Using Kane’s framework to build an assessment tool for undergraduate medical student’s clinical competency with point of care ultrasound
BMC Medical Education volume 23, Article number: 43 (2023)
Point-of-care ultrasonography (POCUS) is a portable imaging technology used in clinical settings. There is a need for valid tools to assess clinical competency in POCUS in medical students. The primary aim of this study was to use Kane’s framework to evaluate an interpretation-use argument (IUA) for an undergraduate POCUS assessment tool.
Participants from Memorial University of Newfoundland, the University of Calgary, and the University of Ottawa were recruited between 2014 and 2018. A total of 86 participants and seven expert raters were recruited. The participants performed abdominal, sub-xiphoid cardiac, and aorta POCUS scans on a volunteer patient after watching an instruction video. The participant-generated POCUS images were assessed by the raters using a checklist and a global rating scale. Kane’s framework was used to determine validity evidence for the scoring inference. Fleiss’ kappa was used to measure agreement between seven raters on five questions that reflected clinical competence. The descriptive comments collected from the raters were systematically coded and analyzed.
The overall agreement between the seven raters on five questions on clinical competency ranged from fair to moderate (κ = 0.32 to 0.55). The themes from the qualitative data were poor image generation and interpretation (22%), items not applicable (20%), poor audio and video quality (20%), poor probe handling (10%), and participant did not verbalize findings (14%).
The POCUS assessment tool requires further modification and testing prior before it can be used for reliable undergraduate POCUS assessment.
Point of Care Ultrasonography (POCUS) is portable ultrasound technology that is used to diagnose medical conditions and guide procedures at the bedside . In Canada over the past 20 years, emergency physicians and other specialists have used POCUS to diagnose medical conditions like pericardial effusion and first trimester pregnancy [2,3,4]. POCUS has been shown to improve patient safety for medical procedures by improving operator effectiveness and reducing procedure-related complications [5, 6]. Given the clinical utility of this technology, competence in POCUS has been integrated into the Entrustable Professional Activities of the Royal College of Physicians and Surgeons of Canada postgraduate Competence by Design frameworks for several residency training programs [7,8,9].
As practicing physicians and postgraduate trainees become proficient with POCUS, educators have introduced POCUS into undergraduate medical education, with many universities describing their programs in the literature [10,11,12,13,14,15,16,17,18,19,20,21,22]. In 2014, 50% of the 13 accredited medical schools who responded to a survey about POCUS education in Canada had already integrated POCUS into their undergraduate medical education curriculum . Although there is not a universally accepted or standardized POCUS undergraduate curriculum, several groups have published recommendations on curriculum content for undergraduate medical schools [24, 25]. Critics of POCUS in undergraduate medical education report four dominant discursive rationales repeatedly used to make claims to support POCUS for undergraduate medical education . The four dominant discursive rationales are; that ultrasound allows medical students to see inside a living body and leads to a better understanding of anatomy; that ultrasound improves medical students’ ability to learn physical examination techniques; that ultrasound improves medical students’ diagnostic accuracy; and finally that undergraduate ultrasound training ensures a minimum ultrasound skill level, improving patient safety and allowing for advanced training during residency. The authors who described these four dominant discursive rationales point to the small volume and low quality of evidence available to support the ability of POCUS to improve medical students’ knowledge of anatomy or clinical skills. However, there is emerging evidence that POCUS does improve student performance on physical exam skills for standardized clinical skills assessments, improves the diagnostic accuracy for abdominal aortic aneurysm, and improves assessment scores for students who are learning the clinical exam of the abdomen [27,28,29].
