Knowledge and Attitudes of Personalized Medicine, Genetic Testing, and Health Data Sharing: A Comprehensive Survey in the general public of the European Union

Knowledge and Attitudes of Personalized Medicine, Genetic Testing, and Health Data Sharing: A Comprehensive Survey in the general public of the European Union | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Knowledge and Attitudes of Personalized Medicine, Genetic Testing, and Health Data Sharing: A Comprehensive Survey in the general public of the European Union Francesco Andrea Causio, Flavia Beccia, Giovanna Elisa Calabrò, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3960901/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Personalized medicine, leveraging genetic, environmental, and lifestyle data, has transformed healthcare by tailoring prevention, diagnosis, and treatment to individual patients. The successful implementation of personalized approaches relies on the public's awareness and proficiency in personalized medicine, enabling access to innovative techniques and fostering a willingness to share health-related data. During two weeks in April 2023, we distributed an online survey to 6,581 respondents from 8 EU countries, including France, Germany, the Netherlands, Italy, Spain, Poland, Hungary, and Romania. The survey investigated the general public’s knowledge of personalized medicine, support for implementing genetic testing in their healthcare system, and willingness to share health data. We built three indicators from survey questions and investigated their association with each other and the respondent’s gender, age, geographical area of origin, and education level. 52.5% of respondents were female (n = 3,458), with a mean age of 48.5 years (range 18–89 years, median = 49 years, SD = 15.96), and 37.91% of the participants reported achieving tertiary education. 12.11% of respondents had a high compound knowledge of the topics. Knowledge levels, however, vary among the included countries (highest in the Netherlands at 18.87%, lowest in France at 7.44%). 81.5%, instead, supported the implementation of diagnostic or therapeutic applications of genetic testing in their healthcare systems, and nuanced differences in acceptance were observed based on testing purposes. Over half of the respondents (52.35%) reported willingness to share health data for altruistic use. Both support for implementing genetic testing and the desire to share health data correlated positively with knowledge and education levels. Geographical differences within the EU highlighted variations in attitudes toward personalized medicine and data sharing, with respondents from Southern Europe displaying higher odds than their peers in Central and Eastern Europe. The results emphasize the need for targeted communication and education strategies to enhance public understanding and trust in personalized medicine and health data sharing. Introduction In recent years, advancements in medical technology and research have led to new paradigms in healthcare. The personalized medicine approach has transformed healthcare by adapting prevention, diagnosis, and treatment strategies to suit individual patients, considering their genetic, environmental, and lifestyle factors. The effective development and application of these advanced medical methods depend significantly on the public's understanding and knowledge of personalized medicine. This includes their ability to access these novel approaches and their readiness to share health-related information. ( 1 ) The secure and convenient sharing of individual health data is also crucial to enhancing collaboration in research and healthcare. In the face of increasing public concern and scrutiny regarding data privacy, the importance of trust in data sharing in personalized medicine has become increasingly apparent, with a growing body of evidence investigating personal preferences and institutional safeguards for data sharing. ( 2 , 3 , 4 ) Therefore, understanding the level of knowledge and awareness among the European Union (EU) public, as well as their views on health data sharing, is critical for healthcare professionals and policymakers to effectively communicate and educate the public about the latest advancements in the medical field and help build trustworthy institutional arrangements for health research. ( 5 ) In 2017, the international Your DNA Your Say (YDYS) project used film and an online cross-sectional survey to gather public attitudes toward donating, accessing, and sharing DNA information. ( 6 ) The results showed significant variations in willingness to share information and trust in the actors associated with collecting and using DNA information. Specifically, the German public's willingness to donate genomic data was among the lowest recorded in the study, and those who were more familiar with genetics and held views of genetic exceptionalism were more likely to donate data. ( 7 ) Italian respondents were willing to share DNA and health information with entities except for-profit researchers and generally did not trust institutions beyond their own doctors. ( 8 ) A similar survey addressing the Italian public highlighted geographical differences in the public’s knowledge and attitudes toward personalized medicine. ( 9 ) Research in Hungary revealed mixed attitudes toward genetic testing, with access to physician consultation positively influencing attitudes. ( 10 ) A higher self-determined genetic familiarity score was associated with a greater willingness to participate in genetic testing, though medical professionals were more skeptical. In 2020, a systematic review updated the literature on citizens' perspectives toward direct-to-consumer genetic tests (DTC-GTs) in several European countries. It showed that European citizens generally had low awareness levels and a high interest in DTC-GTs, mainly for understanding disease risk predisposition. Concerns about test validity, utility, and data privacy were also highlighted. ( 11 ). Our study aimed to gather comprehensive data to evaluate the level of knowledge and attitudes among the EU public on aspects of personalized medicine. We also sought to explore public views and attitudes towards genetic testing and various forms of health data sharing, such as electronic health records and data generated by health apps, identifying potential knowledge gaps and areas of improvement. Considering the previous evidence, our survey targeted a broad audience in the European Union. The present survey addresses points covered by previous surveys at a national level with an EU-wide perspective while further exploring the factors influencing the public’s attitudes towards health data sharing previously investigated at a multi-country level. Moreover, we built indicators to summarize and analyze the correlation between knowledge levels, support towards implementing genetic testing in the healthcare system, and the respondents’ willingness to share health data. The latter point has not previously been addressed in the literature. It provides valuable insights for researchers and policymakers to enact actions to stimulate the adoption of personalized medicine and related modern medical paradigms. Methods We developed a web-based questionnaire comprising 37 questions distributed across four main modules: Module A, addressing knowledge and attitudes about personalized medicine (PM); Module B, exploring genomic and health data sharing and use; Module C, focusing on governance; and Module D, assessing the needs of the users. The complete questionnaire is available in the Supplementary Material. Researchers agreed to contract the private company YouGov to distribute the survey on their platform. YouGov is a global public opinion and data company whose platform complies with the highest standards for quality and research while ensuring participant privacy. YouGov's methodology complies with GDPR standards and is detailed on their website ( https://yougov.co.uk/about/panel-methodology ). The survey distribution lasted approximately two weeks during April 2023. Respondents were invited to participate in a YouGov survey based on their demographic information, reflecting their country’s population distribution by gender, age, and education level. The survey distribution polling system collected gender, age, country of origin, and education before respondents participated in the survey. Detailed information concerning the survey design and delivery methods is available in the online preprint. ( 12 ) The method section below focuses on the data preprocessing and analysis for the stated objective. Data collection and analysis Survey responses were collected in an electronic data sheet. Descriptive analyses were performed using absolute frequencies and percentages for categorical data and mean and standard deviation (SD) for continuous data. An analysis of determinants of knowledge, attitudes, and willingness to support personalized medicine was carried out by developing multivariable logistic regression models using the strategy outlined by Hosmer and Lemeshow. Following the methodology previously employed in similar surveys ( 9 , 13 , 14 , 15 ), we created new compound variables to measure respondents’ knowledge of personalized medicine, support for implementing genetic testing in healthcare, and willingness to share health and genetic data. A detailed summary of the three compound variables is shown in Table 1 . The variables were built as follows: different survey questions were assigned scores based on respondents' answers, and new variables were then derived from the responses to some of these questions. The “Compound knowledge of Personalized Medicine” indicator was built upon question 1 (score 0–3 points, depending on how many terms the respondents knew before the survey), question 3 (0–7 points, depending on how many uses of genetic testing respondents knew before the survey), question 7 (score 0–1 points depending on whether participants were already aware of health/patient portals before the survey) and question 28 (score 0–1 points depending on participants’ perceived knowledge of personalized medicine, with 1 point to those responding “Definitely” or “Somewhat”), with a maximum achievable indicator value of 12. If the indicator value was ≥ 9/12 (75%), respondents were considered to have a high knowledge level; otherwise, they were considered to have a low knowledge level. The indicator “Compound support of genetic testing implementation in healthcare” was built upon question 4 (score 0–5 points, where 1 point was considered for each option where respondents chose “I would support the test being made available by the health care system of my country, and I would consider taking such test” or “I would support the test being made available by the health care system of my country, but I would NOT consider taking such test”). If the indicator value was ≥ 4/5 (80%), respondents were considered to show support; otherwise, they showed no support. The “Compound willingness to health and genetic data sharing” indicator was built upon questions 8 and 9. Respondents were classified as showing willingness if they answered: “Would share for others’ benefit” to both question 8 and question 9, “Would share for others’ benefit” to question 8 and “Would share for research on a disease running in my family” to question 9, “Would share if reassurances are granted“ to question 8 and “Would share for others’ benefit” to question 9. They were deemed unwilling to share health and genetic data for any other combination. Covariates included in the models were gender, age, geographical region, and education (with not-achieved tertiary education as a reference category). The geographical area was categorized as follows: Eastern Europe (Poland, Hungary, and Romania), Southern Europe (Italy and Spain), and Central Europe (the Netherlands, Germany, and France), with Central Europe as the reference category. Each variable was examined by univariable analysis and was included in the multivariable logistic model when the P value was < 0.15. The influence of the independent variables on each binary outcome investigated was expressed as odds ratios (ORs) and 95% confidence interval (CI). The new binary variables representing knowledge, support, and willingness to share were mutually tested as covariates to assess dependence. Statistical significance was set at a P value < 0.05. The statistical analysis was performed using STATA 18.0 software (Stata Corporation, College Station, TX, USA). Ethical approval for this study was obtained from the Policlinico Universitario ‘Agostino Gemelli’ Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214). Results Demographics Table 2 reports the demographic profile of the survey respondents. Out of the 6,581 respondents, 52.5% were female (n = 3,458). The age of the respondents ranged from 18 to 89 years (mean = 48.5 years, median = 49 years, SD = 15.96). The survey included 6,581 respondents from 8 countries across different European regions. Central Europe, which includes France, Germany, and the Netherlands, represented the most significant proportion with 46.03% of respondents (n = 3,029); Eastern Europe, comprising Hungary, Poland, and Romania, made up 23.20% of the sample (n = 1,527), while Southern Europe, represented by Italy and Spain, accounted for 30.77% of respondents (n = 2,025). The participants displayed diverse educational backgrounds. Approximately 37.91% of the participants reported achieving tertiary education (n = 2,495), whereas a significant majority, constituting 62.09%, indicated that they had not pursued tertiary education (n = 4,086). Knowledge and awareness of citizens regarding key medical advancements and personalized medicine. This section delves into citizens' knowledge and awareness regarding key medical advancements and concepts, including personalized medicine, Big data, genetic testing, and related applications (Table 3 ). Of the respondents, 47.76% (n = 3,143) reported being aware of personalized medicine; 37.03% (n = 2,437) had heard about Big data, and 80.53% (n = 5,300) were familiar with genetic testing. Among the latter familiar with genetic testing, slightly more than half knew about prenatal testing (50.85%, n = 2,695) and risk assessment of passing a disease to the offspring (55.62%, n = 2,948). A majority were unaware of its use in treatment choices (64.34%, n = 3,410), disease diagnosis (51.83%, n = 2,747), drug assessment or pharmacogenomics (78.70%, n = 4,171), and risk assessment for disease (51.26%, n = 2,717), as well as of the existence of heel prick testing for newborns (64.06%, n = 3,395). In addition, over half of all survey respondents (54.3%, n = 3,573) were aware of health/patient portals, indicating a notable familiarity with digital healthcare platforms. A small proportion felt they had “definitely” adequate knowledge (4.42%, n = 291), while a more significant percentage felt “somewhat” knowledgeable (21.81%, n = 1,435). Conversely, a considerable portion expressed limited knowledge, with 41.95% (n = 2,761) feeling “not really” knowledgeable and 23.34% (n = 1,536) feeling “not at all” knowledgeable. Additionally, 8.48% (n = 558) were uncertain about their level of understanding. The compound knowledge level for participants was high (≥ 9/12) for 12.11% of participants (n = 797) and low (≤ 8/12) for most of them (n = 5,784). Attitudes towards support for Genetic Testing Availability within the Healthcare System and Willingness to Undergo Testing. In this section, we explore the level of support for the integration of genetic testing into the healthcare system, as well as the willingness of respondents to undergo such testing for various purposes, given its availability at a low cost (Table 4 ). When considering a diagnosis for a serious genetic disease, most respondents (72.19%, n = 4,751) expressed support for such a test offered by the healthcare system while also being inclined to undergo such testing themselves. A smaller fraction (15.04%, n = 990) supported the availability of the test, albeit opted not to undergo the procedure personally. Similarly, concerning the assessment of predisposition or risk for the development of specific diseases in the future, 67.68% (n = 4,454) of respondents were in favor of offering genetic testing within the healthcare system and indicated a willingness to undergo the test personally, while 16.62% (n = 1,094) favored the availability of the test but opted not to undergo testing themselves. When considering the selection of the most effective or least risky treatment, 70.57% (n = 4,644) of respondents advocated for genetic testing being offered in healthcare for this purpose and were inclined to undergo such testing personally. A smaller portion (14.51%, n = 955) supported the availability of the test but would choose not to undergo testing themselves. In the context of family planning and reproductive health, 64.85% (n = 4,268) of respondents supported the availability of genetic testing to assess the risk of transmitting predispositions for specific diseases to future generations and expressed a willingness to undergo this testing. A fraction (18.46%, n = 1,215) supported the test availability but chose not to take it personally. Similarly, during pregnancy for diagnosing or assessing the risk of serious diseases in the fetus, a substantial 65.52% (n = 4,312) of respondents supported the genetic testing being offered within the healthcare system for this purpose and were willing to be personally tested. Another 17.55% (n = 1,155) supported the availability of the test but preferred not to be tested themselves. The compound support level for participants was high (≥ 4/5) for a large majority of participants (81.52%, n = 5,365) and low (≤ 3/5) for 18.48% of them (n = 1,216). Willingness to Share Health Data and Genomic Information for Medical Research This section explores respondents' perspectives regarding sharing general health information and genomic data (Table 5 ). Regarding sharing health data from their healthcare record, 47.74% (n = 3,142) expressed a willingness to share their health information for the benefit of others. Additionally, 19.86% (n = 1,307) indicated their willingness to share data for research on diseases affecting themselves or their families. 