<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Med Educ</journal-id><journal-id journal-id-type="publisher-id">mededu</journal-id><journal-id journal-id-type="index">20</journal-id><journal-title>JMIR Medical Education</journal-title><abbrev-journal-title>JMIR Med Educ</abbrev-journal-title><issn pub-type="epub">2369-3762</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v11i1e64767</article-id><article-id pub-id-type="doi">10.2196/64767</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>Evolution of Learning Styles in Surgery Comparing Residents and Teachers: Cross-Sectional Study</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Gouvea Silva</surname><given-names>Gabriela</given-names></name><degrees>MD, MSc</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>da Silva Costa</surname><given-names>Carlos Dario</given-names></name><degrees>MD, MSc</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Cardoso Gon&#x00E7;alves</surname><given-names>Bruno</given-names></name><degrees>MD, MSc</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Vianney Saldanha Cidr&#x00E3;o Nunes</surname><given-names>Luiz</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Roberto dos Santos</surname><given-names>Emerson</given-names></name><degrees>MSc</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Almeida de Arnaldo Rodriguez Castro</surname><given-names>Natalia</given-names></name><degrees>MD, MSc</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>de Abreu Lima</surname><given-names>Alba Regina</given-names></name><degrees>MSc, PhD</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Sabadoto Brienze</surname><given-names>V&#x00E2;nia Maria</given-names></name><degrees>MSc, PhD</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Oliani</surname><given-names>Ant&#x00F4;nio H&#x00E9;lio</given-names></name><degrees>MD, MSc, PhD</degrees><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Andr&#x00E9;</surname><given-names>J&#x00FA;lio C&#x00E9;sar</given-names></name><degrees>MD, MSc, PhD</degrees><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff id="aff1"><institution>Center for Studies and Development of Health Education, Faculdade de Medicina de S&#x00E3;o Jos&#x00E9; do Rio Preto</institution><addr-line>Avenida Brigadeiro Faria Lima, 5416</addr-line><addr-line>S&#x00E3;o Jos&#x00E9; do Rio Preto</addr-line><country>Brazil</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Lesselroth</surname><given-names>Blake</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Moldovan</surname><given-names>Flaviu</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Olivier</surname><given-names>James</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Jani</surname><given-names>Mehul</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Gabriela Gouvea Silva, MD, MSc, Center for Studies and Development of Health Education, Faculdade de Medicina de S&#x00E3;o Jos&#x00E9; do Rio Preto, Avenida Brigadeiro Faria Lima, 5416, S&#x00E3;o Jos&#x00E9; do Rio Preto, 15090000, Brazil, 55 17982022252; <email>gouvea.g@hotmail.com</email></corresp></author-notes><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>8</day><month>5</month><year>2025</year></pub-date><volume>11</volume><elocation-id>e64767</elocation-id><history><date date-type="received"><day>25</day><month>07</month><year>2024</year></date><date date-type="rev-recd"><day>11</day><month>03</month><year>2025</year></date><date date-type="accepted"><day>06</day><month>04</month><year>2025</year></date></history><copyright-statement>&#x00A9; Gabriela Gouvea Silva, Carlos Dario da Silva Costa, Bruno Cardoso Gon&#x00E7;alves, Luiz Vianney Saldanha Cidr&#x00E3;o Nunes, Emerson Santos, Natalia Almeida de Arnaldo Rodriguez Castro, Alba Regina Abreu de Lima, V&#x00E2;nia Maria Sabadoto Brienze, Ant&#x00F4;nio H&#x00E9;lio Oliani, J&#x00FA;lio C&#x00E9;sar Andr&#x00E9;. Originally published in JMIR Medical Education (<ext-link ext-link-type="uri" xlink:href="https://mededu.jmir.org">https://mededu.jmir.org</ext-link>), 8.5.2025. </copyright-statement><copyright-year>2025</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Education, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://mededu.jmir.org/">https://mededu.jmir.org/</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://mededu.jmir.org/2025/1/e64767"/><abstract><sec><title>Background</title><p>Studies confirm a relationship between learning style and medical career choice in the learning style patterns observed in distinct types of residency programs. Such patterns can also be applied to general surgery, from medical school to the latest stages of training. Aligning teaching strategies with the predominant learning styles in surgical residency programs has the potential to make training more effective.</p></sec><sec><title>Objective</title><p>This study aimed to determine the learning styles of general surgery residents and professors in a Brazilian teaching hospital and compare the results with the existing literature.