Successful and safe integration of POCUS skills into clinical practice relies on competent end-users, particularly in the age of competency based medical education (CBME) [30, 31]. Presently, there are no validated assessment tools for POCUS skill assessment at the undergraduate level. Valid assessments are critical so that those using them can trust the results and test scores are often used to support claims that go beyond the observed performances [32, 33]. Kane’s framework describes how to generate interpretation use arguments (IUA) to make the reasoning inherent in the proposed interpretations and uses of scores explicit so that they can be better evaluated and understood. Kane’s framework for validation includes four domains: scoring, generalization, extrapolation, and implication. The scoring domain includes an observed performance with an observed score. In the case of POCUS, the observation is a student performing an observed POCUS skill which is rated and results in an observed score. The scores that are generated by the raters will be interpreted using a mean and standard deviation to determine the passing grade. Based on how a student scores on a POCUS assessment educators may make a generalization about the student’s ability to perform other POCUS clinical assessments or the quality of the POCUS curriculum. They may then go one step further and extrapolate that the students who perform well on undergraduate POCUS assessments are able to perform POCUS independently in the clinical setting. If educators are to make these generalizations and extrapolations about POCUS skills, they need to ensure that the assessment tools and scores that are used are both accurate and reliable. Building evidence for the initial scoring IUA is critical to building validity evidence in other domains for undergraduate POCUS programs.
The aim of this study was to use Kane’s framework to test an IUA for the domain of scoring for clinical competence in POCUS. The IUA in this study is that the test scores between the expert raters will be in agreement when they use a previously developed POCUS assessment tool to score participants who perform ultrasound of the heart, aorta, and abdomen . To test this hypothesis, we designed and conducted a multi-center mixed methods study to determine the inter-rater reliability of a POCUS assessment tool.
Ethics approval was granted by the Health Research Ethics board at the University of Ottawa (2017 0803), and the Health Research Ethics Board at the University of Calgary (REB16–1083).
A convenience sample of undergraduate students, postgraduate medical trainees, and emergency medicine physicians were invited to participate in this study at three institutions, Memorial University, University of Ottawa, and the University of Calgary. Inclusion criteria for the study were: undergraduate medical students with or without POCUS training, postgraduate trainees in emergency medicine with POCUS training, or practicing emergency physicians with POCUS training. Participants were recruited at POCUS courses, scanning nights (organized sessions where students scan volunteers or standardized patients as they work toward competence in POCUS), and from local Emergency Departments. Demographic information was recorded for each participant, including their age and sex, level of medical training, whether they completed a formal POCUS course, their independent practitioner (IP) status from the Canadian Point of Care Ultrasound Society (CPOCUS) or equivalent, and the number of supervised POCUS scans they had obtained .
The participants were sorted into novice POCUS users or experienced POCUS users based on the number of supervised abdominal, aorta and cardiac ultrasound scans they had acquired prior to the study. These numbers were chosen based on the CPOCUS training model which assesses competency after participants have completed 50 scans per anatomical area . The novice participants were defined as having fewer than 150 supervised scans. The experienced participants were defined as having > 150 supervised scans and/or IP status. To perform subsequent subgroup analyses, the participants were sorted into groups based on the level of medical training (undergraduate students/postgraduate trainees/practicing physicians).
Expert reviewer selection
Emergency physicians who were experts in POCUS were recruited to rate the participants. The expert physician raters were asked for demographic information including their age, the number of years of experience they had using POCUS, the numbers of years of clinical practice, whether they had IP status, and the type of medical practice (generalist/specialist).
Data collection and materials
A detailed setup and protocol to simultaneously capture the user-generated ultrasound images and the volunteer patient-scanner encounters was developed and is available in Additional file 1 Appendix A. Prior to scanning a volunteer patient, the participants were given standardized instruction or watched a one-minute video detailing the de-identification measures and expectations for the scans. The participants donned a gown, hat, and gloves to provide a measure of standardization and assist with post-processing digital anonymization. Novice ultrasound users were also offered the opportunity to watch a series of four introductory ultrasound videos. The participants and the ultrasound images were then recorded while the participant performed the following POCUS scans on a volunteer patient: abdominal ultrasound, subxiphoid cardiac ultrasound and aorta ultrasound.