8.13% of respondents (n = 535) would share their health data, excluding genomic information. Conversely, some respondents exhibited hesitancy: 12.58% (n = 828) of participants were unwilling to share their health data, while 11.69% (n = 769) remained uncertain. The perspectives were diverse when focusing on genomic data sharing with biobanks. A total of 30.34% (n = 1,997) of respondents expressed a willingness to share their genomic data for the benefit of others, while 30.76% (n = 2,024) would share if they received reassurance. 8.97% (n = 590) would consider sharing if monetarily compensated. However, a notable portion of respondents expressed reluctance towards genomic data sharing. Approximately 14.37% (n = 946) indicated an unwillingness to share their genomic data, while 15.56% (n = 1,024) remained uncertain about their stance on this matter. Overall, 52.35% (n = 3,445) showed a willingness to data sharing, whereas 47.65% (n = 3,136) did not. Predictors of Higher Compound Knowledge Level The female gender (OR 1.40, 95% CI 1.20–1.63, p < 0.0001) and possessing a tertiary education (OR 2.06, 95% CI 1.77–2.39, p < 0.0001) were associated with a higher compound knowledge. Respondents from Southern Europe exhibited a superior level of knowledge compared to Centrale Europe (OR 1.25, 95% CI 1.05–1.48, p = 0.01) (Table 6 ). Predictors of Support for the Availability of Genetic Tests in the Healthcare System The female gender was associated with a positive inclination towards the availability of genetic tests (OR 1.40, 95% CI 1.23–1.59, p < 0.0001). Additionally, education and knowledge showed a positive association with the support for genetic testing availability. Respondents with tertiary education levels were more inclined to support the integration of genetic tests within the healthcare system (OR 1.48, 95% CI 1.29–1.70, p < 0.0001), with individuals possessing a higher level of knowledge displaying a significantly heightened likelihood of supporting the integration of genetic tests within the healthcare system (OR 4.08, 95% CI 2.97–5.60, p < 0.0001). When Central Europe was used as the reference category, both Eastern Europe (OR 2.47, 95% CI 2.08–2.94, p < 0.0001) and Southern Europe (OR 2.85, 95% CI 2.42–3.36, p < 0.0001) exhibited a higher likelihood of supporting the availability of genetic tests within the healthcare system (Table 6 ). Predictors of Willingness to Share Health and Genomic Data Age exhibited a borderline positive association with the willingness to share health and genomic data (OR 1.015, 95% CI 1.011–1.018, p 0.0001), and individuals with a higher level of compound knowledge were more inclined to share their health and genomic information (OR 1.60, 95% CI 1.36–1.89, p < 0.0001). Additionally, individuals supporting the availability of genetic tests offered in the healthcare system were substantially more likely to share their health and genomic data (OR 5.30, 95% CI 4.46–6.06, p < 0.0001). Considering geographical variations and using Central Europe as the reference, both Eastern Europe and Southern Europe displayed a positive association with the willingness to share health and genomic data. Respondents from Eastern Europe (OR 1.32, 95% CI 1.16–1.51, p < 0.0001) and Southern Europe (OR 1.66, 95% CI 1.47–1.87, p < 0.0001) were more inclined to share their data (Table 6 ). Table 1 Components of the compound indicators. In the Questions column, the italic number in brackets indicates the score assigned to each question. Compound indicators Questions Coding Compound knowledge of personalized medicine • Do you think you have adequate knowledge about personalized medicine? (0–4) • Were you aware of the existence of health/patient portals prior to this survey? (0–1) • Which of the following had you ever heard about, prior to this survey? (0–3) • Which of the following uses of genetic testing for medical purposes have you ever heard about prior to this survey? (0–7) The cut-off for high/low compound knowledge was set at 75% - High knowledge if ≥ 9/12 - Low knowledge if ≤ 8/12 Compound support of genetic testing implementation in healthcare • If a genetic test were available at low cost, for what purposes you would support the test being offered by the health care system of your country, and would you consider having such testing? (0–5) The cut-off for support (yes/no) was set at 80%. Support if ≥ 4/5 No support if ≤ 3/5 Compound willingness to data sharing • Would you share your personal genomic data with biobanks or research institutes? • If people were given an option to share their data, would you be willing to share your data - including from any genetic tests - from your health care record or portal to benefit other patients or for medical research purposes? Yes, if answered: - “Would share for others’ benefit” to both Q1 and Q2 - “Would share for others’ benefit” to Q1 AND “Would share for research on a disease running in my family” to Q2 - “Would share if reassurances are granted“ for Q1 AND “Would share for others’ benefit” to Q2 No, for any other combination. Table 2 Demographic information of respondents Demographic information (N = 6,581). No. % Gender Male 3123 47.5 Female 3458 52.5 Age (years) Mean = 48.5 SD = 16.0 Achieved tertiary education No 4086 62.1 Yes 2495 37.9 Country France 1008 15.3 Germany 1009 15.4 Hungary 510 7.7 Italy 1022 15.5 Netherlands 1012 15.4 Poland 509 7.7 Romania 508 7.7 Spain 1003 15.3 Geographic area Central Europe 3029 46.03 Eastern Europe 1527 23.20 Southern Europe 2025 30.77 Table 3 Knowledge and awareness of citizens regarding key medical advancements and personalized medicine. Personal knowledge (N = 6,581). No. % Which of the following had you ever heard about, prior to this survey? Personalized Medicine 3143 47.76 Big data 2437 37.03 Genetic Testing 5300 80.53 Which of the following uses of genetic testing for medical purposes have you ever heard about prior to this survey?* (N = 5,300) Diagnosis of a disease 2553 48.17 Assessment of risk to develop a specific disease, for the disease to be prevented or treated at an early stage 2583 48.74 Choice of the treatment for a disease (e.g. the choice of chemotherapy in case of cancer) 1890 35.66 Assessment of a specific drug in a person (e.g. to avoid wrong dosage or adverse effects) 1129 21.30 Assessment of the risk of passing a genetic disease to future children 2948 55.62 Prenatal testing during pregnancy 2695 50.85 Heel prick of newborn baby to detect a genetic disorder 1905 35.94 Were you aware of the existence of health/patient portals prior to this survey? Yes 3573 54.30 No 2501 38.00 Don't know 507 7.70 Do you think you have adequate knowledge about personalized medicine? Definitely 291 4.42 Somewhat 1435 21.81 Not really 2761 41.95 Not at all 1536 23.34 Don't know 558 8.48 Compound knowledge Level High (≥ 9/12) 797 12.11 Low (≤ 8/12) 5784 87.89 This table only reports those who answered affirmatively to the questions asked. *only available to those who stated they knew about genetic testing; hence the total is 5300. Table 4 Support for Genetic Testing Availability within the Healthcare System and Willingness to Undergo Testing. Support (N = 6,581) No. % If a genetic test were available at low cost, for what purposes you would support the test being offered by the health care system of your country, and would you consider having such testing? 6581 100.00 To diagnose a serious genetic disease I would support the test being made available by the health care system of my country, and I would consider taking such test 4751 72.19 I would support being made available by the health care system of my country, but I would NOT consider taking such test 990 15.04 I do not support the test being made available by the health care system of my country 268 4.07 Don’t know 572 8.69 To assess the predisposition or risk for you to develop a specific disease in the future I would support the test being made available by the health care system of my country, and I would consider taking such test 4454 67.68 I would support being made available by the health care system of my country, but I would NOT consider taking such test 1094 16.62 I do not support the test being made available in by the health care system of my country 357 5.43 Don’t know 676 10.27 To choose the most effective treatment or a treatment with the lowest risk of potential adverse effects I would support the test being made available by the health care system of my country, and I would consider taking such test 4644 70.57 I would support being made available by the health care system of my country, but I would NOT consider taking such test 955 14.51 I do not support the test being made available in by the health care system of my country 290 4.40 Don’t know 692 10.52 Before pregnancy, to assess the risk of future parents transmitting a predisposition for a specific disease to their future children I would support the test being made available by the health care system of my country, and I would consider taking such test 4268 65.52 I would support being made available by the health care system of my country, but I would NOT consider taking such test 1215 18.46 I do not support the test being made available in by the health care system of my country 357 5.42 Don’t know 741 11.27 During pregnancy, to diagnose or assess the risk of a serious disease in the foetus? I would support the test being made available by the health care system of my country, and I would consider taking such test 4312 65.52 I would support being made available by the health care system of my country, but I would NOT consider taking such test 1155 17.55 I do not support the test being made available in by the health care system of my country 351 5.34 Don’t know 763 11.59 Compound support Yes (≥ 4/5) 5365 81.52 No (≤ 3/5) 1216 18.48 Table 5 Willingness to Share Health Data and Genomic Information for Medical Research Willingness to Share Health Data and Genomic Information for Medical Research (N = 6581) No. % If people were given an option to share their data, would you be willing to share your data - including from any genetic tests - from your health care record or portal to benefit other patients or for medical research purposes? Yes, to help health care professionals interpret findings and diagnose other patients 3142 47.74 Yes, but only to support research into a disease I or members in my family suffer from 1307 19.86 I would share health data with researchers, but not genetic data 535 8.13 No, I wouldn’t 828 12.58 Don’t know 769 11.69 Would you share your personal genomic data with biobanks or research institutes? Yes, for the sake of contributing to science 1997 30.34 Only provided some information are granted to me 2024 30.76 Only provided I would be adequately compensated monetarily 590 8.97 No, I wouldn’t 946 14.37 Don’t know 1024 15.56 Willingness to data sharing Yes 3445 52.35 No 3136 47.65 Table 6 Predictors of Higher Compound Knowledge Level, Support for the Availability of Genetic Tests in the Healthcare System, and Willingness to Share Health and Genomic Data Predictors of Higher Compound Knowledge Level Explanatory variable OR (95% CI) p-value Gender, female 1.40 (1.20–1.63) < 0.0001 Tertiary education 2.06 (1.77–2.39) < 0.0001 Geographical area (ref: Central Europe) Eastern Europe 1.10 (0.90–1.33) 0.329 Southern Europe 1.25 (1.05–1.48) 0.010 Predictors of Support for the Availability of Genetic Tests in the Healthcare System Explanatory variable OR (95% CI) p-value Gender, female 1.40 (1.23–1.59) < 0.0001 Age 0.99 (0.99–1.00) 0.112 Tertiary education 1.48 (1.29–1.70) < 0.0001 Compound knowledge 4.08 (2.97–5.60) < 0.0001 Geographical area (ref: Central Europe) Eastern Europe 2.47 (2.08–2.94) < 0.0001 Southern Europe 2.85 (2.42–3.36) < 0.0001 Predictors of Willingness to Share Health and Genomic Data Explanatory variable OR (95% CI) p-value Age 1.015 (1.011–1.018) < 0.0001 Tertiary education 1.20 (1.08–1.33) < 0.0001 Compound knowledge 1.60 (1.36–1.89) < 0.0001 Compound support 5.30 (4.46–6.06) < 0.0001 Geographical area (ref: Central Europe) Eastern Europe 1.32 (1.16–1.51) < 0.0001 Southern Europe 1.66 (1.47–1.87) < 0.0001 Discussion In discussing the results of this survey, we highlight three key variables impacting the implementation of personalized medicine in health care: Knowledge and awareness, Support towards genetic testing implementation in the healthcare system, and Willingness to health data sharing. Knowledge and Awareness Respondents' knowledge about various aspects of personalized medicine differed strongly per concept. At the end of the survey, a considerable proportion of respondents expressed limited knowledge about personalized medicine, with 41.95% feeling “not really” knowledgeable and 23.34% feeling “not at all” knowledgeable. At the start of the survey, 47.76% of respondents had heard about personalized medicine, 37.03% about big data, and 80.53% about genetic testing. These results align with existing literature, reporting that the general public has limited knowledge of the more recent medical paradigms in omics sciences, nonetheless showing room for educational initiatives, following an overall positive attitude. ( 16 ) Additionally, previous research investigating knowledge of personalized medicine and genetic testing focused on specific categories rather than the general public. Rosso et al. highlighted a general need to increase awareness of genomics among European public health professionals. It indicated that while there were positive attitudes towards genetic testing, there was a significant knowledge gap, even among those involved in public health genomics activities. ( 15 ) Genetic testing has been around for a long time since the introduction of sickle-cell genetic testing approximately forty years ago ( 17 ), and the various applications of such testing were acknowledged by as high as 55.62% of respondents. Previous research suggests that communicating about aspects of personalized medicine benefits by building on concepts and applications that people are already familiar with. ( 9 , 18 , 19 ) Support towards genetic testing implementation in the healthcare system Our findings indicate widespread acceptance and endorsement of integrating genetic testing into the healthcare system. The insights gathered shed light on the public's stance regarding incorporating genetic testing into the healthcare framework and their intention to undergo testing themselves. As we explored the available literature, no previous study investigated citizens’ attitudes toward this theme. Nonetheless, a scoping review found that complete coverage of the cost of clinical genetic testing is not always available through public or private insurance programs, leading to financial barriers for patients who do not qualify for full coverage. ( 20 ) We framed the question in a manner that assumed the genetic test would incur minimal expenses for the healthcare system or the patients themselves. This approach was designed to mitigate potential biases that might dissuade respondents from accepting the test's integration into their healthcare system due to cost-related concerns rather than any reservations about the test itself. However, nuanced variations in support exist, influenced by specific testing purposes. Respondents