Knowledge, Attitudes, and Readiness of Pharmacy Faculty toward Competency-Based Learning in Syrian Universities: A Cross-Sectional Study [version 1; peer review: awaiting peer review]

Дата публикации: 08-08-2026 08:55:45

Background Competency-based learning (CBL) is transformative in health professions education, yet its adoption in Syrian pharmacy education remains unexamined, especially after the country’s prolonged conflict. Methods A cross-sectional study (autumn 2022) surveyed pharmacy faculty across Syrian universities using a validated online questionnaire (response rate: 39.7%; 124/312). Knowledge items were assessed via KR-20 (bootstrap 95% CI). Statistical analyses included descriptive statistics, chi-squared tests, ANOVA, Spearman’s correlations, multivariate binary logistic regression, multinomial logistic regression, and wave-based non-response analysis (STROBE-compliant). Results Of 124 respondents, 57.3% were female, 62.1% aged 25–42 years. Knowledge sub-scale consistency was modest (KR-20 = 0.386; 95% bootstrap CI: 0.230–0.509). Prior CBL awareness was 70.2%; support for pedagogical modification (98.4%) and faculty training (87.9%) was near-universal; 89.5% favored CBL adoption (56.5% preferring blended learning). Younger age (aOR = 0.08; p = 0.020) and female gender (aOR = 0.15; p = 0.025) independently predicted positive CBL attitudes (model χ2 = 28.93, p

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1. Introduction

Competency-based learning (CBL) has emerged as a transformative paradigm in health professions education, shifting the focus from traditional time-bound instructional models to outcome-driven approaches that prioritize the attainment of pre-defined competencies.¹ Unlike conventional curricula organized around fixed course durations and credit hours, CBL is structured around the demonstration of specific knowledge, skills and attitudes that graduates must possess to perform effectively in their professional roles.²^,³ This educational framework has been widely adopted across medical, nursing and dental education globally, driven by the imperative to produce graduates who are not only knowledgeable but also clinically competent and responsive to evolving healthcare needs.⁴

The pharmacy profession itself has undergone substantial transformation over the past two decades, evolving from a product-focused dispensing role to a patient-centered clinical discipline that requires advanced cognitive and interpersonal competencies.⁵^,⁶ Contemporary pharmacy practice demands proficiency in medication-therapy management, patient communication, interprofessional collaboration, critical thinking and evidence-based decision making.⁷ Traditional didactic models, while effective for transmitting foundational knowledge, often fall short in developing these higher-order competencies.⁸ In response, pharmacy educators worldwide have increasingly embraced CBL as a pedagogical strategy to bridge the gap between theoretical instruction and clinical practice.⁹^,¹⁰

The core principles of CBL include explicit articulation of learning outcomes, flexible time allocation based on individual student progress, integration of knowledge and skill development, continuous formative assessment, and a shift in the instructor’s role from knowledge transmitter to learning facilitator.¹¹^,¹² Within a CBL framework, students progress through the curriculum upon mastery of pre-defined competencies rather than after completing a fixed period of study. This approach has been associated with enhanced clinical reasoning, improved student engagement and better preparation for workplace practice.¹³^,¹⁴

Despite the international consensus that supports CBL in pharmacy education, the adoption of this model across the Eastern Mediterranean region remains inconsistent and poorly documented.¹⁵^,¹⁶ In Syria, pharmacy education has historically followed traditional lecture-based curricula, with limited incorporation of competency-based approaches. The protracted armed conflict that began in 2011 has profoundly disrupted higher-education infrastructure, leading to faculty attrition, curriculum fragmentation and reduced opportunities for pedagogical innovation.¹⁷^–³³ A recent systematic review of medical and health-professions education in Syria specifically documented severe disruptions to teaching delivery, faculty development and clinical training across the past decade,³³^,³⁴ findings that pharmacy programs have not been spared.¹⁹ Empirical work using national medical-examination scores from 18 312 students in nine Syrian medical schools further confirms a measurable, conflict-related decrement in academic performance during the most intense periods of the war.²⁷

In this challenging context, understanding the knowledge, attitudes and readiness of pharmacy faculty members toward CBL becomes critically important. Faculty members are the primary agents of curricular change; their acceptance of, and preparedness for, new pedagogical approaches are essential determinants of successful implementation.²⁰^,²¹ Research in other settings has identified prior exposure to competency-based education, age, years of teaching experience and institutional support structures as factors associated with faculty readiness for CBL.²²^,²³ Younger faculty often demonstrate greater openness to pedagogical innovation, whereas more experienced faculty may harbor reservations rooted in familiarity with traditional methods.²⁴ Gender differences have also been reported, with some studies indicating that female faculty exhibit more positive attitudes toward student-centered learning approaches.²⁵ However, no published study has systematically examined these factors among pharmacy faculty in Syria, leaving a critical evidence gap.