The video files were edited to blur faces and the video files were coded. The coded video files were randomized and distributed to seven expert reviewers along with the assessment tool. The assessment tool had three checklists with 11 abdomen, 11 cardiac, and 9 aorta items, and a global rating scale (GRS) with 9 items . The expert raters scored the videos using the checklists and the GRS and provided written comments about their overall experience using the tool and reviewing the videos. The comments from the expert raters were analyzed to understand their experience using the assessment tool. The comments were de-identified, anonymized, and loaded into a Microsoft Excel® spreadsheet, and two reviewers (AJ and GS) coded the comments separately. Using a constant comparison technique, the reviewers met twice to make sure that the themes were aligned. Once no new themes were identified, the results were analyzed.
In consideration of multiple testing and the small sample size (n = 59), Fleiss’ Kappa (κ) statistic and the corresponding p-values were calculated for five items from the checklists that reflected clinical competence (focused abdominal exam Q6,8,9, Cardiac Q9, Aorta Q7) using Stata software (version 14.0; Stata Corporation, College Station, TX). The five items were selected before analyzing the data.
The Fleiss’ Kappa (κ) results were interpreted as follows: values < 0 as poor, and 0.00–0.20 as slight, 0.21–0.40 as fair, 0.41–0.60 as moderate, 0.61–0.80 as substantial, and 0.81–1.00 as almost perfect agreement [36, 37]. The Weighted Fleiss’ Kappa (κ) values were reported for all eight GRS items.
Between 2014 and 2018, a total of 86 participants were recruited: 30 participants were recruited from Memorial University of Newfoundland, 34 from the University of Ottawa, and 22 from the University of Calgary [Table 1]. Eighteen out of the fifty-nine participants included in the analysis were female and 41 were male. Twenty-one participants were undergraduate students, 26 were resident physicians and 12 participants were practicing physicians. Participants were between 21 and 57 years old. Thirty-nine participants were considered novice POCUS users and 20 participants were considered experienced POCUS users. The novice group included all the undergraduate students (n = 19) and some postgraduate trainees (n = 20). The experienced group was composed of both postgraduate trainees (n = 11) and physicians in practice (n = 9). Among the experienced group, 16 participants had IP status while four did not have IP status. Thirty-six participants had completed a formal POCUS course and eighteen had IP status with the CPOCUS . Videos for 27 participants were excluded due to poor video quality, incomplete documentation, and breach of protocol, leaving 59 videos eligible for analysis.
The characteristics of the expert raters are described in Table 2. On average, the physician raters were 45 years old, had 10 of years of experience using POCUS, and 15 years of experience practicing emergency medicine.
The level of agreement between seven expert raters for all participants on five questions on clinical competency using Fleiss’ kappa ranged from fair to moderate (Abdomen Q 6: 0.52, CI 0.29–0.75; Abdomen Q 8:0.55, CI 0.33–0.77; Abdomen Q 9: 0.32, CI 0.07–0.57; Cardiac Q 9: 0.54, CI 0.32–0.77; and Aorta Q 7: 0.48, CI 0.24–0.73) (n = 59) [Table 3], where the confidence intervals (CI) are 95% CIs. Except Abdomen Q 9, the lower bounds of those intervals are in the range of fair agreement. After adjusting for multiple testing using Bonferroni’s correction, agreements for the four questions on clinical competency (Abdomen Q 6 and Q 8; Cardiac Q 9; and Aorta Q 7) were statistically significant (p < 0.01) except Abdomen Q 9 (p = 0.013) at the family wise error rate of 0.05. An exploratory analysis of Fleiss’ kappa for all the checklist items and the weighted Fleiss’ kappa for the global rating scale are available in Additional file 2 Appendix B.
Three subgroups were assessed for rater agreement in the following categories: novice vs. experienced POCUS users, novice POCUS users who were undergraduate students vs. postgraduate students, and experienced POCUS users who were postgraduate students vs. practicing physicians [Table 3]. The agreement between seven raters for the novice and experienced POCUS users ranged from 0.53 to 0.69 (n = 39) and − 0.08 to 0.17 (n = 20) respectively. The agreement between seven raters for the novice POCUS users who were either undergraduate students or postgraduate students ranged from 0.22 to 0.77 (n = 19) and 0.14 to 0.69 (n = 20) respectively. The agreement between seven raters for the experienced POCUS users who were either postgraduate students or practicing physicians ranged from − 0.04 to 0.62 (n = 11) and − 0.47 to 0.77 (n = 9) respectively. The agreement between seven raters for all participants on 8 items included in the GRS ranged from slight to fair (0.12 to 0.31) (n = 12 to 59) [Supplementary Material – Additional file 2 Appendix B].
