Feasibility study and implementation of a questionnaire on the effectiveness of PhD curricula for knowledge management at medical universities in Iran

Journal of Medical Education Development Volume 18, Issue 4 e-ISSN: 2980-7670 December 2025 www.https://edujournal.zums.ac.ir Pages 4-17 Copyright © 2025 Zanjan University of Medical Sciences. Published by Zanjan University of Medical Sciences. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/bync/4.0/). Noncommercial uses of the work are permitted, provided the original work is properly cited. Feasibility study and implementation of a questionnaire on the effectiveness of PhD curricula for knowledge management at medical universities in Iran Shokouh Sedghi 1 , Fereshteh Sepehr 2* , Abolfazl Golestani 3 1 Responsible Expert of the Library and Learning Center, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran 2 Department of Knowledge and Information Science, Islamic Azad University of Tehran North Branch, Tehran, Iran 3 Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Article info Abstract Introduction Knowledge is a valuable resource, and its transformation from raw data into actionable knowledge depends on effective human management [1]. With the transition from the industrial age to the information era, knowledge has become a key driver of competitiveness for organizations and nations. Administration provides a platform for creating, checking, presenting, disseminating, and applying knowledge to benefit both organizations and clients [2, 3]. As a result, knowledge management has gained increasing importance and has become a central concern for organizations in recent years [4]. Various definitions of knowledge management stress its evolution, implementation, workflow, or technological Article history: Received 21 Jan. 2025 Revised 10 Mar. 2025 Accepted 30 Sep. 2025 Published 19 Nov. 2025 Background & Objective: Checking the quality and dynamics of higher education curricula and checking the effectiveness of courses provide valuable feedback for improving educational standards. This study aimed to design and carry out a questionnaire to investigate and compare the effectiveness of PhD. curricula in encouraging knowledge management, as perceived by graduates of medical sciences universities in Iran. Materials & Methods: A questionnaire based on the components of the Bukowitz and Williams knowledge management model was built, comprising 38 items. The Content Validity Index (CVI), Content Validity Ratio (CVR), and question clarity were checked. Internal consistency and reliability were confirmed using Cronbach's alpha and correlation coefficients. The finalized questionnaire was distributed to 221 PhD graduates in various fields of basic medical sciences from Tehran University of Medical Sciences (TUMS), Iran University of Medical Sciences (IUMS), and Shahid Beheshti University of Medical Sciences (SBUMS). Data were analyzed using descriptive and inferential statistics. Results: The questionnaire consisted of seven components, with a CVR of 0.72, CVI of 0.86, and clarity score of 0.82. The reliability of the questionnaire was strong, with a Cronbach's alpha of 0.935, and a positive, significant correlation was seen among its components (p < 0.01). The mean scores for knowledge management in PhD courses, as rated by graduates, were similar across the three universities and above average. The highest mean scores were related to the "knowledge sharing" component (TUMS:3.2, IUMS:3.18, and SBUMS:3.14). The lowest mean scores were seen for the "learning from the knowledge process" component (IUMS:2.53, and SBUMS:2.65), and the "knowledge evaluation" component (TUMS:2.69). Conclusion: The effectiveness of PhD curricula in encouraging knowledge management was rated above average by graduates of the investigated medical universities. However, the results highlight the need for greater stress on knowledge evaluation, knowledge elimination, and learning processes to improve the overall effectiveness of these programs. Keywords: questionnaire, knowledge management, curriculum, medical universities *Corresponding author: Fereshteh Sepehr, Department of Knowledge and Information Science, Islamic Azad University of Tehran North Branch, Tehran, Iran. Email: [email protected] Original Article How to cite this article: Sedghi Sh, Sepehr