</p></sec><sec sec-type="methods"><title>Methods</title><p>This was a cross-sectional study conducted in a teaching hospital of a public university in Brazil. Thirty-four general surgery residents of any year of training and 30 professors participated in the study. Participants completed a sociodemographic survey and David Kolb&#x2019;s Learning Style Inventory. This was used to classify participants into one of four distinct types of learners: accommodating, diverging, assimilating, and converging. The relationship between sociodemographic data and learning styles was analyzed using the Fisher test, adjusted using the Bonferroni method, and the effect size was measured using the Cramer V test.</p></sec><sec sec-type="results"><title>Results</title><p>The learning style distribution was similar in both groups, with 43,75% diverging, 42,18% accommodating, 10.93% assimilating, and 3.12% converging styles. A significant relationship was found between sex and learning style (<italic>P</italic>=.049) and between age and learning style for professors (<italic>P</italic>=.029). The effect sizes were strong (0.46) and very strong (0.506).</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>The prevalence of learning styles among general surgery residents and professors at this Brazilian hospital differs from that observed in previous studies, with more diverging and accommodating learners and fewer converging learners, suggesting a shift in learning styles. Understanding learning styles is important for effective surgical training programs. Further research with larger and more diverse populations is needed to confirm these results and explore the factors contributing to the observed differences in learning styles.</p></sec></abstract><kwd-group><kwd>learning</kwd><kwd>general surgery</kwd><kwd>medical education</kwd><kwd>internship and residency</kwd><kwd>surgeons</kwd><kwd>Brazil</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><sec id="s1-1"><title>Background</title><p>The concept of learning styles was first developed at the beginning of 1960 as a result of the interest in individual differences while learning [<xref ref-type="bibr" rid="ref1">1</xref>]. According to Dunn [<xref ref-type="bibr" rid="ref2">2</xref>], everyone has a unique learning style, like a signature. In this prospect, adjusting the teaching to the different learning styles may help learners and improve educational outcomes. In the current literature, there are various models to determine the learning styles. There is a long and active discussion about whether learning styles are fixed or flexible, and to what extent the context can determine it [<xref ref-type="bibr" rid="ref3">3</xref>]. Adapting learning styles can enhance student engagement, motivation, and academic performance [<xref ref-type="bibr" rid="ref4">4</xref>]. Furthermore, the integration of technology and personalized learning approaches has shown promise in enhancing medical education [<xref ref-type="bibr" rid="ref5">5</xref>].</p><p>To provide a more comprehensive understanding, learning styles can be defined as the cognitive, affective, and physiological traits that serve as relatively stable indicators of how learners perceive, interact with, and respond to the learning environment [<xref ref-type="bibr" rid="ref6">6</xref>]. Empirical evidence supports the existence of learning styles, demonstrating that individuals exhibit consistent preferences and strengths in how they approach learning tasks. For example, some learners may excel in visual tasks, while others thrive in auditory or kinesthetic activities [<xref ref-type="bibr" rid="ref7">7</xref>].</p><p>The Kolb Experiential Learning Theory (ELT) is a prominent framework for understanding learning styles. The ELT posits that learning is a cyclical process involving four modes: concrete experience (CE), reflective observation (RO), abstract conceptualization (AC), and active experimentation (AE) [<xref ref-type="bibr" rid="ref8">8</xref>]. Individuals develop preferences for certain modes, leading to four distinct learning styles: converging (AC/AE), diverging (CE/RO), assimilating (AC/RO), and accommodating (CE/AE). The Kolb Learning Style Inventory (LSI) is a widely used tool for assessing these preferences. The validity of Kolb&#x2019;s work in the context of medical education has been demonstrated in numerous studies [<xref ref-type="bibr" rid="ref9">9</xref>-<xref ref-type="bibr" rid="ref13">13</xref>], which have found that medical students and professionals exhibit distinct learning style preferences that can influence their academic and professional performance.</p><p>Knowledge is the main domain of medical education, but outcomes strongly depend on other domains such as attitude, lifelong learning, and empathy; in surgery, some domains are central including resilience, craftsmanship, and decision-making, among other domains [<xref ref-type="bibr" rid="ref14">14</xref>].</p></sec><sec id="s1-2"><title>Research Gap and Problem Statement</title><p>Despite the established importance of learning styles in education, limited research has specifically examined their prevalence and impact within general surgery residency programs, particularly in diverse cultural and geographical settings. The clinical and surgical environments present unique challenges for both trainees and educators, requiring the development of complex skills and behaviors [<xref ref-type="bibr" rid="ref14">14</xref>]. Understanding how surgical residents learn is crucial for optimizing the training process and ensuring the development of competent and well-rounded surgeons.