Beyond Attendance: Evaluating Knowledge Acquisition in Continuing Medical Education Using Objective Pre–Post Assessment

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Ayhan Caliskan, Mohi Magzoub This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9437333/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Continuing Medical Education (CME) is widely implemented to enhance healthcare professionals’ knowledge and maintain clinical competence. However, evidence regarding objective knowledge acquisition, particularly using pre–post assessment designs, remains limited. This study aimed to evaluate the effectiveness of CME programs in improving knowledge among healthcare professionals using objective and self-reported measures. This study evaluates CME activities using Kirkpatrick’s model of training evaluation, with the present analysis focusing on Level 2 (learning). A quantitative pre–post design was conducted among healthcare professionals attending four accredited CME programs. Participants completed structured knowledge assessments immediately before and after the programs. A total of 191 participants completed both assessments and were included in the analysis. Knowledge acquisition was measured as the change in test scores, and subgroup analyses were performed across professional groups. Paired-sample t-tests and descriptive statistics were used for analysis. Knowledge scores increased significantly from 1.78 (SD = 1.37) pre-CME to 3.07 (SD = 1.22) post-CME (mean difference = 1.29, 95% CI: 1.09–1.50; p < 0.001). Improvements were observed across all professional groups, with the largest gains among nurses. At the item level, 31.6% of responses showed positive knowledge change, while 54.6% showed no change and 13.8% showed negative change. Participants reported that 55.6% of the content represented new knowledge, with high anticipated application in clinical practice. No significant association was found between attending CME for credit hours and knowledge gain (p = 0.356). CME programs were associated with significant improvements in healthcare professionals’ knowledge, supporting their role as an effective educational strategy. However, variability in learning outcomes highlights the need to shift from attendance-based models toward outcome-driven, learner-centered CME approaches. Incorporating objective assessment of knowledge acquisition into CME evaluation frameworks may enhance educational impact and accountability. Continuing Medical Education Knowledge Acquisition Pre–Post Study Design Healthcare Professionals Educational Measurement Learning Outcomes Kirkpatrick Model Continuing Professional Development Background Continuing Medical Education (CME) remains a cornerstone of lifelong learning in healthcare, supporting the continuous development of healthcare professionals (HCPs) in response to rapidly evolving biomedical knowledge and increasingly complex healthcare systems. Ensuring that HCPs maintain up-to-date knowledge is essential for delivering safe, effective, and evidence-based patient care. Consequently, CME programs are widely implemented to facilitate knowledge acquisition and improve clinical performance and patient outcomes [ 1 , 2 ]. Recent evidence suggests that the effectiveness of CME is influenced by instructional design, interactivity, and contextual relevance. Contemporary systematic reviews indicate that interactive, practice-oriented, and digitally supported CME interventions are more likely to produce meaningful improvements in knowledge and clinical performance compared to traditional didactic approaches [ 3 , 4 ]. Additionally, the increasing integration of online and blended learning modalities has expanded access to CME and demonstrated comparable or superior knowledge gains relative to face-to-face formats [ 5 ]. The evaluation of CME effectiveness is commonly guided by frameworks such as Donald Kirkpatrick’s model, which conceptualizes outcomes across multiple levels, including reaction, learning (knowledge acquisition), behavior, and results. Within this framework, knowledge acquisition represents a fundamental and measurable outcome, serving as a prerequisite for subsequent behavioral and clinical improvements [ 6 ]. However, recent literature highlights that many CME evaluations continue to rely on self-reported outcomes rather than objective measures of knowledge gain, limiting the robustness of conclusions regarding effectiveness [ 7 ]. In the United Arab Emirates (UAE), CME is a mandatory requirement for licensure renewal, reflecting its central role in maintaining healthcare quality. Substantial investments are made in CME activities, including conferences, workshops, and accredited educational programs. These initiatives aim to enhance professional knowledge and align clinical practice with current evidence. Nevertheless, concerns have been raised regarding variability in CME quality, alignment with learners’ needs, and the extent to which such programs achieve measurable learning outcomes [ 8 , 9 ]. Although CME is generally assumed to improve knowledge, recent global evidence presents mixed findings regarding the magnitude and sustainability of knowledge gains. Some studies report significant short-term improvements in knowledge following CME interventions, while others demonstrate limited or context-dependent effects, particularly when programs lack alignment with practice needs or fail to incorporate active learning strategies [ 3 , 10 ]. Furthermore, there is growing recognition that combining objective knowledge assessments with learner perceptions provides a more comprehensive evaluation of CME effectiveness [ 7 ]. Despite the widespread implementation and mandatory nature of CME in the UAE, there is limited recent empirical evidence specifically examining objective knowledge acquisition outcomes among CME participants. Existing studies in the region have predominantly focused on satisfaction and perceived effectiveness rather than rigorously measured learning gains. Moreover, few studies have employed pre–post knowledge assessment designs or explored differences in knowledge acquisition across diverse groups of healthcare professionals within CME settings. This gap limits the ability of educators and policymakers to optimize CME design and ensure its educational impact. This study is part of a larger project evaluating CME activities based on Kirkpatrick’s model of training evaluation, with the present analysis situated at Level 2 (learning) [ 11 ]. The study aims to evaluate the effectiveness of CME programs in enhancing knowledge acquisition among healthcare professionals, using objective pre- and post-program knowledge measures alongside participant-reported perceptions of learning. Research Questions To what extent do CME programs lead to measurable improvements in healthcare professionals’ knowledge? What is the magnitude of change in knowledge following participation in CME activities? Are there differences in knowledge acquisition across different groups of healthcare professionals? How do participants perceive the knowledge gained from CME programs? Methods This study forms part of a broader mixed-methods project, with the current report focusing specifically on the quantitative evaluation of knowledge acquisition among healthcare professionals (HCPs) attending Continuing Medical Education (CME) programs. The study was conducted in the United Arab Emirates, a Middle Eastern country characterized by a multicultural healthcare workforce and mandatory CME requirements for professional license renewal. Four CME programs accredited by a national university were purposively selected for inclusion: an Acute Coronary Syndrome course, an Infectious Diseases course, a Cardio-rheumatology review, and a Respiratory rapid review course. For each program, detailed information was obtained, including date, duration, topic, expected attendance, and actual attendance. All programs were fee-based, industry-independent, and nationally recognized for license renewal, and participants were drawn from both public and private healthcare sectors. Program organizers were contacted prior to data collection