F, Golestani A. Feasibility study and implementation of a questionnaire on the effectiveness of PhD curricula for knowledge management at medical universities in Iran. J Med Edu Dev. 2025;18(4):4 - 17. http://dx.doi.org/10.61882/edcj.18.4.4 [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 1 / 14 5PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) aspects [2, 5]. Alavi and Leidner described it as the process of converting data into information and then into knowledge [1]. This process includes creating internal knowledge, getting external knowledge, storing and updating knowledge, and sharing it across systems [6]. Overall, knowledge management identifies values that improve products and services through the effective use of intellectual resources [7]. In a knowledge-based society, the role of knowledge management goes beyond enterprises [8]. Within education, it makes working together easier, effective use of knowledge, and transformation of personal knowledge into collective knowledge, thereby fostering innovation [9]. Universities, as the core institutions of higher education, play a vital role in knowledge production and dissemination, directly affecting societal growth [10]. Because education is basic to societal progress, curriculum quality—including its design, delivery, and outcomes—remains critical [11]. A curriculum provides structured pathways for knowledge and skill acquisition, shaping values and attitudes. Haav et al. identified two main objectives of higher education: preparing skilled professionals and growing engaged citizens [12]. To meet modern demands, curricula must be dynamic and continuously improved, which needs integration of knowledge management principles [13]. Survival in today's competitive environment depends on employee knowledge and skills. In universities and institutions, intellectual capital must be managed effectively by embedding knowledge into curricula, encouraging learning, working together, and innovation [14]. This is especially important in doctoral education, which addresses evolving societal needs amid technological advances and the rapid expansion of knowledge [15]. In health sciences, specialized doctoral programs are crucial due to healthcare complexities, demographic changes, and the centrality of human health in national growth. Medical science universities must deliver curricula that adapt to external changes while keeping high quality. Curriculum evaluation is essential to refine content, improve implementation, and improve teaching ways. Adding feedback from students and faculty further guides improvement. Although tools exist for checking knowledge management in other fields [16], there is a lack of reliable instruments tailored to checking knowledge management in PhD graduates of medical sciences. This gap hinders efforts to strengthen postgraduate education and knowledge production. So, the present study aimed to design and check a reliable questionnaire to check knowledge management components in PhD programs of basic medical sciences. By addressing this gap, the study provides university administrators with insights into curriculum strengths and weaknesses, helping efforts to improve educational quality and institutional performance. Materials & Methods Design and setting(s) The present study is applied in nature and uses a mixedmethods approach, adding both quantitative and qualitative components. In the first stage, a questionnaire was built based on the components of the Bukowitz and Williams knowledge management model, and its validity and reliability were checked. In the second stage, the validated questionnaire was used to check the effectiveness of the PhD curriculum in terms of knowledge management. The study focused on specialized fields within the basic medical sciences at Tehran University of Medical Sciences (TUMS), Iran University of Medical Sciences (IUMS), and Shahid Beheshti University of Medical Sciences (SBUMS). Participants and sampling The study population comprised experts and professors in information science and knowledge studies, as well as specialists in basic sciences and graduate studies, including members of the curriculum evaluation committee. Inclusion criteria were faculty members from these disciplines who served on the curriculum evaluation committee, while the exclusion standard was