or the clinical task was the source. Some participants expressed concern that the recordings might be used to evaluate their performance. To mitigate this, Larsen et al. ( 2020 ) engaged clinical teams early in the process, clarified the study's purpose and explained that the researchers—engineers by training—had no expertise to assess care quality. This open communication helped build trust over time, and some participants later encouraged colleagues to join the study. Knowledge users viewed these findings as reinforcing the need for consistent communication with participants. Consent procedures should explicitly outline how data will be used, how identities will be protected and how confidentiality will be maintained. While some knowledge users suggested that involving non‐clinical researchers in data analysis may reduce performance‐related anxiety, they acknowledged that this may not always be practical. They also recommended that presenting data in aggregated or de‐identified formats—for instance, using numeric summaries or coded excerpts—could help mitigate concerns about individual performance being scrutinised. Knowledge users underscored the value of collecting qualitative data on participants' experiences of wearing the device. Such insights could inform adjustments to study protocols and enhance the overall acceptability of eye‐tracking research in clinical settings. They advocated for routine inclusion of post‐participation feedback or interviews to better understand barriers to comfort and guide improvements in future studies. 3.8. Data Loss or Unreliable Data Technical limitations were a frequent challenge across the included studies, with 14 studies (56%) reporting data loss or reliability issues. Only one study reported no technical difficulties (Hofmaenner et al. 2020 ). The most common problems included calibration loss ( n = 6, 24%), equipment malfunctions ( n = 3, 12%), low accuracy ( n = 3, 12%) and data corruption ( n = 1, 4%). In one case, participant movement or interaction with the device led to a systematic offset between recorded and actual gaze positions. To address these issues, Poulsen et al. ( 2021 ) incorporated external cameras to verify gaze direction in case of tracking failure. However, knowledge users questioned the practicality of such setups in the clinical environment. Two studies (8%) reviewed recordings with participants to verify data accuracy (Herrick et al. 2020 ; Weinberg et al. 2020 ). Technical difficulties also affected participant inclusion. In three studies (12%), individuals were excluded due to calibration problems, while two studies (8%) precluded participants with visual impairments to avoid such issues. Data fidelity was insufficient for analysis in two additional studies (8%). One study (4%) raised concerns about the subjectivity of defining areas of interest, further complicating interpretation and limiting reproducibility. Beyond technical issues, participant behaviour was a source of potential bias. Five studies (20%) reported that participants may have altered their gaze behaviour due to awareness of being observed. One study proposed comparing gaze distributions against reference datasets to identify potential outliers (Evans‐Harvey et al. 2020 ). Knowledge users suggested using post‐study questionnaires to explore whether participants felt their behaviour had changed during recording. Drawing from experience in clinical simulation, they noted that while some individuals habituate to being recorded, others may still alter verbal or non‐verbal behaviours, omit specific actions, or respond differently under observation in real clinical settings. 4. Discussion This scoping review identified ethical, feasibility and acceptability challenges in implementing eye‐tracking research with clinicians in acute care settings. Drawing on the published literature and input from knowledge users, we synthesised these challenges into five overarching areas of concern, presented in Table 3 . Many of the identified challenges parallel those found in video‐based research, particularly regarding privacy, consent and legal considerations (Asan and Montague 2014 ; Broyles et al. 2008 ; Butler 2018 ; Henken et al. 2012 ; Henry et al. 2020 ; Parry et al. 2016 ; Scott et al. 2020 ). However, eye‐tracking introduces distinct complexities due to its wearable nature, leading to variations in captured data and potential interference with clinical workflow. Addressing these issues requires context‐sensitive, flexible approaches that uphold ethical integrity and methodological rigour. TABLE 3. Reflections for planning an eye‐tracking study in clinical settings. Concerns Reflections Suggested practices Privacy and Consent processes Who needs to provide consent, and how will it be obtained (e.g., written vs. verbal)? Who may be incidentally captured, and how will their rights be protected? How will ongoing consent be ensured? What opt‐out mechanisms will be provided for participants and incidental figures? What strategies will safeguard patient and clinician privacy? Will participants be allowed to request segment removal, or will entire recordings be deleted upon request? Does the study require full disclosure, or is partial blinding of objectives necessary? What data will be shared or published, and how will participants be informed? Use written consent as the standard, with verbal consent in exceptional