and provided consent for inclusion of their CME activities in the study. They were also asked to supply relevant program information, including learning objectives, agendas, expected outcomes, and suggested assessment questions. The questionnaires were adapted for each CME program to ensure alignment with the specific content delivered. The quantitative component utilized a pre–post study design to measure changes in participants’ knowledge before and after CME participation. The study was conceptually informed by Donald Kirkpatrick’s evaluation framework, specifically Level 2 (learning), which focuses on knowledge acquisition as a key indicator of educational effectiveness. Participants included a multidisciplinary group of HCPs, comprising physicians, nurses, pharmacists, and other allied health professionals. A non-probability convenience sampling strategy was adopted, whereby all attendees of the selected CME programs during the study period were invited to participate. Inclusion criteria required attendance at one of the selected CME programs and completion of both pre- and post-CME knowledge assessments. Participants with incomplete responses or those who did not attend the full CME session were excluded. This approach allowed for the inclusion of all eligible participants within the natural educational setting while maximizing response rates. Data collection focused on the assessment of knowledge acquisition using structured pre- and post-CME questionnaires administered immediately before and after each program. Participants were recruited at the beginning of each CME program and provided written informed consent prior to participation. Data was collected using self-administered questionnaires. The questionnaire was paper-based and distributed to participants at the registration desk before the CME activities started; completion was voluntary and anonymous. The assessment tools consisted of content-specific questions aligned with the learning objectives of each CME program. These questions were initially developed by CME program faculty based on key concepts covered in the sessions and were subsequently reviewed and validated by a panel of subject matter experts, chaired by a professor of internal medicine at the College of Medicine, United Arab Emirates University. A sample of the questionnaire (pre- and post-knowledge test) for one of the CME events is provided in Supplementary File 1. The same or equivalent questions were used in both pre- and post-tests to ensure comparability. Each participant was assigned a unique code to link pre- and post-test responses while maintaining anonymity. Participants’ responses were scored, and total knowledge scores were calculated for everyone before and after the intervention. The validity of the assessment instruments was supported through expert review to ensure alignment with program objectives and content relevance, thereby enhancing content validity. Reliability was strengthened by using consistent pre- and post-test formats across participants and standardized administration procedures, ensuring comparability of measurements over time. In addition to objective knowledge assessment, participants were asked to estimate the proportion of new knowledge gained from the CME program and to report perceived changes in their understanding of the topic. These measures provided complementary insights into perceived knowledge acquisition. A target sample of at least 200 participants completing both pre- and post-assessments was set. The pre-CME questionnaire was distributed to all 334 attendees across the four programs, with 302 participants (88%) returning the pre-test questionnaires. Response rates varied by program but remained high overall, reflecting strong participant engagement. The primary outcome variable was knowledge acquisition, operationalized as the difference between pre- and post-CME knowledge scores. Secondary variables included pre-test scores, post-test scores, change in knowledge scores (Δ scores), and self-reported perceived knowledge gain. Independent variables included participants’ professional category and demographic characteristics, such as years of experience and workplace setting. Ethical approval for this study was obtained from the Research Ethics Committee of the British University in Dubai and the ethics committee of the UAE university. Both committees granted permission to conduct the study, access accreditation data, and collect information from participants. Written informed consent was obtained from all participants. Confidentiality and anonymity were strictly maintained, and all data were reported in aggregate form. Data Analysis Participants’ responses to the pre- and post-test assessments were entered into an Excel spreadsheet, coded using unique identifiers, and then combined for analysis using IBM SPSS Statistics version 26. Descriptive statistics were used to summaries the data, with means and standard deviations calculated for pre- and post-test knowledge scores, and frequencies and percentages used to describe categorical variables. Inferential analysis was conducted to evaluate changes in knowledge following CME participation. Paired-sample t-tests were used to compare pre- and post-CME knowledge scores and determine the statistical significance of observed differences. Subgroup analyses were also performed to examine variations in knowledge acquisition across different professional groups. Statistical significance was set at p < 0.05. Additional analyses included cross-tabulation to explore relationships between participant characteristics and knowledge gain. Self-reported measures of knowledge acquisition were analyzed descriptively and compared with objective assessment results to provide a more comprehensive evaluation of learning outcomes. Results A total of 302 healthcare professionals (HCPs) participated in this study. Of these, 254 (84.1%) completed the pre-test, 216 (71.5%) completed the post-test, and 191 participants completed both assessments and were included in the paired analysis. Participation in the CME programs was associated with a statistically significant improvement in knowledge scores. The mean score increased from 1.78 (SD = 1.37) pre-CME to 3.07 (SD = 1.22) post-CME, representing a mean difference of 1.29 (95% CI: 1.09–1.50) (t(190) = 12.6, p < 0.001). These findings indicate a substantial and consistent gain in knowledge following CME participation. Knowledge improvement was observed across all professional groups. The magnitude of gain varied, with nurses demonstrating the largest improvement (mean increase = 1.6), followed by pharmacists and other HCPs (1.4 each), and physicians (0.9). Despite these differences, all groups showed statistically significant improvement, indicating that the CME programs were effective across a multidisciplinary audience. At the item-response level (n = 955 responses), analysis of knowledge change patterns revealed that 31.6% of responses reflected positive change, where incorrect or “don’t know” answers were converted to correct responses after the CME programs. In contrast, 54.6% of responses showed no change, and 13.8% reflected negative change. These findings suggest that while a meaningful proportion of participants experienced true knowledge acquisition, a substantial proportion did not demonstrate measurable change, Table 1 displays the Item Analysis for the participant’s answers to pre- and post-CME knowledge test. Table 1 Item Analysis for the participant’s answers to pre- and post-CME knowledge questions. Knowledge Change Group Pre-CME Answer Post-CME Answer Frequency Percentage No change in knowledge Right Right 287 30.1 Wrong Wrong 194 20.3 Don’t know Don’t know 34 3.6 Wrong Don’t know 6 0.6 Total 54.6 Positive change in knowledge Wrong Right 165 17.3 Don’t know Right 137 14.3 Total 31.6 Negative change in knowledge Right Wrong 53 5.5 Right Don’t know 1 0.1 Don’t know Wrong 78 8.2 Total 13.8 Grand total 955 100.0 The distribution of knowledge changes varied across professions as illustrated in Table 2. The proportion of participants demonstrating positive change was highest among pharmacists (38.7%), followed