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Examining key factors impact on health science students’ intentions to adopt genetic and pharmacogenomics testing: a comparative path analysis in two different healthcare settings



There is an increasing interest worldwide in investigating healthcare stakeholders’ perceptions and intentions to adopt pharmacogenomics (PGx) into clinical practice. However, the existing inquiries based on well-established theories and models that interpret their intentions to implement PGx are scarce. This study is the first that examines the impact of selected factors on health science students’ intention to adopt genetic testing applications using the technology acceptance model while it compares two different cultural groups: Greeks (Europe; Christian) and Malays (Asia; Muslim).


Malay students were more persuaded about benefits of genomics for drug management compared to their Greek counterparts. However, participants from both countries appear to be particularly convinced about the benefits of genomics on disease management. Moreover, students from both countries considered the potential misuse of genetic information by corporate or government bodies as their most important concern; Greek students appeared to be considerably less worried than Malay about other probable hazards such as the deficient protection of privacy and confidentiality, which could be attributed to their religious background. Participants from both samples expressed very positive attitudes towards genetic research and testing and their favourable intentions to adopt genetic testing for personal use. Exploratory factors analysis and path analysis yielded quite similar results for both samples. Path analysis revealed that the factors of attitudes, concerns, drug management benefits and disease management benefits significantly influenced students’ intentions to adopt genetic testing for personal use, with attitudes being the most inspirational factor with rather high impact, while training did not seem to affect participant’s intentions. The squared multiple correlation of both models was quite satisfactory reaching to 0.55 for the Malaysian sample.


Similarities in the results of the two groups along with the relevant validity and reliability tests indicate that the proposed model is a good fit for future studies to interpret stakeholders’ intentions to adopt genetic testing. Therefore, it can provide a promising and reliable basis for future model development to explain the relationships between intentions to adopt genetic testing and its predictors.


During the past decades, genetic research has played an essential role in understanding diseases’ pathophysiology and patients’ input, underscoring the impact of personalized medicine (PM). PM as a clinical approach has a beneficial impact on patients, health care delivery systems and researchers by offering adequate therapeutic approaches to each patient and saving time, effort, and money for disease and drug management [1].

Nowadays, PM significance and contribution in clinical practice has been acknowledged, and for this reason, there is a plethora of research studies available in the literature. The majority of these studies aim to explore and understand the attitudes and perceptions of healthcare professionals, health science students and patients towards the use of genetic testing in clinical practice, the benefits and risks of genetic applications such as pharmacogenomics (PGx) testing and the potential barriers that impede their wider implementation. Admittedly, the adoption level of genetic testing varies across the globe [2]. In western societies, for instance, the genetic testing applications such as pharmacogenomics (PGx) in clinical practice are popular, whereas in Asia, PGx implementation is limited and restricted only in urban areas [3,4,5].

Notably discrepancies may be attributed to the existence of different cultural backgrounds, professionals' perceptions, society ethnicity mix and the way the health system works which is of major importance [2, 6]. Even if there is a great number of publications addressing the possible barriers that impede PM implementation and the use of genetic testing, there are only a few studies focusing on determining and empirically investigating the factors and their relationship to the adoption of genetic testing. This gap in the literature is significantly important since understanding the way these factors affect the rate of adoption and recognizing the influence of cultural differences in the implementation of innovative services is essential to develop and enact more targeted healthcare policies [789].

Our group has an active research interest in assessing and reporting the level of awareness of pharmacy students regarding genetic testing and its application in Greece [8]. In previous surveys, we have investigated the perceptions and attitudes of medical and pharmacy health science students towards genetic testing in Southeast Asia and Southern Europe, gaining insight into their existing perceptions [10, 11]. Evidently, it was possible to estimate the adoption level of PM in Malaysia and Greece correspondingly by pinpointing the main factors that affect genetic testing adoption and to explore the impact that cultural differences exert on technological innovation acceptance.

Here, we suggest a new model which investigates the impact of selected factors on health science students' intention to adopt genetic testing by probing into the similarities and differences of two disparate cultural settings, namely a European, Greece, and an Asian, Malaysia.


Framework for the proposed model

In this study, we have developed a customized model framework to estimate the impact of several factors on health science students’ intention to adopt a new innovation such as genetic testing using technology acceptance model (TAM). TAM is a behavioural model which intends to discover and highlight the principles and mechanisms of human conduct and to determine the factors which formulate people’s perceptions and attitudes towards technology acceptance and adoption of innovative products or services. In terms of healthcare innovation, scientists prefer TAM because it is dedicated to study user acceptance and use of health technology by examining the effect of attitudes, intentions and social rules in peoples’ behaviour [12]. This information system theory is able to model the way users accept and make use of a new technological advance. By combining two variables notably perceived usefulness (PU) and perceived ease of use (PEU) of the technology, TAM manages to find out the factors affecting a person’s decision related to how and when a person will use a technology [13]. In addition, it is an easily adjustable model to meet the objectives of each study, a feature that makes it more suitable for healthcare innovation [12].

