Benefits and Risks of Sharing Genomic Data for Research: Comparing the Views of Rare Disease Patients, Informal Carers and Healthcare Professionals
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants and Procedure
2.2. Data Collection
2.3. Data Analysis
3. Results
3.1. Benefits and Risks of Sharing Genetic Information
3.2. Factors Associated with the Selection of Benefits and Risks of Sharing Genetic Information
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Clayton, E.W.; Halverson, C.M.; Sathe, N.A.; Malin, B.A. A systematic literature review of individuals’ perspectives on privacy and genetic information in the United States. PLoS ONE 2018, 13, e0204417. [Google Scholar] [CrossRef] [PubMed]
- Heath, D.; Ardestani, A.; Nemati, H. Sharing personal genetic information: The impact of privacy concern and awareness of benefit. J. Inf. Commun. Ethics Soc. 2016, 14, 288–308. [Google Scholar] [CrossRef]
- Erlich, Y.; Williams, J.B.; Glazer, D.; Yocum, K.; Farahany, N.; Olson, M.; Narayanan, A.; Stein, L.D.; Witkowski, J.A.; Kain, R.C. Redefining Genomic Privacy: Trust and Empowerment. PLoS Biol. 2014, 12, e1001983. [Google Scholar] [CrossRef] [PubMed]
- Decherchi, S.; Pedrini, E.; Mordenti, M.; Cavalli, A.; Sangiorgi, L. Opportunities and Challenges for Machine Learning in Rare Diseases. Front. Med. 2021, 8, 747612. [Google Scholar] [CrossRef] [PubMed]
- Boulanger, V.; Schlemmer, M.; Rossov, S.; Seebald, A.; Gavin, P. Establishing Patient Registries for Rare Diseases: Rationale and Challenges. Pharm. Med. 2020, 34, 185–190. [Google Scholar] [CrossRef] [Green Version]
- Courbier, S.; Dimond, R.; Bros-Facer, V. Share and protect our health data: An evidence based approach to rare disease patients’ perspectives on data sharing and data protection—Quantitative survey and recommendations. Orphanet J. Rare Dis. 2019, 14, 175. [Google Scholar] [CrossRef]
- De Freitas, C.; Dos Reis, V.; Silva, S.; Videira, P.A.; Morava, E.; Jaeken, J. Public and patient involvement in needs assessment and social innovation: A people-centred approach to care and research for congenital disorders of glycosylation. BMC Health Serv. Res. 2017, 17, 682. [Google Scholar] [CrossRef] [Green Version]
- Thorogood, A. International Data Sharing and Rare Disease: The Importance of Ethics and Patient Involvement. In Rare Diseases; Wu, Z.H., Ed.; IntechOpen: London, UK, 2020. [Google Scholar]
- Ali, S.R.; Bryce, J.; Cools, M.; Korbonits, M.; Beun, J.G.; Taruscio, D.; Danne, T.; Dattani, M.; Dekkers, O.M.; Linglart, A.; et al. The current landscape of European registries for rare endocrine conditions. Eur. J. Endocrinol. 2019, 180, 89–98. [Google Scholar] [CrossRef]
- European Commission. Support for the Setting-Up of Registries of Patients Affected by Rare Diseases Available for All the ERNs. 2019. Available online: https://ec.europa.eu/health/system/files/2019-06/2019041052_news_en_0.pdf (accessed on 26 May 2022).
- European Commission. Declaration of Cooperation: Towards Access to at Least 1 Million Sequenced Genomes in the European Union by 2022. 2018. Available online: https://www.euapm.eu/pdf/EAPM_Declaration_Genome.pdf (accessed on 26 May 2022).