incomplete questionnaire responses. Convenience sampling was used because of limited access to eligible experts across faculties and the necessity to get timely responses from a specialized population. A total of 23 experts took part: 15 from information science and knowledge studies and 8 from basic sciences and graduate studies. Tools/Instruments The data collection tool was a researcher-built questionnaire based on the components of the Bukowitz and Williams knowledge management model [17]. To build this tool, various dimensions of knowledge management were identified through a literature review and qualitative panel discussions. The literature review was performed by searching keywords in the "Scopus," "PubMed," "ScienceDirect," [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 2 / 14 6PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) "Google Scholar," "Medline," "Embase," "Web of Science," and "Cochrane" databases. The keywords, used alone and in combination, were: "effectiveness," "PhD curricula," "curricula," "curriculum," "knowledge management," "medical universities," "medical sciences," and "questionnaire." We found 345 articles and excluded 266 due to unrelated content, 18 due to incomplete presentation of results relevant to our study, and 12 due to unavailability of the main text or because they were in languages other than English or Persian. Finally, 49 articles remained for further checking. An early questionnaire comprising 64 questions was created. To ensure the clarity and interpretability of questionnaire items, Cognitive Interviews (CI) were done between the authors and five PhD graduates in basic medical sciences from different specializations (anatomy, physiology, biochemistry, pharmacology, and immunology). Using think-aloud and verbal probing techniques, participants were asked to clearly articulate their understanding of each item, highlight ambiguities, and suggest improvements. These interviews revealed issues such as vague terminology, double-barreled questions, and redundant phrasing. Based on the feedback, items were revised to improve clarity, relevance, and consistency with the intended knowledge management dimensions. This CI phase played a crucial role in improving the content validity and user-friendliness of the final 38-item instrument (provided in the Appendix 1 as a supplementary table). After adding the suggested revisions, the final version of the questionnaire, consisting of 38 items, was approved by the authors. For the quantitative content validity of the questionnaire, experts were asked to complete forms for the Content Validity Ratio (CVR) and Content Validity Index (CVI), and to provide comments on each item in the designated box or, if necessary, more generally at the end of the questionnaire. For CVR, the Lawshe table [18] was used, where a score above 0.42 was considered acceptable based on the critical value specified. CVI was checked using the method provided by Polit et al. [19], in which experts rated each item on a 4-point scale for relevance (1 = not relevant to 4 = highly relevant). The item-level CVI was calculated as the proportion of experts rating the item as either 3 or 4. A score of 0.78 or higher was considered acceptable. To check the clarity of the questionnaire, experts rated each item on a four-point scale (completely clear, clear, relatively clear, and unclear). The clarity score was calculated by dividing the number of experts who considered each item either "completely clear" or "clear" by the total number of experts. Based on various sources, an acceptable clarity score for a new tool was 0.8 [20, 21]. For checking the reliability of the questionnaire, Cronbach's alpha was used, with an acceptable value set at 0.8 or higher [22]. To check construct validity, an Exploratory Factor Analysis (EFA) was performed using principal component analysis with varimax rotation [22]. Sampling adequacy was backed up by the Kaiser– Meyer–Olkin (KMO) measure (0.842), and Bartlett's test of sphericity was significant (χ² = 3210.4, p < 0.001), confirming the suitability of the data for factor analysis. Factors with eigenvalues greater than 1 were extracted, and items with loadings ≥ 0.40 were retained. The final solution identified four factors that together accounted for 68.4% of the total variance. The overall internal