</p><p>Moreover, current surgical trainees come from diverse educational, cultural, ethnic, and gender backgrounds, and personal factors also influence their learning characteristics [<xref ref-type="bibr" rid="ref15">15</xref>]. Little is known about the teaching and learning preferences among surgeons and how they influence the effectiveness of training [<xref ref-type="bibr" rid="ref16">16</xref>]. Addressing this gap in knowledge is essential for designing effective and inclusive surgical training programs that cater to the diverse needs of learners. To this end, simulation-based surgical training has emerged as a valuable tool for enhancing technical skills and improving patient outcomes [<xref ref-type="bibr" rid="ref17">17</xref>].</p></sec><sec id="s1-3"><title>Research Aims and Objectives</title><p>Little is known about the teaching and learning preferences among surgeons and how they influence the effectiveness of training [<xref ref-type="bibr" rid="ref16">16</xref>]. Despite its relevance, studies investigating learning styles in the context of general surgery residency are scarce, especially in countries outside North America and Europe.</p><p>Therefore, to address the gaps in understanding learning styles in general surgery, particularly in diverse cultural and geographical settings, this study aims to (1) determine the learning styles of general surgery residents and professors in a Brazilian teaching hospital; (2) compare these findings with existing literature on learning styles in surgery; and (3) discuss the implications of these findings for surgical training programs.</p><p>By providing data from a Brazilian teaching hospital, we aim to contribute to a more comprehensive understanding of learning styles in surgical training and inform the development of more effective and inclusive surgical education strategies. This knowledge can inform the development of more effective and inclusive surgical education strategies, ultimately leading to better-prepared and more competent surgeons.</p></sec></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Study Design and Setting</title><p>This cross-sectional study was conducted in 2022 at the Hospital de Base de S&#x00E3;o Jos&#x00E9; do Rio Preto, a teaching hospital affiliated with Faculdade de Medicina de S&#x00E3;o Jos&#x00E9; do Rio Preto (a public university in S&#x00E3;o Paulo, Brazil).</p></sec><sec id="s2-2"><title>Participants and Recruitment</title><p>The study population consisted of general surgery residents in any year of training and hospital professors. All participants were over 18 years old and signed the free and informed consent form.</p></sec><sec id="s2-3"><title>Data Collection</title><p>Data collection involved two instruments: a sociodemographic survey and David Kolb&#x2019;s LSI. The sociodemographic survey collected information on participants&#x2019; age and sex, and years of residency (for residents) or teaching experience (for professors). The LSI is a validated tool that consists of 12 questions, each with four statements that the participants ranked from 1 to 4 according to their learning preferences. The LSI tool classifies the participants into one of four types of learners based on Kolb&#x2019;s learning cycle: (1) accommodating (learn primarily by experience), (2) diverging (learn by RO), (3) assimilating (learn by exploring associations and interrelationships), and (4) converging (learn by doing or trying things with practical results) [<xref ref-type="bibr" rid="ref18">18</xref>].</p><p>The LSI test was administered in a controlled environment, with a researcher present to provide instructions and clarify any doubts. Participants had 30 minutes to complete it. The sociodemographic survey was completed immediately after completing the LSI test.</p></sec><sec id="s2-4"><title>Statistical Analysis</title><sec id="s2-4-1"><title>Software</title><p>Data analysis was performed using the Statistical Package for the Social Sciences (SPSS), version 26.0 (IBM Corp.).</p></sec><sec id="s2-4-2"><title>Normality Check</title><p>Due to the relatively small sample size and the nature of the data, the Shapiro-Wilk test was used to assess the normality of continuous variables (age and years of experience).</p></sec><sec id="s2-4-3"><title>Statistical Tests</title><p>A <italic>P</italic> value &#x003C;.05 was considered statistically significant. The relationship between data was calculated using the Fisher test, adjusted by the Bonferroni method [<xref ref-type="bibr" rid="ref19">19</xref>]. The Fisher exact test was chosen due to the small sample size and the presence of categories with expected frequencies lower than 5 [<xref ref-type="bibr" rid="ref20">20</xref>]. The size effect was measured using Cramer V test, which indicates the grade of association between variables: the result is stronger as it approaches the value of 1 [<xref ref-type="bibr" rid="ref21">21</xref>].</p></sec><sec id="s2-4-4"><title>Power</title><p>The sample size was calculated using the formula for finite populations, considering a confidence level of 95%, a margin of error of 5%, and an expected prevalence of 50% for each learning style. The minimum sample size was 67 participants, and the total number of residents and professors was 80 [<xref ref-type="bibr" rid="ref22">22</xref>].