As mentioned before, this study aims to investigate the health science students’ intentions to adopt genetic testing applications in two different cultural backgrounds. In general, the literature so far shows a great effort in understanding the level of awareness of healthcare professionals. Indeed, respondents in several studies stated that the implementation of genetic testing has a positive impact in drug management because it supports the delivery of personalised pharmacotherapy services. By adjusting the adequate dosage scheme to each patient’s needs, it manages to reduce the incidence rate of adverse drug reactions and the expenditures for medications [14,15,16]. In addition, when students were asked about how genetic testing can influence their health, most of them believed that it could moderately influence it, highlighting the importance of relevant testing in disease management thanks to its contribution in prevention, early diagnosis and treatment [17]. Apart from the benefits of genetic testing, studies have highlighted the existing risks and concerns that pose a burden in its adoption. Most healthcare professionals are significantly worried about the shortage of available resources to apply genetic testing and its various applications, and about the lack of clinical guidelines, while they pounded the alarm about confidentiality and discrimination issues that may occur due to the improper usage and storage of data [18, 19]. Furthermore, the level of knowledge, expertise and genetic training of professionals in the field was found to be low or insufficient to support such innovations [20,21,22]. Despite the low level of knowledge among healthcare professionals, it is noticeable that there is a rather positive attitude towards the adoption of genetic testing and of PGx in particular, in the clinical setting [16, 23]. Finally, other barriers impeding genetic testing implementation are religious matters and the potential psychological impact that such a test may provoke [24].

Nonetheless, there are only a few research projects that apply TAM or other related theories, and they are dedicated to unveiling the factors which determine healthcare professionals’ intention to adopt genetic testing in their everyday life [14, 25]. According to those, factors such as perceived benefits from the innovation, subjective norms, self-efficacy or self-use, concerns and level of knowledge and training are the most common factors that influence a person’s intention to adopt a technology [26, 27].

Based on the aforementioned findings derived from an extensive literature review, we chose to include the following variables: genomic training, benefits of genetic testing on disease management, benefits of genetic testing applications on drug management, concerns and attitudes (Fig. 1) as factors that can have an impact on a person’s intention to adopt PGx.

Fig. 1
figure 1

Theoretical model of students’ intention to adopt genetic testing and its predicting factors

Survey instrument

The instrument employed in this research was a validated questionnaire elaborated by the Laboratory of Pharmacogenomics and Individualized Therapy at the Department of Pharmacy, University of Patras, Greece in collaboration with the Department of Social and Preventive Medicine, University of Malaya, Malaysia which has already been published [10, 11]. Considering its aim and objectives, this study focused on students’ perceptions probed by close-ended questions regarding 6 topics of interest; (1) Students’ genetic training, (2) Benefits of genetic testing on disease management, (3) PGx benefits on drug management, (4) Concerns (risks) about genetics, (5) Attitudes towards genetics’ research and testing usefulness and (6) Students’ intention to adopt genetic testing for personal use (Additional file 1: Table S1). A 5-point Likert scale ranging from “strongly disagree” (= 1) to “strongly agree” (= 5) was deployed for these questionnaire items. Additionally, student demographics such as gender, study course, year of course were taken into account. The study was reviewed and approved by the Institutional Review Board of the University of Patras.

Study sample

The survey sample consisted of health science students from Greece and Malaysia, a Southeast European and a Southeast Asian country, respectively. Specifically, 205 students from the Health Sciences School of the University of Patras, Greece, and 201 Pharmacy and Medical students from the University of Malaya, Kuala Lumpur, Malaysia, participated in the study (Table 1) and were asked in person to complete a self-administered questionnaire during May 2018 and October–November 2017, respectively. Student samples presented similarities in terms of gender and study course. In both cases, female students outnumbered male counterparts (63.4% in Greece, 72.6% in Malaysian), while around 60% of the participants were medical students. In addition, the Greek sample consisted to great extent, of first year students (around 84%) in contrast to the Malay sample in which participants were more evenly distributed regarding their year of study, and about half of them attended the second year and nearly 40% the third year, while the rest of 7.5% the fourth and fifth year. Therefore, the Malay students involved in the survey are expected to be more familiar with the topic and they have attended more courses relevant to human genomics, genetics and PM than their Greek counterparts.