The following themes emerged from the coded expert rater written comments: poor image generation and interpretation (22%), items not applicable (20%), poor audio and video quality (20%), poor probe handling (10%), and participant did not verbalize findings (14%) [Table 4, Fig. 1]. For items not applicable, the most common checklist items that were not applicable were focused abdominal exam item 10, cardiac item 11, and on the GRS items 5, 6, and 7.
Kane’s framework is centred on stages of argument and includes scoring, generalization, extrapolation, and inference . Based on Kane’s framework, our interpretation-use argument for this study was that if an undergraduate medical student performs well on a series of POCUS skill checklists and a global rating scale, they are considered competent to perform these select POCUS skills. This interpretation-use argument is based on several assumptions. First, a passing score means that an undergraduate medical student can perform the POCUS exam correctly on a patient. Second, that the physical set-up for the POCUS assessment is consistent. Third, that the raters understand how to use the assessment tool and that their scores are reproducible. Finally, that the scores would relate to real-world performance.
There was fair to moderate inter-rater reliability for the questions related to clinical competence on the three checklists (abdomen, cardiac, and aorta). In a previous systematic review of checklists and global rating scales used in the health professions, most demonstrated good inter-rater reliability with κ of 0.80 [38, 39]. Overall our checklists performed moderately with κ values between 0.33 and 0.55. Within the subgroup analysis, there was moderate agreement amongst the expert raters for novice POCUS participants. Interestingly, the expert rater agreement was poor for the more skilled clinicians using POCUS. It is possible that the novice POCUS participants may have demonstrated a clear lack of POCUS skill that was easy for the raters to distinguish through the videos. There was poor agreement amongst the raters for the other subgroups. On the GRS there was modest agreement amongst the raters for “Preparation for Procedure,” “Image Optimization,” “Probe Technique” and “Troubleshooting,” with fair to poor agreement for the other items. Overall, the scores between the raters were not reliable enough to use this scoring system to generalize, extrapolate or make inferences about undergraduate students POCUS skill level. The checklists and the global rating scale must therefore be modified and tested again before using them to assess undergraduate POCUS skills.
The strengths of this study include the large number of participants and the inclusion of multiple testing sites across Canada. In addition, we used standardized protocols and post-production video editing to provide a measure of anonymity for the volunteer patients. The expert raters were all experienced in POCUS and were from both rural and urban practice locations, with generalist and specialist training, and with a range of years of both clinical practice and POCUS experience. The raters were blinded to the level of training of the participants, and they did not have any knowledge of the scores given by the other raters. Each video was reviewed by a minimum of two raters.
There were several limitations in this study. First, there were technical issues related to poor audio and video quality. Future studies should include a set of criteria to assess the quality of the videos. Secondly, the expert raters described several problems with the scoring system. There were some items on the checklists that were not applicable to the exam. For example, there were no abnormal ultrasound findings in the volunteer patients, but there was a checkbox for identifying abnormalities and the raters were unsure how to handle this item. This may be a fault in using a checklist for this type of assessment or in the design of the tool itself which was developed by practicing physicians who use POCUS. This may be fixed in the future by giving the raters three columns to select from (yes, no, or not applicable). The expert raters did not receive any training on how to use the assessment tool. Strategies to improve the inter-rater reliability might include developing a standardized program to train the raters on the assessment tool virtually or in-person. Finally, expert-novice comparisons for validity arguments have several inherent limitations . In this study, there was difficulty recruiting participants who were medical students with expert level ultrasound training, leading us to recruit postgraduate students and practicing physicians as participants. Using this tool in a heterogenous population may have negatively impacted the inter-rater reliability and the subgroup analysis explored these effects.