</p></sec><sec id="s2-4-5"><title>Data Exclusion</title><p>Questionnaires that were responded to incorrectly according to Kolb&#x2019;s rules were discarded.</p></sec></sec><sec id="s2-5"><title>Ethical Considerations</title><p>The study was approved by the Research Ethics Committee of Faculdade de Medicina de S&#x00E3;o Jos&#x00E9; do Rio Preto (approval number: 12345/2022). All participants signed the free informed consent form. Data were anonymized.</p></sec><sec id="s2-6"><title>Recruitment</title><p>This study is grounded in Kolb&#x2019;s ELT, which posits that learning is a cyclical process involving four modes: CE, RO, AC, and AE [<xref ref-type="bibr" rid="ref23">23</xref>]. Individuals develop preferences for certain modes, leading to four distinct learning styles:</p><list list-type="bullet"><list-item><p>Converging: Individuals with this learning style excel in AC and AE. They are practical, enjoy problem-solving, and are skilled at applying theories to real-world situations.</p></list-item><list-item><p>Diverging: Individuals with this learning style excel in concrete CE and RO. They are imaginative, enjoy brainstorming, and are skilled at generating ideas.</p></list-item><list-item><p>Assimilating: Individuals with this learning style excel in AC and RO. They are logical, enjoy analyzing data, and are skilled at creating models and theories.</p></list-item><list-item><p>Accommodating: Individuals with this learning style excel in concrete CE and AE. They are hands-on, enjoy taking risks, and are skilled at implementing plans and getting things done.</p></list-item></list><p>Our logic model is based on the premise that aligning teaching strategies with the predominant learning styles of surgical residents and professors can enhance the effectiveness of surgical training. We hypothesize that by identifying the learning styles of our participants and tailoring instructional approaches accordingly, we can improve learning outcomes and promote a more engaging and inclusive learning environment.</p><p><xref ref-type="table" rid="table1">Table 1</xref> provides a more detailed overview of the four learning styles, including concrete examples of learning activities and instructional approaches that are best suited for each style.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Learning styles, characteristics, and instructional approaches. Source: [<xref ref-type="bibr" rid="ref8">8</xref>].</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Learning style</td><td align="left" valign="bottom">Characteristics</td><td align="left" valign="bottom">Example learning activities</td><td align="left" valign="bottom">Example instructional approaches</td></tr></thead><tbody><tr><td align="left" valign="top">Converging</td><td align="left" valign="top">Practical, problem-solver, applies theories</td><td align="left" valign="top">Simulation-based training, case studies</td><td align="left" valign="top">Problem-based learning, hands-on workshops</td></tr><tr><td align="left" valign="top">Diverging</td><td align="left" valign="top">Imaginative, brainstormer, generates ideas</td><td align="left" valign="top">Group discussions, reflective writing</td><td align="left" valign="top">Mentoring, collaborative projects</td></tr><tr><td align="left" valign="top">Assimilating</td><td align="left" valign="top">Logical, analytical, creates models</td><td align="left" valign="top">Literature reviews, data analysis</td><td align="left" valign="top">Lectures, seminars</td></tr><tr><td align="left" valign="top">Accommodating</td><td align="left" valign="top">Hands-on, risk-taker, implements plans</td><td align="left" valign="top">Surgical procedures, clinical rotations</td><td align="left" valign="top">Apprenticeship, on-the-job training</td></tr></tbody></table></table-wrap><p>All general surgery residents were invited to answer printed free and informed consent form and the LSI&#x2019;s test, in person. The same was done with the faculty members. The questionnaires were then collected and transformed into digital archives, processed in digital tables after codification.</p></sec><sec id="s2-7"><title>Statistical Analysis</title><sec id="s2-7-1"><title>Power</title><p>The sample size was calculated using the formula for finite populations, considering a confidence level of 95%, a margin of error of 5%, and an expected prevalence of 50% for each learning style. The minimum sample size was 67 participants, and the total number of residents and professors was 80 [<xref ref-type="bibr" rid="ref22">22</xref>].</p></sec></sec></sec><sec id="s3" sec-type="results"><title>Results</title><p>A total of 64 participants (34 residents and 30 professors) were included in this study. The sociodemographic characteristics of the participants are presented in <xref ref-type="table" rid="table2">Table 2</xref>. Among the 34 residents, 18 (52.9%) were male and 16 (47.1%) were female. Most residents (91.2%, 31/34) were under 30 years of age. Among the 30 professors, 24 (80%) were male, and 6 (20%) were female, and most of them (17/30, 56.7%) were between 40 and 70 years of age. All professors graduated from universities when traditional teaching methods (ie, primarily lecture-based instruction with limited student interaction) were used, whereas 47% of the residents graduated from universities that used active or mixed teaching methods (ie, incorporating strategies such as problem-based learning, group work, and case studies to promote student engagement).