Table 1 Sample descriptive statistics (valid %)

Data analysis

Study data were initially analysed using SPSS statistical program (version 27; IBM, NY, USA). Data analysis included frequencies and percentage of valid responses (valid %), descriptive statistics [mean value, standard deviation (SD)]. Moreover, exploratory factor analysis, accompanied with relevant reliability and validity tests [e.g. Cronbach’s alpha, average variance explained (AVE), composite reliability (CR)], was chosen to be conducted thanks to their accuracy to reveal the latent structure of the observed variables. Mann–Whitney 2-Independent Samples test was utilized to specify the scale of differences between the Greek and Malay samples concerning the questionnaires’ answers. Finally, path analysis was run using AMOS (version 26; IBM, NY, USA) to examine the relationships among the factors accrued by the factor analysis and the student intention to adopt genetic testing.


Exploratory factor analysis

All aspects of exploratory factor analysis used to confirm the validity and reliability of the results, indicated that the sample and the questionnaire is well-suited and valid. Indeed, FA (Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalization) for both samples revealed five factors which are expected to affect students’ intention to adopt a genetic testing (Table 2). Bartlett’s test of sphericity yielded a statistically significant value (Chi-Square = 1261.43, p = 0.000 for Greece; Chi-Square = 1980.78, p = 0.000 for Malaysia) suggesting that there are substantial (overall significantly different from zero) correlations between variables. Moreover, Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was well above the critical value of 0.5 (0.701 and 0.848, respectively, for Greece and Malaysia) indicating the presence of a strong partial correlation among variables. These indices implied that the matrix was well suited for FA. Moreover, the percentage of variance was 56.65% and 65.85%, for the Greek and Malaysian groups, respectively, while Cronbach’s alpha coefficients for the Greek sample ranged from 0.68 to 0.82 and from 0.73 to 0.89 for the Malaysian, indicating a rather strong internal consistency and reliability among different measurements using same factors. Furthermore, AVE values for both the Greek (ranging from 0.46 to 0.71) and the Malaysian group (ranging from 0.53 to 0.75) were close to the recommended value (≥ 0.5), a fact that indicated a convergent validity. The square of the correlation among all investigated factors was zero in all cases, a finding that confirmed the factors’ discriminant validity for both samples compared to the AVE values. CR values of all factors for both samples (ranging from 0.77 to 0.89) are well above the critical value of 0.7, implying the factors’ internal consistency. Evidently, it was proven that all reliability tests performed corroborated that both models were good fit.

Table 2 Results of exploratory factor analysis

The questionnaire items were grouped in an expected and similar way for both samples, and it was revealed that the examined factors affect students’ intention to adopt PGx testing. The first two factors, in terms of percentage of explained variance, in both samples refer to the benefits of PGx on drug management and the concerns associated with the use of genetic testing. The next two factors were related to student attitudes towards genetics and their benefits on disease management, while the fifth factor was about students’ self-evaluation of their genetic training.

Comparative analysis of students’ views on questionnaire items

Students’ answers from both groups were compared using the nonparametric Mann–Whitney test (Table 3). It is shown that Greek students are more confident about the contribution of genetic testing in terms of disease diagnosis, prevention and prognosis, whereas Malay students are more convinced about PGx benefits on drug management, with respect to the reduction in healthcare expenses on medication, the potential decrease in adverse drug reactions’s incidence, in symptoms’ severity, and in the number of exacerbations. However, students from both countries appear to be particularly convinced about the benefits of genetic testing on disease management (mean values ranged from 4.07 to 4.35), while Greek students felt to be less adequately trained to discuss with a family member the results of a genetic test and consult him/her accordingly. The mean values for the relevant statements range from 3.73 to 3.95 for the Malay sample, and from 3.20 to 3.77 for the Greek sample.

Table 3 Comparison of students’ views on questionnaire items

Moreover, it is noticed that for both groups (mean 3.78) the potential misuse of genetic information by corporate or governmental bodies is the most important concern, followed by the possible impact to employability and fears about unforeseen consequences due to the widespread use of genetic research (means varied from 3.56 to 3.69). Greek students appear to be considerably less worried than Malay students about the potential discrimination and privacy issues, the promotion of discrimination against groups of people and the potential inability to get insured. In line with participants’ beliefs about the benefits of genetic testing on drug and disease management, students from both countries expressed positive attitudes towards genetic research and testing, especially in terms of its valuable contribution to the early detection of diseases (means > 4.5 for Greeks and ~ 4.3 for Malays). Nevertheless, Greek students are shown to be more enthusiastic about genetic research and testing outcomes compared to their counterparts.