The goal of this study was to propose and test an IUA for the scoring domain within Kane’s framework. The results of this study do not provide enough evidence to support the IUA in the scoring domain. Therefore, the POCUS assessment tool requires further modification and testing prior before it can be used for reliable undergraduate POCUS assessment.
Availability of data and materials
The dataset analyzed during the current study are available from the corresponding author upon request.
Point of care ultrasound
Competency based medical education
Interpretation use argument
The Canadian Point of Care Ultrasound Society
Global rating scale
Díaz-Gómez JL, Mayo PH, Koenig SJ. Point-of-care ultrasonography. N Engl J Med. 2021;385(17):1593–602. https://doi.org/10.1056/NEJMra1916062.
Lewis D, Rang L, Kim D, Robichaud L, Kwan C, Pham C, et al. Recommendations for the use of point-of-care ultr CJEM asound (POCUS) by emergency physicians in Canada. 2019;21(6):721–6. https://doi.org/10.1017/cem.2019.392.
Ailon J, Mourad O, Nadjafi M, Cavalcanti R. Point-of-care ultrasound as a competency for general internists: a survey of internal medicine training programs in Canada. CJEM. 2016;7(2):e51.
Løkkegaard T, Todsen T, Nayahangan LJ, Andersen CA, Jensen MB, Konge L. Point-of-care ultrasound for general practitioners: a systematic needs assessment. Scand J Prim Health Care. 2020;38(1):3–11. https://doi.org/10.1080/02813432.2020.1711572.
Smit JM, Raadsen R, Blans MJ, Petjak M, Van de Ven PM, Tuinman PR. Bedside ultrasound to detect central venous catheter misplacement and associated iatrogenic complications: a systematic review and meta-analysis. Crit Care. 2018;22(1):1–5. https://doi.org/10.1186/s13054-018-1989-x.
Helgeson SA, Fritz AV, Tatari MM, Daniels CE, Diaz-Gomez JL. Reducing iatrogenic Pneumothoraces: using real-time ultrasound guidance for pleural procedures. Crit Care Med. 2019;47(7):903–9. https://doi.org/10.1097/CCM.0000000000003761.
Sherbino J, Bandiera G, Doyle K, Frank JR, Holroyd BR, Jones G, et al. The competency-based medical education evolution of Canadian emergency medicine specialist training. CJEM. 2020;22(1):95–102. https://doi.org/10.1017/cem.2019.417.
Iobst WF, Sherbino J, Cate OT, Richardson DL, Dath D, Swing SR, et al. Collaborators. Competency-based medical education in postgraduate medical education. Med Teach. 2010;32(8):651–6. https://doi.org/10.3109/0142159X.2010.500709.
Royal College of Physicians and Surgeons of Canada. Emergency medicine competencies and Anesthesia competencies; 2018. Available at: http://www.royalcollege.ca/rcsite/ibd-search-e?N=10000033+10000034+4294967050. (Accessed 19 Nov 2021).
Teichgräber UK, Meyer JM, Nautrup CP, von Rautenfeld DB. Ultrasound anatomy: a practical teaching system in human gross anatomy. Med Educ. 1996;30(4):296–8. https://doi.org/10.1111/j.1365-2923.1996.tb00832.x.
Wittich CM, Montgomery SC, Neben MA, Palmer BA, Callahan MJ, Seward JB, et al. Teaching cardiovascular anatomy to medical students by using a handheld ultrasound device. JAMA. 2002;288(9):1062–3. https://doi.org/10.1001/jama.288.9.1062.
Rao S, van Holsbeeck L, Musial JL, Parker A, Bouffard JA, Bridge P, et al. A pilot study of comprehensive ultrasound education at the Wayne State University School of Medicine: a pioneer year review. J Ultrasound Med. 2008;27(5):745–9. https://doi.org/10.7863/jum.2008.27.5.745.