supported genetic testing for diagnostics (72.19%) and pharmacogenomics (70,57%) while also considering undergoing such tests, while 15.04% and 14,51%, respectively, supported such an offer but indicated they would not take the test themselves. Another 67.68% supported offering testing to assess a predisposition or risk for the development of specific diseases, while 16.62% supported availability without considering having such testing themselves. These results indicate that a relevant share of respondents in the general public have some form of reservation against the uses of genetic testing in health care that would be most relevant for personalized medicine. This might be related to needing more knowledge of applications and potential benefits, as already addressed in scientific literature. ( 21 ) Among the survey respondents, having more knowledge and higher education were associated with support for offering genetic testing. Potential knowledge gaps should be addressed in research and policymaking when further implementing promising applications. For some applications, e.g., to establish drug dose or compatibility, more routine testing may become feasible when evidence for pharmacogenomics increases and guidelines for, e.g., companion diagnostics are further developed. This may increase acceptability and is currently being researched for various applications. ( 22 , 23 ) However, respondents may also have concerns or other considerations regarding genetic testing that need to be addressed to better tailor approaches to genetic testing implementation within healthcare frameworks. Especially regarding predisposition to disease, a discussion is ongoing, acknowledging that for some people, having prior knowledge would be seen as beneficial per se or because this would enable interventions, while others might prefer not to know whether they are at risk. ( 21 , 24 , 25 ) Such decisions may also be influenced by the available interventions and their perceived burdens, while such interventions and preferences may also change over time. ( 24 ) In clinical genetics practice, such questions would be addressed via extensive counseling of patients and their first-degree family members. However, as genetic information will play an increasingly important role in prevention and health care outside such clinical genetic settings, education and communication about the pros and cons of genetic testing will more generally need to be available before citizens fall ill. For many years, it has been suggested that genetic education be stimulated in secondary education. ( 26 ) In recent years, new promising online tools have been developed that enable people to learn more about genetics in medicine, and such tools can also aid in optimizing giving information and counseling before more specific forms of testing. ( 27 , 28 ) Similar initiatives dedicated to fostering genetic education and increasing awareness about genetic testing could prove to be particularly useful in improving the general public’s support of the implementation of genetic testing in healthcare by providing them with the tools and knowledge to understand better the genetic information they are handled and the related possibilities. Improving healthcare professionals’ literacy and awareness is also crucial, as they are the gateway to the general public’s unaddressed needs. Healthcare professionals must make decisions based on complex biological, environmental, and lifestyle information and address patients’ needs and inquiries. Ultimately, they positively impact previously unaddressed knowledge gaps and the needs of the general public. ( 16 , 29 ) Willingness to health data sharing Our results show that individuals with higher knowledge, education, and support for integrating genetic testing are more willing to share their data. This is consistent with what was previously highlighted in the literature. ( 9 , 10 , 15 , 16 ) Also, in this case, better information provision and communication between healthcare providers and patients about the importance of data sharing may stimulate awareness and a more positive attitude toward data sharing. Recent research has shown that, in general, people are more willing to trust their health care provider or non-profit researchers in universities rather than commercial institutions, though public trust and willingness to donate differ per country. However, Savić-Kallesøe et al. argue that their results “suggest that while public trust is significant, it may be neither necessary nor sufficient in influencing willingness to donate. Future research could do well to investigate how the importance of public trust compares in countries with lower public trust.” ( 30 ) A recent expert workshop for the Beyond 1 Million Genomics Initiative stressed that trust is contextual and relational and may also depend on national contingencies. ( 31 ) In an increasingly international field of data sharing extending trust from such local or national conditions to European and potentially global research consortia, it underlines the significance of individuals' trust and belief in healthcare institutions regarding data sharing for research. Geographical differences European perspectives on personalized medicine and data sharing highlight the importance of interoperability, willingness to share personal health data, and the challenges in achieving adequate data sharing across diverse populations. Our results indicate national and supranational differences regarding knowledge, support for integrating genetic testing in health care, and willingness to share health and genomic data. This is coherent with what was highlighted in the literature, providing additional information on previously unaddressed topics, such as citizens’ support towards implementing genetic testing in their country’s healthcare system. Respondents from the Southern European countries in our sample scored higher on knowledge; respondents from the Southern and Eastern European countries showed more support for offering genetic testing within their healthcare systems and willingness to share data than respondents from Central Europe. These findings align with what is retrieved in scientific literature, that individuals' trust and belief in the healthcare system may vary across countries and that it influences their attitudes towards novel medical paradigms and medical innovations, such as genetic testing and sharing their own health and genomic data. ( 32 , 33 ) Although a similar supranational analysis is not found in the literature, similar articles highlight how specific populations display less favorable attitudes towards data sharing and adoption of genomics, such as the Your DNA Your Say analysis particular to the German people. ( 34 ) The variance in our sample emphasizes the role of geographical context in shaping perspectives on healthcare advancements, advocating for targeted strategies for integrating personalized prevention based on region and country-specific needs and possibilities. In this paper, we refrain from conducting national-level analyses, as our focus is on a broader examination of the European scenario. In other publications, we will delve deeper into country-specific manuscript features to provide a more nuanced and comprehensive understanding of the subject from national perspectives. Future perspectives The results of our investigation shed light on the heterogeneous situation in the European Union towards personalized medicine and data sharing. Despite numerous positive indicators, this survey paints a scenario where the general public still needs to be made aware of available medical resources and the possibilities of novel medical advancements. This is particularly true when examining genetic testing and the applications investigated in this survey. Still, the pace at which medical advancements proceed makes it likely that other fields would also show similar outcomes. Furthermore, health data and genomic data sharing are essential to research in all healthcare and medical sciences fields, calling for increased responsibilities of the general public. European policymakers are active in addressing personalized medicine with legislation and directives. ( 35 , 36 ) The importance of secondary use of health data is widely embraced in the European Union, where the European Commission oversees and coordinates the establishment of the European Health Data Space (EHDS) to ensure that generated health data is available to researchers and policymakers for secondary use in the future. ( 37 ) Similarly, the One Million Genomes initiative aims to build a genomic data infrastructure to foster cross-border access and sharing of genomic information and related clinical data to be integrated with the EHDS. ( 38 ) These initiatives address relevant issues, such as frameworks for adequate informed consent, data management, and privacy. Addressing citizens’ concerns and stimulating further education and communication to establish responsible research practices will be particularly relevant to ensure these ambitious programs achieve their fullest potential. This would positively impact research and development of improved technologies and medical approaches, benefiting the European population by increasing health outcomes. However, it should be noted that advocating for data sharing should be regarded as something other than an all-cost strategy. Patients might be defensive regarding susceptible data, such as health and genomic data. Increased transparency about who benefits from data access and providing the option to withdraw are crucial measures to increase trust in health data sharing, potentially having a positive impact on the adherence and sharing to genetic testing in the first place. ( 39 ) Similarly, if they are reassured, patients and citizens might as well undergo genetic testing for research purposes out of altruism rather than to get results back. ( 40 ) A patient-controlled approach to data sharing, where patients are in control of their biomedical and genetic data and can share it with healthcare providers and researchers, would be the ideal outcome for data sharing policies if patients are empowered to decide responsibly and freely about their health and the use that their data undergoes. Such patient engagement would promote data sharing across health organizations for clinical care purposes and contribution to research databases. ( 41 ) Limitations The results of this survey aim to lay the foundations for future education and communication activities to improve the general public’s attitudes towards personalized medicine and data sharing. The survey was distributed using a professional polling system to ensure that the considered sample represents the general population regarding age, gender, and education level. Nonetheless, this survey’s results should be regarded in light of some limitations. Despite covering a considerable majority of EU citizens, it should be noted that we only distributed our survey in 8 out of 27 countries. In addition, the sampling between different countries did not consider the countries’ population count, possibly introducing bias related to unequal sampling ratios following varying sample size ratios to population size. When detailing the statistical analysis, geographical bias should be considered due to the clustering of different countries in the same geographical area. Results related to one geographical area should be distinct from the countries involved (e.g., Italy and Spain might display opposite outcomes, which are masked by each other when merged as Southern Europe in the logistic regression models). Despite providing a relevant outlook on the factors influencing the general public’s knowledge of personalized medicine, support that genetic testing is implemented in healthcare, and willingness to data sharing, it should be noted that these are complex factors influenced by several variables. With this in mind, our analysis should not be deemed exhaustive but rather as the foundation of future research in this field. Conclusions The findings of this survey reveal a complex landscape of knowledge, attitudes, and willingness to engage in personalized medicine and health data sharing within the EU. While there is broad support for genetic testing and a recognition of its potential benefits, substantial gaps in knowledge and varying levels of trust in data-sharing practices exist. These disparities underscore the necessity for targeted educational and communicative efforts to bridge these gaps. Initiatives like the European Health Data Space and the One Million Genomes initiative are crucial in promoting secure and responsible data sharing for advancing personalized medicine, improving health outcomes, and encouraging progress in research. However, such initiatives should be accompanied by public and patient-centric approaches and transparency in health data usage to gain public trust and participation. Future efforts should prioritize target interventions to increase general understanding of personalized medicine, including health data sharing, to fully realize its potential in improving healthcare outcomes across the EU. Declarations Acknowledgments We thank the respondents to the survey who took the time to answer the questions on personalized medicine. We thank the Italian Ministry of Health for supporting the activities of the National Center for Disease Prevention and Control (CCM) projects related to genomics and omics sciences, including implementing our survey. Funding The survey is part of the “European network staff eXchange for integrating precision health in the Health Care Systems” (ExACT) project, supported by the European Union’s Horizon 2020 research and innovation program under the RISE Marie Curie Actions, under grant agreement n. 823995. This survey contributes to a project funded by the Italian Center for Disease Prevention and Control of the Ministry of Health (CCM2021, CUP B85F21004970001), which focuses on creating the Italian Genomic Strategy and providing national backing for the European initiatives 1+Million Genomes (1+MG) and Beyond 1+Million Genomes (B1MG). 1. Please provide a Consent to Participate declaration in the manuscript. Every human participant should provide their consent: Participants were asked to participate in the study before accessing the questionnaire. The first page of the Supplementary Material includes the introduction provided to the participants before they joined. Upon clicking the “Please click here to continue” button, participants had access to the questionnnaire; 2. Human Ethics and Consent to Participate declarations: Ethical approval for this study was obtained from the Policlinico Universitario ‘Agostino Gemelli’ Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214); 3. Competing Interests: No, I declare that the authors have no competing interests as defined by BMC, or other interests that might be perceived to influence the results and/or discussion reported in this paper; 4.1. Ethics approval and consent to participate: Ethical approval for this study was obtained from the Policlinico Universitario ‘Agostino Gemelli’ Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214); 4.2. Consent for publication: I confirm that I understand BMC Public Health is an open access journal that levies an article processing charge per articles accepted for publication. By submitting my article I agree to pay this charge in full if my article is accepted for publication; 4.3. Availability of data and materials: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. 4.4. Competing Interests: No, I declare that the authors have no competing interests as defined by BMC, or other interests that might be perceived to influence the results and/or discussion reported in this paper; 4.5. Funding: The survey is part of the “European network staff eXchange for integrating precision health in the Health Care Systems” (ExACT) project, supported by the European Union’s Horizon 2020 research and innovation program under the RISE Marie Curie Actions, under grant agreement n. 823995. This survey contributes to a project funded by the Italian Center for Disease Prevention and Control of the Ministry of Health (CCM2021, CUP B85F21004970001), which focuses on creating the Italian Genomic Strategy and providing national backing for the European initiatives 1+Million Genomes (1+MG) and Beyond 1+Million Genomes (B1MG); 4.6. Authors' contributions: Substantial contributions to the conception and design of the work: F.A.C., C.V.E.; R.P.; L.L.K.; Drafting the work or revising it critically for important content: All authors; Prepared supplementary material: F.A.C.; Final approval of the version to be published: C.V.E., S.B., R.P., G.E.C; 4.7. Acknowledgements: We thank the respondents to the survey who took the time to answer the questions on personalized medicine. We thank the Italian Ministry of Health for supporting the activities of the National Center for Disease Prevention and Control (CCM) projects related to genomics and omics sciences, including implementing our survey; 4.8. Authors' information (optional) 5. Availability of Data and Materials: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. 