consistency was acceptable, with Cronbach's alpha = 0.82. To check item-level quality and ensure rigor, the Critical Appraisal Skills Programme (CASP) checklist was applied to score each question. Five PhD graduates from different medical disciplines checked each item regarding three dimensions: 1) relevance to the knowledge management construct, 2) clarity and wording precision, and 3) practical applicability within the context of PhD curricula in medical universities. Each item was rated between 1 and 10, with 10 showing the highest level and contextual quality. Final scores were averaged across the evaluators. Items receiving a CASP score of 8 or higher were retained without modification, as they showed enough conceptual and linguistic quality. On the other hand, items scoring below 8 were reviewed and revised for clarity or removed if deemed redundant or misaligned with the study objectives. The CASP scoring process complemented the CVR and CVI analyses by adding expert judgment on the practical utility and interpretability of the questionnaire items. In summary, the questionnaire was built using a multistep process informed by the AMEE Guide No. 87. The growth stages included: [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 3 / 14 7PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) 1. Identification of research objectives and questions aligned with the Bukowitz and Williams knowledge management model. 2. Literature review to tell item generation and model suitability. 3. Qualitative panel discussions to ensure contextual relevance. 4. Item generation based on conceptual mapping of model components. These items covered the following components: knowledge acquisition (4 items), knowledge application (7 items), learning from the knowledge process (6 items), knowledge sharing (6 items), knowledge evaluation (4 items), knowledge production and registration (5 items), and the optimum use of knowledge (elimination of unnecessary knowledge) (6 items). 5. Cognitive Interviews (CI): Five PhD graduates from different medical disciplines took part in CI to test question clarity, logic, and interpretation. Feedback from these interviews led to refinement of question wording and item sequence. 6. Content validity checking using CVI and CVR metrics. 7. Pilot testing and psychometric checking through reliability analysis and correlation matrices. Data collection methods After confirming the reliability of the questionnaire, the opinions of graduates were checked across various knowledge management components. Responses were measured using a five-point Likert scale, ranging from "very little" to "very much." For this purpose, 221 PhD graduates from various departments of basic medical sciences—including anatomy, parasitology, immunology, bacteriology, biochemistry, physiology, and pharmacology—at the medical faculties of TUMS, IUMS, and SBUMS were included in the study. These graduates had completed all mandatory courses before the first or second semester of the 2018–2019 academic year and were selected through convenience sampling. To ensure the quality of the research, a final open-ended question was included in the questionnaire, focusing on graduates' opinions regarding the effect of the PhD curriculum on encouraging creativity, innovation, and knowledge. This question aimed to capture participants' views in four areas: weaknesses, suggestions, strengths, and other comments. Graduates from each field answered this question descriptively, thinking about the curriculum relevant to their specific area of study. Qualitative content analysis The open-ended final question of the questionnaire was designed to check the effect of the PhD curriculum on creativity, innovation, and knowledge advancement. The responses were subjected to qualitative content analysis. Participant responses were coded inductively using content analysis techniques and categorized into four main themes: 1) theoretical overload with minimal application, 2) misalignment with societal and market needs, 3) lack of modern laboratory infrastructure, and 4) minimal fostering of creativity. Data analysis SPSS version 22 was used to analyze the questionnaire data. The Kolmogorov-Smirnov test was performed to check the normality of the data. Then, the Intraclass Correlation Coefficient (ICC) was calculated to assess the