- Gainotti, S.; Turner, C.; Woods, S.; Kole, A.; Mccormack, P.; Lochmüller, H.; Riess, O.; Straub, V.; Posada, M.; Taruscio, D.; et al. Improving the informed consent process in international collaborative rare disease research: Effective consent for effective research. Eur. J. Hum. Genet. 2016, 24, 1248–1254. [Google Scholar] [CrossRef] [Green Version]
- Shabani, M.; Bezuidenhout, L.; Borry, P. Attitudes of research participants and the general public towards genomic data sharing: A systematic literature review. Expert Rev. Mol. Diagn. 2014, 14, 1053–1065. [Google Scholar] [CrossRef]
- Godard, B.; Ozdemir, V.; Fortin, M.; Egalité, N. Ethnocultural community leaders’ views and perceptions on biobanks and population specific genomic research: A qualitative research study. Public Underst. Sci. 2010, 19, 469–485. [Google Scholar] [CrossRef] [PubMed]
- Richards, T.; Coulter, A.; Wicks, P. Time to deliver patient centred care. BMJ 2015, 350, h530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pulvirenti, M.; McMillan, J.; Lawn, S. Empowerment, patient-centred care and self-management. Health Exp. 2011, 17, 303–310. [Google Scholar] [CrossRef] [PubMed]
- Darquy, S.; Moutel, G.; Lapointe, A.-S.; D’Audiffret, D.; Champagnat, J.; Guerroui, S.; Vendeville, M.-L.; Boespflug-Tanguy, O.; Duchange, N. Patient/family views on data sharing in rare diseases: Study in the European LeukoTreat project. Eur. J. Hum. Genet. 2016, 24, 338–343. [Google Scholar] [CrossRef] [Green Version]
- Nwebonyi, N.; Silva, S.; De Freitas, C. Public Views About Involvement in Decision-Making on Health Data Sharing, Access, Use and Reuse: The Importance of Trust in Science and Other Institutions. Front. Public Health 2022, 10, 852971. [Google Scholar] [CrossRef]
- McCormack, P.; Kole, A.; Gainotti, S.; Mascalzoni, D.; Molster, C.; Lochmüller, H.; Woods, S. ‘You should at least ask’. The expectations, hopes and fears of rare disease patients on large-scale data and biomaterial sharing for genomics research. Eur. J. Hum. Genet. 2016, 24, 1403–1408. [Google Scholar] [CrossRef] [Green Version]
- Tabor, H.K.; Stock, J.; Brazg, T.; Mcmillin, M.J.; Dent, K.M.; Yu, J.-H.; Shendure, J.; Bamshad, M.J. Informed consent for whole genome sequencing: A qualitative analysis of participant expectations and perceptions of risks, benefits, and harms. Am. J. Med. Genet. Part A 2012, 158A, 1310–1319. [Google Scholar] [CrossRef] [Green Version]
- Kalkman, S.; van Delden, J.; Banerjee, A.; Tyl, B.; Mostert, M.; van Thiel, G. Patients’ and public views and attitudes towards the sharing of health data for research: A narrative review of the empirical evidence. J. Med. Ethics 2022, 48, 3–13. [Google Scholar] [CrossRef] [Green Version]
- Milne, R.; Morley, K.I.; Howard, H.; Niemiec, E.; Nicol, D.; Critchley, C.; Prainsack, B.; Vears, D.; Smith, J.; Steed, C.; et al. Trust in genomic data sharing among members of the general public in the UK, USA, Canada and Australia. Hum. Genet. 2019, 138, 1237–1246. [Google Scholar] [CrossRef] [Green Version]
- Black, L.; Batist, G.; Avard, D.; Rousseau, C.; Diaz, Z.; Knoppers, B.M. Physician recruitment of patients to non-therapeutic oncology clinical trials: Ethics revisited. Front. Pharmacol. 2013, 4, 25. [Google Scholar] [CrossRef] [Green Version]
- Inês, M.; Coelho, T.; Conceição, I.; Duarte-Ramos, F.; de Carvalho, M.; Costa, J. Epidemiology of Transthyretin Familial Amyloid Polyneuropathy in Portugal: A Nationwide Study. Neuroepidemiology 2018, 51, 177–182. [Google Scholar] [CrossRef] [PubMed]
- Mendes, Á.; Sousa, L.; Sequeiros, J.; Clarke, A. Discredited legacy: Stigma and familial amyloid polyneuropathy in Northwestern Portugal. Soc. Sci. Med. 2017, 182, 73–80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Middleton, A.; Milne, R.; Almarri, M.A.; Anwer, S.; Atutornu, J.; Baranova, E.E.; Bevan, P.; Cerezo, M.; Cong, Y.; Critchley, C.; et al. Global Public Perceptions of Genomic Data Sharing: What Shapes the Willingness to Donate DNA and Health Data? Am. J. Med. Genet. 2020, 107, 743–752. [Google Scholar] [CrossRef]
- De Freitas, C.; Amorim, M.; Machado, H.; Leão Teles, E.; Baptista, M.J.; Renedo, A.; Provoost, V.; Silva, S. Public and patient involvement in health data governance (DATAGov): Protocol of a people-centred, mixed-methods study on data use and sharing for rare diseases care and research. BMJ Open 2021, 11, e044289. [Google Scholar] [CrossRef] [PubMed]
- Statistics Portugal. Portuguese Classification of Occupations. 2010. Available online: https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_publicacoes&PUBLICACOESpub_boui=107961853&PUBLICACOESmodo=2&xlang=en (accessed on 8 November 2017).