5.2. The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Corresponding Author: [email protected] . References Etchegary H, Wilson B. Bringing personalized medicine to the community through public engagement. Per Med. 2013;10(7):647-59. Grande D, Mitra N, Shah A, Wan F, Asch DA. Public preferences about secondary uses of electronic health information. JAMA Intern Med. 2013;173(19):1798-806. Liang X, Zhao J, Shetty S, Liu J, Li D, editors. Integrating blockchain for data sharing and collaboration in mobile healthcare applications. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC); 2017 8-13 Oct. 2017. Kim KK, Joseph JG, Ohno-Machado L. Comparison of consumers' views on electronic data sharing for healthcare and research. J Am Med Inform Assoc. 2015;22(4):821-30. Lock K. Health impact assessment: assessing opportunities and barriers to intersectoral health improvement in an expanded European Union. Journal of Epidemiology & Community Health. 2005;59(5):356-60. Middleton A, Niemiec E, Prainsack B, Bobe J, Farley L, Steed C, et al. ‘Your DNA, Your Say’: global survey gathering attitudes toward genomics: design, delivery and methods. Personalized Medicine. 2018;15(4):311-8. Voigt TH, Holtz V, Niemiec E, Howard HC, Middleton A, Prainsack B. Willingness to donate genomic and other medical data: results from Germany. Eur J Hum Genet. 2020;28(8):1000-9. Romano V, Milne R, Mascalzoni D. Italian public's views on sharing genetic information and medical information: findings from the 'Your DNA, Your Say' study. Wellcome Open Res. 2021;6:180. Calabrò GE, Causio FA, Pires Marafon D, Sassano M, Moccia F, Pastorino R, et al. Public attitudes, knowledge and educational needs toward genetic testing and omics sciences: a pilot survey conducted in Italy. Eur J Public Health. 2023. Balicza P, Terebessy A, Grosz Z, Varga NA, Gal A, Fekete BA, et al. Implementation of personalized medicine in Central-Eastern Europe: pitfalls and potentials based on citizen’s attitude. EPMA Journal. 2018;9(1):103-12. Hoxhaj I, Stojanovic J, Boccia S. European citizens' perspectives on direct-to-consumer genetic testing: an updated systematic review. Eur J Public Health. 2020. Causio FA, Beccia F, Kreeftenberg LL, Calabro GE, Pastorino R, Boccia S, et al. European Survey on Citizens' Attitudes towards Personalized Medicine, Genetic Testing, and Health Data Sharing: Design and Delivery. medRxiv. 2024:2024.02.02.24302142. Beccia F, Hoxhaj I, Sassano M, Stojanovic J, Acampora A, Pastorino R, et al. Survey of Professionals of the European Public Health Association (EUPHA) towards Direct-to-Consumer Genetic Testing. Eur J Public Health. 2023;33(1):139-45. Villani L, Pastorino R, Molinari E, Anelli F, Ricciardi W, Graffigna G, et al. Impact of the COVID-19 pandemic on psychological well-being of students in an Italian university: a web-based cross-sectional survey. Globalization and Health. 2021;17(1):39. Rosso A, Pitini E, D'Andrea E, Di Marco M, Unim B, Baccolini V, et al. Genomics knowledge and attitudes among European public health professionals: Results of a cross-sectional survey. PLoS One. 2020;15(4):e0230749. Calabrò GE, Sassano M, Tognetto A, Boccia S. Citizens' Attitudes, Knowledge, and Educational Needs in the Field of Omics Sciences: A Systematic Literature Review. Frontiers in Genetics. 2020;11. Scott S, Abul-Husn N, Owusu Obeng A, Sanderson S, Gottesman O. Implementation and utilization of genetic testing in personalized medicine. Pharmacogenomics and Personalized Medicine. 2014:227. Calabro GE, Sassano M, Boccia S. Citizens' Literacy in Genomics: A Delphi Survey of Multidisciplinary Experts in the Field. Genes (Basel). 2022;13(3). Sassano M, Calabro GE, Boccia S. A Web Screening on Educational Initiatives to Increase Citizens' Literacy on Genomics and Genetics. Front Genet. 2021;12:637438. Grant P, Langlois S, Lynd LD, Austin JC, Elliott AM. Out-of-pocket and private pay in clinical genetic testing: A scoping review. Clin Genet. 2021;100(5):504-21. Yanes T, Willis AM, Meiser B, Tucker KM, Best M. Psychosocial and behavioral outcomes of genomic testing in cancer: a systematic review. Eur J Hum Genet. 2019;27(1):28-35. Peruzzi E, Roncato R, De Mattia E, Bignucolo A, Swen JJ, Guchelaar H-J, et al. Implementation of preemptive testing of a pharmacogenomic panel in clinical practice: Where do we stand? British Journal of Clinical Pharmacology.n/a(n/a). Martens FK, Huntjens DW, Rigter T, Bartels M, Bet PM, Cornel MC. DPD Testing Before Treatment With Fluoropyrimidines in the Amsterdam UMCs: An Evaluation of Current Pharmacogenetic Practice. Frontiers in Pharmacology. 2020;10. Lupo PJ, Robinson JO, Diamond PM, Jamal L, Danysh HE, Blumenthal-Barby J, et al. Patients' perceived utility of whole-genome sequencing for their healthcare: findings from the MedSeq project. Per Med. 2016;13(1):13-20. Mighton C, Carlsson L, Clausen M, Casalino S, Shickh S, McCuaig L, et al. Development of patient "profiles" to tailor counseling for incidental genomic sequencing results. Eur J Hum Genet. 2019;27(7):1008-17. Warne RT. Are you ready for the genetic revolution in education? Phi Delta Kappan. 2021;103(2):34-9. Rayes N, Bowen DJ, Coffin T, Nebgen D, Peterson C, Munsell MF, et al. MAGENTA (Making Genetic testing accessible): a prospective randomized controlled trial comparing online genetic education and telephone genetic counseling for hereditary cancer genetic testing. BMC Cancer. 2019;19(1):648. Shickh S, Hirjikaka D, Clausen M, Kodida R, Mighton C, Reble E, et al. Genetics Adviser: a protocol for a mixed-methods randomised controlled trial evaluating a digital platform for genetics service delivery. BMJ Open. 2022;12(4):e060899. Ricciardi W, Boccia S. New challenges of public health: bringing the future of personalised healthcare into focus. Eur J Public Health. 2017;27(suppl_4):36-9. Savi?-Kalles¯e S, Middleton A, Milne R. Public trust and genomic medicine in Canada and the UK [version 2; peer review: 3 approved]. Wellcome Open Research. 2021;6(124). Maria Fátima Lopes AM, Alexandra Costa X, Perez ML, Cardoso M, Konopko M, Bourbon S, et al. Genomics in Healthcare - Key issues for implementation. 2021. Kalkman S, Delden Jv, Banerjee A, Tyl B, Mostert M, Thiel Gv. Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. Journal of Medical Ethics. 2022;48(1):3-13. Biasiotto R, Viberg Johansson J, Alemu MB, Romano V, Bentzen HB, Kaye J, et al. Public Preferences for Digital Health Data Sharing: Discrete Choice Experiment Study in 12 European Countries. J Med Internet Res. 2023;25:e47066. Voigt TH, Holtz V, Niemiec E, Howard HC, Middleton A, Prainsack B. Willingness to donate genomic and other medical data: results from Germany. European Journal of Human Genetics. 2020;28(8):1000-9. Causio FA, Hoxhaj I, Beccia F, Marcantonio MD, Strohäker T, Cadeddu C, et al. Big data and ICT solutions in the European Union and in China: A comparative analysis of policies in personalized medicine. Digit Health. 2022;8:20552076221129060. Beccia F, Hoxhaj I, Castagna C, Strohäker T, Cadeddu C, Ricciardi W, et al. An overview of Personalized Medicine landscape and policies in the European Union. European Journal of Public Health. 2022;32(6):844-51. Cascini F, Santaroni F, Lanzetti R, Failla G, Gentili A, Ricciardi W. Developing a Data-Driven Approach in Order to Improve the Safety and Quality of Patient Care. Front Public Health. 2021;9:667819. Saunders G, Baudis M, Becker R, Beltran S, Béroud C, Birney E, et al. Leveraging European infrastructures to access 1 million human genomes by 2022. Nat Rev Genet. 2019;20(11):693-701. Milne R, Morley KI, Almarri MA, Atutornu J, Baranova EE, Bevan P, et al. Return of genomic results does not motivate intent to participate in research for all: Perspectives across 22 countries. Genet Med. 2022;24(5):1120-9. Milne R, Morley KI, Almarri MA, Anwer S, Atutornu J, Baranova EE, et al. Demonstrating trustworthiness when collecting and sharing genomic data: public views across 22 countries. Genome Medicine. 2021;13(1):92. Miller KE, Lin SM. Addressing a patient-controlled approach for genomic data sharing. Genetics in Medicine. 2017;19(11):1280-5. Additional Declarations No competing interests reported. Supplementary Files QuestionslistSurvey.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3960901","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278272206,"identity":"4de3865a-cbed-49a5-acae-c1d4756599c1","order_by":0,"name":"Francesco Andrea Causio","email":"","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Francesco","middleName":"Andrea","lastName":"Causio","suffix":""},{"id":278272207,"identity":"29b8fa59-9f01-40ad-8038-918f5a8f4c46","order_by":1,"name":"Flavia Beccia","email":"","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Flavia","middleName":"","lastName":"Beccia","suffix":""},{"id":278272208,"identity":"8f0947f7-2fd0-49ae-9773-f9948991774d","order_by":2,"name":"Giovanna Elisa Calabrò","email":"","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Giovanna","middleName":"Elisa","lastName":"Calabrò","suffix":""},{"id":278272209,"identity":"5d9aef6f-cb06-41e4-859a-772996f3adde","order_by":3,"name":"Loes Lindiwe Kreeftenberg","email":"","orcid":"","institution":"APH research institute, Amsterdam UMC, location Vrije Universiteit","correspondingAuthor":false,"prefix":"","firstName":"Loes","middleName":"Lindiwe","lastName":"Kreeftenberg","suffix":""},{"id":278272210,"identity":"b15cc265-fe2c-40c0-8eec-b4e61ec439ff","order_by":4,"name":"Roberta Pastorino","email":"data:image/png;base64,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","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":true,"prefix":"","firstName":"Roberta","middleName":"","lastName":"Pastorino","suffix":""},{"id":278272211,"identity":"ae7d8f6f-399f-4f05-921b-38ad335c7572","order_by":5,"name":"Carla El","email":"","orcid":"","institution":"APH research institute, Amsterdam UMC, location Vrije Universiteit","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"","lastName":"El","suffix":""},{"id":278272212,"identity":"d8ab4a3a-53b2-4201-85db-dabf9d438970","order_by":6,"name":"Stefania Boccia","email":"","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Stefania","middleName":"","lastName":"Boccia","suffix":""}],"badges":[],"createdAt":"2024-02-16 10:00:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3960901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3960901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58358275,"identity":"cbf79bca-7931-4a5a-a47a-2dc1f193f44e","added_by":"auto","created_at":"2024-06-14 10:35:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":850804,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3960901/v1/f7deb6fa-c559-4c71-98c9-71b30d28c109.pdf"},{"id":52541214,"identity":"cff7da81-3182-4fbb-a3bf-a182fbb3979f","added_by":"auto","created_at":"2024-03-12 17:31:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":367682,"visible":true,"origin":"","legend":"","description":"","filename":"QuestionslistSurvey.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3960901/v1/fe87551ec9a542c144877da7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knowledge and Attitudes of Personalized Medicine, Genetic Testing, and Health Data Sharing: A Comprehensive Survey in the general public of the European Union","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn recent years, advancements in medical technology and research have led to new paradigms in healthcare. The personalized medicine approach has transformed healthcare by adapting prevention, diagnosis, and treatment strategies to suit individual patients, considering their genetic, environmental, and lifestyle factors. The effective development and application of these advanced medical methods depend significantly on the public's understanding and knowledge of personalized medicine. This includes their ability to access these novel approaches and their readiness to share health-related information. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe secure and convenient sharing of individual health data is also crucial to enhancing collaboration in research and healthcare. In the face of increasing public concern and scrutiny regarding data privacy, the importance of trust in data sharing in personalized medicine has become increasingly apparent, with a growing body of evidence investigating personal preferences and institutional safeguards for data sharing. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eTherefore, understanding the level of knowledge and awareness among the European Union (EU) public, as well as their views on health data sharing, is critical for healthcare professionals and policymakers to effectively communicate and educate the public about the latest advancements in the medical field and help build trustworthy institutional arrangements for health research. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn 2017, the international Your DNA Your Say (YDYS) project used film and an online cross-sectional survey to gather public attitudes toward donating, accessing, and sharing DNA information. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) The results showed significant variations in willingness to share information and trust in the actors associated with collecting and using DNA information. Specifically, the German public's willingness to donate genomic data was among the lowest recorded in the study, and those who were more familiar with genetics and held views of genetic exceptionalism were more likely to donate data. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Italian respondents were willing to share DNA and health information with entities except for-profit researchers and generally did not trust institutions beyond their own doctors. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) A similar survey addressing the Italian public highlighted geographical differences in the public\u0026rsquo;s knowledge and attitudes toward personalized medicine. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Research in Hungary revealed mixed attitudes toward genetic testing, with access to physician consultation positively influencing attitudes. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) A higher self-determined genetic familiarity score was associated with a greater willingness to participate in genetic testing, though medical professionals were more skeptical. In 2020, a systematic review updated the literature on citizens' perspectives toward direct-to-consumer genetic tests (DTC-GTs) in several European countries. It showed that European citizens generally had low awareness levels and a high interest in DTC-GTs, mainly for understanding disease risk predisposition. Concerns about test validity, utility, and data privacy were also highlighted. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study aimed to gather comprehensive data to evaluate the level of knowledge and attitudes among the EU public on aspects of personalized medicine. We also sought to explore public views and attitudes towards genetic testing and various forms of health data sharing, such as electronic health records and data generated by health apps, identifying potential knowledge gaps and areas of improvement. Considering the previous evidence, our survey targeted a broad audience in the European Union. The present survey addresses points covered by previous surveys at a national level with an EU-wide perspective while further exploring the factors influencing the public\u0026rsquo;s attitudes towards health data sharing previously investigated at a multi-country level. Moreover, we built indicators to summarize and analyze the correlation between knowledge levels, support towards implementing genetic testing in the healthcare system, and the respondents\u0026rsquo; willingness to share health data. The latter point has not previously been addressed in the literature. It provides valuable insights for researchers and policymakers to enact actions to stimulate the adoption of personalized medicine and related modern medical paradigms.