</p><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Sociodemographic characteristics of participants.</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Characteristics</td><td align="left" valign="bottom">Residents (n=34)<break/>N (%)</td><td align="left" valign="bottom">Professors (n=30)<break/>N (%)</td></tr></thead><tbody><tr><td align="left" valign="top">Age (years)</td><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="char" char="." valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x003C;30</td><td align="char" char="." valign="top">31 (91.2)</td><td align="char" char="." valign="top">2 (6.7)</td></tr><tr><td align="char" char="." valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>30&#x2010;39</td><td align="left" valign="top">3 (8.8)</td><td align="left" valign="top">11 (36.7)</td></tr><tr><td align="char" char="." valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>40&#x2010;70</td><td align="left" valign="top">0 (0)</td><td align="left" valign="top">17 (56.7)</td></tr><tr><td align="left" valign="top">Sex</td><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Male</td><td align="char" char="." valign="top">18 (52.9)</td><td align="char" char="." valign="top">24 (80)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Female</td><td align="char" char="." valign="top">16 (47.1)</td><td align="char" char="." valign="top">6 (20)</td></tr><tr><td align="left" valign="top">Teaching method used at the University of origin</td><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Traditional</td><td align="char" char="." valign="top">18 (52.9)</td><td align="char" char="." valign="top">30 (100)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Active or mixed</td><td align="left" valign="top">16 (47.1)</td><td align="left" valign="top">0 (0)</td></tr></tbody></table></table-wrap><p>The distribution of Kolb&#x2019;s learning styles is presented in <xref ref-type="table" rid="table3">Table 3</xref> and <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. The most prevalent learning styles were diverging (18/34) in the residents&#x2019; group and accommodating (17/30) in the professors&#x2019; group.</p><table-wrap id="t3" position="float"><label>Table 3.</label><caption><p>Learning styles among surgery groups.</p></caption><table id="table3" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Learning styles</td><td align="left" valign="bottom">Residents<break/>N (%)</td><td align="left" valign="bottom">Professors<break/>N (%)</td><td align="left" valign="bottom">Total<break/>N (%)</td></tr></thead><tbody><tr><td align="left" valign="top">Converging</td><td align="left" valign="top">1/34 (2.94)</td><td align="left" valign="top">1/30 (3.33)</td><td align="left" valign="top">2/64 (3.12)</td></tr><tr><td align="left" valign="top">Assimilating</td><td align="left" valign="top">5/34 (14.7)</td><td align="left" valign="top">2/30 (6.7)</td><td align="left" valign="top">7/64 (10.93)</td></tr><tr><td align="left" valign="top">Accommodating</td><td align="left" valign="top">10/34 (29.4)</td><td align="left" valign="top">17/30 (56.7)</td><td align="left" valign="top">27/64 (42.18)</td></tr><tr><td align="left" valign="top">Diverging</td><td align="left" valign="top">18/34 (52.9)</td><td align="left" valign="top">10/30 (33.3)</td><td align="left" valign="top">28/64 (43.75)</td></tr></tbody></table></table-wrap><p>The relationship between sociodemographic data and learning styles was analyzed using the Fisher exact test (<xref ref-type="table" rid="table4">Table 4</xref>). A significant association was found between sex and learning style (<italic>P</italic>=.049; Cramer V=0.46), indicating a strong effect size. However, determining which specific categories were significantly different using the Bonferroni post-hoc test was not possible. Among professors, a significant relationship was observed between age and learning style (<italic>P</italic>=.029; Cramer V=0.506), suggesting a very strong effect size. However, specific age groups that differed significantly could not be identified with the Bonferroni post-hoc test, possibly due to the small sample size.</p><table-wrap id="t4" position="float"><label>Table 4.</label><caption><p>Relationship between sociodemographic data and learning styles.