- Milne, R.; Morley, K.I.; Almarri, M.A.; Atutornu, J.; Baranova, E.E.; Bevan, P.; Cerezo, M.; Cong, Y.; Costa, A.; Feijao, C.; et al. Return of genomic results does not motivate intent to participate in research for all: Perspectives across 22 countries. Genet. Med. 2022, 24, 1120–1129. [Google Scholar] [CrossRef] [PubMed]
- Hassan, L.; Dalton, A.; Hammond, C.; Tully, M.P. A deliberative study of public attitudes towards sharing genomic data within NHS genomic medicine services in England. Public Underst. Sci. 2020, 29, 702–717. [Google Scholar] [CrossRef]
- Francisco, R.; Brasil, S.; Pascoal, C.; Edmondson, A.C.; Jaeken, J.; Videira, P.A.; De Freitas, C.; Ferreira, V.D.R.; Marques-Da-Silva, D. A Community-Led Approach as a Guide to Overcome Challenges for Therapy Research in Congenital Disorders of Glycosylation. Int. J. Environ. Res. Public Health 2022, 19, 6829. [Google Scholar] [CrossRef]
- Dharssi, S.; Wong-Rieger, D.; Harold, M.; Terry, S. Review of 11 national policies for rare diseases in the context of key patient needs. Orphanet J. Rare Dis. 2017, 12, 63. [Google Scholar] [CrossRef] [Green Version]
- Dwyer, A.A.; Quinton, R.; Morin, D.; Pitteloud, N. Identifying the unmet health needs of patients with congenital hypogonadotropic hypogonadism using a web-based needs assessment: Implications for online interventions and peer-to-peer support. Orphanet J. Rare Dis. 2014, 9, 83. [Google Scholar] [CrossRef] [Green Version]
- Bittles, A. Precision medicine: Rare diseases and community genetics. Digit. Med. 2019, 5, 154–161. [Google Scholar] [CrossRef]
- Cesuroglu, T.; Syurina, E.; Feron, F.; Krumeich, A. Other side of the coin for personalised medicine and healthcare: Content analysis of ‘personalised’ practices in the literature. BMJ Open 2016, 6, e010243. [Google Scholar] [CrossRef] [Green Version]
- Borry, P.; Bentzen, H.B.; Budin-Ljøsne, I.; Cornel, M.C.; Howard, H.C.; Feeney, O.; Jackson, L.; Mascalzoni, D.; Mendes, Á.; Peterlin, B.; et al. The challenges of the expanded availability of genomic information: An agenda-setting paper. J. Community Genet. 2018, 9, 103–116. [Google Scholar] [CrossRef] [Green Version]
- Sacristán, J.A.; Aguarón, A.; Avendaño-Solá, C.; Garrido, P.; Carrión, J.; Gutiérrez, A.; Kroes, R.; Flores, A. Patient involvement in clinical research: Why, when, and how. Patient Prefer. Adher. 2016, 10, 631–640. [Google Scholar] [CrossRef] [Green Version]
- Henderson, G.E.; Churchill, L.R.; Davis, A.M.; Easter, M.M.; Grady, C.; Joffe, S.; Kass, N.; King, N.M.P.; Lidz, C.W.; Miller, F.G.; et al. Clinical trials and medical care: Defining the therapeutic misconception. PLoS Med. 2007, 4, e324. [Google Scholar] [CrossRef] [Green Version]
- Braga, L.A.M.; Filho, C.G.C.; Mota, F.B. Future of genetic therapies for rare genetic diseases: What to expect for the next 15 years? Ther. Adv. Rare Dis. 2022, 3, 26330040221100840. [Google Scholar] [CrossRef]
- EURODIS. Rare Diseases Patients’ Participation in Research. 2018. Available online: https://www.eurordis.org/publication/rare-disease-patients-participation-research (accessed on 27 May 2022).