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe developed a web-based questionnaire comprising 37 questions distributed across four main modules: Module A, addressing knowledge and attitudes about personalized medicine (PM); Module B, exploring genomic and health data sharing and use; Module C, focusing on governance; and Module D, assessing the needs of the users. The complete questionnaire is available in the Supplementary Material. Researchers agreed to contract the private company YouGov to distribute the survey on their platform. YouGov is a global public opinion and data company whose platform complies with the highest standards for quality and research while ensuring participant privacy. YouGov's methodology complies with GDPR standards and is detailed on their website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://yougov.co.uk/about/panel-methodology\u003c/span\u003e\u003cspan address=\"https://yougov.co.uk/about/panel-methodology\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The survey distribution lasted approximately two weeks during April 2023. Respondents were invited to participate in a YouGov survey based on their demographic information, reflecting their country\u0026rsquo;s population distribution by gender, age, and education level. The survey distribution polling system collected gender, age, country of origin, and education before respondents participated in the survey. Detailed information concerning the survey design and delivery methods is available in the online preprint. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe method section below focuses on the data preprocessing and analysis for the stated objective.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection and analysis\u003c/h2\u003e \u003cp\u003eSurvey responses were collected in an electronic data sheet. Descriptive analyses were performed using absolute frequencies and percentages for categorical data and mean and standard deviation (SD) for continuous data. An analysis of determinants of knowledge, attitudes, and willingness to support personalized medicine was carried out by developing multivariable logistic regression models using the strategy outlined by Hosmer and Lemeshow. Following the methodology previously employed in similar surveys (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), we created new compound variables to measure respondents\u0026rsquo; knowledge of personalized medicine, support for implementing genetic testing in healthcare, and willingness to share health and genetic data. A detailed summary of the three compound variables is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe variables were built as follows: different survey questions were assigned scores based on respondents' answers, and new variables were then derived from the responses to some of these questions.\u003c/p\u003e \u003cp\u003eThe \u0026ldquo;Compound knowledge of Personalized Medicine\u0026rdquo; indicator was built upon question 1 (score 0\u0026ndash;3 points, depending on how many terms the respondents knew before the survey), question 3 (0\u0026ndash;7 points, depending on how many uses of genetic testing respondents knew before the survey), question 7 (score 0\u0026ndash;1 points depending on whether participants were already aware of health/patient portals before the survey) and question 28 (score 0\u0026ndash;1 points depending on participants\u0026rsquo; perceived knowledge of personalized medicine, with 1 point to those responding \u0026ldquo;Definitely\u0026rdquo; or \u0026ldquo;Somewhat\u0026rdquo;), with a maximum achievable indicator value of 12. If the indicator value was \u0026ge;\u0026thinsp;9/12 (75%), respondents were considered to have a high knowledge level; otherwise, they were considered to have a low knowledge level.\u003c/p\u003e \u003cp\u003eThe indicator \u0026ldquo;Compound support of genetic testing implementation in healthcare\u0026rdquo; was built upon question 4 (score 0\u0026ndash;5 points, where 1 point was considered for each option where respondents chose \u0026ldquo;I would support the test being made available by the health care system of my country, and I would consider taking such test\u0026rdquo; or \u0026ldquo;I would support the test being made available by the health care system of my country, but I would NOT consider taking such test\u0026rdquo;). If the indicator value was \u0026ge;\u0026thinsp;4/5 (80%), respondents were considered to show support; otherwise, they showed no support.\u003c/p\u003e \u003cp\u003eThe \u0026ldquo;Compound willingness to health and genetic data sharing\u0026rdquo; indicator was built upon questions 8 and 9. Respondents were classified as showing willingness if they answered: \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to both question 8 and question 9, \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to question 8 and \u0026ldquo;Would share for research on a disease running in my family\u0026rdquo; to question 9, \u0026ldquo;Would share if reassurances are granted\u0026ldquo; to question 8 and \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to question 9. They were deemed unwilling to share health and genetic data for any other combination.\u003c/p\u003e \u003cp\u003eCovariates included in the models were gender, age, geographical region, and education (with not-achieved tertiary education as a reference category). The geographical area was categorized as follows: Eastern Europe (Poland, Hungary, and Romania), Southern Europe (Italy and Spain), and Central Europe (the Netherlands, Germany, and France), with Central Europe as the reference category. Each variable was examined by univariable analysis and was included in the multivariable logistic model when the P value was \u0026lt;\u0026thinsp;0.15. The influence of the independent variables on each binary outcome investigated was expressed as odds ratios (ORs) and 95% confidence interval (CI). The new binary variables representing knowledge, support, and willingness to share were mutually tested as covariates to assess dependence. Statistical significance was set at a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The statistical analysis was performed using STATA 18.0 software (Stata Corporation, College Station, TX, USA). Ethical approval for this study was obtained from the Policlinico Universitario \u0026lsquo;Agostino Gemelli\u0026rsquo; Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDemographics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports the demographic profile of the survey respondents. Out of the 6,581 respondents, 52.5% were female (n\u0026thinsp;=\u0026thinsp;3,458). The age of the respondents ranged from 18 to 89 years (mean\u0026thinsp;=\u0026thinsp;48.5 years, median\u0026thinsp;=\u0026thinsp;49 years, SD\u0026thinsp;=\u0026thinsp;15.96).\u003c/p\u003e \u003cp\u003eThe survey included 6,581 respondents from 8 countries across different European regions. Central Europe, which includes France, Germany, and the Netherlands, represented the most significant proportion with 46.03% of respondents (n\u0026thinsp;=\u0026thinsp;3,029); Eastern Europe, comprising Hungary, Poland, and Romania, made up 23.20% of the sample (n\u0026thinsp;=\u0026thinsp;1,527), while Southern Europe, represented by Italy and Spain, accounted for 30.77% of respondents (n\u0026thinsp;=\u0026thinsp;2,025).\u003c/p\u003e \u003cp\u003eThe participants displayed diverse educational backgrounds. Approximately 37.91% of the participants reported achieving tertiary education (n\u0026thinsp;=\u0026thinsp;2,495), whereas a significant majority, constituting 62.09%, indicated that they had not pursued tertiary education (n\u0026thinsp;=\u0026thinsp;4,086).\u003c/p\u003e \u003cp\u003e \u003cem\u003eKnowledge and awareness of citizens regarding key medical advancements and personalized medicine.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis section delves into citizens' knowledge and awareness regarding key medical advancements and concepts, including personalized medicine, Big data, genetic testing, and related applications (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOf the respondents, 47.76% (n\u0026thinsp;=\u0026thinsp;3,143) reported being aware of personalized medicine; 37.03% (n\u0026thinsp;=\u0026thinsp;2,437) had heard about Big data, and 80.53% (n\u0026thinsp;=\u0026thinsp;5,300) were familiar with genetic testing.\u003c/p\u003e \u003cp\u003eAmong the latter familiar with genetic testing, slightly more than half knew about prenatal testing (50.85%, n\u0026thinsp;=\u0026thinsp;2,695) and risk assessment of passing a disease to the offspring (55.62%, n\u0026thinsp;=\u0026thinsp;2,948). A majority were unaware of its use in treatment choices (64.34%, n\u0026thinsp;=\u0026thinsp;3,410), disease diagnosis (51.83%, n\u0026thinsp;=\u0026thinsp;2,747), drug assessment or pharmacogenomics (78.70%, n\u0026thinsp;=\u0026thinsp;4,171), and risk assessment for disease (51.26%, n\u0026thinsp;=\u0026thinsp;2,717), as well as of the existence of heel prick testing for newborns (64.06%, n\u0026thinsp;=\u0026thinsp;3,395).\u003c/p\u003e \u003cp\u003eIn addition, over half of all survey respondents (54.3%, n\u0026thinsp;=\u0026thinsp;3,573) were aware of health/patient portals, indicating a notable familiarity with digital healthcare platforms.\u003c/p\u003e \u003cp\u003eA small proportion felt they had \u0026ldquo;definitely\u0026rdquo; adequate knowledge (4.42%, n\u0026thinsp;=\u0026thinsp;291), while a more significant percentage felt \u0026ldquo;somewhat\u0026rdquo; knowledgeable (21.81%, n\u0026thinsp;=\u0026thinsp;1,435). Conversely, a considerable portion expressed limited knowledge, with 41.95% (n\u0026thinsp;=\u0026thinsp;2,761) feeling \u0026ldquo;not really\u0026rdquo; knowledgeable and 23.34% (n\u0026thinsp;=\u0026thinsp;1,536) feeling \u0026ldquo;not at all\u0026rdquo; knowledgeable. Additionally, 8.48% (n\u0026thinsp;=\u0026thinsp;558) were uncertain about their level of understanding.\u003c/p\u003e \u003cp\u003eThe compound knowledge level for participants was high (\u0026ge;\u0026thinsp;9/12) for 12.11% of participants (n\u0026thinsp;=\u0026thinsp;797) and low (\u0026le;\u0026thinsp;8/12) for most of them (n\u0026thinsp;=\u0026thinsp;5,784).\u003c/p\u003e \u003cp\u003e \u003cem\u003eAttitudes towards support for Genetic Testing Availability within the Healthcare System and Willingness to Undergo Testing.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn this section, we explore the level of support for the integration of genetic testing into the healthcare system, as well as the willingness of respondents to undergo such testing for various purposes, given its availability at a low cost (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen considering a diagnosis for a serious genetic disease, most respondents (72.19%, n\u0026thinsp;=\u0026thinsp;4,751) expressed support for such a test offered by the healthcare system while also being inclined to undergo such testing themselves. A smaller fraction (15.04%, n\u0026thinsp;=\u0026thinsp;990) supported the availability of the test, albeit opted not to undergo the procedure personally. Similarly, concerning the assessment of predisposition or risk for the development of specific diseases in the future, 67.68% (n\u0026thinsp;=\u0026thinsp;4,454) of respondents were in favor of offering genetic testing within the healthcare system and indicated a willingness to undergo the test personally, while 16.62% (n\u0026thinsp;=\u0026thinsp;1,094) favored the availability of the test but opted not to undergo testing themselves. When considering the selection of the most effective or least risky treatment, 70.57% (n\u0026thinsp;=\u0026thinsp;4,644) of respondents advocated for genetic testing being offered in healthcare for this purpose and were inclined to undergo such testing personally. A smaller portion (14.51%, n\u0026thinsp;=\u0026thinsp;955) supported the availability of the test but would choose not to undergo testing themselves.\u003c/p\u003e \u003cp\u003eIn the context of family planning and reproductive health, 64.85% (n\u0026thinsp;=\u0026thinsp;4,268) of respondents supported the availability of genetic testing to assess the risk of transmitting predispositions for specific diseases to future generations and expressed a willingness to undergo this testing. A fraction (18.46%, n\u0026thinsp;=\u0026thinsp;1,215) supported the test availability but chose not to take it personally.\u003c/p\u003e \u003cp\u003eSimilarly, during pregnancy for diagnosing or assessing the risk of serious diseases in the fetus, a substantial 65.52% (n\u0026thinsp;=\u0026thinsp;4,312) of respondents supported the genetic testing being offered within the healthcare system for this purpose and were willing to be personally tested. Another 17.55% (n\u0026thinsp;=\u0026thinsp;1,155) supported the availability of the test but preferred not to be tested themselves.\u003c/p\u003e \u003cp\u003eThe compound support level for participants was high (\u0026ge;\u0026thinsp;4/5) for a large majority of participants (81.52%, n\u0026thinsp;=\u0026thinsp;5,365) and low (\u0026le;\u0026thinsp;3/5) for 18.48% of them (n\u0026thinsp;=\u0026thinsp;1,216).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eWillingness to Share Health Data and Genomic Information for Medical Research\u003c/h2\u003e \u003cp\u003eThis section explores respondents' perspectives regarding sharing general health information and genomic data (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding sharing health data from their healthcare record, 47.74% (n\u0026thinsp;=\u0026thinsp;3,142) expressed a willingness to share their health information for the benefit of others. Additionally, 19.86% (n\u0026thinsp;=\u0026thinsp;1,307) indicated their willingness to share data for research on diseases affecting themselves or their families. 8.13% of respondents (n\u0026thinsp;=\u0026thinsp;535) would share their health data, excluding genomic information. Conversely, some respondents exhibited hesitancy: 12.58% (n\u0026thinsp;=\u0026thinsp;828) of participants were unwilling to share their health data, while 11.69% (n\u0026thinsp;=\u0026thinsp;769) remained uncertain.\u003c/p\u003e \u003cp\u003eThe perspectives were diverse when focusing on genomic data sharing with biobanks. A total of 30.34% (n\u0026thinsp;=\u0026thinsp;1,997) of respondents expressed a willingness to share their genomic data for the benefit of others, while 30.76% (n\u0026thinsp;=\u0026thinsp;2,024) would share if they received reassurance. 8.97% (n\u0026thinsp;=\u0026thinsp;590) would consider sharing if monetarily compensated. However, a notable portion of respondents expressed reluctance towards genomic data sharing. Approximately 14.37% (n\u0026thinsp;=\u0026thinsp;946) indicated an unwillingness to share their genomic data, while 15.56% (n\u0026thinsp;=\u0026thinsp;1,024) remained uncertain about their stance on this matter. Overall, 52.35% (n\u0026thinsp;=\u0026thinsp;3,445) showed a willingness to data sharing, whereas 47.65% (n\u0026thinsp;=\u0026thinsp;3,136) did not.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003ePredictors of Higher Compound Knowledge Level\u003c/h2\u003e \u003cp\u003eThe female gender (OR 1.40, 95% CI 1.20\u0026ndash;1.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and possessing a tertiary education (OR 2.06, 95% CI 1.77\u0026ndash;2.39, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were associated with a higher compound knowledge. Respondents from Southern Europe exhibited a superior level of knowledge compared to Centrale Europe (OR 1.25, 95% CI 1.05\u0026ndash;1.48, p\u0026thinsp;=\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Support for the Availability of Genetic Tests in the Healthcare System\u003c/h2\u003e \u003cp\u003eThe female gender was associated with a positive inclination towards the availability of genetic tests (OR 1.40, 95% CI 1.23\u0026ndash;1.59, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Additionally, education and knowledge showed a positive association with the support for genetic testing availability. Respondents with tertiary education levels were more inclined to support the integration of genetic tests within the healthcare system (OR 1.48, 95% CI 1.29\u0026ndash;1.70, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with individuals possessing a higher level of knowledge displaying a significantly heightened likelihood of supporting the integration of genetic tests within the healthcare system (OR 4.08, 95% CI 2.97\u0026ndash;5.60, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). When Central Europe was used as the reference category, both Eastern Europe (OR 2.47, 95% CI 2.08\u0026ndash;2.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and Southern Europe (OR 2.85, 95% CI 2.42\u0026ndash;3.