Introduction
Design thinking, as conceptualized by Simon (1973) and elaborated by Dorst and Cross (2001), represents a dynamic, human-centered approach to problem-solving that integrates creativity, empathy, and iterative processes to tackle complex and ambiguous challenges. Unlike traditional linear problem-solving methods, design thinking emphasizes reframing problems, fostering collaboration, and generating innovative solutions through reflective practice (Schön, 1992). Its interdisciplinary relevance has extended its application beyond design professions to fields such as education, management, technology, and social innovation (Brown, 2008; Manzini, 2015). Manzini (2015) underscores design thinking as a universal human capability, not confined to professionals, but accessible to all as a means of creating social meaning and fostering sustainable change. Despite its growing prominence, tools to assess design thinking mindsets in non-design contexts remain limited. The Design Thinking Mindset Questionnaire by Vignoli et al. (2023) offers a comprehensive framework, measuring 10 dimensions: tolerance for uncertainty and risk-taking, empathy, holistic thinking, collaboration and diversity, learning orientation, experimentation, critical questioning, estimation, creative confidence, and impact. This scale, however, has not been validated in Iran, where cultural and professional contexts may influence its applicability. This study evaluates the psychometric properties of this questionnaire and compares its factor structure between architects (design professionals) and non-architects (general social actors) in Tehran, Iran. It addresses two research questions: (1) To what extent does the questionnaire demonstrate validity and reliability for measuring design thinking among Iranian architects and non-architects? (2) What similarities and differences exist in the factor structure of the design thinking mindset between these groups? The study contributes to localizing assessment tools and understanding how professional training shapes cognitive approaches to design thinking.

Methodology
This quantitative study employed a survey design with a sample of 674 participants, comprising 412 architects and 262 non-architects, randomly selected in Tehran. The architects’ group included students from Shahid Beheshti and Tehran Universities and professional engineers registered with the Tehran Engineering Organization. The non-architects’ group encompassed individuals with diverse ages, genders, and educational backgrounds, recruited via the National Library of Iran’s Telegram channel. Data were collected using a Persian translation of Vignoli et al.’s (2023) questionnaire, comprising 40 items across the 10 dimensions noted above. To enhance response precision and reduce central tendency bias, a 7-point Likert scale (1 = completely disagree, 7 = completely agree) was adopted, supported by research indicating improved measurement accuracy with broader scales (Babai et al., 1400; Smith & Johnson, 2018). The translation process involved experts in architecture, education, and English to ensure content and face validity. Items were refined based on feedback from three English language specialists, with final validation by a dual expert in design and psychology.
Data analysis was conducted in three phases: exploratory factor analysis (EFA), first-order confirmatory factor analysis (CFA), and second-order CFA, using SPSS 27.0.1 and AMOS software. The Kaiser-Meyer-Olkin (KMO) test assessed sampling adequacy, and Bartlett’s test of sphericity verified variable correlations. EFA identified the factor structure, while CFA validated structural and hierarchical relationships. Reliability was evaluated through internal consistency, and group differences were analyzed to compare mindset manifestations. The sample size exceeded the minimum threshold for structural equation modeling (Hair et al., 2010; Kline, 2015), ensuring robust statistical power.

Results and discussion
The KMO test confirmed sampling adequacy (KMO = 0.884 for architects; 0.855 for non-architects), and Bartlett’s test (p < 0.001) verified significant correlations. EFA revealed a 10-factor structure, explaining 64.913% of the variance for architects and 61.46% for non-architects. Most items had factor loadings above 0.5, though some (e.g., Q12: “I can easily utilize solutions from a broader perspective”; Q13: “I can revisit the initial project question”) showed lower loadings among non-architects, suggesting cultural or contextual misalignments. First-order CFA confirmed the 10-factor model, with fit indices indicating acceptable validity for architects (CMIN/DF = 2.000, RMSEA = 0.062, CFI = 0.815, TLI = 0.793) and non-architects (CMIN/DF = 2.597, RMSEA = 0.070, CFI = 0.814, TLI = 0.791). Second-order CFA validated the hierarchical structure, with all dimensions significantly contributing to the overarching design thinking mindset (p < 0.001). Reliability analyses demonstrated high internal consistency across dimensions.
Significant group differences emerged. Architects showed stronger loadings in holistic thinking (Q12: 0.826 vs. 0.432) and experimentation (Q24: 0.760 vs. 0.463), reflecting their design training and familiarity with iterative processes. Non-architects exhibited higher loadings in learning orientation (Q19: 0.716 vs. 0.367), indicating a more theoretical, experience-driven approach. These findings align with Vignoli et al. (2023) and underscore the influence of professional expertise on cognitive frameworks. For instance, architects’ exposure to prototyping enhanced their experimentation scores, while non-architects’ unfamiliarity with such practices weakened these items’ relevance. Items like Q5 (“I dedicate significant time to understanding user needs”) and Q13 require revision for non-designers, potentially using more relatable, everyday examples. The study also suggests rephrasing items like Q18 (“I am ready to collaborate with individuals from different backgrounds”) to enhance clarity for architects.

Conclusion
This study validates the psychometric properties of the Design Thinking Mindset Questionnaire in Iran, confirming its reliability and structural validity for architects and non-architects. The 10-factor model is robust, with group differences highlighting the impact of professional training. Architects exhibit a practice-driven, integrated mindset, while non-architects display a learning-oriented approach. The scale’s adaptability supports its use in educational and interdisciplinary contexts, facilitating the development of localized tools and targeted interventions. For example, enhancing experimentation skills among non-architects or critical questioning among architects could bridge mindset gaps. Limitations include potential cultural influences on responses and reliance on self-reported data, which may introduce bias. Future research should explore cross-cultural comparisons, incorporate mixed-methods approaches, and conduct longitudinal studies to examine mindset evolution. This study lays a foundation for advancing design thinking education and fostering innovation in Iran’s academic and professional landscapes.