reliability of the data. To compare knowledge management components across different courses, a onesample t-test and Friedman's test were used. A significance level of p < 0.05 was considered for all statistical analyses. Results The CVR results were calculated to fall within the acceptable range of 0.5–1, with a mean of 0.72. The CVI values, with a mean of 0.86, and the clarity score, with a mean of 0.82, were both within acceptable ranges. The overall content validity of the questionnaire was calculated to be 0.8 (Table 1), showing that the researcher-built questionnaire used in this study was validated. Cronbach's alpha for all seven components of knowledge management ranged from 0.661 to 0.811, showing acceptable reliability across the components. Also, the overall Cronbach's alpha for the 38 questions covering the seven components was calculated to be 0.935, showing the high reliability of the questionnaire used in this study (Table 1). The CASP scores for each question are presented in Table 1. The mean CASP score across all items was 8.7, showing a generally high level of expert agreement on the relevance, clarity, and applicability of the items. Specifically, 33 out of 38 items received scores of ≥ 8, confirming their appropriateness for inclusion without revision. The five items with CASP scores between 7 and 8 were re-checked and slightly revised for wording clarity based on expert feedback received during the cognitive interviewing phase. [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 4 / 14 8PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) Table 1. Content validity ratio, content validity index, clarity, Cronbach's Alpha, and CASP score for knowledge management capability questionnaire items Components Objects CVR CVI Clarity Cronbach's Alpha CASP Score (out of 10) Knowledge acquisition Q1 0.62 0.86 0.62 0.708 8 Q2 0.62 1.00 0.87 9 Q3 0.62 0.87 0.75 9 Q4 0.73 0.87 0.75 9 Knowledge application Q5 0.87 0.81 0.87 0.811 9 Q6 0.60 0.93 0.86 8 Q7 0.86 1.00 0.93 10 Q8 0.86 0.93 0.80 9 Q9 0.60 0.85 0.73 8 Q10 0.71 0.86 0.85 9 Learning from the knowledge process Q11 0.60 0.86 0.80 0.661 8 Q12 0.60 0.86 0.73 8 Q13 0.86 1.00 0.86 10 Q14,15,16 0.73 0.93 0.80 9 Q17 0.86 0.93 0.93 10 Knowledge sharing Q18 0.60 0.86 0.86 0.709 8 Q19 0.73 0.86 0.80 9 Q20 0.60 0.86 0.80 8 Q21 0.86 1.00 0.80 10 Q22 0.85 1.00 0.92 10 Q23 0.86 0.86 0.93 9 Knowledge evaluation Q24 0.86 1.00 0.86 0.796 9 Q25 0.73 0.93 0.80 8 Q26 0.73 0.86 0.73 8 Q27 0.73 1.00 0.86 9 Production and registration of knowledge Q28 0.73 0.86 0.73 0.777 8 Q29 0.73 0.86 0.80 9 Q30 0.73 0.93 0.80 9 Q31 0.60 0.86 0.73 8 Q32 0.73 0.80 0.86 8 Optimum use of knowledge Q33 0.60 0.80 0.93 0.810 8 Q34 0.60 0.86 0.86 8 Q35,36 0.60 0.86 0.80 8 Q37 0.86 0.86 0.93 9 Q38 0.85 0.85 0.85 9 Mean 0.935 8.71 Note: To assess item-level quality and ensure methodological rigor, the CASP checklist was applied to score each question. To assess the reliability of the questionnaire, Cronbach's alpha was used. Abbreviations: CVR, content validity ratio; CVI, content validity index; CASP, critical appraisal skills programme; Q, question. The evaluation of the correlations among the measured components, using a correlation matrix, revealed that all seven components were significantly correlated with each other and with the total scale score (p < 0.01). Also, [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 5 / 14 9PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) the highest correlation coefficient was seen between the total knowledge management score and the knowledge application component (p < 0.01, r = 0.88), while the lowest correlation coefficient was found between the knowledge production and knowledge application components (p < 0.01, r = 0.48) (Table 2). Table 2. Correlation matrix between knowledge management components and total score Variables Knowledge acquisition Knowledge application Learning from the knowledge process Knowledge sharing Knowledge evaluation Production and registration of knowledge Optimum use of knowledge Total Score Knowledge acquisition - Knowledge application 0.68** - Learning from the knowledge process 0.72** 0.60** - Knowledge sharing 0.60** 0.65** 0.59** - Knowledge evaluation 0.67** 0.61** 0.67** 0.59** - Production and registration of knowledge 0.51** 0.50** 0.50** 0.48** 0.54** - Optimum use of