</p></caption><table id="table4" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Variables</td><td align="left" valign="bottom"><italic>P</italic> value (Fisher exact test)</td><td align="left" valign="bottom">Effect sizes (Cramer V)</td></tr></thead><tbody><tr><td align="left" valign="top">Sex</td><td align="left" valign="top">0.049<sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup></td><td align="left" valign="top">0.46 (strong)</td></tr><tr><td align="left" valign="top">Age (residents)</td><td align="left" valign="top">0.999</td><td align="left" valign="top">0.12 (weak)</td></tr><tr><td align="left" valign="top">Age (professors)</td><td align="left" valign="top">0.029<sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup></td><td align="left" valign="top">0.506 (very strong)</td></tr><tr><td align="left" valign="top">Teaching method used at the university of origin (residents)</td><td align="left" valign="top">0.999</td><td align="left" valign="top">0.08 (weak)</td></tr></tbody></table><table-wrap-foot><fn id="table4fn1"><p><sup>a</sup>Statistically significant at P&#x003C;.05</p></fn></table-wrap-foot></table-wrap></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><sec id="s4-1"><title>Principal Findings</title><p>Our study, utilizing Kolb&#x2019;s LSI, identified the distribution of four learning styles among general surgery residents and professors at a Brazilian teaching hospital. These learning styles are:</p><list list-type="bullet"><list-item><p>Diverging: Learners who excel in CE and RO, are imaginative, and generate ideas effectively.</p></list-item><list-item><p>Accommodating: Learners who excel in CE and AE, are hands-on, and enjoy implementing plans.</p></list-item><list-item><p>Assimilating: Learners who excel in AC and RO, are logical, and create models and theories.</p></list-item><list-item><p>Converging: Learners who excel in AC and AE, are practical, and apply theories to real-world situations.</p></list-item></list><p>The most prevalent learning styles were diverging (52.9%) in the residents&#x2019; group and accommodating (56.7%) in the professors&#x2019; group (<xref ref-type="table" rid="table2">Table 2</xref> and <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). A significant association was found between sex and learning style (<italic>P</italic>=.049; Cramer V=0.46), indicating a strong effect size. Among professors, a significant relationship was observed between age and learning style (<italic>P</italic>=0.029; Cramer V=0.506), suggesting a very strong effect size.</p><p><xref ref-type="table" rid="table2">Table 2</xref> and <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref> show that while diverging was the most common style among residents and accommodating was most common among professors, the overall learning style distribution was relatively similar between the two groups. This convergence, where both residents and professors exhibit a blend of diverging and accommodating tendencies, can potentially facilitate both teaching and learning [<xref ref-type="bibr" rid="ref16">16</xref>]. The shared presence of these styles suggests that both groups may value CEs and RO (diverging) as well as hands-on activities and practical application (accommodating).</p><p>This alignment can be leveraged to support instruction in different ways. For diverging learners (both residents and some professors), emphasize group discussions, brainstorming sessions, and reflective writing assignments. Encourage the sharing of diverse perspectives and the exploration of different approaches to surgical problems. In contrast, for accommodating learners (both professors and some residents), Provide opportunities for hands-on practice, simulation-based training, and real-world clinical rotations. Encourage AE and problem-solving in practical settings. By incorporating these strategies, educators can create a learning environment that caters to the predominant learning styles of both residents and professors, fostering more effective communication, engagement, and knowledge acquisition.</p><p>However, it is important to acknowledge that the similarity in distribution does not guarantee a perfect match for all individuals. The relatively lower prevalence of converging and assimilating styles in both groups suggests that those learners might require more tailored support and learning opportunities to ensure their needs are met. This underscores the importance of mapping learning styles when designing a comprehensive residency program, as it provides a basis for guiding the learning needs of all residents and professors, not just the majority.</p></sec><sec id="s4-2"><title>Implications of Findings</title><p>The findings of our study have important implications for surgical education. Understanding the predominant learning styles of residents and professors can help adapt teaching strategies and curriculum design to better meet their needs. For example, incorporating more RO and practical experiences can benefit diverging and accommodating learners while also providing opportunities for AC and AE to support assimilating and converging learners.</p><p>Furthermore, with the occurrence of the pandemic, the increased distances imposed by contact restrictions have further deepened these changes. The COVID-19 pandemic has also presented unique challenges to surgical training, with restrictions on in-person learning and clinical experiences. A pan-Romanian survey by Moldovan et al [<xref ref-type="bibr" rid="ref24">24</xref>] highlighted the impact of the pandemic on orthopedic residents, including reduced surgical volume, limited access to educational resources, and increased stress and anxiety. These challenges may have further influenced the learning styles and preferences of surgical residents and professors during this period.