Despite the noteworthy differences between the two groups’ perceptions regarding the aforementioned factors, students from both countries exhibited almost similar favourable intentions to adopt genetic testing for personal use, with mean values varying from 4.1 to 4.3 (Table 3). This trend provides an additional impetus to conduct the comparative path analysis.

Path analysis

Structural equation modelling (SEM) and, in particular, path analysis were conducted to estimate the impact of the revealed factors to students’ intention to adopt genetic testing applications (Figs. 2, 3). Anderson–Rubin factor scores produced by the exploratory factor analysis for five selected predicting factors of students’ intention to adopt genetic testing were applied in this analysis. Model fitness indices (Table 4) unveil that both SEM models are good fit [27, 28].

Fig. 2
figure 2

Path diagram of Greek sample (standardized estimates)

Fig. 3
figure 3

Path diagram of Malaysian sample (standardized estimates)

Table 4 Model fitness indices for both SEM models

Path diagram (Fig. 1), regression weights (Additional file 1: Table S2) and squared multiple correlations (R2) of Intention to Adopt (0.303) for the Greek sample reveal that all examined factors, except of training, have a significant impact on students’ intention to adopt genetic testing for personal use. However, there is an observed variation on the factors’ regression coefficients. Attitudes as a factor exert the most significant positive effect on students’ intention (0.416) compared to the rest of the factors. Standardized regression results concerning the variable of perceived benefits on disease and drug management are around 0.20–0.22, indicating a positive impact on students’ intention. On the contrary, concerns exert a negative impact (− 0.196) towards the testing adoption, as expected. Consequently, these four factors’ influence (directly or not) students’ intention and its antecedents (variables) (“I want to know my own genetic profile” and “I want to know what kind of diseases I could get in the future”) (Additional file 1: Table S3). Path analysis including Greek students’ demographics reveals that study year was their only characteristic with a significant impact on their intention to adopt genetic testing, raising the model’s R2 to 0.342. In particular, the negative regression weight (− 0.21) indicates that 1st-year students were more inclined to adopt a genetic test compared to their 2nd-year peers (Additional file 1: Fig. S1, Table S6).

SEM analysis for the Malaysian sample demonstrates similar findings to those of the Greek sample (Fig. 3, Additional file 1: Tables S4 and S5). Indeed, training constitutes the only factor found not to influence students’ intention towards genetic testing adoption, while the other four factors have a significant effect. Attitudes’ factor impinges more on students’ intention, with its standardized regression estimated to be considerably higher (0.539) compared to the Greek sample (0.416). Rather interestingly, concerns about genetics have a noteworthy positive impact (0.431) on students’ intentions, contrary to the expected relationship and the observed in the Greek sample (− 0.196). This fact implies that the more the Malay students are concerned about the genetics risks, the more are inclined to adopt genetic testing. This ostensible paradox may indicate that high level of genetic knowledge is positively associated with both students’ worries and intention to adopt genetic testing. Yet, it is worth mentioning that the concerns as a factor is proven to have a relatively modest negative impact (− 0.215) on students’ intentions to know what kind of diseases they could get in the future. The last two factors, genomics benefits on disease and drug management, appear to exert a rather positive impact (0.17 and 0.18, respectively) on students’ intentions like the Greek sample (0.22 and 0.20). The squared multiple correlation (R2) of students’ intention to adopt genetic testing was much higher (0.547) than the observed in the Greek sample (0.303). This may be due to the composition of the two samples, as the Malay participants are expected to be more knowledgeable and familiar with the corresponding topics than their Greek counterparts. Path analysis including Malay students’ demographics manifests that the examined characteristics exert almost a null impact on their intention to genetic test adoption (Additional file 1: Fig. S2, Table S7).


Genomics and genetic testing applications have significantly changed the way modern clinical routine works. The wide range of testing applications is believed to improve the whole workflow of drug and disease management, on the grounds that it can enhance disease diagnosis, offer personalised therapeutic schemes, reduce the time and money required for treatment, increase a patient’s life expectancy and ameliorate a person's quality of life during therapy [1]. Although it is proven that genetic testing has a positive impact on clinical practice, its adoption rate remains low across the different healthcare systems due to social, educational, religious, cultural and legal barriers as many studies have previously shown [16, 29].

Even if there is a great number of publications addressing the possible barriers that may impede PM implementation and the use of different types of genetic testing, there are only a few studies focusing on determining and empirically investigating the factors and their association with the testing adoption. According to Salleh et al. [6], exploring a person’s behaviour, action and attitude could predict a positive relationship between a person’s intention and his tendency to adopt a new technology [7].