knowledge 0.51** 0.62** 0.65** 0.63** 0.72** 0.63** - Total Score 0.85** 0.68** 0.80** 0.80** 0.86** 0.88** 0.79** - Note: To compare knowledge management components across different courses, a one-sample t-test and Friedman's test were employed. An asterisk (**) indicates that p < 0.01. The results of the knowledge management study in courses, based on responses from PhD students in various fields of basic medical sciences at TUMS, IUMS, and SBUMS (Table 3), revealed that the mean scores seen at TUMS (133.16), IUMS (128.14), and SBUMS (129.67) were all higher than the assumed benchmark value (x  = 114). This indicates that, based on graduates’ responses, the potential for implementing the knowledge management model in the courses is above the expected level. Table 3. One-way analysis of variance results comparing university effect on knowledge management level Variable University Mean SD F-value p-value Knowledge management model Tehran 133.16 23.51 1.90 p = 0.151 Iran 128.14 25.62 Shahid Beheshti 129.67 22.79 Note: One-way ANOVA test was used to compare the effect of the university factor on the level of knowledge management. Abbreviations: SD, standard deviation; F, analysis of variance test; p, probability-value. According to Table 4, the most frequently used component of knowledge management is "knowledge sharing," with mean scores of 3.2 at TUMS, 3.18 at IUMS, and 3.14 at SBUMS. In contrast, the least frequently used components are "learning from the knowledge process", with a mean score of 2.53 at IUMS, and "knowledge evaluation", with mean scores of 2.69 at TUMS and 2.62 at SBUMS. Table 5 presents the mean ± standard deviation for each of the knowledge management components in the PhD courses at TUMS, IUMS, and SBUMS. According to these results, "knowledge sharing" remains the most frequently used component, and no significant statistical differences were seen among the universities (p > 0.05). To complement the quantitative findings, responses to the final open-ended question of the questionnaire — regarding the effect of the PhD curriculum on creativity, innovation, and knowledge advancement — were subjected to qualitative content analysis. A total of 85 participants (52 from TUMS, 18 from IUMS, and 15 from SBUMS) provided narrative feedback. [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 6 / 14 10PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) Table 4. Multivariate analysis of variance results comparing knowledge management components across universities Variable University Mean SD Knowledge acquisition Tehran 2.81 0.64 Iran 2.77 0.54 Shahid Beheshti 2.82 0.57 Knowledge application Tehran 2.98 0.60 Iran 2.84 0.63 Shahid Beheshti 2.86 0.62 Learning from the knowledge process Tehran 2.83 1.14 Iran 2.53 0.86 Shahid Beheshti 2.65 0.70 Knowledge sharing Tehran 2.83 1.14 Iran 3.18 0.54 Shahid Beheshti 3.14 0.49 Knowledge evaluation Tehran 2.69 0.54 Iran 2.63 0.65 Shahid Beheshti 2.62 0.54 Production and registration of knowledge Tehran 2.93 0.62 Iran 3.01 0.62 Shahid Beheshti 3.01 0.56 Optimum use of knowledge Tehran 2.75 0.64 Iran 2.54 0.81 Shahid Beheshti 2.64 0.74 Statistical test results Value F-value 0.652 Degrees of Freedom 0.141 p-value p = 0.810 Note: MANOVA test was used to compare the knowledge management components in the courses based on the graduates' responses. Abbreviations: SD, standard deviation; F, analysis of variance test; p, probability-value. Table 5. Comparison of the average (± standard deviation) of knowledge management components in Ph.D. courses. P-value Optimum use of knowledge Production and registration of knowledge Knowledge evaluation Knowledge sharing Learning from the knowledge process Knowledge application Knowledge acquisition University Variation 0.036 3.19±0.6 3.4±0.52 2.8±0.4 3.31±0.55 2.9±0.82 3.06±0.39 2.9±0.64 Tehran Anatomy (reproductive biology) 2.65±1.2 2.92±1.1 2.48±0.6 3.2±0.9 2.76±1.1 3.03±0.37 2.83±0.5 Iran 3.42±0.49 3.26±0.46 3±0.62 3.4±0.51 3.3±0.66 3.39±0.62 3.21±0.6 Shahid Beheshti 0.024 2.6±0.64 2.83±0.51 2.7±0.47 3.34±0.54 2.9±0.33 3.13±0.4 2.9±0.27 Tehran Anatomy (dissection) 1.35±0.29 2.06±0.21 1.88±0.65 2.91±0.47 1.35±0.44 2.12±0.33 1.88±0.3 Iran 2.83±0.44 3.04±0.41 2.79±0.32 3.35±0.37 3.06±0.38 2.95±0.45 2.98±0.44 Shahid Beheshti 0.58 2.61±0.52 2.96±0.37 2.87±0.3 3.2±0.31 2.6±0.48 2.9±0.59 3.04±0.63 Tehran