</p></sec><sec id="s4-3"><title>Comparison With Prior Work</title><p>Few studies on learning styles in surgery were found in the literature, but we can state that our results are different from previous results.</p><p>In the 1980s, Baker III et al [<xref ref-type="bibr" rid="ref25">25</xref>] reported a prevalence of converging (46%), followed by accommodating (26%) and assimilating (20%) styles among surgeons. In the 2000s, this pattern was confirmed by Contessa et al [<xref ref-type="bibr" rid="ref26">26</xref>]. They argued that surgical practice requires quick decision-making and problem-resolution, justifying the converging style and its more pragmatic view. In 2007, Mammen et al [<xref ref-type="bibr" rid="ref27">27</xref>] published similar results obtained in the US population.</p><p>After Quillin [<xref ref-type="bibr" rid="ref28">28</xref>] reduced his working hours in general surgery residency, he showed the results collected from 1999 to 2012. At that time, the proportion of accommodating learners was higher, especially after 2003, when the workload was reduced [<xref ref-type="bibr" rid="ref28">28</xref>].</p><p>In 2017, for the first time, diverging learners became the majority in a study with 47 surgeons in the United Kingdom [<xref ref-type="bibr" rid="ref29">29</xref>]. In 2018, also in the United Kingdom, a study with residents in various surgical areas found that converging, followed by accommodating styles were predominant [<xref ref-type="bibr" rid="ref30">30</xref>]. In 2020, similar results were published in Scotland by Hopkins et al [<xref ref-type="bibr" rid="ref15">15</xref>]. The most recent publication on the topic reported a predominance of assimilating followed by converging styles in Spain [<xref ref-type="bibr" rid="ref31">31</xref>]. <xref ref-type="table" rid="table5">Table 5</xref> and <xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref> show the existing literature.</p><table-wrap id="t5" position="float"><label>Table 5.</label><caption><p>Data of learning styles in surgery through time around the world.</p></caption><table id="table5" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Author</td><td align="left" valign="bottom">Publication year</td><td align="left" valign="bottom">Country</td><td align="left" valign="bottom">Population (n)</td><td align="left" valign="bottom">Diverging</td><td align="left" valign="bottom">Accomodator</td><td align="left" valign="bottom">Assimilating</td><td align="left" valign="bottom">Converging</td></tr></thead><tbody><tr><td align="left" valign="top">Baker III</td><td align="left" valign="top">1985</td><td align="left" valign="top">USA</td><td align="left" valign="top">Surgeons (39)</td><td align="left" valign="top">8%</td><td align="left" valign="top">26%</td><td align="left" valign="top">20%</td><td align="left" valign="top">46%</td></tr><tr><td align="left" valign="top">Drew</td><td align="left" valign="top">1999</td><td align="left" valign="top">UK</td><td align="left" valign="top">Basic surgical trainees (52)</td><td align="left" valign="top">3.9%</td><td align="left" valign="top">27%</td><td align="left" valign="top">9.6%</td><td align="left" valign="top">59.5%</td></tr><tr><td align="left" valign="top">Mammen</td><td align="left" valign="top">2007</td><td align="left" valign="top">USA</td><td align="left" valign="top">General surgery residents (91)</td><td align="left" valign="top">10.6%</td><td align="left" valign="top">14.6%</td><td align="left" valign="top">17.2%</td><td align="left" valign="top">57.8%</td></tr><tr><td align="left" valign="top">Brown</td><td align="left" valign="top">2018</td><td align="left" valign="top">UK</td><td align="left" valign="top">Medical students (60)</td><td align="left" valign="top">20.8%</td><td align="left" valign="top">30.2%</td><td align="left" valign="top">17%</td><td align="left" valign="top">32%</td></tr><tr><td align="left" valign="top">Parra</td><td align="left" valign="top">2021</td><td align="left" valign="top">Spain</td><td align="left" valign="top">Surgical residents and staff (64)</td><td align="left" valign="top">14.1%</td><td align="left" valign="top">21.9%</td><td align="left" valign="top">39.1%</td><td align="left" valign="top">25%</td></tr></tbody></table></table-wrap><p>The results of the present study were diverging (43,8%), accommodating (42,2%), assimilating (11,0%), and converging (3,12%) styles. These results amplify the existing literature, showing an increase in diverging and a decrease in converging styles over the years. These findings indicate a shift in the learning preferences of surgical residents and professors, which may have been influenced by various factors, such as changes in surgical education, technological advancements, and sociocultural aspects.</p><p>The geographical location may be a possible explanation for our results, as previous studies were conducted in North America and Europe (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). Cultural differences and variations in surgical training programs across countries may have contributed to the observed differences in learning styles. Another hypothesis may be the course of time: the last two decades have seen huge technological changes, when social media, smartphones, and laptops became widely available, greatly impacting the teaching-learning process [<xref ref-type="bibr" rid="ref32">32</xref>]. Recent studies have further explored the impact of digital technologies on medical education, highlighting both the opportunities and challenges associated with their integration [<xref ref-type="bibr" rid="ref5">5</xref>]. Furthermore, with the occurrence of the pandemic, the increased distances imposed by contact restrictions have further deepened these changes [<xref ref-type="bibr" rid="ref33">33</xref>].