Oct 2026· Qlantic Journal of Social Sciences· 0 citations· 21 references
Abstract
Pharmaceutical companies increasingly rely on Medical Science Liaisons (MSLs), which is a structured, science-led process of engagement rather than a sales role, to exchange clinical evidence with specialist healthcare professionals (HCPs). However, few empirical studies have explored the relationship between the perceived professionalism of this process and the belief-formation stage of the Theory of Planned Behavior (TPB). This study tests a structural model, based on data collected from 400 specialist physicians in nine cities in Pakistan, in which the professionalism of the MSL process explains the level of knowledge that physicians acquire, which in turn influences their attitude towards scientific information provided by MSL. Both direct paths (Professionalism → Knowledge Acquisition, β = .521, p < .001; Knowledge Acquisition → Attitude, β = .552, p < .001) were supported with partial least squares structural equation modeling (PLS-SEM), and a significant indirect effect of Professionalism on Attitude through Knowledge Acquisition was supported (Professionalism → Knowledge Acquisition → Attitude, β = .288, p < .001). All constructs demonstrated strong reliability and discriminant validity. The findings position knowledge acquisition as the mechanism through which a professionally conducted MSL process translates into favorable physician attitudes, which is the upstream, belief-formation stage of TPB, with implications for how pharmaceutical companies structure scientific engagement and for the broader application of TPB in professional, non-consumer decision contexts.
Concerns about reproducibility, transparency, and research waste have intensified debates about trust in medical research and health-related sciences. Although Open science initiatives aim to address these challenges, their role in undergraduate medical education remains underexplored. Undergraduate medical education t...
H. Jeung-Maarse, Rosa L. Ecos, L. F. Jiménez-Soto et al.· Perspectives on Medical Educ...· 0 citations
Introduction Little is known about how language, gender, and perceived professional authority simultaneously influence medical communication between doctors and patients. This study addresses this gap by examining Saudi medical and health science students' attribution of miscommunication in four medical simulation scen...
Mohammed Alzahrani, Yousef Hadhram· Frontiers in Medicine· 0 citations
Introduction: Professional identity formation constitutes a central dimension of contemporary medical education, involving a progressive process through which medical students and physicians in training internalize the values, norms, roles, behaviors, and ways of understanding practice that characterize the medical pro...
Rodolfo de Oliveira Medeiros, C. Galhardi, Viviane Canhizares Evangelista de Araújo et al.· Veredas do Direito· 0 citations
Aim: To assess perceived research knowledge, attitudes, barriers, and factors associated with participation in scientific events among medical sciences students in Albania.
Methods: This cross-sectional study included 721 Bachelor’s and Master’s students at Albanian universities. A pilot-tested 20-item online questionn...
Patient-centricity is a well-established healthcare principle that emphasizes active patient engagement as a driver of innovation. However, the regulatory environment in which pharmaceutical companies operate restricts direct interaction with patients, thereby limiting access to experiential knowledge, a form of ta...
C. Esposito, C. Dell’Era· Journal of Knowledge Managem...· 0 citations
OBJECTIVE
Professional identity formation (PIF) is increasingly recognized as a core outcome of pharmacy education; however, little is known about how pharmacy students conceptualize what it means to be a pharmacist and the factors shaping this process. This scoping review aimed to map the literature on pharmacy studen...
N. R. Espinoza Suarez, Aya Benharira, Lilia Ben Abdelkader et al.· American Journal of Pharmace...· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.