by nurses (35.4%), other HCPs (36.7%), and physicians (24.8%). Across all groups, however, the largest proportion remained within the “no change” category, reinforcing variability in learning outcomes. Table 2 Cross tabulation for participants’ profession and change in knowledge after the CME programs. Change in Knowledge Profession No change Positive change Negative change Total Doctor Count 212 82 36 330 % within profession 64.2% 24.8% 10.9% 100.0% Nurse Count 243 168 64 475 % within profession 51.2% 35.4% 13.5% 100.0% Pharmacist Count 30 29 16 75 % within profession 40.0% 38.7% 21.3% 100.0% Other HCPs Count 25 22 13 60 % within profession 41.7% 36.7% 21.7% 100.0% Total Count 510 301 129 940 % within Profession 54.3% 32.0% 13.7% 100.0% Further analysis showed that motivation for attending CME (i.e., attending solely to obtain CME credit hours) was not significantly associated with knowledge gain (χ²(2, N = 185) = 2.06, p = 0.356), suggesting that learning outcomes were independent of extrinsic motivation. Participants’ self-reported data supported the objective findings. On average, participants estimated that 55.6% (SD = 23.6) of the CME content represented new knowledge, indicating substantial perceived learning. In addition, participants reported a high likelihood of applying this knowledge in practice, with an estimated 59.9% of their patients potentially benefiting, a mean strategy change score of 5.28/7, and a strong intention to share knowledge with colleagues (mean = 5.84/7). Overall, the results demonstrate that CME participation leads to significant knowledge acquisition, supported by both objective assessment and participant perception, although the extent of learning varies across individuals and professional groups. Discussion This study evaluated the effectiveness of accredited Continuing Medical Education (CME) programs in enhancing knowledge acquisition among healthcare professionals (HCPs) and demonstrated a statistically significant improvement in knowledge scores following participation. The increase in mean scores from 1.78 to 3.07 reflects a substantial gain in knowledge, supported by both objective pre–post assessments and participant-reported outcomes. Importantly, knowledge improvement was observed across all professional groups, including physicians, nurses, pharmacists, and other HCPs, indicating that CME programs were broadly effective in a multidisciplinary context. However, the magnitude of improvement varied, with nurses and pharmacists demonstrating greater gains compared to physicians. At the item-response level, approximately one-third of responses reflected positive knowledge change, confirming that a meaningful proportion of learning occurred as a direct result of CME participation. Participants further reported that more than half of the CME content represented new knowledge, reinforcing the effectiveness of these programs in addressing knowledge gaps. These findings are consistent with recent systematic reviews suggesting that CME interventions can produce modest to moderate improvements in knowledge and professional performance, particularly when educational activities are well designed and aligned with learner needs [ 3 , 10 ]. The magnitude of knowledge gain observed in this study is comparable to that reported in contemporary evaluations of both traditional and technology-enhanced CME, which have demonstrated that interactive and blended learning approaches are associated with improved learning outcomes [ 4 , 5 ]. The observed variation in knowledge acquisition across professional groups is also supported by prior literature, which highlights the influence of baseline knowledge, professional role, and relevance of content on learning outcomes [ 7 ]. In particular, greater gains among nurses and pharmacists may reflect closer alignment between CME content and their immediate clinical responsibilities or comparatively lower baseline knowledge levels. Despite these positive findings, the observation that more than half of responses showed no change in knowledge highlights an important limitation in CME effectiveness. This finding aligns with existing evidence indicating that not all participants benefit equally from CME activities and that passive or poorly targeted educational interventions may have limited impact [ 12 ]. It suggests that while CME programs can be effective overall, their impact is not uniform, and there remains considerable scope for improving instructional design and learner engagement. The findings of this study have important implications for CME design, policy, and practice. From an educational perspective, the coexistence of significant knowledge gains and a substantial proportion of unchanged responses underscores the need for more learner-centered approaches that actively engage participants and address their specific learning needs [ 7 ]. Incorporating interactive strategies such as case-based discussions, simulations, and problem-solving activities may enhance knowledge retention and applicability. Furthermore, the integration of objective knowledge assessments alongside self-reported learning, as demonstrated in this study, provides a more comprehensive evaluation of CME effectiveness and should be more widely adopted [ 12 ]. From a policy perspective, the mandatory nature of CME highlights the importance of ensuring that such programs deliver measurable educational value. While current systems emphasize participation and accumulation of credit hours, the findings suggest that greater emphasis should be placed on outcome-based evaluation, particularly the measurement of knowledge acquisition. Accrediting bodies may consider incorporating requirements for pre–post assessment or other objective measures of learning as part of CME accreditation processes. Such an approach would enhance accountability and ensure that investments in CME translate into meaningful improvements in professional competence. From a clinical practice standpoint, the results suggest that CME contributes to improved knowledge that is likely to influence clinical decision-making and patient care. This is supported by participants’ reported intentions to modify management strategies and share acquired knowledge with colleagues. However, the absence of a significant relationship between attending CME for credit hours and knowledge gain indicates that external motivations alone do not drive learning outcomes. Instead, the quality, relevance, and engagement level of the educational content appear to be the primary determinants of effective knowledge acquisition. This study has several strengths, including the use of a pre–post design with objective knowledge assessment, which strengthens internal validity, and the inclusion of a large, multidisciplinary sample, which enhances generalizability. The integration of both objective and subjective measures of knowledge acquisition provides a comprehensive evaluation of learning outcomes, while the detailed analysis of response patterns offers deeper insight into how knowledge changes at the individual level. Nevertheless, several limitations should be acknowledged. The use of a convenience sample may limit the generalizability of findings beyond the study setting. The assessment of knowledge was limited to short-term outcomes, and long-term retention of knowledge was not evaluated. Additionally, the study focused on learning outcomes corresponding to Level 2 of Donald Kirkpatrick and did not assess higher-level outcomes such as behavior change or patient outcomes. Variations in assessment content across CME programs may also have influenced the results, and self-reported measures are subject to potential response bias. Overall, this study provides robust evidence that CME programs can lead to significant knowledge acquisition among healthcare professionals, although the extent of learning varies across participants. These findings highlight the need for more targeted, outcome-driven, and learner-centered CME design, supported by policy frameworks that priorities measurable educational impact. Conclusion This study provides robust evidence that CME programs lead to significant and measurable improvements in healthcare professionals’ knowledge, confirming their value as an effective educational strategy. The consistency of knowledge gains across professional groups underscores the relevance of CME in supporting multidisciplinary learning and maintaining clinical competence. However, the variability in learning outcomes highlights a critical need to move beyond traditional, attendance-based models of CME toward outcome-driven, learner-centered approaches. Embedding objective assessment of knowledge acquisition, aligning content with learners’ needs, and adopting interactive and practice-oriented educational strategies are essential to maximize impact. At a policy level, these findings strongly support the integration of mandatory outcome evaluation within CME accreditation systems, ensuring that CME investments translate into demonstrable learning gains. Strengthening the design and evaluation of CME programs will be key to enhancing their contribution to clinical practice and, ultimately, to improving patient care. Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the Research Ethical Committee of the British University in Dubai and from the ethical committee of the national university that accredited the CME programs. The study was conducted in accordance with the Declaration of Helsinki and relevant institutional ethical guidelines. Written informed consent was obtained from all participants prior to data collection. Participation was voluntary, and confidentiality and anonymity were assured; data are reported in aggregate form only. Consent for publication Not applicable. The manuscript does not contain any individual person’s identifiable data, images, or videos. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author (AA) on reasonable request. Clinical Trial Number Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work from any public, commercial, or not-for-profit funding agency. Authors’ contributions The study was conceived and designed by AA, who also led the development of the questionnaire and interview guide, as well as data collection, analysis, interpretation, and critical appraisal of the findings. AA prepared the initial draft of the manuscript, while SAC and MM contributed to substantial revisions for important intellectual content. All authors reviewed and approved the final manuscript and accept responsibility for all aspects of the work. Acknowledgement The authors sincerely thank all healthcare professionals who participated in the survey and interviews. They also express their appreciation to the organizers and administrative staff of the four CME programs for their valuable support in facilitating data collection. The authors are grateful to the CME event faculty who developed the pre- and post-test questions, as well as the content experts who reviewed and validated these assessment tools. In addition, the authors acknowledge the support of the Medical Education Department at the College of Medicine and Health Sciences, United Arab Emirates University. References Frenk J, Chen L, Bhutta ZA, Cohen J, Crisp N, Evans T, et al. Challenges and opportunities for educating health professionals after the COVID-19 pandemic. Lancet. 2022;400:1539–56. Davis D, O’Brien MAT, Freemantle N, Wolf FM, Mazmanian P, Taylor-Vaisey A. Impact of formal continuing medical education: do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? JAMA. 1999;282:867–74. Mueller MR, Croghan IT, Schroeder DR, Bhuiyan MN, Ganesh R, Mohabbat AB, et al. Physician preferences for online and in-person continuing medical education: a cross-sectional study. BMC Med Educ. 2024;24:1142. McMahon GT. Accredited continuing medical education delivers: evidence of value, trust, and impact across the healthcare system. J CME. 2025;14:2584927. Vallée A, Blacher J, Cariou A, Sorbets E. Blended learning compared to traditional learning in medical education: systematic review and meta-analysis. J Med Internet Res. 2020;22:e16504. Kirkpatrick DL, Kirkpatrick JD. Evaluating training programs: the four levels. 3rd ed. San Francisco: Berrett-Koehler; 2006. Cervero RM, Gaines JK. The impact of CME on physician performance and patient health outcomes: an updated synthesis of systematic reviews. J Contin Educ Health Prof. 2015;35:131–8. Younies H, Berham B, Smith P. Perceptions of continuing medical education, professional development, and organizational support in the United Arab Emirates. J Contin Educ Health Prof. 2010;30:251–6. Shehab A, Elnour A, Al Sowaidi S, Abdulle A. Continuing professional development evaluation: two rapid review courses in nephrology and rheumatology. Oman Med J. 2012;27:402–7. Cervero RM, Gaines JK. Continuing medical education and continuing professional development: effectiveness revisited. J Contin Educ Health Prof. 2022;42:54–9. Kirkpatrick DL. Evaluating training programs: the four levels. 2nd ed. San Francisco: Berrett-Koehler; 1998. Sherman L, Aboulsoud S, Leon-Borquez R, Ming K, Yang DYD, Chappell K. An overview of global CME/CPD systems. Med Teach. 2024;46:1428–40. Additional Declarations No competing interests reported. Supplementary Files QuestionaireIDRRC.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers invited by journal 23 Apr, 2026 Editor assigned by journal 23 Apr, 2026 Editor invited by journal 21 Apr, 2026 Submission checks completed at journal 20 Apr, 2026 First submitted to journal 20 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9437333","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633515327,"identity":"90d65d2c-01ef-4006-89a8-d0280c9de714","order_by":0,"name":"Awad Al Essa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYHACxgMgkp8kPWAtkg0kazE4QKxy/gbmBwc+/KmTN76R/PAxD4OdPAP7Yfy6JQ6wGRyc2XbYcNuNNGNjHoZkwwaetARCrjI4zNtwgHHbjQQzaR4GZqDyHAO8OuQPsH84/OdPnf3mGenff/Mw1Ccw8L//gFeLwQEeg8MMbMyJGyRyzJh5GA4nMEjk4HeX4WGegoO9bYeTZ5x5Uyw5x+C4YZvEM/wOkzvevvHBjz91tv3t6Rs/vKmolufnT36A3xpmVHcyMLDhVz8KRsEoGAWjgBgAAOD9RJe+3bRpAAAAAElFTkSuQmCC","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":true,"prefix":"","firstName":"Awad","middleName":"Al","lastName":"Essa","suffix":""},{"id":633515328,"identity":"52630523-2875-4562-a406-ff5b8fbf7bcb","order_by":1,"name":"S. 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Ensuring that HCPs maintain up-to-date knowledge is essential for delivering safe, effective, and evidence-based patient care. Consequently, CME programs are widely implemented to facilitate knowledge acquisition and improve clinical performance and patient outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent evidence suggests that the effectiveness of CME is influenced by instructional design, interactivity, and contextual relevance. Contemporary systematic reviews indicate that interactive, practice-oriented, and digitally supported CME interventions are more likely to produce meaningful improvements in knowledge and clinical performance compared to traditional didactic approaches [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, the increasing integration of online and blended learning modalities has expanded access to CME and demonstrated comparable or superior knowledge gains relative to face-to-face formats [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe evaluation of CME effectiveness is commonly guided by frameworks such as Donald Kirkpatrick\u0026rsquo;s model, which conceptualizes outcomes across multiple levels, including reaction, learning (knowledge acquisition), behavior, and results. Within this framework, knowledge acquisition represents a fundamental and measurable outcome, serving as a prerequisite for subsequent behavioral and clinical improvements [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, recent literature highlights that many CME evaluations continue to rely on self-reported outcomes rather than objective measures of knowledge gain, limiting the robustness of conclusions regarding effectiveness [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the United Arab Emirates (UAE), CME is a mandatory requirement for licensure renewal, reflecting its central role in maintaining healthcare quality. Substantial investments are made