The Syrian higher-education landscape comprises both public and private universities that differ substantially in their resources, governance structures and institutional cultures.²⁶ Public universities have faced severe resource constraints during the conflict, while private universities have emerged as alternative providers with potentially greater flexibility for curricular innovation.²⁷ Whether faculty from different institutional backgrounds hold divergent views on CBL remains unknown, yet this information is essential for designing context-sensitive implementation strategies.

Against this backdrop, the present study was designed to address the following objectives: (1) to assess the level of knowledge regarding CBL principles among pharmacy faculty members in Syrian universities; (2) to explore their attitudes toward the feasibility and desirability of CBL implementation; (3) to identify demographic and professional factors independently associated with CBL knowledge and attitudes, while controlling for potential confounders; and (4) to generate evidence-based recommendations for faculty development and curricular reform. Building on the existing literature, four a priori hypotheses were formulated: (H1) younger faculty members would demonstrate more favorable attitudes toward CBL adoption than their older counterparts; (H2) female faculty would exhibit greater willingness to adopt CBL than male faculty; (H3) faculty affiliated with private universities would perceive CBL as more feasible than those at public institutions; and (H4) prior familiarity with CBL would be positively associated with willingness to adopt this approach.

2. Materials and methods

2.1 Study design and ethical approval

This cross-sectional descriptive study employed a structured self-administered online survey to assess the knowledge and perceptions of pharmacy faculty members regarding CBL across Syrian universities. The protocol received ethical approval from the Ethics Committee of the Syrian Virtual University (approval no. 240/0) prior to data collection, and all procedures adhered to the principles of the Declaration of Helsinki. Electronic informed consent was obtained from each participant before survey completion. Participation was entirely voluntary, and respondents were assured of the anonymity and confidentiality of their data. All records were stored on a password-protected computer accessible only to the research team.

2.2 Study population, sampling and data collection

The target population comprised faculty members currently engaged in teaching within pharmacy programs at Syrian universities. A convenience sampling approach was employed, encompassing both public and private institutions across multiple Syrian governorates. Eligible participants were required to hold a current teaching appointment in a pharmacy department, to be between 25 and 60 years of age and to provide informed consent. The upper age limit of 60 years corresponds to the mandatory retirement age for public-university faculty in Syria; respondents over this age were not encountered.

The survey was distributed in the autumn of 2022 (15 October–8 December 2022) via an electronic questionnaire hosted on Google Forms. Invitations were disseminated through professionally dedicated social-media groups (WhatsApp and Telegram) used by pharmacy faculty networks across Syria; admission to these groups requires verified institutional affiliation, providing a first layer of identity assurance. Invitations were sent through 14 university-affiliated professional groups spanning the principal Syrian governorates with active pharmacy programs, in order to maximize institutional and geographical reach. The closed and confidential nature of these groups, together with the continuing security context, precluded the public release of governorate-level participant counts; nevertheless, both the public and private institutional sectors and both metropolitan and provincial faculties were represented in the final sample, in proportions broadly consistent with national pharmacy-faculty distribution.

A total of 312 unique invitations were distributed. The survey link was accessed by 189 individuals, of whom 127 initiated the questionnaire. Three incomplete responses (missing >50% of items) were excluded, yielding a final analytic sample of 124 completed surveys. The overall response rate was 39.7% (124/312), while the completion rate among those who accessed the link was 65.6% (124/189). The 54-day collection window reflected several practical constraints inherent to the Syrian context, including intermittent internet connectivity in conflict-affected areas, faculty workload fluctuations during examination periods, and the necessity of distributing reminder invitations at four-week intervals.¹⁷^–³⁴

2.3 Survey instrument development, translation, validation and reliability

A structured questionnaire comprising 19 items was developed specifically for this study, informed by the existing literature on competency-based education in health professions [1–10]. The instrument was organized into three domains: (i) demographic and professional characteristics (gender, age group, institutional affiliation); (ii) knowledge of CBL principles, indexed by eight dichotomous items covering educational outcomes focus, knowledge–skill emphasis, time flexibility and assessment role; and (iii) attitudes toward CBL implementation (feasibility, pedagogical-modification needs, training requirements, adoption preference and institutional suitability). Response formats included dichotomous items (yes/no; true/false), single-selection multiple-choice items, and one open-ended question subsequently re-coded into three categorical responses based on thematic convergence.

The questionnaire was initially drafted in English, translated into Arabic by a bilingual faculty member with expertise in medical education, and independently back-translated into English by a second bilingual translator who was blinded to the original version. Discrepancies between the original and back-translated versions were resolved through discussion among the research team until consensus was reached. The Arabic version was subsequently piloted with five pharmacy faculty members who were not included in the final study sample, and minor linguistic adjustments were made to improve clarity and cultural appropriateness.