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) exhibited a higher likelihood of supporting the availability of genetic tests within the healthcare system (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Willingness to Share Health and Genomic Data\u003c/h2\u003e \u003cp\u003eAge exhibited a borderline positive association with the willingness to share health and genomic data (OR 1.015, 95% CI 1.011\u0026ndash;1.018, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The achievement of tertiary education emerged as a factor positively associated with the willingness to share data (OR 1.20, 95% CI 1.08\u0026ndash;1.33, p\u0026thinsp;\u0026gt;\u0026thinsp;0.0001), and individuals with a higher level of compound knowledge were more inclined to share their health and genomic information (OR 1.60, 95% CI 1.36\u0026ndash;1.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Additionally, individuals supporting the availability of genetic tests offered in the healthcare system were substantially more likely to share their health and genomic data (OR 5.30, 95% CI 4.46\u0026ndash;6.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eConsidering geographical variations and using Central Europe as the reference, both Eastern Europe and Southern Europe displayed a positive association with the willingness to share health and genomic data. Respondents from Eastern Europe (OR 1.32, 95% CI 1.16\u0026ndash;1.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and Southern Europe (OR 1.66, 95% CI 1.47\u0026ndash;1.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were more inclined to share their data (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eComponents of the compound indicators. In the Questions column, the italic number in brackets indicates the score assigned to each question.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuestions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound knowledge of personalized medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Do you think you have adequate knowledge about personalized medicine? \u003cem\u003e(0\u0026ndash;4)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u0026bull; Were you aware of the existence of health/patient portals prior to this survey? \u003cem\u003e(0\u0026ndash;1)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u0026bull; Which of the following had you ever heard about, prior to this survey? \u003cem\u003e(0\u0026ndash;3)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u0026bull; Which of the following uses of genetic testing for medical purposes have you ever heard about prior to this survey? \u003cem\u003e(0\u0026ndash;7)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe cut-off for high/low compound knowledge was set at 75%\u003c/p\u003e \u003cp\u003e- High knowledge if\u0026thinsp;\u0026ge;\u0026thinsp;9/12\u003c/p\u003e \u003cp\u003e- Low knowledge if\u0026thinsp;\u0026le;\u0026thinsp;8/12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound support of genetic testing implementation in healthcare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; If a genetic test were available at low cost, for what purposes you would support the test being offered by the health care system of your country, and would you consider having such testing? \u003cem\u003e(0\u0026ndash;5)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe cut-off for support (yes/no) was set at 80%.\u003c/p\u003e \u003cp\u003eSupport if\u0026thinsp;\u0026ge;\u0026thinsp;4/5\u003c/p\u003e \u003cp\u003eNo support if\u0026thinsp;\u0026le;\u0026thinsp;3/5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound willingness to data sharing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Would you share your personal genomic data with biobanks or research institutes?\u003c/p\u003e \u003cp\u003e\u0026bull; If people were given an option to share their data, would you be willing to share your data - including from any genetic tests - from your health care record or portal to benefit other patients or for medical research purposes?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes, if answered:\u003c/p\u003e \u003cp\u003e- \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to both Q1 and Q2\u003c/p\u003e \u003cp\u003e- \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to Q1 \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAND\u003c/span\u003e \u0026ldquo;Would share for research on a disease running in my family\u0026rdquo; to Q2\u003c/p\u003e \u003cp\u003e- \u0026ldquo;Would share if reassurances are granted\u0026ldquo; for Q1 \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAND\u003c/span\u003e \u0026ldquo;Would share for others\u0026rsquo; benefit\u0026rdquo; to Q2\u003c/p\u003e\u003cp\u003eNo, for any other combination.\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information of respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic information (N\u0026thinsp;=\u0026thinsp;6,581).\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;=\u0026thinsp;48.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u0026thinsp;=\u0026thinsp;16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAchieved tertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRomania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGeographic area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKnowledge and awareness of citizens regarding key medical advancements and personalized medicine.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonal knowledge (N\u0026thinsp;=\u0026thinsp;6,581).\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWhich of the following had you ever heard about, prior to this survey?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonalized Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBig data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenetic Testing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWhich of the following uses of genetic testing for medical purposes have you ever heard about prior to this survey?* (N\u0026thinsp;=\u0026thinsp;5,300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiagnosis of a disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssessment of risk to develop a specific disease, for the disease to be prevented or treated at an early stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChoice of the treatment for a disease (e.g. the choice of chemotherapy in case of cancer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssessment of a specific drug in a person (e.g. to avoid wrong dosage or adverse effects)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssessment of the risk of passing a genetic disease to future children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrenatal testing during pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeel prick of newborn baby to detect a genetic disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWere you aware of the existence of health/patient portals prior to this survey?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDo you think you have adequate knowledge about personalized medicine?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinitely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomewhat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot really\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompound knowledge Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (\u0026ge;\u0026thinsp;9/12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (\u0026le;\u0026thinsp;8/12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThis table only reports those who answered affirmatively to the questions asked. *only available to those who stated they knew about genetic testing; hence the total is 5300.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSupport for Genetic Testing Availability within the Healthcare System and Willingness to Undergo Testing.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSupport (N\u0026thinsp;=\u0026thinsp;6,581)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIf a genetic test were available at low cost, for what purposes you would support the test being offered by the health care system of your country, and would you consider having such testing?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTo diagnose a serious genetic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support the test being made available by the health care system of my country, and I would consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support being made available by the health care system of my country, but I would NOT consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI do not support the test being made available by the health care system of my country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTo assess the predisposition or risk for you to develop a specific disease in the future\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support the test being made available by the health care system of my country, and I would consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support being made available by the health care system of my country, but I would NOT consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI do not support the test being made available in by the health care system of my country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTo choose the most effective treatment or a treatment with the lowest risk of potential adverse effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support the test being made available by the health care system of my country, and I would consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support being made available by the health care system of my country, but I would NOT consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI do not support the test being made available in by the health care system of my country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBefore pregnancy, to assess the risk of future parents transmitting a predisposition for a specific disease to their future children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support the test being made available by the health care system of my country, and I would consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support being made available by the health care system of my country, but I would NOT consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI do not support the test being made available in by the health care system of my country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDuring pregnancy, to diagnose or assess the risk of a serious disease in the foetus?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support the test being made available by the health care system of my country, and I would consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would support being made available by the health care system of my country, but I would NOT consider taking such test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI do not support the test being made available in by the health care system of my country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompound support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes (\u0026ge;\u0026thinsp;4/5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo (\u0026le;\u0026thinsp;3/5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWillingness to Share Health Data and Genomic Information for Medical Research\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWillingness to Share Health Data and Genomic Information for Medical Research (N\u0026thinsp;=\u0026thinsp;6581)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIf people were given an option to share their data, would you be willing to share your data - including from any genetic tests - from your health care record or portal to benefit other patients or for medical research purposes?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, to help health care professionals interpret findings and diagnose other patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, but only to support research into a disease I or members in my family suffer from\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI would share health data with researchers, but not genetic data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo, I wouldn\u0026rsquo;t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWould you share your personal genomic data with biobanks or research institutes?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, for the sake of contributing to science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly provided some information are granted to me\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly provided I would be adequately compensated monetarily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo, I wouldn\u0026rsquo;t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWillingness to data sharing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of Higher Compound Knowledge Level, Support for the Availability of Genetic Tests in the Healthcare System, and Willingness to Share Health and Genomic Data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePredictors of Higher Compound Knowledge Level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplanatory variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40 (1.20\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.06 (1.77\u0026ndash;2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGeographical area (ref: Central Europe)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 (0.90\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25 (1.05\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePredictors of Support for the Availability of Genetic Tests in the Healthcare System\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplanatory variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40 (1.23\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.99\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.48 (1.29\u0026ndash;1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.08 (2.97\u0026ndash;5.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGeographical area (ref: Central Europe)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.47 (2.08\u0026ndash;2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85 (2.42\u0026ndash;3.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePredictors of Willingness to Share Health and Genomic Data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplanatory variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.015 (1.011\u0026ndash;1.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20 (1.08\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.60 (1.36\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.30 (4.46\u0026ndash;6.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGeographical area (ref: Central Europe)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (1.16\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66 (1.47\u0026ndash;1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn discussing the results of this survey, we highlight three key variables impacting the implementation of personalized medicine in health care: Knowledge and awareness, Support towards genetic testing implementation in the healthcare system, and Willingness to health data sharing.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eKnowledge and Awareness\u003c/h2\u003e \u003cp\u003eRespondents' knowledge about various aspects of personalized medicine differed strongly per concept. At the end of the survey, a considerable proportion of respondents expressed limited knowledge about personalized medicine, with 41.95% feeling \u0026ldquo;not really\u0026rdquo; knowledgeable and 23.34% feeling \u0026ldquo;not at all\u0026rdquo; knowledgeable. At the start of the survey, 47.76% of respondents had heard about personalized medicine, 37.03% about big data, and 80.53% about genetic testing. These results align with existing literature, reporting that the general public has limited knowledge of the more recent medical paradigms in omics sciences, nonetheless showing room for educational initiatives, following an overall positive attitude. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) Additionally, previous research investigating knowledge of personalized medicine and genetic testing focused on specific categories rather than the general public. Rosso et al. highlighted a general need to increase awareness of genomics among European public health professionals. It indicated that while there were positive attitudes towards genetic testing, there was a significant knowledge gap, even among those involved in public health genomics activities. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eGenetic testing has been around for a long time since the introduction of sickle-cell genetic testing approximately forty years ago (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), and the various applications of such testing were acknowledged by as high as 55.62% of respondents. Previous research suggests that communicating about aspects of personalized medicine benefits by building on concepts and applications that people are already familiar with. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSupport towards genetic testing implementation in the healthcare system\u003c/h2\u003e \u003cp\u003eOur findings indicate widespread acceptance and endorsement of integrating genetic testing into the healthcare system. The insights gathered shed light on the public's stance regarding incorporating genetic testing into the healthcare framework and their intention to undergo testing themselves. As we explored the available literature, no previous study investigated citizens\u0026rsquo; attitudes toward this theme. Nonetheless, a scoping review found that complete coverage of the cost of clinical genetic testing is not always available through public or private insurance programs, leading to financial barriers for patients who do not qualify for full coverage. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWe framed the question in a manner that assumed the genetic test would incur minimal expenses for the healthcare system or the patients themselves. This approach was designed to mitigate potential biases that might dissuade respondents from accepting the test's integration into their healthcare system due to cost-related concerns rather than any reservations about the test itself. However, nuanced variations in support exist, influenced by specific testing purposes.\u003c/p\u003e \u003cp\u003eRespondents supported genetic testing for diagnostics (72.19%) and pharmacogenomics (70,57%) while also considering undergoing such tests, while 15.04% and 14,51%, respectively, supported such an offer but indicated they would not take the test themselves. Another 67.68% supported offering testing to assess a predisposition or risk for the development of specific diseases, while 16.62% supported availability without considering having such testing themselves. These results indicate that a relevant share of respondents in the general public have some form of reservation against the uses of genetic testing in health care that would be most relevant for personalized medicine. This might be related to needing more knowledge of applications and potential benefits, as already addressed in scientific literature. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAmong the survey respondents, having more knowledge and higher education were associated with support for offering genetic testing. Potential knowledge gaps should be addressed in research and policymaking when further implementing promising applications. For some applications, e.g., to establish drug dose or compatibility, more routine testing may become feasible when evidence for pharmacogenomics increases and guidelines for, e.g., companion diagnostics are further developed. This may increase acceptability and is currently being researched for various applications. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) However, respondents may also have concerns or other considerations regarding genetic testing that need to be addressed to better tailor approaches to genetic testing implementation within healthcare frameworks. Especially regarding predisposition to disease, a discussion is ongoing, acknowledging that for some people, having prior knowledge would be seen as beneficial per se or because this would enable interventions, while others might prefer not to know whether they are at risk. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) Such decisions may also be influenced by the available interventions and their perceived burdens, while such interventions and preferences may also change over time. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) In clinical genetics practice, such questions would be addressed via extensive counseling of patients and their first-degree family members. However, as genetic information will play an increasingly important role in prevention and health care outside such clinical genetic settings, education and communication about the pros and cons of genetic testing will more generally need to be available before citizens fall ill. For many years, it has been suggested that genetic education be stimulated in secondary education. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) In recent years, new promising online tools have been developed that enable people to learn more about genetics in medicine, and such tools can also aid in optimizing giving information and counseling before more specific forms of testing. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) Similar initiatives dedicated to fostering genetic education and increasing awareness about genetic testing could prove to be particularly useful in improving the general public\u0026rsquo;s support of the implementation of genetic testing in healthcare by providing them with the tools and knowledge to understand better the genetic information they are handled and the related possibilities. Improving healthcare professionals\u0026rsquo; literacy and awareness is also crucial, as they are the gateway to the general public\u0026rsquo;s unaddressed needs. Healthcare professionals must make decisions based on complex biological, environmental, and lifestyle information and address patients\u0026rsquo; needs and inquiries. Ultimately, they positively impact previously unaddressed knowledge gaps and the needs of the general public. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWillingness to health data sharing\u003c/h2\u003e \u003cp\u003eOur results show that individuals with higher knowledge, education, and support for integrating genetic testing are more willing to share their data. This is consistent with what was previously highlighted in the literature. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAlso, in this case, better information provision and communication between healthcare providers and patients about the importance of data sharing may stimulate awareness and a more positive attitude toward data sharing. Recent research has shown that, in general, people are more willing to trust their health care provider or non-profit researchers in universities rather than commercial institutions, though public trust and willingness to donate differ per country. However, Savić-Kalles\u0026oslash;e et al. argue that their results \u0026ldquo;suggest that while public trust is significant, it may be neither necessary nor sufficient in influencing willingness to donate. Future research could do well to investigate how the importance of public trust compares in countries with lower public trust.\u0026rdquo; (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) A recent expert workshop for the Beyond 1\u0026nbsp;Million Genomics Initiative stressed that trust is contextual and relational and may also depend on national contingencies. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) In an increasingly international field of data sharing extending trust from such local or national conditions to European and potentially global research consortia, it underlines the significance of individuals' trust and belief in healthcare institutions regarding data sharing for research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGeographical differences\u003c/h2\u003e \u003cp\u003eEuropean perspectives on personalized medicine and data sharing highlight the importance of interoperability, willingness to share personal health data, and the challenges in achieving adequate data sharing across diverse populations. Our results indicate national and supranational differences regarding knowledge, support for integrating genetic testing in health care, and willingness to share health and genomic data. This is coherent with what was highlighted in the literature, providing additional information on previously unaddressed topics, such as citizens\u0026rsquo; support towards implementing genetic testing in their country\u0026rsquo;s healthcare system.\u003c/p\u003e \u003cp\u003eRespondents from the Southern European countries in our sample scored higher on knowledge; respondents from the Southern and Eastern European countries showed more support for offering genetic testing within their healthcare systems and willingness to share data than respondents from Central Europe. These findings align with what is retrieved in scientific literature, that individuals' trust and belief in the healthcare system may vary across countries and that it influences their attitudes towards novel medical paradigms and medical innovations, such as genetic testing and sharing their own health and genomic data. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) Although a similar supranational analysis is not found in the literature, similar articles highlight how specific populations display less favorable attitudes towards data sharing and adoption of genomics, such as the Your DNA Your Say analysis particular to the German people. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe variance in our sample emphasizes the role of geographical context in shaping perspectives on healthcare advancements, advocating for targeted strategies for integrating personalized prevention based on region and country-specific needs and possibilities. In this paper, we refrain from conducting national-level analyses, as our focus is on a broader examination of the European scenario. In other publications, we will delve deeper into country-specific manuscript features to provide a more nuanced and comprehensive understanding of the subject from national perspectives.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFuture perspectives\u003c/h2\u003e \u003cp\u003eThe results of our investigation shed light on the heterogeneous situation in the European Union towards personalized medicine and data sharing. Despite numerous positive indicators, this survey paints a scenario where the general public still needs to be made aware of available medical resources and the possibilities of novel medical advancements. This is particularly true when examining genetic testing and the applications investigated in this survey. Still, the pace at which medical advancements proceed makes it likely that other fields would also show similar outcomes. Furthermore, health data and genomic data sharing are essential to research in all healthcare and medical sciences fields, calling for increased responsibilities of the general public.\u003c/p\u003e \u003cp\u003eEuropean policymakers are active in addressing personalized medicine with legislation and directives. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) The importance of secondary use of health data is widely embraced in the European Union, where the European Commission oversees and coordinates the establishment of the European Health Data Space (EHDS) to ensure that generated health data is available to researchers and policymakers for secondary use in the future. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) Similarly, the One Million Genomes initiative aims to build a genomic data infrastructure to foster cross-border access and sharing of genomic information and related clinical data to be integrated with the EHDS. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) These initiatives address relevant issues, such as frameworks for adequate informed consent, data management, and privacy. Addressing citizens\u0026rsquo; concerns and stimulating further education and communication to establish responsible research practices will be particularly relevant to ensure these ambitious programs achieve their fullest potential. This would positively impact research and development of improved technologies and medical approaches, benefiting the European population by increasing health outcomes.\u003c/p\u003e \u003cp\u003eHowever, it should be noted that advocating for data sharing should be regarded as something other than an all-cost strategy. Patients might be defensive regarding susceptible data, such as health and genomic data. Increased transparency about who benefits from data access and providing the option to withdraw are crucial measures to increase trust in health data sharing, potentially having a positive impact on the adherence and sharing to genetic testing in the first place. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) Similarly, if they are reassured, patients and citizens might as well undergo genetic testing for research purposes out of altruism rather than to get results back. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eA patient-controlled approach to data sharing, where patients are in control of their biomedical and genetic data and can share it with healthcare providers and researchers, would be the ideal outcome for data sharing policies if patients are empowered to decide responsibly and freely about their health and the use that their data undergoes. Such patient engagement would promote data sharing across health organizations for clinical care purposes and contribution to research databases. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe results of this survey aim to lay the foundations for future education and communication activities to improve the general public\u0026rsquo;s attitudes towards personalized medicine and data sharing. The survey was distributed using a professional polling system to ensure that the considered sample represents the general population regarding age, gender, and education level. Nonetheless, this survey\u0026rsquo;s results should be regarded in light of some limitations.\u003c/p\u003e \u003cp\u003eDespite covering a considerable majority of EU citizens, it should be noted that we only distributed our survey in 8 out of 27 countries. In addition, the sampling between different countries did not consider the countries\u0026rsquo; population count, possibly introducing bias related to unequal sampling ratios following varying sample size ratios to population size.\u003c/p\u003e \u003cp\u003eWhen detailing the statistical analysis, geographical bias should be considered due to the clustering of different countries in the same geographical area. Results related to one geographical area should be distinct from the countries involved (e.g., Italy and Spain might display opposite outcomes, which are masked by each other when merged as Southern Europe in the logistic regression models).\u003c/p\u003e \u003cp\u003eDespite providing a relevant outlook on the factors influencing the general public\u0026rsquo;s knowledge of personalized medicine, support that genetic testing is implemented in healthcare, and willingness to data sharing, it should be noted that these are complex factors influenced by several variables. With this in mind, our analysis should not be deemed exhaustive but rather as the foundation of future research in this field.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this survey reveal a complex landscape of knowledge, attitudes, and willingness to engage in personalized medicine and health data sharing within the EU. While there is broad support for genetic testing and a recognition of its potential benefits, substantial gaps in knowledge and varying levels of trust in data-sharing practices exist. These disparities underscore the necessity for targeted educational and communicative efforts to bridge these gaps. Initiatives like the European Health Data Space and the One Million Genomes initiative are crucial in promoting secure and responsible data sharing for advancing personalized medicine, improving health outcomes, and encouraging progress in research. However, such initiatives should be accompanied by public and patient-centric approaches and transparency in health data usage to gain public trust and participation. Future efforts should prioritize target interventions to increase general understanding of personalized medicine, including health data sharing, to fully realize its potential in improving healthcare outcomes across the EU.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the respondents to the survey who took the time to answer the questions on personalized medicine. We thank the Italian Ministry of Health for supporting the activities of the National Center for Disease Prevention and Control (CCM) projects related to genomics and omics sciences, including implementing our survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey is part of the \u0026ldquo;European network staff eXchange for integrating precision health in the Health Care Systems\u0026rdquo; (ExACT) project, supported by the European Union\u0026rsquo;s Horizon 2020 research and innovation program under the RISE Marie Curie Actions, under grant agreement n. 823995. This survey contributes to a project funded by the Italian Center for Disease Prevention and Control of the Ministry of Health (CCM2021, CUP B85F21004970001), which focuses on creating the Italian Genomic Strategy and providing national backing for the European initiatives 1+Million Genomes (1+MG) and Beyond 1+Million Genomes (B1MG).