in CME activities, including conferences, workshops, and accredited educational programs. These initiatives aim to enhance professional knowledge and align clinical practice with current evidence. Nevertheless, concerns have been raised regarding variability in CME quality, alignment with learners\u0026rsquo; needs, and the extent to which such programs achieve measurable learning outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough CME is generally assumed to improve knowledge, recent global evidence presents mixed findings regarding the magnitude and sustainability of knowledge gains. Some studies report significant short-term improvements in knowledge following CME interventions, while others demonstrate limited or context-dependent effects, particularly when programs lack alignment with practice needs or fail to incorporate active learning strategies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, there is growing recognition that combining objective knowledge assessments with learner perceptions provides a more comprehensive evaluation of CME effectiveness [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the widespread implementation and mandatory nature of CME in the UAE, there is limited recent empirical evidence specifically examining objective knowledge acquisition outcomes among CME participants. Existing studies in the region have predominantly focused on satisfaction and perceived effectiveness rather than rigorously measured learning gains. Moreover, few studies have employed pre\u0026ndash;post knowledge assessment designs or explored differences in knowledge acquisition across diverse groups of healthcare professionals within CME settings. This gap limits the ability of educators and policymakers to optimize CME design and ensure its educational impact.\u003c/p\u003e \u003cp\u003eThis study is part of a larger project evaluating CME activities based on Kirkpatrick\u0026rsquo;s model of training evaluation, with the present analysis situated at Level 2 (learning) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The study aims to evaluate the effectiveness of CME programs in enhancing knowledge acquisition among healthcare professionals, using objective pre- and post-program knowledge measures alongside participant-reported perceptions of learning.\u003c/p\u003e \u003cp\u003eResearch Questions\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo what extent do CME programs lead to measurable improvements in healthcare professionals\u0026rsquo; knowledge?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat is the magnitude of change in knowledge following participation in CME activities?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAre there differences in knowledge acquisition across different groups of healthcare professionals?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHow do participants perceive the knowledge gained from CME programs?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study forms part of a broader mixed-methods project, with the current report focusing specifically on the quantitative evaluation of knowledge acquisition among healthcare professionals (HCPs) attending Continuing Medical Education (CME) programs. The study was conducted in the United Arab Emirates, a Middle Eastern country characterized by a multicultural healthcare workforce and mandatory CME requirements for professional license renewal.\u003c/p\u003e \u003cp\u003eFour CME programs accredited by a national university were purposively selected for inclusion: an Acute Coronary Syndrome course, an Infectious Diseases course, a Cardio-rheumatology review, and a Respiratory rapid review course. For each program, detailed information was obtained, including date, duration, topic, expected attendance, and actual attendance. All programs were fee-based, industry-independent, and nationally recognized for license renewal, and participants were drawn from both public and private healthcare sectors. Program organizers were contacted prior to data collection and provided consent for inclusion of their CME activities in the study. They were also asked to supply relevant program information, including learning objectives, agendas, expected outcomes, and suggested assessment questions. The questionnaires were adapted for each CME program to ensure alignment with the specific content delivered.\u003c/p\u003e \u003cp\u003eThe quantitative component utilized a pre\u0026ndash;post study design to measure changes in participants\u0026rsquo; knowledge before and after CME participation. The study was conceptually informed by Donald Kirkpatrick\u0026rsquo;s evaluation framework, specifically Level 2 (learning), which focuses on knowledge acquisition as a key indicator of educational effectiveness.\u003c/p\u003e \u003cp\u003eParticipants included a multidisciplinary group of HCPs, comprising physicians, nurses, pharmacists, and other allied health professionals. A non-probability convenience sampling strategy was adopted, whereby all attendees of the selected CME programs during the study period were invited to participate. Inclusion criteria required attendance at one of the selected CME programs and completion of both pre- and post-CME knowledge assessments. Participants with incomplete responses or those who did not attend the full CME session were excluded. This approach allowed for the inclusion of all eligible participants within the natural educational setting while maximizing response rates.\u003c/p\u003e \u003cp\u003eData collection focused on the assessment of knowledge acquisition using structured pre- and post-CME questionnaires administered immediately before and after each program. Participants were recruited at the beginning of each CME program and provided written informed consent prior to participation. Data was collected using self-administered questionnaires. The questionnaire was paper-based and distributed to participants at the registration desk before the CME activities started; completion was voluntary and anonymous. The assessment tools consisted of content-specific questions aligned with the learning objectives of each CME program. These questions were initially developed by CME program faculty based on key concepts covered in the sessions and were subsequently reviewed and validated by a panel of subject matter experts, chaired by a professor of internal medicine at the College of Medicine, United Arab Emirates University. A sample of the questionnaire (pre- and post-knowledge test) for one of the CME events is provided in Supplementary File 1. The same or equivalent questions were used in both pre- and post-tests to ensure comparability. Each participant was assigned a unique code to link pre- and post-test responses while maintaining anonymity. Participants\u0026rsquo; responses were scored, and total knowledge scores were calculated for everyone before and after the intervention.\u003c/p\u003e \u003cp\u003eThe validity of the assessment instruments was supported through expert review to ensure alignment with program objectives and content relevance, thereby enhancing content validity. Reliability was strengthened by using consistent pre- and post-test formats across participants and standardized administration procedures, ensuring comparability of measurements over time.\u003c/p\u003e \u003cp\u003eIn addition to objective knowledge assessment, participants were asked to estimate the proportion of new knowledge gained from the CME program and to report perceived changes in their understanding of the topic. These measures provided complementary insights into perceived knowledge acquisition.\u003c/p\u003e \u003cp\u003eA target sample of at least 200 participants completing both pre- and post-assessments was set. The pre-CME questionnaire was distributed to all 334 attendees across the four programs, with 302 participants (88%) returning the pre-test questionnaires. Response rates varied by program but remained high overall, reflecting strong participant engagement.