Content validity was established through independent review by two senior faculty members with expertise in pharmacy education and curriculum development; both reviewers confirmed that the instrument adequately represented the constructs of interest. Because the questionnaire deliberately mixes three structurally heterogeneous domains—demographic items, dichotomous knowledge items and categorical attitude items—that do not constitute a single unidimensional summated scale, a single global Cronbach’s α was not psychometrically appropriate.³⁵ Internal consistency for the eight dichotomous knowledge items, which form a coherent sub-scale, was therefore quantified by the Kuder–Richardson 20 (KR-20) coefficient, the binary-item analogue of α,³⁶^,³⁷ with a 1 000-resample bootstrap 95% confidence interval. Item-level difficulty (p_i) and discrimination (point-biserial r_pb) statistics, together with the KR-20 that would result from removing each item in turn, are reported in Section 3.9. Open-ended responses to the question on reasons for not preferring CBL were classified into three thematic categories by members of the research team, with the final coding reached through team consensus discussion; raw rater-level data were not retained, precluding formal computation of an inter-rater agreement coefficient. Test–retest reliability was likewise not assessed in the present study; both gaps are acknowledged as priorities for the planned validation study of a stand-alone CBL knowledge-and-attitudes scale (Section 4.1).

2.4 Statistical analysis

Data were exported from Google Forms into Microsoft Excel, cleaned for completeness and imported into IBM SPSS Statistics v.23.0 (IBM Corporation, Armonk, NY, USA). Bootstrap and multinomial analyses were additionally performed in Python v.3.12 with statsmodels v.0.14 and scipy v.1.13. Descriptive statistics were computed for all variables and expressed as frequencies, percentages and 95% confidence intervals (CI) for proportions using the Wilson method.

Inferential analyses proceeded in five stages. First, bivariate associations between demographic variables and survey responses were evaluated using Pearson’s chi-squared (χ²) test for categorical data, with Fisher’s exact test applied when expected cell frequencies fell below 5. Cramér’s V was reported as the effect size for all chi-squared tests. One-way ANOVA was used to compare ordinal response distributions across the three institutional-affiliation categories, with Levene’s test used to assess homogeneity of variances; the Kruskal–Wallis H test served as a non-parametric verification.

Second, to identify independent predictors of positive attitudes toward CBL adoption while controlling for confounders, a multivariate binary logistic regression model was fitted. The dependent variable was operationalized as a binary outcome (1 = preference for full adoption or for blended adoption; 0 = no preference for CBL). This binary specification was chosen a priori to maximize statistical power, given that the no-preference group constituted only 10.5% (n = 13) of respondents and a three-category outcome would have been underpowered for the principal model. Gender, age group, institutional affiliation (collapsed to ‘both public-and-private’ versus other) and prior CBL knowledge were entered simultaneously as independent variables. Adjusted odds ratios (aOR) with 95% Wald confidence intervals were reported. Model fit was evaluated using the Hosmer–Leme show goodness-of-fit test, McFadden’s pseudo-R² and overall classification accuracy.

Third, given the modest sample size (N = 124) and the wide confidence intervals associated with the smallest subgroups, the stability of the adjusted odds-ratio estimates was verified by a non-parametric bootstrap (1 000 resamples with replacement) on the same logistic-regression specification.³⁸^,⁴² Resamples that failed to converge or produced extreme coefficients consistent with quasi-separation in the smallest subgroups (|β| > 10 on the log-odds scale) were excluded; percentile rather than bias-corrected and accelerated intervals are reported, as the latter were unstable for these resamples. Of the 1 000 resamples, 554 produced stable estimates, 253 produced extreme coefficients, and 193 failed to converge (Section 3.10). As a sensitivity analysis for the binary specification of the dependent variable, a multinomial logistic regression contrasting the three outcome categories (full adoption /blended adoption/no preference; reference = no preference) was fitted with the same four predictors; adjusted relative-risk ratios (aRRR) with 95% confidence intervals and a likelihood-ratio test of the overall model are reported (Section 3.11).

Fourth, Spearman’s rank correlation coefficients (ρ) were calculated to quantify monotonic associations among the principal study variables.

Fifth, a pre-planned sensitivity analysis was conducted by excluding respondents affiliated exclusively with private universities (n = 20)—the smallest subgroup—to assess whether the principal findings were robust to the removal of this potentially influential subgroup. Post-hoc statistical power was calculated for all chi-squared tests using the non-central chi-squared distribution. Following Armstrong and Overton,⁴³ the demographic characteristics of respondents who completed the survey before and after the median submission date were compared by χ² tests as a wave-based assessment of potential non-response bias (Section 3.12). A two-tailed significance level of α = 0.05 was adopted throughout. Results are reported in accordance with the STROBE guidelines for cross-sectional studies.²⁸

3. Results

3.1 Demographic characteristics

A total of 124 pharmacy faculty members completed the survey, representing a response rate of 39.7% (124/312). The sample comprised 71 women (57.3%) and 53 men (42.7%). The majority (n = 77; 62.1%) belonged to the 25–42 years age group, while 47 (37.9%) were aged 43–60 years. Regarding institutional affiliation, 60 (48.4%) reported working at both public and private universities, 44 (35.5%) exclusively at public universities and 20 (16.1%) exclusively at private universities ( Table 1).