Afonso N, Amponsah D, Yang J, Mendez J, Bridge P, Hays G, et al. Adding new tools to the black bag—introduction of ultrasound into the physical diagnosis course. J Gen Intern Med. 2010;25(11):1248–52. https://doi.org/10.1007/s11606-010-1451-5.
Hoppmann RA, Rao VV, Poston MB, Howe DB, Hunt PS, Fowler SD, et al. An integrated ultrasound curriculum (iUSC) for medical students: 4-year experience. Crit Ultrasound J. 2011;3(1):1–2. https://doi.org/10.1186/s13089-015-0035-3.
Brown B, Adhikari S, Marx J, Lander L, Todd GL. Introduction of ultrasound into gross anatomy curriculum: perceptions of medical students. J Emerg Med. 2012;43(6):1098–102. https://doi.org/10.1016/j.jemermed.2012.01.041.
Bahner DP, Goldman E, Way D, Royall NA, Liu YT. The state of ultrasound education in US medical schools: results of a national survey. Acad Med. 2014;89(12):1681–6. https://doi.org/10.1097/ACM.0000000000000414.
Dinh VA, Frederick J, Bartos R, Shankel TM, Werner L. Effects of ultrasound implementation on physical examination learning and teaching during the first year of medical education. J Ultrasound Med. 2015;34(1):43–50. https://doi.org/10.7863/ultra.34.1.43.
Cantisani V, Dietrich CF, Badea R, Dudea S, Prosch H, Cerezo E, et al. EFSUMB statement on medical student education in ultrasound [long version]. Ultrasound Int Open. 2016;2(1):E2. https://doi.org/10.1055/s-0035-1569413.
Nelson BP, Hojsak J, Dei Rossi E, Karani R, Narula J. Seeing is believing evaluating a point-of-care ultrasound curriculum for 1st-year medical students. Teach Learn Med. 2017;29(1):85–92. https://doi.org/10.1080/10401334.2016.1172012.
Stone-McLean J, Metcalfe B, Sheppard G, Murphy J, Black H, McCarthy H. Dubrowski Developing an undergraduate ultrasound curriculum: a needs assessment. Cureus. 2017;9(9):e1720. https://doi.org/10.7759/cureus.1720.
Tarique U, Tang B, Singh M, Kulasegaram KM, Ailon J. Ultrasound curricula in undergraduate medical education: a scoping review. J Ultrasound Med. 2018;37(1):69–82. https://doi.org/10.1002/jum.14333.
Celebi N, Griewatz J, Malek NP, Krieg S, Kuehnl T, Muller R, et al. Development and implementation of a comprehensive ultrasound curriculum for undergraduate medical students–a feasibility study. BMC Med Educ. 2019;19(1):1–8. https://doi.org/10.1186/s12909-019-1611-1.
Steinmetz P, Dobrescu O, Oleskevich S, Lewis J. Bedside ultrasound education in Canadian medical schools: a national survey. CJEM. 2016;7(1):e78.
Baltarowich OH, Di Salvo DN, Scoutt LM, Brown DL, Cox CW, DiPietro MA, et al. National ultrasound curriculum for medical students. Ultrasound Quarterly. 2014;30(1):13–9. https://doi.org/10.1097/RUQ.0000000000000066.
Ma IW, Steinmetz P, Weerdenburg K, Woo MY, Olszynski P, Heslop CL, et al. The Canadian medical student ultrasound curriculum: a statement from the Canadian ultrasound consensus for undergraduate medical education group. J Ultrasound Med. 2020;39(7):1279–87. https://doi.org/10.1002/jum.15218.
Feilchenfeld Z, Dornan T, Whitehead C, Kuper A. Ultrasound in undergraduate medical education: a systematic and critical review. Med Educ. 2017;51(4):366–78. https://doi.org/10.1111/medu.13211.
Suwondo, David, “Evaluation Of The Impact Of A Novel Bedside Ultrasound Curriculum On Undergraduate Medical Education” (2017). Yale Med Thesis Digital Library 2176. https://elischolar.library.yale.edu/ymtdl/2176
Wong CK, Hai J, Chan KY, Un KC, Zhou M, Huang D, et al. Point-of-care ultrasound augments physical examination learning by undergraduate medical students. Postgrad Med J. 2021;97(1143):10–5. https://doi.org/10.1136/postgradmedj-2020-137773.