\u003c/p\u003e \u003cp\u003eThe primary outcome variable was knowledge acquisition, operationalized as the difference between pre- and post-CME knowledge scores. Secondary variables included pre-test scores, post-test scores, change in knowledge scores (Δ scores), and self-reported perceived knowledge gain. Independent variables included participants\u0026rsquo; professional category and demographic characteristics, such as years of experience and workplace setting.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e for this study was obtained from the Research Ethics Committee of the British University in Dubai and the ethics committee of the UAE university. Both committees granted permission to conduct the study, access accreditation data, and collect information from participants. Written informed consent was obtained from all participants. Confidentiality and anonymity were strictly maintained, and all data were reported in aggregate form.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eParticipants\u0026rsquo; responses to the pre- and post-test assessments were entered into an Excel spreadsheet, coded using unique identifiers, and then combined for analysis using IBM SPSS Statistics version 26. Descriptive statistics were used to summaries the data, with means and standard deviations calculated for pre- and post-test knowledge scores, and frequencies and percentages used to describe categorical variables.\u003c/p\u003e \u003cp\u003eInferential analysis was conducted to evaluate changes in knowledge following CME participation. Paired-sample t-tests were used to compare pre- and post-CME knowledge scores and determine the statistical significance of observed differences. Subgroup analyses were also performed to examine variations in knowledge acquisition across different professional groups. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eAdditional analyses included cross-tabulation to explore relationships between participant characteristics and knowledge gain. Self-reported measures of knowledge acquisition were analyzed descriptively and compared with objective assessment results to provide a more comprehensive evaluation of learning outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 302 healthcare professionals (HCPs) participated in this study. Of these, 254 (84.1%) completed the pre-test, 216 (71.5%) completed the post-test, and 191 participants completed both assessments and were included in the paired analysis.\u003c/p\u003e \u003cp\u003e Participation in the CME programs was associated with a statistically significant improvement in knowledge scores. The mean score increased from 1.78 (SD\u0026thinsp;=\u0026thinsp;1.37) pre-CME to 3.07 (SD\u0026thinsp;=\u0026thinsp;1.22) post-CME, representing a mean difference of 1.29 (95% CI: 1.09\u0026ndash;1.50) (t(190)\u0026thinsp;=\u0026thinsp;12.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings indicate a substantial and consistent gain in knowledge following CME participation.\u003c/p\u003e \u003cp\u003eKnowledge improvement was observed across all professional groups. The magnitude of gain varied, with nurses demonstrating the largest improvement (mean increase\u0026thinsp;=\u0026thinsp;1.6), followed by pharmacists and other HCPs (1.4 each), and physicians (0.9). Despite these differences, all groups showed statistically significant improvement, indicating that the CME programs were effective across a multidisciplinary audience.\u003c/p\u003e \u003cp\u003eAt the item-response level (n\u0026thinsp;=\u0026thinsp;955 responses), analysis of knowledge change patterns revealed that 31.6% of responses reflected positive change, where incorrect or \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; answers were converted to correct responses after the CME programs. In contrast, 54.6% of responses showed no change, and 13.8% reflected negative change. These findings suggest that while a meaningful proportion of participants experienced true knowledge acquisition, a substantial proportion did not demonstrate measurable change, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the Item Analysis for the participant\u0026rsquo;s answers to pre- and post-CME knowledge test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eItem Analysis for the participant\u0026rsquo;s answers to pre- and post-CME knowledge questions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge Change Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-CME Answer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-CME Answer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo change in knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePositive change in knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNegative change in knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrand total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe distribution of knowledge changes varied across professions as illustrated in Table 2. The proportion of participants demonstrating positive change was highest among pharmacists (38.7%), followed by nurses (35.4%), other HCPs (36.7%), and physicians (24.8%). Across all groups, however, the largest proportion remained within the \u0026ldquo;no change\u0026rdquo; category, reinforcing variability in learning outcomes.\u0026nbsp;\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCross tabulation for participants\u0026rsquo; profession and change in knowledge after the CME programs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eChange in Knowledge\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfession\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePositive change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDoctor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% within profession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNurse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% within profession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePharmacist\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% within profession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther HCPs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% within profession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% within Profession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther analysis showed that motivation for attending CME (i.e., attending solely to obtain CME credit hours) was not significantly associated with knowledge gain (χ\u0026sup2;(2, N\u0026thinsp;=\u0026thinsp;185)\u0026thinsp;=\u0026thinsp;2.06, p\u0026thinsp;=\u0026thinsp;0.356), suggesting that learning outcomes were independent of extrinsic motivation.\u003c/p\u003e \u003cp\u003eParticipants\u0026rsquo; self-reported data supported the objective findings. On average, participants estimated that 55.6% (SD\u0026thinsp;=\u0026thinsp;23.6) of the CME content represented new knowledge, indicating substantial perceived learning. In addition, participants reported a high likelihood of applying this knowledge in practice, with an estimated 59.9% of their patients potentially benefiting, a mean strategy change score of 5.28/7, and a strong intention to share knowledge with colleagues (mean\u0026thinsp;=\u0026thinsp;5.84/7).\u003c/p\u003e \u003cp\u003eOverall, the results demonstrate that CME participation leads to significant knowledge acquisition, supported by both objective assessment and participant perception, although the extent of learning varies across individuals and professional groups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This study evaluated the effectiveness of accredited Continuing Medical Education (CME) programs in enhancing knowledge acquisition among healthcare professionals (HCPs) and demonstrated a statistically significant improvement in knowledge scores following participation. The increase in mean scores from 1.78 to 3.07 reflects a substantial gain in knowledge, supported by both objective pre\u0026ndash;post assessments and participant-reported outcomes. Importantly, knowledge improvement was observed across all professional groups, including physicians, nurses, pharmacists, and other HCPs, indicating that CME programs were broadly effective in a multidisciplinary context. However, the magnitude of improvement varied, with nurses and pharmacists demonstrating greater gains compared to physicians. At the item-response level, approximately one-third of responses reflected positive knowledge change, confirming that a meaningful proportion of learning occurred as a direct result of CME participation. Participants further reported that more than half of the CME content represented new knowledge, reinforcing the effectiveness of these programs in addressing knowledge gaps.