Table 1. Demographic characteristics of participating pharmacy faculty members (N = 124).VariableCategoryN % (95% CI)Gender Female7157.3 (48.3–65.7)Male5342.7 (34.3–51.7)Age group 25–42 years7762.1 (53.2–70.2)43–60 years4737.9 (29.8–46.8)Institutional affiliation Public university4435.5 (27.4–44.4)Private university2016.1 (10.5–23.8)Both public and private6048.4 (39.6–57.2)

3.2 Faculty knowledge of CBL principles

Approximately 70.2% (n = 87; 95% CI: 61.5–77.7) of respondents reported prior awareness of CBL. The majority (61.3%) correctly identified educational outcomes as the primary focus, while 84.7% agreed that CBL should emphasize knowledge and skill development in parallel. Most respondents (86.3%) recognized that CBL affords flexible time allocation, and 95.2% endorsed assessment as essential. The perceived need for pedagogical modification (98.4%) and faculty training (87.9%) was near-universal ( Figure 1).

Figure 1. Faculty responses to key CBL knowledge items (N = 124).

3.3 Faculty attitudes toward CBL implementation

When asked about feasibility, 58.1% indicated that CBL requires prolonged integration, 27.4% considered it immediately feasible and 14.5% not feasible. The majority (56.5%) preferred a blended approach, 33.1% expressed full willingness and 10.5% did not favor CBL. Regarding the instructor’s role, 50.8% described it as ‘facilitator’, 47.6% as ‘essential’ and 1.6% as non-existent. Private universities were deemed most suitable for CBL by 47.6% of respondents, while 38.7% perceived no institutional difference and 13.7% favored public universities.

3.4 Bivariate associations

No significant association was found between prior CBL knowledge and gender (χ² < 0.001, p = 1.000), age (χ² < 0.001, p = 1.000) or institutional affiliation (χ² = 4.012, p = 0.135; post-hoc power = 0.42). CBL preference, however, differed significantly by gender (χ² = 13.586, df = 2, p = 0.001, V = 0.331, power = 0.92) and age (χ² = 18.874, df = 2, p < 0.001, V = 0.390, power = 0.98; Figure 2). Institutional affiliation was significantly associated with perceived institutional suitability (χ² = 20.109, df = 4, p < 0.001, V = 0.285; Figure 3), training necessity (χ² = 7.601, p = 0.022, V = 0.248) and pedagogical modification (χ² = 10.570, p = 0.005, V = 0.292). One-way ANOVA and Kruskal–Wallis tests yielded concordant results ( Table 2).

Figure 2. Analyzing CBL preference by age group (χ² = 18.874, p < 0.001, V = 0.390).

Figure 3. Suitable institution for CBL by affiliation (χ² = 20.109, p < 0.001, V = 0.285).

Table 2. Chi-squared (χ²) tests of association between demographic variables and survey responses.IndependentDependentχ²DfpVEffect Power GenderPrior CBL knowledge<0.0111.000—Negl.—AgePrior CBL knowledge<0.0111.000—Negl.—AffiliationPrior CBL knowledge4.0120.1350.18Small0.42 Gender CBL preference 13.59 2 0.001 **0.33 Med. 0.92 Age CBL preference 18.87 2 <0.001 ***0.39 Med. 0.98 Affiliation Suitable institution 20.11 4 <0.001 ***0.29 S–M 0.72 Affiliation Training courses 7.60 2 0.022 *0.25 Small — Affiliation Pedagogical modification 10.57 2 0.005 **0.29 S–M — AffiliationTeacher role3.5040.4780.12Small0.16

3.5 Multivariate logistic regression

Table 3 presents the multivariate binary logistic regression predicting positive CBL attitudes. The model was significant (χ²(4) = 28.93, p < 0.001; McFadden pseudo-R² = 0.348; classification accuracy = 89.5%). Age (aOR = 0.08, 95% CI: 0.01–0.67, p = 0.020) and gender (aOR = 0.15, 95% CI: 0.03–0.79, p = 0.025) were significant independent predictors, confirming H1 and H2. Institutional affiliation did not reach significance under the asymptotic Wald test (aOR = 0.23, p = 0.099), failing to confirm H3. Prior CBL knowledge was not independently predictive (aOR = 1.63, p = 0.509), rejecting H4. The bootstrap-derived intervals presented in Section 3.10 reinforce the stability of the principal effects, while the multinomial sensitivity analysis (Section 3.11) demonstrates that the age effect holds across both the blended-vs-no-preference and full-vs-no-preference contrasts.