For instance, Mustapa et al. [25] have investigated the intention to adopt PGx, a type of genetic testing, using TAM among Malaysian stakeholders (healthcare professionals, public, policymakers) and they concluded in similar results to other TAM studies [26]. More precisely, they showed that perceived benefits and risks of PGx along with concerns, self-efficacy and level of knowledge affected the public's willingness to adopt PGx. Chen et al. [26] had conducted a similar research in Taiwanese physicians to investigate the professionals’ attitudes and their intention to adopt genomic medicine, and they concluded that education level and knowledge related to genomics is positively associated with physicians intention to adopt genomic medicine in their practice along with other external factors such as the existing health policies, administration support, cultural setting and other important elements related to the feasibility of this innovation in everyday clinical practice [27]. The above studies are focusing on healthcare professionals and not on the health science students which are the future generations of professionals. Our study is the first that examines the impact of selected factors on health science students’ intention to adopt genetic testing using TAM, while it compares two different cultural groups: a European, (Greece), and an Asian, (Malaysia), with the aim to highlight any existing similarities and differences between them.

Based on our results, it was illustrated that students from both groups appear to be particularly convinced about the benefits of genetic testing on disease management thanks to its contribution in the disease prognosis and on the improvement of patient’s quality of life, a finding that is also supported by Mahmutovic et al. [17]. More precisely, Malay students tend to believe more in the significance of genetic testing applications, such as PGx, in drug management than in disease management compared to their Greek counterparts. This observation may have a double meaning.

On the one hand, it might be related to the fact that the majority of Greek respondents were in their first- or second-year of studies and thus, they were not aware of the impact of drug management on patient’s overall management. According to Yau and Haque [30], it was indicated that the knowledge of PGx among students varied depending on the course of study and age, while Malay students had the same results in relevant questions, a fact that underlies the reliability and reproducibility of our observations [31]. On the other hand, it could be a result of cultural difference since pharmacists in Malaysia have a broader participation in the complete control of medication supply in comparison with their colleagues in Greece [31]. Indeed, Malay pharmacists have the authority to do medication reviews, identify medication issues and provide recommendations for better drug administration to patients and doctors.

Furthermore, the major students’ concern was the security of their genetic information and their potential misuse by corporate or government bodies. Malay students were shown to be extremely worried about it along with the existence of phenomena of racial and religious discrimination and privacy deprivation. Cheung et al. [32] stated that the majority of undergraduate students believed that the biggest threats of genetic testing, implementation were “Patient Privacy” (80%) and “Data Confidentiality” (68%), supporting our findings. In general, many studies have pointed out similar conclusions especially in terms of religiosity and religious restrictions [33, 34]. However, in general, Asians were found to worry more about the improper use of their data in many sectors of their lives compared to Western societies [6].

The noticeable difference between Malay and Greek students could also be explained by the existence and implementation of strict European directives and legislations such as GDPR [35]. Greece has complied with these laws and citizens’ personal data are legally protected, while there is not a similar legal framework in Malaysia. In addition to, as Mitropoulou et al., [36] have mentioned, Greek stakeholders in the healthcare sector and especially policymakers had a positive attitude towards genetic testing and they were willing to overcome any potential barrier to enhance PM implementation along with genetic testing.

Another noteworthy observation is related to the positive attitude of students from both groups towards the genetic testing for personal purposes to find out their genetic makeup and their prevalence for disease. In the literature, there is evidence that a small number of healthcare professionals claimed to have ordered or performed a genetic testing for themselves in the last six months. For example, 14.7% of respondents in Bank et al. [37] study reported having ordered or recommended genetic testing like PGx in the last 6 months, similar to 12.7% of respondents in Stanek et al. [38]. However, it seems that undergraduate students (83%) are more prone to undergo genetic testing to find out their genetic profile in the future [39]. Mahmutovic et al. [17] highlighted that 40% of participants were willing to undertake a genetic test in the future, while Sindi et al. [20] showed that 80.5% of students wanted to take a genetic test for themselves [17, 21].

Finally, training was also a significant concern for both groups, an observation that is really common in the literature [18]. Greek students felt to be less adequately trained to interpret the genetic data of their family members and discuss the results with them in order to consult them, whereas their Malay counterparts were more confident with that aspect. This difference may be attributed to the fact that almost 84% of Greek participants attended the first year of their studies and they lacked experience, while 92% of the Malay sample were in their second and third year and, hence, they had already attended more courses relevant to human genomics, genetic testing and PM to gain some experience.