\u003c/p\u003e \u003cp\u003eThese findings are consistent with recent systematic reviews suggesting that CME interventions can produce modest to moderate improvements in knowledge and professional performance, particularly when educational activities are well designed and aligned with learner needs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The magnitude of knowledge gain observed in this study is comparable to that reported in contemporary evaluations of both traditional and technology-enhanced CME, which have demonstrated that interactive and blended learning approaches are associated with improved learning outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The observed variation in knowledge acquisition across professional groups is also supported by prior literature, which highlights the influence of baseline knowledge, professional role, and relevance of content on learning outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In particular, greater gains among nurses and pharmacists may reflect closer alignment between CME content and their immediate clinical responsibilities or comparatively lower baseline knowledge levels.\u003c/p\u003e \u003cp\u003eDespite these positive findings, the observation that more than half of responses showed no change in knowledge highlights an important limitation in CME effectiveness. This finding aligns with existing evidence indicating that not all participants benefit equally from CME activities and that passive or poorly targeted educational interventions may have limited impact [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It suggests that while CME programs can be effective overall, their impact is not uniform, and there remains considerable scope for improving instructional design and learner engagement.\u003c/p\u003e \u003cp\u003eThe findings of this study have important implications for CME design, policy, and practice. From an educational perspective, the coexistence of significant knowledge gains and a substantial proportion of unchanged responses underscores the need for more learner-centered approaches that actively engage participants and address their specific learning needs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Incorporating interactive strategies such as case-based discussions, simulations, and problem-solving activities may enhance knowledge retention and applicability. Furthermore, the integration of objective knowledge assessments alongside self-reported learning, as demonstrated in this study, provides a more comprehensive evaluation of CME effectiveness and should be more widely adopted [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a policy perspective, the mandatory nature of CME highlights the importance of ensuring that such programs deliver measurable educational value. While current systems emphasize participation and accumulation of credit hours, the findings suggest that greater emphasis should be placed on outcome-based evaluation, particularly the measurement of knowledge acquisition. Accrediting bodies may consider incorporating requirements for pre\u0026ndash;post assessment or other objective measures of learning as part of CME accreditation processes. Such an approach would enhance accountability and ensure that investments in CME translate into meaningful improvements in professional competence.\u003c/p\u003e \u003cp\u003eFrom a clinical practice standpoint, the results suggest that CME contributes to improved knowledge that is likely to influence clinical decision-making and patient care. This is supported by participants\u0026rsquo; reported intentions to modify management strategies and share acquired knowledge with colleagues. However, the absence of a significant relationship between attending CME for credit hours and knowledge gain indicates that external motivations alone do not drive learning outcomes. Instead, the quality, relevance, and engagement level of the educational content appear to be the primary determinants of effective knowledge acquisition.\u003c/p\u003e \u003cp\u003eThis study has several strengths, including the use of a pre\u0026ndash;post design with objective knowledge assessment, which strengthens internal validity, and the inclusion of a large, multidisciplinary sample, which enhances generalizability. The integration of both objective and subjective measures of knowledge acquisition provides a comprehensive evaluation of learning outcomes, while the detailed analysis of response patterns offers deeper insight into how knowledge changes at the individual level.\u003c/p\u003e \u003cp\u003eNevertheless, several limitations should be acknowledged. The use of a convenience sample may limit the generalizability of findings beyond the study setting. The assessment of knowledge was limited to short-term outcomes, and long-term retention of knowledge was not evaluated. Additionally, the study focused on learning outcomes corresponding to Level 2 of Donald Kirkpatrick and did not assess higher-level outcomes such as behavior change or patient outcomes. Variations in assessment content across CME programs may also have influenced the results, and self-reported measures are subject to potential response bias.\u003c/p\u003e \u003cp\u003eOverall, this study provides robust evidence that CME programs can lead to significant knowledge acquisition among healthcare professionals, although the extent of learning varies across participants. These findings highlight the need for more targeted, outcome-driven, and learner-centered CME design, supported by policy frameworks that priorities measurable educational impact.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides robust evidence that CME programs lead to significant and measurable improvements in healthcare professionals\u0026rsquo; knowledge, confirming their value as an effective educational strategy. The consistency of knowledge gains across professional groups underscores the relevance of CME in supporting multidisciplinary learning and maintaining clinical competence.\u003c/p\u003e \u003cp\u003eHowever, the variability in learning outcomes highlights a critical need to move beyond traditional, attendance-based models of CME toward outcome-driven, learner-centered approaches. Embedding objective assessment of knowledge acquisition, aligning content with learners\u0026rsquo; needs, and adopting interactive and practice-oriented educational strategies are essential to maximize impact.\u003c/p\u003e \u003cp\u003eAt a policy level, these findings strongly support the integration of mandatory outcome evaluation within CME accreditation systems, ensuring that CME investments translate into demonstrable learning gains. Strengthening the design and evaluation of CME programs will be key to enhancing their contribution to clinical practice and, ultimately, to improving patient care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Research Ethical Committee of the British University in Dubai and from the ethical committee of the national university that accredited the CME programs. The study was conducted in accordance with the Declaration of Helsinki and relevant institutional ethical guidelines. Written informed consent was obtained from all participants prior to data collection. Participation was voluntary, and confidentiality and anonymity were assured; data are reported in aggregate form only.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable. The manuscript does not contain any individual person’s identifiable data, images, or videos.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author (AA) on reasonable request.\u003c/p\u003e\n\u003cp\u003eClinical Trial Number\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work from any public, commercial, or not-for-profit funding agency.