Table 3. Multivariate binary logistic regression predicting positive CBL attitude (N = 124).PredictoraOR95% Wald CIp-value Hypothesis Age (43–60 vs. 25–42) 0.08 0.01–0.67 0.020 *H1 ✓ Gender (male vs. female) 0.15 0.03–0.79 0.025 *H2 ✓ Affiliation (both vs. other)0.230.04–1.320.099H3 ✗Prior CBL knowledge1.630.38–6.880.509H4 ✗

3.6 Correlation analysis

The strongest Spearman correlation was between implementation feasibility and CBL preference (ρ = 0.367, p < 0.001). Age correlated with institutional affiliation (ρ = 0.349, p < 0.001). Prior knowledge was associated with assessment endorsement (ρ = 0.264, p = 0.003) and inversely with implementation barriers (ρ = −0.202, p = 0.024). Younger faculty were more receptive to training (ρ = −0.271, p = 0.002) ( Figure 4).

Figure 4. Spearman’s rank correlation matrix among the principal study variables (*p < 0.05; **p < 0.01; ***p < 0.001).

3.7 Sensitivity analysis (excluding the private-university subgroup)

After exclusion of the 20 private-university respondents (reduced N = 104), all primary significant associations persisted: age–preference (χ² = 16.41, p < 0.001), gender–preference (χ² = 12.49, p = 0.002), affiliation–suitability (χ² = 18.70, p < 0.001) and affiliation–training (χ² = 5.76, p = 0.016). The findings were therefore not disproportionately driven by the small private-university subgroup.

3.8 Post-hoc statistical power

Statistical power was adequate for the two strongest associations: age–preference (V = 0.390, power = 0.98) and gender–preference (V = 0.331, power = 0.92). Power for affiliation–suitability (V = 0.285, power = 0.72) approached but did not reach the conventional threshold of 0.80. For non-significant associations, power was low (0.16–0.42), indicating that the study was underpowered to detect small effects. The minimum detectable effect at 80% power was V = 0.28 (df = 2) and V = 0.32 (df = 4) at N = 124.

3.9 Internal consistency of the dichotomous knowledge sub-scale

Across the eight dichotomous knowledge items, the Kuder–Richardson 20 coefficient was KR-20 = 0.386 (95% bootstrap CI: 0.230–0.509; 1 000 resamples), placing the sub-scale below the conventional 0.70 threshold for acceptable internal consistency. Item-level statistics ( Table 4) help to localize this finding. Item difficulties (p_i) ranged from 0.613 (K1, outcomes focus) to 0.952 (K8, assessment essential), and point-biserial discrimination indices (r_pb) ranged from 0.007 (K8) to 0.305 (K7, flexibility benefit). Two items contributed disproportionately to the modest internal consistency: K8 showed a near-ceiling p_i of 0.952 together with negligible discrimination (r_pb = 0.007), and K2 (compensation across competencies) similarly showed weak discrimination (r_pb = 0.056). Removing K8 alone left the coefficient essentially unchanged (KR-20-if-deleted = 0.393), which indicates that the modest reliability is not driven by a single deviant item but by the conceptual heterogeneity of the dimensions sampled by the sub-scale—educational-outcomes focus, knowledge–skill emphasis, time flexibility and assessment role each tap a distinct facet of competency-based pedagogy. Composite knowledge scores should accordingly be interpreted as exploratory; descriptive item-level percentages, on which the principal substantive interpretations rest, are unaffected. The development of a fully validated multidimensional CBL knowledge-and-attitudes scale is identified as a research priority in Section 5.

Table 4. Item-level psychometrics for the eight dichotomous knowledge items (N = 124).ItemConstruct (abbreviated)p_ir_pb KR-20 if deleted K1 Educational outcomes as the primary focus of CBL0.6130.2660.284 K2 Competence in one area cannot compensate for another0.7740.0560.397 K3 Desired outcomes must be clearly defined at program end0.7260.1090.374 K4 Knowledge and skill should be developed in parallel0.8470.1530.350 K5 Focus on student abilities should derive from local community needs0.6690.1660.344 K6 Time allocation is flexible, tied to learner pace0.8630.1620.347 K7 Increased learning flexibility makes learning more effective0.7180.3050.266 K8 Assessment is an essential element of CBL0.9520.0070.393

3.10 Bootstrap-derived confidence intervals for the binary logistic regression

A non-parametric bootstrap with 1 000 resamples was applied to the multivariate logistic-regression model. Of the 1 000 resamples, 554 (55.4%) yielded stable parameter estimates; 253 resamples produced extreme coefficients (|β| > 10 on the log-odds scale), and 193 failed to converge. The instability reflects quasi-separation in resamples that drew few or no observations from the smallest demographic subgroups (the 13 ‘no-preference’ and 20 private-only respondents); percentile rather than bias-corrected and accelerated intervals are therefore reported, as the latter were unstable for these resamples. The 44.6% instability rate is itself a diagnostically informative finding: it confirms the sample-size sensitivity flagged by the elevated pseudo-R² in the principal model (Section 3.5) and reinforces the recommendation for replication with N ≥ 300 made in Section 4.1; it does not, however, invalidate the percentile intervals derived from the stable resamples, which represent the subset of bootstrap draws that did not encounter separation.

