Informed consent for human genetic and genomic studies: a systematic review
As genetic and genomic studies grow in scale, there are ethical concerns related to the collection and use of genetic information. The emergence of large public databases potentially redefine the terms of participation in genetic and genomic research, and suggests the changing application of traditional ethical principles such as privacy or consent. For this study, we wanted to see whether such developments are reflected in the informed consent processes in human genetic and genomic studies. Therefore, we performed a systematic review of the empirical studies that examined informed consent involving large genetic databases in human genetic and genomic studies, grouped the identified issues related to the different stakeholders (including subjects, researchers, and institutional review boards) and discussed the limitations and implications of these findings. Major themes related to the place of bioethical considerations, procured tissues, people involved, process of informed consent and study procedures. Frequently raised issues included confidentiality of participants, documentation of informed consent, public attitudes, future use of participant samples or data, and disclosure of results. Awareness and attention to these bioethical issues as well as assiduousness in managing these concerns in genetic/genomic research would further strengthen and safeguard the rights, safety and well-being of genetic research participants.
Genetic testing, privacy and discrimination
The concept of "genetic discrimination" only recently entered our vocabulary. But the problem is well documented. Indeed, the Council for Responsible Genetics was the first organization to compile documented cases of genetic discrimination, laying the intellectual groundwork for future legislation. In as many as five hundred cases, individuals and family members have been barred from employment or lost their health and life insurance based on an apparent or perceived genetic abnormality. Many of those who have suffered discrimination are clinically healthy and exhibit none of the symptoms of a genetic disorder. Often, genetic tests deliver uncertain probabilities rather than clear-cut predictions of disease.
Broad consent versus dynamic consent in biobank research: Is passive participation an ethical problem?
In the endeavour of biobank research there is dispute concerning what type of consent and which form of donor–biobank relationship meet high ethical standards. Up until now, a ‘broad consent’ model has been used in many present-day biobank projects. However it has been, by some scholars, deemed as a pragmatic, and not an acceptable ethical solution. Calls for change have been made on the basis of avoidance of paternalism, intentions to fulfil the principle of autonomy, wish for increased user participation, a questioning of the role of experts and ideas advocating reduction of top–down governance. Recently, an approach termed ‘dynamic consent’ has been proposed to meet such challenges. Dynamic consent uses modern communication strategies to inform, involve, offer choices and last but not the least obtain consent for every research projects based on biobank resources. At first glance dynamic consent seems appealing, and we have identified six claims of superiority of this model; claims pertaining to autonomy, information, increased engagement, control, social robustness and reciprocity. However, after closer examination, there seems to be several weaknesses with a dynamic consent approach; among others the risk of inviting people into the therapeutic misconception as well as individualizing the ethical review of research projects. When comparing the two models, broad consent still holds and can be deemed a good ethical solution for longitudinal biobank research. Nevertheless, there is potential for improvement in the broad model, and criticism can be met by adapting some of the modern communication strategies proposed in the dynamic consent approach.
Understanding p-value – statistics help
This video explains how to use the p-value to draw conclusions from statistical output. It includes the story of Helen, making sure that the choconutties she sells have sufficient peanuts.
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
If you really want to understand types of data, along with appropriate statistics and graphs, this video can help.
Choosing which statistical test to use – statistics help
Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together all the CreativeHeuristics videos about Helen, her brother, Luke and the choconutties.
For a 2x2 contingency table
For two groups of subjects, each sorted according to the absence or presence of some particular characteristic or condition, this page will calculate standard measures for Rates, Risk Ratio, Odds, Odds Ratio, and Log Odds.
2-way Contingency Table Analysis
This page computes various statistics from a 2-by-2 table. It will calculate the Yates-corrected chi-square, the Mantel-Haenszel chi-square, the Fisher Exact Test, and other indices relevant to various special kinds of 2-by-2 tables:
- analysis of risk factors for unfavorable outcomes (odds ratio, relative risk, difference in proportions, absolute and relative reduction in risk, number needed to treat)
- analysis of the effectiveness of a diagnostic criterion for some condition (sensitivity, specificity, prevalence, pos & neg predictive values, adjusted predictive values, pos & neg likelihood ratios, diagnostic and error odds ratios)
- measures of inter-rater reliability (% correct or consistent, mis-classification rate, kappa, Forbes' NMI)
- other measures of association (contingency coefficient, Cramer's phi coefficient, Yule's Q)
The Comprehensive R Archive Network
R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc.
Online statistics education: An interactive multimedia course of study
Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.