cases Clearly outline participant rights, including the ability to withdraw consent and request segment removal or recording deletion Differentiate between active participants and incidental figures, favouring explicit consent where feasible Provide clear opt‐out mechanisms for individuals in the visual field Limit unnecessary data capture and use access‐controlled data storage Ensure transparency about data use and sharing in consent forms Ethical and Institutional Considerations Does this project meet the definition of research in the EPTC 2, or is it more aligned with quality improvement or program evaluation? What ethical concerns might the IRB raise, and how can they be proactively addressed? How will participant confidentiality be maintained, and under what conditions might confidentiality be breached? What are the anticipated secondary uses of data, and how should these be addressed in consent forms? How can institutional stakeholders be engaged early to facilitate acceptability and feasibility? Differentiate research from quality improvement in study protocols Engage IRB early to clarify ethical concerns and obtain institutional support Involve bioethicists in study design to anticipate ethical challenges Clearly define data handling, retention and secondary use policies Secure institutional buy‐in through early engagement with management and clinical teams Integration into Clinical Workflows What level of standardisation is necessary for data consistency without compromising ecological validity? How can data collection be aligned with clinical workflows while minimising disruptions? How can settings be chosen based on the level of control required (e.g., controlled OR vs. dynamic ER)? What potential events may be recorded and what criteria determine whether an event requires researcher intervention (e.g., severity, certainty, risk level, timing)? What procedures should be in place for reporting unexpected clinical events or safety concerns? Align data collection with natural workflows to reduce interference Establish clear protocols for pausing or stopping recordings when necessary Minimise researcher presence to avoid influencing behaviours Create an advisory panel within the research team to review and address ethical dilemmas Provide clear guidance on reporting unexpected clinical events or findings Develop a communication plan to inform participants about how recorded events will be handled Participant comfort What measures will minimise physical discomfort from wearing the device? How will participants be informed about their ability to remove the device? What steps will mitigate psychological discomfort, particularly concerns about performance evaluation? How can participant perceptions be assessed to refine study design? Introduce a habituation period before data collection to allow participants to adjust Limit recording durations to avoid fatigue Clearly communicate that recordings are not for performance evaluation Consider qualitative assessments of participant experiences to refine protocols Data loss or unreliability How can the study anticipate and mitigate data loss due to technical failures? What participant behaviours might affect data reliability (e.g., Hawthorne effect), and how can these be accounted for? How should participant training and validation methods improve data accuracy? Do we have enough or adequate equipment to prevent exclusions? Provide clear handling instructions to participants to avoid calibration loss Develop robust data validation strategies, including post‐study interviews or secondary observational methods, when feasible Define clear parameters for areas of interest to improve coding reliability Plan for backup equipment or alternative data sources to mitigate technical failures Open in a new tab Privacy and confidentiality emerged as primary concerns among knowledge users, yet most reviewed studies discussed these only briefly. The sensitivity of video‐based research in healthcare settings, particularly when patients are involved, requires robust privacy safeguards, as recording may include highly identifiable information and inadvertently expose institutional practices (Broyles et al. 2008 ; Henken et al. 2012 ; Scott et al. 2020 ). In eye‐tracking research, the potential to capture medical errors, safety events, or emotionally charged moments raises ethical dilemmas about researcher responsibilities and data management (Butler 2018 ; Scott et al. 2020 ). These concerns are further complicated by legal uncertainties, such as the potential for recordings to be subpoenaed (Asan and Montague 2014 ; Henken et al. 2012 ), and by varying privacy laws across jurisdictions, complicating efforts to establish guidelines (Henken et al. 2012 ). Consent processes also require particular attention in eye‐tracking research. As with video‐based studies, obtaining informed consent from all individuals within the visual field, including patients, staff and visitors, can be challenging in acute care environments. Knowledge users emphasised the importance of explicit, written consent whenever feasible while acknowledging that proper informed consent may be difficult to achieve in high‐pressure clinical settings. Participants may not fully appreciate how their data could be used, particularly for secondary purposes such as education or future research (Parry et al. 2016 ; Scott et al. 2020 ). To