\u003c/p\u003e\n\u003cp\u003eAuthors’ contributions\u003c/p\u003e\n\u003cp\u003eThe study was conceived and designed by AA, who also led the development of the questionnaire and interview guide, as well as data collection, analysis, interpretation, and critical appraisal of the findings. AA prepared the initial draft of the manuscript, while SAC and MM contributed to substantial revisions for important intellectual content. All authors reviewed and approved the final manuscript and accept responsibility for all aspects of the work.\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank all healthcare professionals who participated in the survey and interviews. They also express their appreciation to the organizers and administrative staff of the four CME programs for their valuable support in facilitating data collection. The authors are grateful to the CME event faculty who developed the pre- and post-test questions, as well as the content experts who reviewed and validated these assessment tools. In addition, the authors acknowledge the support of the Medical Education Department at the College of Medicine and Health Sciences, United Arab Emirates University.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFrenk J, Chen L, Bhutta ZA, Cohen J, Crisp N, Evans T, et al. Challenges and opportunities for educating health professionals after the COVID-19 pandemic. Lancet. 2022;400:1539\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis D, O\u0026rsquo;Brien MAT, Freemantle N, Wolf FM, Mazmanian P, Taylor-Vaisey A. Impact of formal continuing medical education: do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? JAMA. 1999;282:867\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMueller MR, Croghan IT, Schroeder DR, Bhuiyan MN, Ganesh R, Mohabbat AB, et al. Physician preferences for online and in-person continuing medical education: a cross-sectional study. BMC Med Educ. 2024;24:1142.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcMahon GT. Accredited continuing medical education delivers: evidence of value, trust, and impact across the healthcare system. J CME. 2025;14:2584927.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVall\u0026eacute;e A, Blacher J, Cariou A, Sorbets E. Blended learning compared to traditional learning in medical education: systematic review and meta-analysis. J Med Internet Res. 2020;22:e16504.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKirkpatrick DL, Kirkpatrick JD. Evaluating training programs: the four levels. 3rd ed. San Francisco: Berrett-Koehler; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCervero RM, Gaines JK. The impact of CME on physician performance and patient health outcomes: an updated synthesis of systematic reviews. J Contin Educ Health Prof. 2015;35:131\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYounies H, Berham B, Smith P. Perceptions of continuing medical education, professional development, and organizational support in the United Arab Emirates. J Contin Educ Health Prof. 2010;30:251\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShehab A, Elnour A, Al Sowaidi S, Abdulle A. Continuing professional development evaluation: two rapid review courses in nephrology and rheumatology. Oman Med J. 2012;27:402\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCervero RM, Gaines JK. Continuing medical education and continuing professional development: effectiveness revisited. J Contin Educ Health Prof. 2022;42:54\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKirkpatrick DL. Evaluating training programs: the four levels. 2nd ed. San Francisco: Berrett-Koehler; 1998.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSherman L, Aboulsoud S, Leon-Borquez R, Ming K, Yang DYD, Chappell K. An overview of global CME/CPD systems. Med Teach. 2024;46:1428\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Continuing Medical Education, Knowledge Acquisition, Pre–Post Study Design, Healthcare Professionals, Educational Measurement, Learning Outcomes, Kirkpatrick Model, Continuing Professional Development","lastPublishedDoi":"10.21203/rs.3.rs-9437333/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9437333/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eContinuing Medical Education (CME) is widely implemented to enhance healthcare professionals\u0026rsquo; knowledge and maintain clinical competence. However, evidence regarding objective knowledge acquisition, particularly using pre\u0026ndash;post assessment designs, remains limited. This study aimed to evaluate the effectiveness of CME programs in improving knowledge among healthcare professionals using objective and self-reported measures.\u003c/p\u003e \u003cp\u003eThis study evaluates CME activities using Kirkpatrick\u0026rsquo;s model of training evaluation, with the present analysis focusing on Level 2 (learning). A quantitative pre\u0026ndash;post design was conducted among healthcare professionals attending four accredited CME programs. Participants completed structured knowledge assessments immediately before and after the programs. A total of 191 participants completed both assessments and were included in the analysis. Knowledge acquisition was measured as the change in test scores, and subgroup analyses were performed across professional groups. Paired-sample t-tests and descriptive statistics were used for analysis.\u003c/p\u003e \u003cp\u003eKnowledge scores increased significantly from 1.78 (SD\u0026thinsp;=\u0026thinsp;1.37) pre-CME to 3.07 (SD\u0026thinsp;=\u0026thinsp;1.22) post-CME (mean difference\u0026thinsp;=\u0026thinsp;1.29, 95% CI: 1.09\u0026ndash;1.50; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Improvements were observed across all professional groups, with the largest gains among nurses. At the item level, 31.6% of responses showed positive knowledge change, while 54.6% showed no change and 13.8% showed negative change. Participants reported that 55.6% of the content represented new knowledge, with high anticipated application in clinical practice. No significant association was found between attending CME for credit hours and knowledge gain (p\u0026thinsp;=\u0026thinsp;0.356).\u003c/p\u003e \u003cp\u003eCME programs were associated with significant improvements in healthcare professionals\u0026rsquo; knowledge, supporting their role as an effective educational strategy. However, variability in learning outcomes highlights the need to shift from attendance-based models toward outcome-driven, learner-centered CME approaches. Incorporating objective assessment of knowledge acquisition into CME evaluation frameworks may enhance educational impact and accountability.\u003c/p\u003e","manuscriptTitle":"Beyond Attendance: Evaluating Knowledge Acquisition in Continuing Medical Education Using Objective Pre–Post Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 00:26:17","doi":"10.21203/rs.3.rs-9437333/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"130566812123298144837796612657372961173","date":"2026-05-10T23:28:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294256566388482173864607207043203729590","date":"2026-05-10T17:38:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-23T05:04:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T04:59:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-21T16:15:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-20T19:28:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-04-20T19:24:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a330821-03f3-415f-b363-3b33bd81e7c5","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"130566812123298144837796612657372961173","date":"2026-05-10T23:28:06+00:00","index":51,"fulltext":""},{"type":"reviewerAgreed","content":"294256566388482173864607207043203729590","date":"2026-05-10T17:38:41+00:00","index":50,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T00:26:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 00:26:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9437333","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9437333","identity":"rs-9437333","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}