Table 5 compares the asymptotic Wald and percentile bootstrap intervals on the adjusted-odds-ratio scale. For the two principal predictors, the bootstrap intervals were narrower than the Wald intervals: the age coefficient (aOR = 0.08) had a Wald 95% CI of 0.01–0.67 and a bootstrap 95% CI of 0.036–0.375; the gender coefficient (aOR = 0.15) had a Wald 95% CI of 0.03–0.79 and a bootstrap 95% CI of 0.039–0.613. Both bootstrap intervals exclude unity by a wide margin, supporting the stability of the age and gender effects despite the modest sample size. Notably, the bootstrap interval for the affiliation coefficient (aOR = 0.23, Wald 95% CI: 0.04–1.32; bootstrap 95% CI: 0.062–0.801) excludes unity, suggesting that the institutional-affiliation effect may be more substantively meaningful than the marginal Wald p-value of 0.099 indicates. The bootstrap interval for prior CBL knowledge spanned unity in the same direction as the asymptotic interval, consistent with the absence of an independent predictive contribution from this variable.

Table 5. Multivariate binary logistic regression—Wald versus percentile bootstrap 95% confidence intervals (N = 124; 1 000 resamples).PredictoraOR95% Wald CI 95% bootstrap CI Age (43–60 vs. 25–42) 0.078 0.009–0.673 0.036–0.375 Gender (male vs. female) 0.151 0.029–0.792 0.039–0.613 Affiliation (both vs. other)0.2340.041–1.3170.062–0.801 Prior CBL knowledge1.6260.385–6.8780.474–6.148

3.11 Multinomial logistic regression — sensitivity analysis for dependent-variable coding

To examine the robustness of the principal findings to the binary specification of the dependent variable, a multinomial logistic regression was fitted with the three-category outcome (full adoption /blended adoption/no preference; reference = no preference). The overall model was significant (likelihood-ratio χ²(8) = 35.00, p < 0.001; McFadden pseudo-R² = 0.15). Adjusted relative-risk ratios are presented in Table 6.

Table 6. Multinomial logistic regression—adjusted relative-risk ratios (aRRR) for the three-category CBL preference outcome (reference = no preference; N = 124).PredictorContrastaRRR95% CI P Age Group Blended (1) vs None (0)0.095 0.011–0.839 0.034 Gender Blended (1) vs None (0)0.117 0.022–0.629 0.012 Institutional affiliationBlended (1) vs None (0)0.2410.041–1.3970.112 Prior KnowledgeBlended (1) vs None (0)1.3290.303–5.8180.706 Age Group Full (2) vs None (0)0.059 0.006–0.546 0.013 GenderFull (2) vs None (0)0.2570.045–1.4820.129 Institutional affiliationFull (2) vs None (0)0.2210.036–1.3520.102 Prior KnowledgeFull (2) vs None (0)2.3660.488–11.4720.285

The age effect held with consistent direction and statistical significance across both contrasts: faculty aged 43–60 years were less likely than younger colleagues to favor the blended approach over no preference (aRRR = 0.095, 95% CI: 0.011–0.839, p = 0.034) and likewise less likely to favor full adoption over no preference (aRRR = 0.059, 95% CI: 0.006–0.546, p = 0.013). The gender effect was significant for the blended-vs-no-preference contrast (aRRR = 0.117, 95% CI: 0.022–0.629, p = 0.012) but attenuated and non-significant for the full-vs-no-preference contrast (aRRR = 0.257, p = 0.129). Substantively, this pattern indicates that gender differentiates whether faculty are willing to engage with CBL in any form rather than the intensity of that engagement. Institutional affiliation and prior CBL knowledge did not reach significance in either contrast. Taken together, the multinomial sensitivity analysis confirms that the age effect identified in the principal binary model is not an artefact of pooling ‘full’ and ‘blended’ preferences, while the gender effect’s attenuation in the full-vs-none contrast adds nuance that should be considered in interpreting Section 3.5.

3.12 Armstrong–Overton wave-based non-response analysis

Following Armstrong and Overton [38], the 124 respondents were partitioned at the median submission timestamp into early (n = 62) and late (n = 62) waves; under this principle, late respondents serve as proxies for non-respondents. The two waves did not differ significantly on gender (χ² = 0.527, df = 1, p = 0.468). Age-group distribution did differ significantly (χ² = 8.771, df = 1, p = 0.003): the late wave contained a higher proportion of 43–60-year-old faculty than the early wave. Institutional affiliation also differed significantly (χ² = 20.291, df = 2, p < 0.001): faculty with dual public-and-private affiliation were over-represented among late respondents, while public-only faculty were over-represented among early respondents. The absence of an early–late gender difference supports the gender-balanced representation of the present sample. The differences observed for age and affiliation, however, indicate that non-respondents may have been systematically older and more likely to hold dual appointments than the respondents who completed the survey early; generalizations regarding age and affiliation effects should therefore be made with appropriate caution. This is the most informative non-response analysis attainable in the absence of demographic data on actual non-respondents and does not, by itself, invalidate the principal findings.