address these concerns, knowledge users recommended the development of clear, detailed protocols and consent forms that explicitly outline the scope of data collection, storage, access and conditions of use. Transparent policies that clarify the potential for secondary use are essential for maintaining trust and upholding ethical standards (Asan and Montague 2014 ; Broyles et al. 2008 ; Butler 2018 ; Henry et al. 2020 ; Parry et al. 2016 ). Informed consent should include discussions on the purpose of the research, types of data collected, data processing methods and the rights of participants (Henry et al. 2020 ). Parry et al. ( 2016 ) and Butler ( 2018 ) provide valuable guidelines for video‐based research. While most studies reported securing IRB approval, knowledge users stressed the value of early engagement with ethics committees to anticipate concerns and strengthen protocols. Some IRBs may hesitate to approve video‐based or eye‐tracking research, especially where data identifiability is high (Asan and Montague 2014 ; Henry et al. 2020 ; Scott et al. 2020 ). Determining whether a project constitutes research, quality improvement, or program evaluation is critical, as this classification influences the requirement for ethical review. According to the Canadian Tri‐Council Policy Statement 2 ( 2022 ), research is “an undertaking intended to extend knowledge through a disciplined inquiry and/or systematic investigation.” In contrast, quality improvement and program evaluation efforts within an organisation's operational mandate may fall outside IRB requirements. Researchers must, therefore, assess their study's classification carefully and apply ethical principles regarding participant involvement, data identifiability and informed consent accordingly. The Tri‐Council Policy Statement 2 ( 2022 ) further underscores participant autonomy by referring to individuals as “participants” rather than “subjects.” Knowledge users highlighted that securing institutional support is as vital as IRB approval. Engaging hospital leadership, clinical teams and patient partners early in the planning process enhances feasibility, fosters trust and facilitates implementation. Eye‐tracking research demands deliberative ethics: ethical considerations must be adapted to the study's context, data sensitivity and objectives, as rigid guidelines cannot fully account for the complexities of clinical practice. Initially, we anticipated that the literature would offer clear guidance; however, knowledge users reinforced that ethical reflection must be ongoing and tailored to the specifics of each study. In response, we developed Table 3 to offer practical considerations for protocol development, ensuring that ethical considerations are carefully deliberated and adapted to the research's specific objectives, data sensitivity and context. As described by Senghor and Racine ( 2022 ), ethical deliberation is a structured yet flexible process that involves broadening the understanding of an issue, envisioning action scenarios and arriving at reasoned judgements through dialogue. This view reinforces the need for proactive, ongoing stakeholder engagement and reflection. Unlike controlled research environments, real‐world eye‐tracking studies require continuous ethical adaptation to emerging challenges (Scott et al. 2020 ). Institutional partnerships and advisory groups can help develop responsive, ethically sound protocols that maintain participant trust and support rigorous inquiry. In addition to ethical concerns, the integration of eye‐tracking into clinical workflow introduces methodological and logistical challenges. Researchers must strike a balance between standardisation and ecological validity. While standardisation enhances consistency, it may alter natural behaviour. One persistent issue is participant reactivity, or the Hawthorne effect, where clinicians may modify their gaze, body language, or communication when aware of being recorded (Asan and Montague 2014 ; Parry et al. 2016 ; Scott et al. 2020 ). Some clinicians also worry that recordings might be used to evaluate their performance or capture moments that could reflect poorly on their practice (Broyles et al. 2008 ; Henry et al. 2020 ; Parry et al. 2016 ). Knowledge users reiterated that research should never compromise patient care. To mitigate these concerns, strategies such as post‐study surveys, habituation periods and triangulation methods can help researchers assess how observation influences behaviour (Table 3 ). Reducing researcher presence and engaging clinical teams in advance were seen as helpful in reducing anxiety and improving participant comfort (Parry et al. 2016 ). Knowledge users also encouraged incorporating participant feedback into study design to improve acceptability and ensure eye‐tracking remains methodologically robust and ethically responsible. Finally, data reliability was a significant concern. Nearly half of the studies reported missing or compromised data due to calibration failure, device malfunction, or participant movement. While some data loss is inevitable, knowledge users advocated for anticipatory strategies, such as providing clear usage instructions, implementing backup validation procedures and incorporating complementary data sources to support data integrity and enhance feasibility in clinical settings. This review has several strengths and limitations. A major strength is the integration of knowledge user perspectives, which enriched the interpretation of findings and ensured relevance to real‐world practice. However, most included studies were not primarily designed to examine ethical or feasibility concerns, potentially limiting the depth of available evidence. Additionally, the ethical and regulatory landscape for eye‐tracking research is rapidly evolving, necessitating ongoing attention to institutional policies and data protection regulations. Finally, no studies empirically assessed the impact of identified challenges on research outcomes or participant experiences, highlighting the need for future investigations to evaluate proposed safeguards' effectiveness. 