- Pereira, S.; Gibbs, R.; Mcguire, A. Open Access Data Sharing in Genomic Research. Genes 2014, 5, 739–747. [Google Scholar] [CrossRef] [Green Version]
- Geelen, E.; Horstman, K.; Marcelis, C.L.; Doevendans, P.A.; Van Hoyweghen, I. Unravelling fears of genetic discrimination: An exploratory study of Dutch HCM families in an era of genetic non-discrimination acts. Eur. J. Hum. Genet. 2012, 20, 1018–1023. [Google Scholar] [CrossRef] [Green Version]
- Bombard, Y.; Palin, J.; Friedman, J.M.; Veenstra, G.; Creighton, S.; Bottorff, J.L.; Hayden, M.R.; The Canadian Respond-HD Collaborative Research Group. Beyond the Patient: The Broader Impact of Genetic Discrimination Among Individuals at Risk of Huntington Disease. Am. J. Med. Genet. Part B Neuropsychiatr. Genet. 2012, 159B, 217–226. [Google Scholar] [CrossRef]
- Erwin, C.; Williams, J.K.; Juhl, A.R.; Mengeling, M.; Mills, J.A.; Bombard, Y.; Hayden, M.R.; Quaid, K.; Shoulson, I.; Taylor, S.; et al. Perception, Experience, and Response to Genetic Discrimination in Huntington Disease: The International RESPOND-HD Study. Am. J. Med. Genet. Part B Neuropsychiatr. Genet. 2010, 1538, 1081–1093. [Google Scholar] [CrossRef] [Green Version]
- Klitzman, R. Views of Discrimination among Individuals Confronting Genetic Disease. J. Genet. Couns. 2010, 19, 68–83. [Google Scholar] [CrossRef] [Green Version]
- Wauters, A.; Van Hoyweghen, I. Global trends on fears and concerns of genetic discrimination: A systematic literature review. J. Hum. Genet. 2016, 61, 275–282. [Google Scholar] [CrossRef]
- Budin-Ljøsne, I.; Teare, H.J.A.; Kaye, J.; Beck, S.; Bentzen, H.B.; Caenazzo, L.; Collett, C.; D’Abramo, F.; Felzmann, H.; Finlay, T.; et al. Dynamic Consent: A potential solution to some of the challenges of modern biomedical research. BMC Med. Ethics 2017, 18, 4. [Google Scholar] [CrossRef]
- Spencer, K.; Sanders, C.; Whitley, E.A.; Lund, D.; Kaye, J.; Dixon, W.G. Patient Perspectives on Sharing Anonymized Personal Health Data Using a Digital System for Dynamic Consent and Research Feedback: A Qualitative Study. J. Med. Internet Res. 2016, 18, e66. [Google Scholar] [CrossRef] [Green Version]
- Kaye, J.; Muddyman, D.; Smee, C.; Kennedy, K.; Bell, J. ‘Pop-Up’ Governance: Developing internal governance frameworks for consortia: The example of UK10K. Life Sci. Soc. Policy 2015, 11, 10. [Google Scholar] [CrossRef] [Green Version]
- Kaye, J.; Whitley, E.A.; Lund, D.; Morrison, M.; Teare, H.; Melham, K. Dynamic consent: A patient interface for twenty-first century research networks. Eur. J. Hum. Genet. 2015, 23, 141–146. [Google Scholar] [CrossRef] [Green Version]
- Jamal, L.; Sapp, J.C.; Lewis, K.; Yanes, T.; Facio, F.M.; Biesecker, L.G.; Biesecker, B.B. Research participants’ attitudes towards the confidentiality of genomic sequence information. Eur. J. Hum. Genet. 2014, 22, 964–968. [Google Scholar] [CrossRef] [Green Version]