4. Discussion

This study provides the first systematic assessment of pharmacy-faculty knowledge and attitudes regarding CBL in Syrian universities, generating quantitative evidence from a context that has been largely absent from the global literature on competency-based pharmacy education. The findings reveal a landscape of moderate awareness and broadly favorable disposition toward educational reform, with notable demographic variation that carries direct implications for implementation strategies. The internal-consistency, bootstrap, multinomial and wave-based analyses reported in Sections 3.9–3.12 collectively support the interpretive validity of the principal results while flagging dimensions—non-response on age and affiliation, modest sub-scale reliability—on which generalization should be tempered.

That 70.2% of respondents reported prior awareness of CBL is encouraging given the limited opportunities for faculty development in the Syrian context.¹⁷^,¹⁸ However, the fact that 34.7% incorrectly identified the educational process rather than outcomes as the primary focus of CBL suggests that awareness alone does not equate to accurate conceptual understanding. This distinction has practical implications: faculty-development programs should move beyond introductory awareness-raising to provide structured training in the operationalization of competency frameworks, assessment design and outcome mapping.¹¹^,¹²

The multivariate logistic regression—conducted to address the limitation of bivariate analyses in identifying independent predictors—confirmed that age and gender were significant independent determinants of positive CBL attitudes after adjusting for institutional affiliation and prior knowledge. Faculty aged 43–60 years had substantially lower odds of holding positive attitudes (aOR = 0.08) compared with younger colleagues, even after controlling for other factors. This finding aligns with the broader pedagogical literature documenting generational differences in receptivity to educational innovation²²^–²⁴ and carries direct implications for faculty-development design: programs should engage younger faculty as early adopters and change agents, while providing older faculty with dedicated support, mentorship and gradual exposure to CBL methodologies.²⁰^,²¹ The robustness of the age effect is further supported by both the bootstrap intervals (Section 3.10) and by its consistency across the binary and three-category model specifications (Section 3.11).

The significant gender effect (aOR = 0.15 for male vs. female) corroborates findings from other settings indicating that female faculty tend to hold more favorable attitudes toward student-centered pedagogies.²⁵ The multinomial analysis adds a useful nuance to this finding: gender differentiated the blended-vs-no-preference contrast strongly but the full-vs-no-preference contrast only modestly, suggesting that gender effects in the present sample operate primarily on the threshold of engagement with CBL rather than on the intensity of that engagement. The mechanism underlying this association remains speculative but may relate to differential socialization patterns, collaborative teaching preferences or greater comfort with facilitative educational roles among female educators. Future qualitative research should elucidate these gendered patterns rather than infer them from a quantitative association alone.

The preference for blended implementation expressed by 56.5% of respondents reflects a pragmatic recognition that phased, hybrid models may represent the most feasible pathway for introducing competency-based principles in settings where existing curricular infrastructure cannot be rapidly dismantled.³⁰^,³¹ The high receptivity to faculty training (87.9%) provides a concrete foundation upon which educational leaders can build structured professional-development programs.

The significant association between institutional affiliation and perceived suitability of university type for CBL (χ² = 20.109, p < 0.001) suggests that faculty perceptions are shaped by their lived experience within different institutional environments. Faculty working at both public and private universities overwhelmingly favored private institutions for CBL implementation, likely reflecting differential resource availability, smaller class sizes and greater administrative flexibility, in keeping with the documented heterogeneity of academic outcomes across Syrian higher-education institutions during the conflict.²⁷ The bootstrap-derived 95% confidence interval for the affiliation coefficient (Section 3.10) excludes unity, suggesting that the affiliation effect may carry more substantive weight than the asymptotic Wald p-value of 0.099 first implied; this reading should be tempered, however, by the wave-based finding (Section 3.12) that institutional affiliation was one of the two dimensions on which late and early respondents differed.