However, based on the path analysis results, it seems that training constituted the only factor which did not influence students’ intentions towards genetic testing adoption, while attitude is the most influential factor with rather high impact followed by genetic testing benefits. This fact is in accordance with the fact that Malay health science students are still rather worried about the potential perils associated with genetic testing even if they are highly convinced about the benefits of testing on both drug and disease management. This paradox indicates that a high level of genetic knowledge may be potentially positively associated with both students’ worries towards and intentions to adopt genetic testing.

The study results provide crucial evidence of the proposed model’s external validity, although, in general, external validity’s evaluation always poses significant challenges. The questionnaire survey has been conducted in two quite different cultures, and the actual correlation coefficients between the predicting factors and students’ intentions to adopt genetic testing were rather similar in these two cultural settings.

This study has a few limitations related to the composition of the sample. In particular, the Greek sample consisted mainly of first year students (around 84%) with the rest of cohort attending the second year, while the Malay sample consisted of older students. This discrepancy may explain the better statistical results (exploratory factor analysis, path analysis) of the Malay sample compared to the Greek one and affect the correlations. Moreover, the samples from both countries derived from students attending one public University accordingly.


This study shows that TAM has been successfully applied in many studies to explain the acceptance and the intention to adopt several health innovations. By using an extended version of TAM adapted for the needs of these research questions, and a series of multivariate statistical analyses, a new reliable and promising model has been developed to interpret health science students’ intentions to adopt genetic testing such as PGx in different cultural settings, with good fit thanks to the results of validity and reliability tests along with the observed similarities of the two samples.

It was shown that the intention of health science students to adopt PGx is affected by several factors such as attitudes, the perceived benefits of genetic testing, the risks and concerns of such technology. Our study model is suitable to investigate the factors influencing the intention to adopt genetic testing services even in different cultural settings. In the future, this model could have further marketing implications in different domains of the healthcare sector which will improve the adoption rate of genetic testing. For example, it would be used to upgrade Universities’ curriculum to assess the perception of students and then incorporate students’ programs accordingly. In parallel, by enacting strict and universal legislations for the protection of sensitive personal data such as the genomic data, it is possible to overcome some of the main barriers and convince the future healthcare professionals to widely implement PGx in the clinical setting. Finally, another marketing application is the extension of our model applicability in other healthcare stakeholders such as patients, public, policymakers to understand in depth the intention to adopt PGx with the aim of improving and strengthening the presence of PGx in clinical routine and drug administration.

Availability of data and materials

Please contact author for data requests.



Personalised medicine




Technology acceptance model


Perceived usefulness


Perceived ease of use

Std Dev:

Standard deviation


Average variance explained


Composite reliability


Factor analysis




Structural equation modelling


Chi-square fit statistics/degree of freedom 


Incremental fit index


Normed fit index


Tucker–Lewis index


Comparative fit index


Root mean squared error approximation


p Value of the null hypothesis that the RMSEA equals 0.05 (a close-fitting model)


  1. Rahma AT, Elbarazi I, Ali BR, et al. Development of the pharmacogenomics and genomics literacy framework for pharmacists. Hum Genomics. 2021;15:62.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Lim MT, Ong SM, Tong SF, Groenewegen P, Sivasampu S. Comparison between primary care service delivery in Malaysia and other participating countries of the QUALICOPC project: a cross-sectional study. BMJ Open. 2021;11(5):e047126.

    Article  Google Scholar 

  3. Ang HX, Chan SL, Sani LL, et al. Pharmacogenomics in Asia: a systematic review on current trends and novel discoveries. Pharmacogenomics. 2017;18(9):891–910.

    Article  CAS  PubMed  Google Scholar 

  4. Lim JF, Zafra M, Mocanu JD, Umareddy I, de Lima Lopes G Jr, Foo R, Jha A, Hickinbotham L. Preparing health systems in Southeast and East Asia for new paradigms of care/personalized medicine in cancers: are health systems ready for evolving cancer management? J Asian Public Policy. 2017;10(3):268–86.

    Article  Google Scholar 

  5. Lee JM, Thong MK. Genetic counseling services and development of training programs in Malaysia. J Genet Couns. 2013;22(6):911–6.

    Article  PubMed  Google Scholar 

  6. Salleh HS, Noor AM, Mat NHN, Yusof Y, Mohamed WN. Consumer-behavioural intention towards the consumption of functional food in Malaysia: their profiles and behaviours. Int Bus Econ Res J (IBER). 2015;14(4):727–34.

    Article  Google Scholar 

  7. Pisanu C, Tsermpini EE, Mavroidi E, Katsila T, Patrinos GP, Squassina A. Assessment of the pharmacogenomics educational environment in Southeast Europe. Public Health Genomics. 2016;17(5–6):272–9.