- Macfarlane, A.; Phelan, H.; Tighe, S.M.; Garry, F.; Punch, P. The use of music as an arts-based method in migrant health research: A scoping review. HRB Open Res. 2022, 3, 75. [Google Scholar] [CrossRef]
- Middleton, A.; Milne, R.; Thorogood, A.; Kleiderman, E.; Niemiec, E.; Prainsack, B.; Farley, L.; Bevan, P.; Steed, C.; Smith, J.; et al. Attitudes of publics who are unwilling to donate DNA data for research. Eur. J. Hum. Genet. 2019, 62, 316–323. [Google Scholar] [CrossRef]
- Fiske, A.; Buyx, A.; Prainsack, B. Health Information Counselors. Acad. Med. 2019, 94, 37–41. [Google Scholar] [CrossRef] [Green Version]
- De Freitas, C. Public and patient participation in health policy, care and research. Porto Biomed. J. 2017, 2, 31–32. [Google Scholar] [CrossRef]
- Ploug, T.; Holm, S. Meta consent: A flexible and autonomous way of obtaining informed consent for secondary research. BMJ 2015, 350, h2146. [Google Scholar] [CrossRef]
- Streicher, S.A.; Sanderson, S.C.; Jabs, E.W.; Diefenbach, M.; Smirnoff, M.; Peter, I.; Horowitz, C.R.; Brenner, B.; Richardson, L.D. Reasons for participating and genetic information needs among racially and ethnically diverse biobank participants: A focus group study. J. Community Genet. 2011, 2, 153–163. [Google Scholar] [CrossRef] [Green Version]
- Howe, N.; Giles, E.; Newbury-Birch, D.; McColl, E. Systematic review of participants’ attitudes towards data sharing: A thematic synthesis. J. Health Serv. Res. Policy 2018, 23, 123–133. [Google Scholar] [CrossRef] [Green Version]
- Balaji, D.; Terry, S.F. Benefits and Risks of Sharing Genomic Information. Genet. Test. Mol. Biomark. 2015, 19, 648–649. [Google Scholar] [CrossRef] [Green Version]
- Gallup. How Does the World Feel about Science and Health? 2019. Available online: https://cms.wellcome.org/sites/default/files/wellcome-global-monitor-2018.pdf (accessed on 3 June 2022).
- Critchley, C.R.; Nicol, D.; Otlowski, M.F.A.; Stranger, M.J.A. Predicting intention to biobank: A national survey. Eur. J. Public Health 2012, 22, 139–144. [Google Scholar] [CrossRef] [Green Version]
- Nguyen, M.T.; Goldblatt, J.; Isasi, R.; Jagut, M.; Jonker, A.H.; Kaufmann, P.; Ouillade, L.; Molnar-Gabor, F.; Shabani, M.; Sid, E.; et al. Model consent clauses for rare disease research. BMC Med. Ethics 2019, 20, 55. [Google Scholar] [CrossRef]
- Hansson, M.G.; Lochmüller, H.; Riess, O.; Schaefer, F.; Orth, M.; Rubinstein, Y.; Molster, C.; Dawkins, H.; Taruscio, D.; Posada, M.; et al. The risk of re-identification versus the need to identify individuals in rare disease research. Eur. J. Hum. Genet. 2016, 24, 1553–1558. [Google Scholar] [CrossRef] [Green Version]
- Mascalzoni, D.; Petrini, C.; Taruscio, D.; Gainotti, S. The Role of Solidarity(-ies) in Rare Diseases Research. In Rare Diseases Epidemiology, 2nd ed.; Posada de la Paz, M., Taruscio, D., Groft, S., Eds.; Springer: Cham, Switzerland, 2017; Volume 1031. [Google Scholar]