4.1 Limitations

Several limitations should be acknowledged. (i) The cross-sectional design precludes causal inference; the observed associations between demographic variables and CBL attitudes may be influenced by unmeasured confounders such as teaching experience, academic rank and prior pedagogical training, which were not captured by the instrument. (ii) The convenience sampling strategy and the 39.7% response rate limit generalizability; the wave-based comparison reported in Section 3.12 indicates non-response bias on age and affiliation, suggesting that the sample may under-represent older faculty and faculty with dual public-and-private appointments. Generalization to those subgroups therefore warrants caution. (iii) The dichotomous knowledge sub-scale showed modest internal consistency (KR-20 = 0.386, 95% CI: 0.230–0.509); item-level analysis (Section 3.9) attributes the modest coefficient to a ceiling effect on K8 and weak discrimination on K2 rather than to systematic measurement noise, but composite knowledge scores should be treated as exploratory. Test–retest reliability and a formal inter-rater agreement coefficient for the recoded open-ended item were not assessed in the present study; the consensus-based team coding used here does not permit retrospective estimation of Cohen’s κ, and this gap limits the interpretive weight that should be placed on the three-category distribution of reasons for not preferring CBL. Both psychometric gaps are identified as priorities for the planned validation study of a stand-alone CBL knowledge-and-attitudes scale. (iv) Although the binary specification of the dependent variable in the principal logistic regression collapses two qualitatively distinct positions (full vs. blended adoption), the multinomial sensitivity analysis (Section 3.11) confirmed that the principal age effect is consistent across both contrasts. (v) The McFadden pseudo-R² of 0.348 is relatively high for a four-predictor model on N = 124; the bootstrap diagnostics (Section 3.10), in which approximately 45% of resamples produced unstable estimates, indicate genuine sample-size sensitivity, but the percentile bootstrap intervals from the stable resamples were narrower than the Wald intervals, supporting the substantive interpretation. (vi) Although post-hoc power was adequate for the primary associations, several non-significant findings (e.g., affiliation–teacher role, V = 0.119, power = 0.16) may reflect insufficient statistical power rather than true null effects; replication with larger samples (N ≥ 300) is recommended. (vii) The 54-day data-collection window, while necessitated by contextual constraints, is shorter than ideal for a national-level survey; the sample analyzed here should accordingly be considered an autumn-2022 cross-section rather than a year-long national census. (viii) Reliance on self-reported data is subject to social-desirability bias.

5. Conclusion

Pharmacy faculty in Syrian universities show moderate awareness and broadly favorable attitudes toward competency-based learning, but the readiness gradient is steepest along age and gender lines, with younger and female faculty significantly more open to adoption. The encouraging implication is that change leadership already exists within Syrian pharmacy programs; the practical question is how to translate that latent willingness into structured, system-level reform under continuing resource constraints. We therefore advance four actionable recommendations directed at distinct stakeholder groups, rather than a re-statement of the empirical findings.

First, for ministerial and accreditation bodies, a national CBL roadmap for the pharmacy profession should be developed jointly by the Higher Education Council, the Ministry of Health and the Syrian Pharmaceutical Association, anchored on a phased, blended implementation timeline and benchmarked against international competency frameworks (e.g., the FIP Global Competency Framework and ACPE outcomes).⁵^,⁶ The roadmap should commit to publishing minimum competency standards and a national assessment blueprint within twenty-four months.

Second, for deans and curriculum committees, each pharmacy faculty should establish a CBL Curriculum Reform Committee with deliberately intergenerational composition: at least 50% of seats reserved for faculty under 42 years of age, paired with senior faculty as co-leads. This pairing strategy operationalizes our finding that age is a key determinant of CBL receptivity and converts a potential generational divide into a co-design mechanism. We further recommend that an initial pilot focus on three or four core clinical-pharmacy modules in a single cohort, with pre-defined competency milestones, before any system-wide scaling.

Third, for faculty-development units, a Train-the-Trainer program should be commissioned that targets early adopters first—younger faculty, female faculty and those with prior CBL exposure—and that explicitly integrates assessment redesign (workplace-based assessment, OSCE adaptation), entrustable professional activities and outcome mapping.¹¹^–³² Because 87.9% of faculty in our sample already endorse the need for training, the demand-side conditions for such a program are already in place; what remains is a supply-side commitment of dedicated time, recognition and budget.

Fourth, for the research community, the present cross-sectional snapshot must be extended along three axes. (a) A longitudinal cohort study should track faculty attitudes and self-reported CBL practice annually for at least five years, so that the effects of any reform initiative can be detected and the temporal stability of the demographic gradients tested. (b) A psychometrically validated CBL knowledge-and-attitudes scale—including KR-20 internal consistency, test–retest reliability and confirmatory factor analysis—should be developed for the Eastern Mediterranean context.³⁵^–³⁷ (c) Multi-site, multi-country studies that include Lebanon, Jordan and Iraq would test whether the demographic patterns observed here generalize across the region.

The protracted Syrian conflict has constrained but not eliminated the appetite for pedagogical reform. The faculty surveyed here are not asking whether CBL should be adopted; they are asking how it can be adopted in a context where resources are limited and trust in institutional change has been eroded. Translating that readiness into reality will require coordinated action across the four stakeholder groups identified above—and the time for that action is now.

Acknowledgments

The authors thank all pharmacy faculty members who participated in this study despite the challenging circumstances in Syria. We also acknowledge the support of the Syrian Virtual University for facilitating ethical approval.

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Knowledge, Attitudes, and Readiness of Pharmacy Faculty toward Competency-Based Learning in Syrian Universities: A Cross-Sectional Study [version 1; peer review: awaiting peer review]

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