| Literature DB >> 28960139 |
Georgia Lowe1, Jonathan Pugh2, Guy Kahane2, Louise Corben3, Sharon Lewis4, Martin Delatycki5, Julian Savulescu1.
Abstract
BACKGROUND: Increasing use of genetic technologies in clinical and research settings increases the potential for misattributed paternity to be identified. Yet existing guidance from the President's Commission for the Study of Ethical Problems in Biomedical and Behavioral Research and the Institute of Medicine (among others) offers contradictory advice. Genetic health professionals are thus likely to vary in their practice when misattributed paternity is identified, and empirical investigation into the disclosure of misattributed paternity is scarce. Given the relevance of this ethical dilemma and its significance to users of genetic services, this study aimed to investigate the attitudes of lay people with regard to the disclosure of misattributed paternity.Entities:
Keywords: ethics; genetics; misattributed paternity; practice guidelines as a topic; public perspective; questionnaire
Mesh:
Year: 2017 PMID: 28960139 PMCID: PMC5849225 DOI: 10.1080/23294515.2017.1378751
Source DB: PubMed Journal: AJOB Empir Bioeth ISSN: 2329-4515
Vignettes.
| A. Discuss this confidentially with the mother? | ||
| B. Ignore it on the basis that it is not relevant to the child's abnormality? | ||
| C. Encourage the mother to reveal this finding to her husband and explain it? | ||
| D. Inform the husband that he is not the father of the child, even if the woman does not want them to? | ||
| A. Ask permission to reveal the truth from the mother? | ||
| B. Tell the truth, regardless of the mother's wishes? | ||
| C. Lie, and say that the boy is the man's son? | ||
| D. Lie, and say they can't tell whether or not the boy is the man's son? | ||
| E. Tell the truth only if the mother lets them? | ||
| F. Do what the doctors judge to be in the best interests of the boy? | ||
Demographic characteristics of the cohort.
| Demographic | Category | Number of participants (percentage), |
|---|---|---|
| Age (years) | 18–24 | 26 (13.0%) |
| 25–34 | 73 (36.5%) | |
| 35–44 | 49 (24.5%) | |
| 45–54 | 34 (17.0%) | |
| 55 or older | 18 (9.0%) | |
| Gender | Female | 129 (64.5%) |
| Male | 71 (35.5%) | |
| Highest level of education | Less than high school/high school/general educational development | 23 (11.5%) |
| Some college | 63 (31.5%) | |
| Two-year college degree | 29 (14.5%) | |
| Four-year college degree (BA, BS) | 63 (31.5%) | |
| Master's degree/doctorate degree/professional degree | 22 (11.0%) |
Figure 1.Vignette results showing percentage of respondents for each ethical permissbility category and corresponding doctor scenario. (a) Vignette 1 results. (b) Vignette 2 results.
Comparison of demographic characteristics and ethical permissibly of scenario.
| Vignette and scenario | Demographic characteristic | Significance (chi-squared statistic and |
|---|---|---|
| 1A | Gender | 2.17, |
| Age | 13.47, | |
| Education | 5.69, | |
| 1B | Gender | 1.50, |
| Age | 13.17, | |
| Education | 5.69, | |
| 1C | Gender | 3.72, |
| Age | 3.87, | |
| Education | 14.86, | |
| 1D | Gender | |
| Age | 5.98, | |
| Education | 4.00, | |
| 2A | Gender | 1.75, |
| Age | 8.58, | |
| Education | 11.08, | |
| 2B | Gender | |
| Age | 9.11, | |
| Education | 7.65, | |
| 2C | Gender | 2.70, |
| Age | 7.47, | |
| Education | 6.14, | |
| 2D | Gender | 0.05, |
| Age | 13.45, | |
| Education | 9.44, | |
| 2E | Gender | 5.59, |
| Age | 11.03, | |
| Education | 2.62, | |
| 2F | Gender | 5.44, |
| Age | ||
| Education | 14.00, | |
| 3 | Gender | |
| Age | ||
| Education | 8.31, |
Indicates a p value of less than .05 was obtained.
indicates a Fisher's exact test was used.
Comparison of demographic characteristics and ethical permissibly of scenario with percentage of respondent values.
| Number of participants (% of demographic characteristic) | ||||||
|---|---|---|---|---|---|---|
| Likert scale | ||||||
| Question | Demographic | Characteristic | Unacceptable | Ambivalent | Acceptable | Significance |
| 1D | Gender | Male ( | 46 (64.8) | 16 (22.5) | 9 (12.7) | χ2 = 8.61, |
| Female ( | 105 (81.4) | 11 (8.5) | 13 (10.1) | |||
| 2B | Gender | Male ( | 24 (33.8) | 9 (12.7) | 38 (53.5) | χ2 = 5.80, |
| Female ( | 64 (49.6) | 18 (14.0) | 47 (36.4) | |||
| 2F | Age (years) | 18–24 ( | 3 (11.5) | 12 (46.2) | 11 (42.3) | χ2 = 18.94, |
| 25–34 ( | 26 (35.6) | 16 (21.9) | 31 (42.5) | |||
| 35–44 ( | 18 (36.7) | 9 (18.4) | 22 (44.9) | |||
| 45–54 ( | 9 (26.5) | 3 (8.8) | 22 (64.7) | |||
| 55 and older ( | 3 (16.7) | 4 (22.2) | 11 (61.1) | |||
| Agree | Disagree | |||||
| 3 | Gender | Male ( | 44 (62.0) | 27 (38.0) | χ2 = 7.41, | |
| Female ( | 54 (41.9) | 75 (58.1) | ||||
| 3 | Age (years) | 18–24 ( | 19 (73.1) | 7 (26.9) | χ2 = 9.96, | |
| 25–34 ( | 30 (41.1) | 43 (58.9) | ||||
| 35–44 ( | 26 (53.1) | 23 (46.9) | ||||
| 45–54 ( | 17 (50.0) | 17 (50.0) | ||||
| 55 and older ( | 6 (33.3) | 12 (66.7) | ||||