- Serapioni, M.; Matos, A.R. Citizen participation and discontent in three Southern European health systems. Soc. Sci. Med. 2014, 123, 226–233. [Google Scholar] [CrossRef]
Patients (n = 159) | Informal Carers (n = 478) | Healthcare Professionals (n = 63) a | |
---|---|---|---|
Sex | |||
Female | 75 (47.2) | 376 (78.7) | 42 (66.7) |
Male | 84 (52.8) | 102 (21.3) | 21 (33.3) |
Age (years) | |||
<18 | 89 (56.0) | 0 (0) | 0 (0) |
18–29 | 44 (27.7) | 47 (9.9) | 0 (0) |
30–49 | 20 (12.6) | 356 (75.1) | 29 (46.0) |
>49 | 6 (3.8) | 71 (15.0) | 34 (54.0) |
Educational level (years) | |||
≤12 | 151 (95.6) | 327 (68.8) | 0 (0) |
>12 | 7 (4.4) | 148 (31.2) | 63 (100) |
Country of origin | |||
Portugal | 154 (96.9) | 447 (93.9) | 61 (96.8) |
Other b | 5 (3.1) | 29 (6.1) | 2 (3.2) |
Marital status | |||
Married/living with partner | 16 (10.1) | 371 (77.9) | 50 (79.4) |
Other c | 142 (89.9) | 105 (22.1) | 13 (20.6) |
Occupation | |||
Upper white-collar | 5 (3.2) | 144 (32.3) | 63 (100) |
Lower white-collar | 7 (4.4) | 108 (24.2) | 0 (0) |
Blue-collar | 9 (5.7) | 79 (17.7) | 0 (0) |
Other d | 137 (86.7) | 115 (25.8) | 0 (0) |
Perceived income adequacy | |||
Insufficient/caution with expenses | 51 (35.4) | 267 (56.4) | 12 (19.4) |
Enough to make ends meet/comfortable | 93 (64.6) | 206 (43.6) | 50 (80.6) |
Involvement in patient organisations | |||
No | 154 (98.1) | 446 (93.7) | 51 (82.3) |
Yes | 3 (1.9) | 30 (6.3) | 11 (17.7) |
Satisfaction with own health | |||
Very unsatisfied/Unsatisfied | 16 (10.1) | 34 (7.1) | |
Neither satisfied nor unsatisfied | 44 (27.7) | 79 (16.6) | -- |
Satisfied/Very satisfied | 99 (62.3) | 364 (76.3) | |
Willingness to share genetic information for research | |||
Always willing/willing | 109 (70.3) | 320 (67.9) | -- |
Other | 46 (29.7) | 151 (32.1) | -- |
Interpersonal Trust, Md (P25–P75) | 4.7 (2.5–6.7) | 4.7 (3.0–6.3) | 6.0 (3.7–7.7) |
Benefits | Patients (n = 159) | Informal Carers (n = 478) | Healthcare Professionals (n = 63) | p Value |
---|---|---|---|---|
Discovery of a cure for untreatable diseases | 134 (84.3) | 418 (87.4) | 40 (63.5) | <0.001 |
Development of new drugs and treatments | 62 (39.0) | 231 (48.3) | 45 (71.4) | <0.001 |
Development of personalised treatments, taking into account the characteristics of each patient | 68 (42.8) | 178 (37.2) | 21 (33.3) | 0.329 |
Development of strategies to control disease dissemination | 51 (32.1) | 120 (25.1) | 19 (30.2) | 0.197 |
Other: Help other people a | 0 (0) | 1 (0.2) | 0 (0) | NA |
Risks | Patients (n = 157) | Informal Carers (n = 477) | Healthcare Professionals (n = 63) | p Value |
Lack of security and control over access to information | 114 (72.6) | 286 (60.0) | 31 (49.2) | 0.002 |
Possibility of extracting information that exceeds the research objectives | 79 (50.3) | 289 (60.6) | 34 (54.0) | 0.064 |