    Article  Google Scholar 

  8. Patrinos GP, Katsila T. Pharmacogenomics education and research at the Department of Pharmacy, University of Patras, Greece. Pharmacogenomics. 2016;17(17):1865–72.

    Article  CAS  PubMed  Google Scholar 

  9. Minari J, Brothers KB, Morrison M. Tensions in ethics and policy created by National Precision Medicine Programs. Hum Genomics. 2018;12:22.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Siamoglou S, Koromina M, Politopoulou K, et al. Attitudes and awareness toward pharmacogenomics and personalized medicine adoption among health sciences trainees: experience from Greece and lessons for Europe. OMICS. 2021;25(3):190–9.

    Article  CAS  PubMed  Google Scholar 

  11. Siamoglou S, Koromina M, Moy F-M, Mitropoulou C, Patrinos GP, Vasileiou K. What do students in pharmacy and medicine think about pharmacogenomics and personalized medicine education? Awareness, attitudes, and perceptions in Malaysian Health Sciences. OMICS J Integr Biol. 2021;25(1):52–9.

    Article  CAS  Google Scholar 

  12. Ketikidis P, Dimitrovski T, Lazuras L, Bath PA. Acceptance of health information technology in health professionals: an application of the revised technology acceptance model. Health Inform J. 2012;18(2):124–34.

    Article  Google Scholar 

  13. Gücin N, Berk Ö. Technology acceptance in health care: an integrative review of predictive factors and intervention programs. Procedia Soc Behav Sci. 2015;195:1698–704.

    Article  Google Scholar 

  14. Abdela OA, Bhagavathula AS, Gebreyohannes EA, Tegegn HG. Ethiopian health care professionals’ knowledge, attitude, and interests toward pharmacogenomics. Pharmgenomics Pers Med. 2017;10:279–85.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Albassam A, Alshammari S, Ouda G, Koshy S, Awad A. Knowledge, perceptions and confidence of physicians and pharmacists towards pharmacogenetics practice in Kuwait. PLoS ONE. 2018;13(9):e0203033.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Muzoriana N, Gavi S, Nembaware V, Dhoro M, Matimba A. Knowledge, attitude, and perceptions of pharmacists and pharmacy students towards pharmacogenomics in Zimbabwe. Pharmacy (Basel). 2017;5(3):36.

    Article  Google Scholar 

  17. Mahmutovic L, Akcesme B, Durakovic C, et al. Perceptions of students in health and molecular life sciences regarding pharmacogenomics and personalized medicine. Hum Genomics. 2018;12(1):50.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Elewa H, Awaisu A. Pharmacogenomics in pharmacy practice: current perspectives. Integr Pharm Res Pract. 2019;8:97–104.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Karuna N, Tragulpiankit P, Mahasirimongkol S, Chumnumwat S. Knowledge, attitude, and practice towards pharmacogenomics among hospital pharmacists in Thailand. Pharmacogenet Genomics. 2020;30(4):73–80.

    Article  CAS  PubMed  Google Scholar 

  20. Sindi A, Altayyari S, Omer A, Aljifri H, Magadmi B, Nemri A, Basheikh M. Knowledge and awareness on personalised medicine amongst medical students: a cross-sectional survey. J Health Spec. 2017;5(3):171.

    Article  Google Scholar 

  21. Algahtani M. Knowledge, perception, and application of pharmacogenomics among hospital pharmacists in Saudi Arabia. Risk Manag Healthc Policy. 2020;13:1279–91.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Alzoubi A, Kanaan H, Alhazaimeh D, Gharaibeh S, Mukattash TL, Kheirallah K. Knowledge, attitude, future expectations and perceived barriers of medical students and physicians regarding pharmacogenomics in Jordan. Int J Clin Pract. 2021;75(1):e13658.

    Article  PubMed  Google Scholar 

  23. Bank PC, Swen JJ, Guchelaar HJ. A nationwide cross-sectional survey of pharmacy students on pharmacogenetic testing in The Netherlands. Pharmacogenomics. 2018;19(4):311–9.

    Article  CAS  PubMed  Google Scholar 

  24. Marcinak R, Paris M, Kinney SRM. Pharmacogenomics education improves pharmacy student perceptions of their abilities and roles in its use. Am J Pharm Educ. 2018;82(9):6424.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mustapa MAC, Amin L, Razman MR. Behavioural intention to adopt pharmacogenomics and its predicting factors in Malaysia. Acad Strat Manag J. 2019;18:1939–6104.