</p><p>The differing proportions of female residents (47.1%) and professors (16.0%) highlight the ongoing evolution of gender representation in surgery. The historical underrepresentation of women in surgical fields may contribute to differences in observed learning styles between residents and professors [<xref ref-type="bibr" rid="ref34">34</xref>]. Despite this, the increasing participation of women in surgery over recent decades is a positive trend [<xref ref-type="bibr" rid="ref22">22</xref>].</p></sec><sec id="s4-4"><title>Strengths and Limitations</title><p>The population included is a small sample of a larger Brazilian surgical group. More data can be further collected to compare the country with other nations, in America, Europe or even Asia. The medical reality in Brazil is diverse and worth a broader approach.</p><p>In addition to the small sample size, our study has several other limitations that should be acknowledged. The study had a sampling bias. Our sample was drawn from a single teaching hospital in Brazil, which may not be representative of all general surgery residents and professors in Brazil or other countries. This limits the generalizability of our findings. Additionally, the voluntary nature of participation may have introduced selection bias, as those who chose to participate may differ systematically from those who did not. In addition, there was measurement bias; the Kolb LSI is a self-report instrument, which is subject to social desirability bias and response bias. Participants may have answered the questions in a way that they perceived as more favorable or aligned with societal expectations, rather than reflecting their true learning preferences. Moreover, our study did not fully explore the potential influence of various sociodemographic factors, such as cultural background, socioeconomic status, and prior educational experiences, on learning styles. However, we did not collect data on other potentially relevant sociodemographic factors such as ethnicity, social class, migration background, or detailed information about prior educational experiences. These factors may interact with learning styles in complex ways and could have influenced our results.Finally, the cross-sectional design of our study limits our ability to draw causal inferences about the relationship between learning styles and other variables. A longitudinal study would be needed to examine how learning styles evolve over time and how they impact training outcomes. These limitations should be considered when interpreting our findings.</p><p>Further research is needed to explore the underlying factors that influence these learning styles, such as personality traits, prior educational experiences, and cultural background. Understanding these factors could allow for more tailored interventions to optimize learning. Moreover, future studies should investigate the potential impact of different learning styles on surgical performance metrics, such as technical skill acquisition, error rates, and patient outcomes. This would provide valuable insights into how learning style preferences translate into real-world surgical practice.</p></sec><sec id="s4-5"><title>Conclusions</title><p>This study found that diverging and accommodating learning styles were more prevalent among general surgery residents and professors in a Brazilian university hospital, differing from previous North American and European studies. The decreased prevalence of the converging style is notable and may be due to changes in surgical education, technology, and cultural differences. Understanding these learning styles can guide more effective and inclusive teaching strategies in surgical residency programs. Further research with larger, diverse populations is needed to explore the relationships between learning styles, demographics, and training outcomes.</p></sec></sec></body><back><fn-group><fn fn-type="conflict"><p>None declared.</p></fn></fn-group><glossary><title>Abbreviations</title><def-list><def-item><term id="abb1">AC</term><def><p>abstract conceptualization</p></def></def-item><def-item><term id="abb2">AE</term><def><p>active experimentation</p></def></def-item><def-item><term id="abb3">CE</term><def><p>concrete experience</p></def></def-item><def-item><term id="abb4">ELT</term><def><p>Experiential Learning Theory</p></def></def-item><def-item><term id="abb5">LSI</term><def><p> learning style inventory</p></def></def-item><def-item><term id="abb6">RO</term><def><p>reflective observation</p></def></def-item></def-list></glossary><ref-list><title>References</title><ref id="ref1"><label>1</label><nlm-citation citation-type="report"><person-group person-group-type="author"><name 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