Performing genetic studies that can discriminate citizens | 54 (34.4) | 189 (39.6) | 43 (68.3) | <0.001 |
Restrictions to citizens’ rights of privacy and autonomy | 64 (40.8) | 158 (33.1) | 17 (27.0) | 0.095 |
Other: Misuse of information a | 0 (0) | 2 (0.4) | 0 (0) | NA |
Other: Commercialisation of information a | 0 (0) | 1 (0.2) | 0 (0) | NA |
Discover a Cure for Untreatable Diseases Crude OR (95% CI) | Development of New Drugs and Treatments Crude OR (95% CI) | Development of Personalised Treatments Crude OR (95% CI) | |||||||
---|---|---|---|---|---|---|---|---|---|
Patients | Informal Carers | Healthcare Professionals | Patients | Informal Carers | Healthcare Professionals | Patients | Informal Carers | Healthcare Professionals | |
Sex | |||||||||
Female | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Male | 1.04 (0.44–2.45) | 1.10 (0.56–2.15) | 0.49 (0.17–1.45) | 0.92 (0.49–1.75) | 0.77 (0.49–1.19) | 1.43 (0.43–4.76) | 1.01 (0.54–1.89) | 0.72 (0.45–1.15) | 1.00 (0.33–3.04) |
Age (years) | |||||||||
<18 | 1 | -- | -- | 1 | -- | -- | 1 | -- | -- |
18–29 | 0.90 (0.33–2.46) | 1 | -- | 1.18 (0.56–2.46) | 1 | -- | 0.74 (0.35–1.54) | 1 | -- |
30–49 | 0.68 (0.20–2.37) | 2.08 (0.96–49) | 1 | 1.39 (0.52–3.70) | 0.58 (0.31–1.08) | 1 | 0.63 (0.23–1.73) | 1.02 (0.55–1.91) | 1 |
>49 | 0.86 (0.09–7.92) | 1.86 (0.69–5.00) | 0.64 (0.23–1.82) | 0.58 (0.15–4.89) | 0.70 (0.33–1.47) | 3.29 (1.04–10.41) | 1.17 (0.22–6.12) | 0.68 (0.31–1.47) | 0.38 (0.13–1.11) |
Educational level (years) | |||||||||
≤12 | 1 | 1 | -- | 1 | 1 | -- | 1 | 1 | -- |
>12 | 1.08 (0.12–9.38) | 2.20 (1.11–4.36) | 1.17 (0.25–5.41) | 1.58 (1.07–2.34) | 0.22 (0.03–1.83) | 0.84 (0.56–1.26) | |||
Occupation | |||||||||
Upper white-collar | 1 | 1 | -- | 1 | 1 | -- | -- | 1 | -- |
Lower white-collar | 1.50 (0.07–31.58) | 1.00 (0.41–2.47) | 2.00 (0.19–20.61) | 0.95 (0.57–1.56) | 0.92 (0.55–1.56) | ||||
Blue-collar | 0.31 (0.02–4.02) | 0.31 (0.14–0.68) | 1.88 (0.20–17.27) | 0.68 (0.39–1.18) | 1.21 (0.69–2.12) | ||||
Other a | 1.65 (0.18–15.63) | 0.49 (0.23–1.06) | 0.86 (0.14–5.34) | 0.87 (0.53–1.42) | 1.10 (0.66–1.82) | ||||
Perceived income | |||||||||
Insufficient/caution with expenses | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Enough to make ends meet/comfortable | 1.32 (0.52–3.34) | 2.08 (1.14–3.77) | 0.82 (0.22–3.08) | 0.90 (0.45–1.81) | 1.16 (0.81–1.67) | 5.60 (1.47–21.40) | 1.28 (0.64–2.56) | 0.89 (0.61–1.30) | 0.43 (0.12-1.55) |
Lack of Security and Control Over Access to Information Crude OR (95% CI) | Possibility of Extracting Information That Exceeds the Research Objectives Crude OR (95% CI) | Performing Genetic Studies That Can Discriminate Citizens Crude OR (95% CI) | |||||||
---|---|---|---|---|---|---|---|---|---|