    Google Scholar 

  26. Chen LS, Chang FW, Kim M, Talwar D, Zhao S. Genomic medicine practice among physicians in Taiwan. Per Med. 2017;14(2):109–21.

    Article  CAS  PubMed  Google Scholar 

  27. Hooper D, Coughlan J, Mullen MR. Structural equation modelling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6:53–60.

    Google Scholar 

  28. Schreiber J, Stage KF, King J, Nora A, Barlow EA. Reporting structural equation modeling and confirmatory factor analysis results: a review. J Educ Res. 2006;99:323–37.

    Article  Google Scholar 

  29. Koufaki M, Karamperis K, Vitsa P, Vasileiou K, Patrinos G, Mitropoulou C. Adoption of pharmacogenomic testing: a marketing perspective. Front Pharmacol. 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Yau A, Haque M. pharmacogenomics: knowledge, attitude and practice among future doctors and pharmacists—a pilot study. J Appl Pharm Sci. 2016;6:141–5.

    Article  Google Scholar 

  31. Cheah M. Public perception of the role of pharmacists and willingness to pay for pharmacist-provided dispensing services: a cross-sectional pilot study in the State of Sabah. Malays Malays J Pharm Sci. 2018;16(1):1–21.

    Google Scholar 

  32. Cheung NYC, Fung JLF, Ng YNC, et al. Perception of personalized medicine, pharmacogenomics, and genetic testing among undergraduates in Hong Kong. Hum Genomics. 2021;15(1):54.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rahma AT, Elsheik M, Elbarazi I, et al. Knowledge and Attitudes of medical and health science students in the United Arab Emirates toward genomic medicine and pharmacogenomics: a cross-sectional study. J Pers Med. 2020;10(4):191.

    Article  PubMed Central  Google Scholar 

  34. Nutter SC, Gálvez-Peralta M. Pharmacogenomics: from classroom to practice. Mol Genet Genomic Med. 2018;6(3):307–13.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kordou Z, Siamoglou S, Patrinos GP. Legal aspects of genomic and personalized medicine. Appl Genomics Public Health. 2020.

    Article  Google Scholar 

  36. Mitropoulou C, Mai Y, van Schaik RH, Vozikis A, Patrinos GP. Stakeholder analysis in pharmacogenomics and genomic medicine in Greece. Public Health Genomics. 2014;17(5–6):280–6.

    Article  PubMed  Google Scholar 

  37. Bank PC, Swen JJ, Guchelaar HJ. A nationwide survey of pharmacists’ perception of pharmacogenetics in the context of a clinical decision support system containing pharmacogenetics dosing recommendations. Pharmacogenomics. 2017;18(3):215–25.

    Article  CAS  PubMed  Google Scholar 

  38. Stanek EJ, Sanders CL, Taber KA, et al. Adoption of pharmacogenomic testing by US physicians: results of a nationwide survey. Clin Pharmacol Ther. 2012;91(3):450–8.

    Article  CAS  PubMed  Google Scholar 

  39. Nagy M, Lynch M, Kamal S, Mohamed S, Hadad A, Abouelnaga S, Aquilante CL. Assessment of healthcare professionals’ knowledge, attitudes, and perceived challenges of clinical pharmacogenetic testing in Egypt. Pers Med. 2020;17(4):251–60.

    Article  CAS  Google Scholar 

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Research has been funded by the University of Patras Special Research Account Funds.

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Authors and Affiliations



KV and GPP conceived this work. KV designed the study. MIK and SS performed literature search. MIK and KV performed pathway and statistical analysis. All authors have written, commented and approved the manuscript.

Corresponding author

Correspondence to Konstantinos Vasileiou.

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Competing interests

GPP is Full Member and National Representative of the European Medicines Agency, Committee for Human Medicinal Products (CHMP)—Pharmacogenomics Working Party, Amsterdam, the Netherlands. All other authors declare that they have no competing interests.

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Supplementary Information

Additional file 1:

 Survey questions and extensive explanation of path analysis results for both groups. The file includes the questions of the survey, demonstration of regression weights as derived upon SEM analysis. and the effects of each factor in students’ intention to adopt genetic testing. Also, it presents more detailed path diagrams of all examined factors in figures  for both groups.

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Koufaki, MI., Siamoglou, S., Patrinos, G.P. et al. Examining key factors impact on health science students’ intentions to adopt genetic and pharmacogenomics testing: a comparative path analysis in two different healthcare settings. Hum Genomics 16, 9 (2022).

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  • Path analysis
  • Comparative analysis
  • Questionnaire survey
  • Genomics
  • Genetic testing
  • Health science students
  • Perceptions
  • Intentions to adopt
  • Different cultural settings