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;1. Please provide a Consent to Participate declaration in the manuscript. Every human participant should provide their consent: Participants were asked to participate in the study before accessing the questionnaire. The first page of the Supplementary Material includes the introduction provided to the participants before they joined. Upon clicking the \u0026ldquo;Please click here to continue\u0026rdquo; button, participants had access to the questionnnaire;\u003c/p\u003e\n\u003cp\u003e2. Human Ethics and Consent to Participate declarations:\u0026nbsp;Ethical approval for this study was obtained from the Policlinico Universitario \u0026lsquo;Agostino Gemelli\u0026rsquo; Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214);\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp;Competing Interests: No, I declare that the authors have no competing interests as defined by BMC, or other interests that might be perceived to influence the results and/or discussion reported in this paper;\u003c/p\u003e\n\u003cp\u003e4.1. Ethics approval and consent to participate: Ethical approval for this study was obtained from the Policlinico Universitario \u0026lsquo;Agostino Gemelli\u0026rsquo; Ethics Committee, Rome (ID 5047) and Amsterdam UMC (reference 2022.0214);\u003c/p\u003e\n\u003cp\u003e4.2. Consent for publication: I confirm that I understand BMC Public Health is an open access journal that levies an article processing charge per articles accepted for publication. By submitting my article I agree to pay this charge in full if my article is accepted for publication;\u003c/p\u003e\n\u003cp\u003e4.3. Availability of data and materials: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e4.4. Competing Interests: No, I declare that the authors have no competing interests as defined by BMC, or other interests that might be perceived to influence the results and/or discussion reported in this paper;\u003c/p\u003e\n\u003cp\u003e4.5. Funding:\u0026nbsp;The survey is part of the \u0026ldquo;European network staff eXchange for integrating precision health in the Health Care Systems\u0026rdquo; (ExACT) project, supported by the European Union\u0026rsquo;s Horizon 2020 research and innovation program under the RISE Marie Curie Actions, under grant agreement n. 823995. This survey contributes to a project funded by the Italian Center for Disease Prevention and Control of the Ministry of Health (CCM2021, CUP B85F21004970001), which focuses on creating the Italian Genomic Strategy and providing national backing for the European initiatives 1+Million Genomes (1+MG) and Beyond 1+Million Genomes (B1MG);\u003c/p\u003e\n\u003cp\u003e4.6. Authors\u0026apos; contributions: Substantial contributions to the conception and design of the work: F.A.C., C.V.E.; R.P.; L.L.K.; Drafting the work or revising it critically for important content: All authors; Prepared supplementary material: F.A.C.; Final approval of the version to be published: C.V.E., S.B., R.P., G.E.C;\u003c/p\u003e\n\u003cp\u003e4.7. Acknowledgements: We thank the respondents to the survey who took the time to answer the questions on personalized medicine. We thank the Italian Ministry of Health for supporting the activities of the National Center for Disease Prevention and Control (CCM) projects related to genomics and omics sciences, including implementing our survey;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4.8. Authors\u0026apos; information (optional)\u003c/p\u003e\n\u003cp\u003e5. Availability of Data and Materials: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e5.2. The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Corresponding Author: [email protected].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEtchegary H, Wilson B. Bringing personalized medicine to the community through public engagement. Per Med. 2013;10(7):647-59.\u003c/li\u003e\n\u003cli\u003eGrande D, Mitra N, Shah A, Wan F, Asch DA. Public preferences about secondary uses of electronic health information. JAMA Intern Med. 2013;173(19):1798-806.\u003c/li\u003e\n\u003cli\u003eLiang X, Zhao J, Shetty S, Liu J, Li D, editors. Integrating blockchain for data sharing and collaboration in mobile healthcare applications. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC); 2017 8-13 Oct. 2017.\u003c/li\u003e\n\u003cli\u003eKim KK, Joseph JG, Ohno-Machado L. Comparison of consumers\u0026apos; views on electronic data sharing for healthcare and research. J Am Med Inform Assoc. 2015;22(4):821-30.\u003c/li\u003e\n\u003cli\u003eLock K. Health impact assessment: assessing opportunities and barriers to intersectoral health improvement in an expanded European Union. Journal of Epidemiology \u0026amp;amp; Community Health. 2005;59(5):356-60.\u003c/li\u003e\n\u003cli\u003eMiddleton A, Niemiec E, Prainsack B, Bobe J, Farley L, Steed C, et al. \u0026lsquo;Your DNA, Your Say\u0026rsquo;: global survey gathering attitudes toward genomics: design, delivery and methods. Personalized Medicine. 2018;15(4):311-8.\u003c/li\u003e\n\u003cli\u003eVoigt TH, Holtz V, Niemiec E, Howard HC, Middleton A, Prainsack B. Willingness to donate genomic and other medical data: results from Germany. Eur J Hum Genet. 2020;28(8):1000-9.\u003c/li\u003e\n\u003cli\u003eRomano V, Milne R, Mascalzoni D. Italian public\u0026apos;s views on sharing genetic information and medical information: findings from the \u0026apos;Your DNA, Your Say\u0026apos; study. Wellcome Open Res. 2021;6:180.\u003c/li\u003e\n\u003cli\u003eCalabr\u0026ograve; GE, Causio FA, Pires Marafon D, Sassano M, Moccia F, Pastorino R, et al. Public attitudes, knowledge and educational needs toward genetic testing and omics sciences: a pilot survey conducted in Italy. Eur J Public Health. 2023.\u003c/li\u003e\n\u003cli\u003eBalicza P, Terebessy A, Grosz Z, Varga NA, Gal A, Fekete BA, et al. Implementation of personalized medicine in Central-Eastern Europe: pitfalls and potentials based on citizen\u0026rsquo;s attitude. EPMA Journal. 2018;9(1):103-12.\u003c/li\u003e\n\u003cli\u003eHoxhaj I, Stojanovic J, Boccia S. European citizens\u0026apos; perspectives on direct-to-consumer genetic testing: an updated systematic review. Eur J Public Health. 2020.\u003c/li\u003e\n\u003cli\u003eCausio FA, Beccia F, Kreeftenberg LL, Calabro GE, Pastorino R, Boccia S, et al. European Survey on Citizens\u0026apos; Attitudes towards Personalized Medicine, Genetic Testing, and Health Data Sharing: Design and Delivery. medRxiv. 2024:2024.02.02.24302142.\u003c/li\u003e\n\u003cli\u003eBeccia F, Hoxhaj I, Sassano M, Stojanovic J, Acampora A, Pastorino R, et al. Survey of Professionals of the European Public Health Association (EUPHA) towards Direct-to-Consumer Genetic Testing. Eur J Public Health. 2023;33(1):139-45.\u003c/li\u003e\n\u003cli\u003eVillani L, Pastorino R, Molinari E, Anelli F, Ricciardi W, Graffigna G, et al. Impact of the COVID-19 pandemic on psychological well-being of students in an Italian university: a web-based cross-sectional survey. Globalization and Health. 2021;17(1):39.\u003c/li\u003e\n\u003cli\u003eRosso A, Pitini E, D\u0026apos;Andrea E, Di Marco M, Unim B, Baccolini V, et al. Genomics knowledge and attitudes among European public health professionals: Results of a cross-sectional survey. PLoS One. 2020;15(4):e0230749.\u003c/li\u003e\n\u003cli\u003eCalabr\u0026ograve; GE, Sassano M, Tognetto A, Boccia S. Citizens\u0026apos; Attitudes, Knowledge, and Educational Needs in the Field of Omics Sciences: A Systematic Literature Review. Frontiers in Genetics. 2020;11.\u003c/li\u003e\n\u003cli\u003eScott S, Abul-Husn N, Owusu Obeng A, Sanderson S, Gottesman O. Implementation and utilization of genetic testing in personalized medicine. Pharmacogenomics and Personalized Medicine. 2014:227.\u003c/li\u003e\n\u003cli\u003eCalabro GE, Sassano M, Boccia S. Citizens\u0026apos; Literacy in Genomics: A Delphi Survey of Multidisciplinary Experts in the Field. Genes (Basel). 2022;13(3).\u003c/li\u003e\n\u003cli\u003eSassano M, Calabro GE, Boccia S. A Web Screening on Educational Initiatives to Increase Citizens\u0026apos; Literacy on Genomics and Genetics. Front Genet. 2021;12:637438.\u003c/li\u003e\n\u003cli\u003eGrant P, Langlois S, Lynd LD, Austin JC, Elliott AM. Out-of-pocket and private pay in clinical genetic testing: A scoping review. Clin Genet. 2021;100(5):504-21.\u003c/li\u003e\n\u003cli\u003eYanes T, Willis AM, Meiser B, Tucker KM, Best M. Psychosocial and behavioral outcomes of genomic testing in cancer: a systematic review. Eur J Hum Genet. 2019;27(1):28-35.\u003c/li\u003e\n\u003cli\u003ePeruzzi E, Roncato R, De Mattia E, Bignucolo A, Swen JJ, Guchelaar H-J, et al. Implementation of preemptive testing of a pharmacogenomic panel in clinical practice: Where do we stand? British Journal of Clinical Pharmacology.n/a(n/a).\u003c/li\u003e\n\u003cli\u003eMartens FK, Huntjens DW, Rigter T, Bartels M, Bet PM, Cornel MC. DPD Testing Before Treatment With Fluoropyrimidines in the Amsterdam UMCs: An Evaluation of Current Pharmacogenetic Practice. Frontiers in Pharmacology. 2020;10.\u003c/li\u003e\n\u003cli\u003eLupo PJ, Robinson JO, Diamond PM, Jamal L, Danysh HE, Blumenthal-Barby J, et al. Patients\u0026apos; perceived utility of whole-genome sequencing for their healthcare: findings from the MedSeq project. Per Med. 2016;13(1):13-20.\u003c/li\u003e\n\u003cli\u003eMighton C, Carlsson L, Clausen M, Casalino S, Shickh S, McCuaig L, et al. Development of patient \u0026quot;profiles\u0026quot; to tailor counseling for incidental genomic sequencing results. Eur J Hum Genet. 2019;27(7):1008-17.\u003c/li\u003e\n\u003cli\u003eWarne RT. Are you ready for the genetic revolution in education? Phi Delta Kappan. 2021;103(2):34-9.\u003c/li\u003e\n\u003cli\u003eRayes N, Bowen DJ, Coffin T, Nebgen D, Peterson C, Munsell MF, et al. MAGENTA (Making Genetic testing accessible): a prospective randomized controlled trial comparing online genetic education and telephone genetic counseling for hereditary cancer genetic testing. BMC Cancer. 2019;19(1):648.\u003c/li\u003e\n\u003cli\u003eShickh S, Hirjikaka D, Clausen M, Kodida R, Mighton C, Reble E, et al. Genetics Adviser: a protocol for a mixed-methods randomised controlled trial evaluating a digital platform for genetics service delivery. BMJ Open. 2022;12(4):e060899.\u003c/li\u003e\n\u003cli\u003eRicciardi W, Boccia S. New challenges of public health: bringing the future of personalised healthcare into focus. Eur J Public Health. 2017;27(suppl_4):36-9.\u003c/li\u003e\n\u003cli\u003eSavi?-Kalles\u0026macr;e S, Middleton A, Milne R. Public trust and genomic medicine in Canada and the UK [version 2; peer review: 3 approved]. Wellcome Open Research. 2021;6(124).\u003c/li\u003e\n\u003cli\u003eMaria F\u0026aacute;tima Lopes AM, Alexandra Costa X, Perez ML, Cardoso M, Konopko M, Bourbon S, et al. Genomics in Healthcare - Key issues for implementation. 2021.\u003c/li\u003e\n\u003cli\u003eKalkman S, Delden Jv, Banerjee A, Tyl B, Mostert M, Thiel Gv. Patients\u0026rsquo; and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. Journal of Medical Ethics. 2022;48(1):3-13.\u003c/li\u003e\n\u003cli\u003eBiasiotto R, Viberg Johansson J, Alemu MB, Romano V, Bentzen HB, Kaye J, et al. Public Preferences for Digital Health Data Sharing: Discrete Choice Experiment Study in 12 European Countries. J Med Internet Res. 2023;25:e47066.\u003c/li\u003e\n\u003cli\u003eVoigt TH, Holtz V, Niemiec E, Howard HC, Middleton A, Prainsack B. Willingness to donate genomic and other medical data: results from Germany. European Journal of Human Genetics. 2020;28(8):1000-9.\u003c/li\u003e\n\u003cli\u003eCausio FA, Hoxhaj I, Beccia F, Marcantonio MD, Stroh\u0026auml;ker T, Cadeddu C, et al. Big data and ICT solutions in the European Union and in China: A comparative analysis of policies in personalized medicine. Digit Health. 2022;8:20552076221129060.\u003c/li\u003e\n\u003cli\u003eBeccia F, Hoxhaj I, Castagna C, Stroh\u0026auml;ker T, Cadeddu C, Ricciardi W, et al. An overview of Personalized Medicine landscape and policies in the European Union. European Journal of Public Health. 2022;32(6):844-51.\u003c/li\u003e\n\u003cli\u003eCascini F, Santaroni F, Lanzetti R, Failla G, Gentili A, Ricciardi W. Developing a Data-Driven Approach in Order to Improve the Safety and Quality of Patient Care. Front Public Health. 2021;9:667819.\u003c/li\u003e\n\u003cli\u003eSaunders G, Baudis M, Becker R, Beltran S, B\u0026eacute;roud C, Birney E, et al. Leveraging European infrastructures to access 1 million human genomes by 2022. Nat Rev Genet. 2019;20(11):693-701.\u003c/li\u003e\n\u003cli\u003eMilne R, Morley KI, Almarri MA, Atutornu J, Baranova EE, Bevan P, et al. Return of genomic results does not motivate intent to participate in research for all: Perspectives across 22 countries. Genet Med. 2022;24(5):1120-9.\u003c/li\u003e\n\u003cli\u003eMilne R, Morley KI, Almarri MA, Anwer S, Atutornu J, Baranova EE, et al. Demonstrating trustworthiness when collecting and sharing genomic data: public views across 22 countries. Genome Medicine. 2021;13(1):92.\u003c/li\u003e\n\u003cli\u003eMiller KE, Lin SM. Addressing a patient-controlled approach for genomic data sharing. Genetics in Medicine. 2017;19(11):1280-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3960901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3960901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePersonalized medicine, leveraging genetic, environmental, and lifestyle data, has transformed healthcare by tailoring prevention, diagnosis, and treatment to individual patients. The successful implementation of personalized approaches relies on the public's awareness and proficiency in personalized medicine, enabling access to innovative techniques and fostering a willingness to share health-related data. During two weeks in April 2023, we distributed an online survey to 6,581 respondents from 8 EU countries, including France, Germany, the Netherlands, Italy, Spain, Poland, Hungary, and Romania. The survey investigated the general public\u0026rsquo;s knowledge of personalized medicine, support for implementing genetic testing in their healthcare system, and willingness to share health data. We built three indicators from survey questions and investigated their association with each other and the respondent\u0026rsquo;s gender, age, geographical area of origin, and education level. 52.5% of respondents were female (n\u0026thinsp;=\u0026thinsp;3,458), with a mean age of 48.5 years (range 18\u0026ndash;89 years, median\u0026thinsp;=\u0026thinsp;49 years, SD\u0026thinsp;=\u0026thinsp;15.96), and 37.91% of the participants reported achieving tertiary education. 12.11% of respondents had a high compound knowledge of the topics. Knowledge levels, however, vary among the included countries (highest in the Netherlands at 18.87%, lowest in France at 7.44%). 81.5%, instead, supported the implementation of diagnostic or therapeutic applications of genetic testing in their healthcare systems, and nuanced differences in acceptance were observed based on testing purposes. Over half of the respondents (52.35%) reported willingness to share health data for altruistic use. Both support for implementing genetic testing and the desire to share health data correlated positively with knowledge and education levels. Geographical differences within the EU highlighted variations in attitudes toward personalized medicine and data sharing, with respondents from Southern Europe displaying higher odds than their peers in Central and Eastern Europe. The results emphasize the need for targeted communication and education strategies to enhance public understanding and trust in personalized medicine and health data sharing.\u003c/p\u003e","manuscriptTitle":"Knowledge and Attitudes of Personalized Medicine, Genetic Testing, and Health Data Sharing: A Comprehensive Survey in the general public of the European Union","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-12 17:31:07","doi":"10.21203/rs.3.rs-3960901/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e83a09f6-aeb7-4d8c-b888-fb00ff088c94","owner":[],"postedDate":"March 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-14T10:27:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-12 17:31:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3960901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3960901","identity":"rs-3960901","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}