Immunology 2.6±0.67 2.9±0.55 2.56±0.67 3.11±0.57 2.45±0.87 2.85±0.55 2.73±0.47 Iran 2.31±0.72 3.16±1.02 2.85±0.42 3.28±0.45 2.24±0.85 2.6±0.72 2.57±0.54 Shahid Beheshti 0.012 2.36±0.65 2.93±0.41 2.9±0.58 3.05±0.3 2.6±0.68 2.72±0.73 2.66±0.88 Tehran Bacteriology 2.19±1.02 2.73±0.41 1.61±0.52 2.65±0.42 1.75±0.38 2.4±0.44 2.22±0.76 Iran 1.98±0.67 2.54±0.43 2.56±0.43 2.93±0.6 2.25±0.49 2.57±0.51 2.7±0.46 Shahid Beheshti 0.248 2.66±0.58 2.88±0.63 2.5±0.49 3.18±0.5 2.6±0.48 2.91±0.55 2.79±0.33 Tehran Biochemistry 2.26±0.82 3.45±0.3 2.68±0.55 3.37±0.24 2.62±1.06 2.95±0.49 2.82±0.72 Iran 2.19±0.82 2.58±0.48 2.1±0.58 2.86±0.17 2.27±0.75 2.53±0.8 2.51±0.42 Shahid Beheshti 0.352 2.23±0.9 2.9±0.94 2.19±0.76 2.57±0.69 2.45±0.71 2.92±0.95 2.5±0.72 Tehran Pharmacology 2.71±0.78 3.14±0.83 3.16±0.47 3.22±0.5 2.57±0.98 2.87±0.63 2.92±0.4 Iran 2.9±1.12 3.46±0.41 2.81±0.96 2.78±0.98 2.95±1.05 3.06±0.85 3.08±0.87 Shahid Beheshti 0.028 3.1±0.5 3.34±0.47 3.01±0.4 3.57±0.32 3.14±0.27 3.28±0.29 3.06±0.29 Tehran Physiology 2.39±0.67 3.14±0.46 2.42±0.54 3.2±0.64 2.87±0.71 2.8±0.65 2.64±0.45 Iran 2.52±0.7 2.98±0.62 2.55±0.4 3.16±0.36 2.63±0.52 2.74±0.69 2.63±0.34 Shahid Beheshti Abbreviations: P, probability-value [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 7 / 14 11PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) As shown in Figure 1, 34 responses (54%) from TUMS, 39 responses (65%) from IUMS, and 12 responses (52%) from SBUMS highlighted weaknesses. Only 5 responses (7.9%), 4 responses (6.67%), and 2 responses (8%) from TUMS, IUMS, and SBUMS, respectively, were related to curriculum strengths. Figure 2 shows the distribution of responses from graduates in various fields of basic medical sciences at TUMS, IUMS, and SBUMS to the qualitative question. As shown, 33.3% of respondents were from the Immunology department at IUMS, 25% from the Physiology department at SBUMS, and 16% from the Biochemistry department at TUMS. Graduates in Reproductive Biology from all three universities provided no responses to the qualitative question. The findings showed that many participants felt the curricula were overly focused on theoretical instruction with limited opportunities for hands-on practice. Respondents frequently cited a disconnect between course content and real-world demands. Many participants mentioned that limited access to up-to-date laboratory facilities hindered innovation and creativity. Several respondents perceived the curriculum as rigid and not good for critical thinking or innovation. The frequency analysis revealed that weaknesses made up the most common response category across all three universities, particularly at IUMS (65% of comments). In contrast, strengths comprised less than 10% of responses at each institution, most often referring to isolated efforts such as journal clubs or up-to-date seminars led by select faculty members. Figure 1. The frequency (%) of participants' comments categorized into the four main codes: weaknesses, suggestions, strengths, and miscellaneous points. Figure 2. The frequency (%) of participants' responses to the qualitative section of the questionnaire, categorized by fields of basic medical sciences. 65 23 75 54 34.9 7.9 3.2 52 40 8 0.0 Weaknesses Suggestions Strengths Miscellaneous Iran Tehran Shahid Beheshti 33.3 11.1 11.1 5.6 11.1 0 0 16.7 0 16.7 25 0 0 0 12 8 8 4 8 16 0 Iran Shahid Beheshti Tehran [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 8 / 14 12PHD CURRICULUM AND KNOWLEDGE MANAGEMENT J Med Edu Dev 2025;18(4) Overall, the qualitative data highlighted several critical areas for improvement in PhD curriculum design, particularly regarding relevance, engagement, infrastructure, and innovation. These findings contextualize the lower mean scores seen for "knowledge evaluation" and "learning from the knowledge process" in the quantitative phase and back up the need for complete curriculum reform. Regarding strengths, graduates from the Physiology department at IUMS and those in Pharmacology and Immunology at TUMS and SBUMS highlighted the inclusion of up-to-date topics by some professors and the regular organization of journal clubs and seminars. They believed that these journal clubs contribute to knowledge production, increase familiarity with global trends, and foster innovation and creativity among students. Discussion This study