5. Conclusion As eye‐tracking becomes increasingly integrated into clinical research, its implementation requires a nuanced and context‐sensitive approach that balances its potential to enhance healthcare delivery and professional training with the ethical complexities of current and future data use. While eye‐tracking offers unique insights into clinician cognition and decision‐making, its use in real‐world environments demands careful planning, ongoing ethical reflection and critical evaluation of whether it is essential to address the research questions, especially when alternative methods may pose fewer risks or burdens. Implementing eye‐tracking in clinical research requires adaptability. Researchers must anticipate and proactively manage ethical dilemmas by engaging stakeholders, securing institutional support, and establishing clear protocols and consent processes. Ensuring scientific value must not come at the expense of ethical integrity. Feasibility and acceptability can be improved through deliberate collaboration with healthcare teams and patient partners, ongoing reflexivity, and transparent communication about data use and participant rights. These steps are critical for maintaining participant trust and supporting meaningful involvement. To support these efforts, we provide reflection points and recommended practices to guide researchers in navigating ethical challenges, engaging with IRBs and participants, and designing methodologically rigorous and ethically sound protocols. These strategies offer a structured yet flexible foundation for conducting responsible eye‐tracking research in clinical settings. Although this review focused on clinical research, the broader implications of eye‐tracking extend beyond healthcare. Its growing use in virtual and extended reality environments raises critical concerns about privacy, identifiability, secondary data use, ownership, and the commodification of attention (Butler et al. 2021 ; Foster et al. 2023 ). As legal and ethical norms continue to evolve, researchers must remain vigilant about how eye‐tracking data—particularly video recordings involving patients or professionals—might be reused or shared, intentionally or otherwise. This underscores the need for sustained dialogue among researchers, ethicists, legal experts, and policymakers to develop robust governance frameworks that anticipate and regulate current and future data use within and beyond clinical research. Author Contributions P.L.: conceptualisation, methodology, investigation, formal analysis, supervision, funding acquisition, writing – original draft. A.D.: conceptualisation, funding acquisition, formal analysis, writing – review and editing. É.P.: conceptualisation, funding acquisition, formal analysis, writing – review and editing. L.P.: formal analysis, writing – review and editing. J.A.: formal analysis, writing – review and editing. D.R.: formal analysis, writing – review and editing. S.M.: formal analysis, writing – review and editing. M.C.: investigation, formal analysis, writing – original draft. I.K.: investigation, formal analysis, writing – review and editing. T.M.: conceptualisation, funding acquisition, methodology, writing – review and editing. Disclosure Declaration of Generative AI and AI‐Assisted Technologies in the Writing Process : In preparing this manuscript, the authors utilised ChatGPT‐4o to enhance readability and language clarity. The author reviewed and revised all content as necessary and assumes full responsibility for the final publication. Ethics Statement This review does not involve human participants, and informed consent is not required. However, knowledge users involved in the review were informed of its purpose and agreed to be co‐authors on the publication. Conflicts of Interest The authors declare no conflicts of interest. Supporting information Data S1: jan70110‐sup‐0001‐Appendix 1.docx. JAN-82-4506-s002.docx (33.3KB, docx) Data S2: PRISMA Checklist. JAN-82-4506-s001.docx (85KB, docx) Acknowledgements The authors thank Rania Benhannache, Marc‐André Desnoyers, Stéphanie Lachance, Alexandra Lapierre, Titiana Anastasie Lumbala Tshilanda, Élisabeth Quesnel, Khiara Royère, and Amélie Tremblay for their contributions to study preparation, screening, data extraction, and synthesis. We also acknowledge Amélie Brasiola, Jean‐Philippe Landry, Hugues Villeneuve, and Sylvain Boloré for their support in study design and securing funding. 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JAN-82-4506-s001.docx (85KB, docx) Data Availability Statement The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. 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