Patients | Informal Carers | Healthcare Professionals | Patients | Informal Carers | Healthcare Professionals | Patients | Informal Carers | Healthcare Professionals | |
Sex | |||||||||
Female | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Male | 0.85 (0.42–1.72) | 1.16 (0.74–1.82) | 0.68 (0.24–1.96) | 1.02 (0.55–1.92) | 1.01 (0.65–1.58) | 1.21 (0.42–3.48) | 0.75 (0.39–1.45) | 1.20 (0.77–1.88) | 1.25 (0.40–3.92) |
Educational level | |||||||||
≤12 | 1 | 1 | -- | 1 | 1 | -- | 1 | 1 | -- |
>12 | 0.92 (0.17–4.92) | 1.03 (0.69–1.53) | 0.72 (0.16–3.33) | 1.60 (1.06–2.41) | 0.77 (0.14–4.10) | 0.85 (0.57–1.26) | |||
Occupation | |||||||||
Upper white-collar | 1 | 1 | -- | 1 | 1 | -- | 1 | 1 | -- |
Lower white-collar | 3.33 (0.20–54.53) | 1.03 (0.62–1.72) | 8.00 (0.50–127.90) | 0.65 (0.38–1.12) | 2.00 (0.13–31.98) | 1.12 (0.67–1.87) | |||
Blue-collar | 0.33 (0.04-3.21) | 0.91 (0.52–1.60) | 5.00 (0.39–64.39) | 0.44 (0.25–0.77) | 2.00 (0.15–26.73) | 1.61 (0.92–2.81) | |||
Other a | 2.00 (0.32–12.48) | 0.97 (0.59–1.60) | 4.12 (0.45–37.81) | 0.44 (0.26–0.74) | 2.18 (0.24–20.08) | 1.23 (0.74–2.05) | |||
Willingness to share genetic data | |||||||||
Other | 1 | 1 | -- | 1 | 1 | -- | 1 | 1 | -- |
Always willing/willing | 0.54 (0.24–1.26) | 0.62 (0.41–0.93) | 0.96 (0.48–1.92) | 1.00 (0.67–1.48) | 2.86 (1.25–6.52) | 2.04 (1.35–3.10) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Amorim, M.; Silva, S.; Machado, H.; Teles, E.L.; Baptista, M.J.; Maia, T.; Nwebonyi, N.; de Freitas, C. Benefits and Risks of Sharing Genomic Data for Research: Comparing the Views of Rare Disease Patients, Informal Carers and Healthcare Professionals. Int. J. Environ. Res. Public Health 2022, 19, 8788. https://doi.org/10.3390/ijerph19148788
Amorim M, Silva S, Machado H, Teles EL, Baptista MJ, Maia T, Nwebonyi N, de Freitas C. Benefits and Risks of Sharing Genomic Data for Research: Comparing the Views of Rare Disease Patients, Informal Carers and Healthcare Professionals. International Journal of Environmental Research and Public Health. 2022; 19(14):8788. https://doi.org/10.3390/ijerph19148788
Chicago/Turabian StyleAmorim, Mariana, Susana Silva, Helena Machado, Elisa Leão Teles, Maria João Baptista, Tiago Maia, Ngozi Nwebonyi, and Cláudia de Freitas. 2022. "Benefits and Risks of Sharing Genomic Data for Research: Comparing the Views of Rare Disease Patients, Informal Carers and Healthcare Professionals" International Journal of Environmental Research and Public Health 19, no. 14: 8788. https://doi.org/10.3390/ijerph19148788
APA StyleAmorim, M., Silva, S., Machado, H., Teles, E. L., Baptista, M. J., Maia, T., Nwebonyi, N., & de Freitas, C. (2022). Benefits and Risks of Sharing Genomic Data for Research: Comparing the Views of Rare Disease Patients, Informal Carers and Healthcare Professionals. International Journal of Environmental Research and Public Health, 19(14), 8788. https://doi.org/10.3390/ijerph19148788