aimed to check the feasibility and implementation of a questionnaire designed to check the effectiveness of PhD courses in the specialized fields of basic medical sciences in Iran, with a focus on knowledge management among graduates. In the first phase of the study, a 38-item questionnaire was built, showing good validity with a CVI of 0.86, a CVR between 0.5 and 1, and a Cronbach's alpha of 0.935. While several researchers have attempted to create models that combine various aspects of knowledge management, no specific questionnaire has been designed to check syllabi. For instance, Aziz et al. [8] built a reliable and valid knowledge management model for companies, categorizing employees into strategic, executive, and operational levels. Their questionnaire provides a complete view of knowledge management in organizations. In a similar study, Karamitri et al. [23] built a valid and appropriate questionnaire for checking knowledge management processes in health organizations, focusing on dimensions such as perceptions of knowledge management, internal and external motivations, knowledge sharing, cooperation, leadership, organizational culture, and barriers. The results of the present study showed that graduates from TUMS, IUMS, and SBUMS rated the effectiveness of the PhD curriculum on knowledge management higher than the average scores reported in previous studies [23–29]. No statistically significant differences were seen (p > 0.05) among the universities checked in our study, showing similar effectiveness in terms of knowledge management. In a study by Kim et al. [26] on the quality of nursing doctoral curricula and related references, undesirable outcomes were reported for knowledge management and its components. Similarly, Wilson et al. [18], in their study on knowledge management in higher education institutions in Tanzania, found that both academic and non-academic staff at the MBA University of Science and Technology were unfamiliar with knowledge management practices. Studies by Asadi et al. [28] at TUMS hospitals and Vali et al. [29] at Kerman University of Medical Sciences reported average or below-average evaluations of knowledge management. In contrast, Davoodi et al. [10] found that knowledge management at Ahvaz Jundishapur University of Medical Sciences was rated highly, with a mean of 3.16, which aligns with the findings of the present study. The differences across studies seen may be attributed to variations in organizational cultures, management and leadership styles, and the differing quality improvement and accreditation processes across institutions. Among the components of the knowledge management model, "knowledge sharing" received the highest scores, with mean values of 3.2 at TUMS, 3.18 at IUMS, and 3.14 at SBUMS. No statistically significant differences were seen among these universities (p > 0.05). Several studies have also reported this component as one of the highest-scoring items [23, 30–32]. This suggests that the PhD curricula at these universities are well-suited for making easier the sharing of existing knowledge and its transfer to graduates. Alhammad et al. [30] looked into knowledge sharing among educational and administrative staff in Jordanian universities, identifying seven components: interactions, organizational experience, teamwork, creativity, positive attitudes toward knowledge sharing, knowledge about knowledge sharing, and knowledge sharing behavior. Their study revealed that educational staff were less willing to share knowledge compared to administrative staff. In a study by Kanzler et al. [33], knowledge sharing within a higher education institution in Mauritius was made easier through departmental meetings, curriculum discussions, annual research seminars, conferences, and journal publications. However, many organizations face challenges in knowledge sharing due to an inadequate organizational culture, which requires careful planning and attention. Knowledge sharing, which bridges knowledge management and creativity, is critical for creating a competitive advantage in today's world. To back up effective knowledge sharing, organizations need appropriate tools and techniques, such as knowledge bases (e.g., encyclopedias), collaborative virtual [ DOI: 10.61882/edcj.18.4.4 ] [ Downloaded from edujournal.zums.ac.ir on 2025-12-18 ] 9 / 14