Mai T, Woo MY, Boles K, Jetty P. Point-of-care ultrasound performed by a medical student compared to physical examination by vascular surgeons in the detection of abdominal aortic aneurysms. Ann Vasc Surg. 2018;52:15–21. https://doi.org/10.1016/j.avsg.2018.03.015.
Frank JR, Snell LS, Cate OT, Holmboe ES, Carraccio C, Swing SR, et al. Competency-based medical education: theory to practice. Med Teach. 2010;32(8):638–45. https://doi.org/10.3109/0142159X.2010.501190.
Holmboe ES, Sherbino J, Long DM, Swing SR, Frank JR, International CBME. Collaborators. The role of assessment in competency-based medical education. Med Teach. 2010;32(8):676–82. https://doi.org/10.3109/0142159X.2010.500704.
Cook DA, Hatala R. Validation of educational assessments: a primer for simulation and beyond. Adv Simul. 2016;1(1):1–2. https://doi.org/10.1186/s41077-016-0033-y.
Kane MT. Validating the interpretations and uses of test scores. J Educ Meas. 2013;50(1):1–73. https://doi.org/10.1111/jedm.12000.
Black H, Sheppard G, Metcalfe B, Stone-McLean J, McCarthy H, Dubrowski A. Expert facilitated development of an objective assessment tool for point-of-care ultrasound performance in undergraduate medical education. Cureus. 2016 Jun;8(6):e636. https://doi.org/10.7759/cureus.636.
Cpocus.ca [Internet] Vancouver: Canadian Society of Point of Care Ultrasound; c2021 [cited 2021 June 23]. Available from: www.cpocus.ca
Fleiss JL, Levin B, Paik MC. Statistical methods for rates and proportions: Wiley; 2013.
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977 Mar;33(1):159–74. https://doi.org/10.2307/2529310.
Ilgen JS, Ma IW, Hatala R, Cook DA. A systematic review of validity evidence for checklists versus global rating scales in simulation-based assessment. Med Educ. 2015;49(2):161–73. https://doi.org/10.1111/medu.12621.
Patrawalla P, Eisen LA, Shiloh A, Shah BJ, Savenkov O, Wise W, et al. Development and validation of an assessment tool for competency in critical care ultrasound. J Grad Med Educ. 2015 Dec;7(4):567. https://doi.org/10.4300/JGME-D-14-00613.1.
Cook DA. Much ado about differences: why expert-novice comparisons add little to the validity argument. Adv Health Sci Educ. 2015;20(3):829–34. https://doi.org/10.4300/JGME-D-14-00613.1.
We would like to thank the expert physician reviewers who generously agreed to review the videos for this project and Mr. Ritchie Perez, Multimedia Specialist at Memorial University for his assistance with video editing. We would like to thank the administrative staff in the Discipline of Emergency Medicine at Memorial University of Newfoundland, especially Ms. Joanne Doyle and Ms. Stephanie Herlidan, for helping with this project. Finally, we would like to thank Dr. Vernon Curran for his help with the manuscript.
This study did not receive any funding.
Ethics approval and consent to participate
Ethics approval was submitted and granted by the Health Research Ethics board at the University of Ottawa (2017 0803), and the Health Research Ethics Board at the University of Calgary (REB16–1083). Informed consent was obtained from all participants in the study. All methods were carried out in accordance with relevant guidelines and regulations.
Consent for publication
All authors have consented to the publication of this article. Author KW has provided informed consent for publication of her photograph within Additional file 1 Appendix A: Setup and Protocol.
None of the authors have any competing interests to declare.
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Sheppard, G., Williams, KL., Metcalfe, B. et al. Using Kane’s framework to build an assessment tool for undergraduate medical student’s clinical competency with point of care ultrasound. BMC Med Educ 23, 43 (2023). https://doi.org/10.1186/s12909-023-04030-9